Parts-based stereoscopic image assessment by learning binocular manifold color visual properties

NASA Astrophysics Data System (ADS)

Xu, Haiyong; Yu, Mei; Luo, Ting; Zhang, Yun; Jiang, Gangyi

2016-11-01

Existing stereoscopic image quality assessment (SIQA) methods are mostly based on the luminance information, in which color information is not sufficiently considered. Actually, color is part of the important factors that affect human visual perception, and nonnegative matrix factorization (NMF) and manifold learning are in line with human visual perception. We propose an SIQA method based on learning binocular manifold color visual properties. To be more specific, in the training phase, a feature detector is created based on NMF with manifold regularization by considering color information, which not only allows parts-based manifold representation of an image, but also manifests localized color visual properties. In the quality estimation phase, visually important regions are selected by considering different human visual attention, and feature vectors are extracted by using the feature detector. Then the feature similarity index is calculated and the parts-based manifold color feature energy (PMCFE) for each view is defined based on the color feature vectors. The final quality score is obtained by considering a binocular combination based on PMCFE. The experimental results on LIVE I and LIVE Π 3-D IQA databases demonstrate that the proposed method can achieve much higher consistency with subjective evaluations than the state-of-the-art SIQA methods.

Self-paced model learning for robust visual tracking

NASA Astrophysics Data System (ADS)

Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

2017-01-01

In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

Visual Learning: A Learner Centered Approach to Enhance English Language Teaching

ERIC Educational Resources Information Center

Philominraj, Andrew; Jeyabalan, David; Vidal-Silva, Christian

2017-01-01

This article presents an empirical study carried out among the students of higher secondary schools to find out how English language learning occurs naturally in an environment where learners are encouraged by an appropriate method such as visual learning. The primary data was collected from 504 students with different pretested questionnaires. A…

Fostering and Assessing Infographic Design for Learning: The Development of Infographic Design Criteria

ERIC Educational Resources Information Center

Nuhoglu Kibar, Pinar; Akkoyunlu, Buket

2017-01-01

In this ever more digital and visual world, it has become more vital that students are encouraged to create content during the learning process through effective visualization of their knowledge. Infographics are an effective method for such visualization. The current study therefore proposes an infographic design rubric (IDR) as a criteria-based…

Webly-Supervised Fine-Grained Visual Categorization via Deep Domain Adaptation.

PubMed

Xu, Zhe; Huang, Shaoli; Zhang, Ya; Tao, Dacheng

2018-05-01

Learning visual representations from web data has recently attracted attention for object recognition. Previous studies have mainly focused on overcoming label noise and data bias and have shown promising results by learning directly from web data. However, we argue that it might be better to transfer knowledge from existing human labeling resources to improve performance at nearly no additional cost. In this paper, we propose a new semi-supervised method for learning via web data. Our method has the unique design of exploiting strong supervision, i.e., in addition to standard image-level labels, our method also utilizes detailed annotations including object bounding boxes and part landmarks. By transferring as much knowledge as possible from existing strongly supervised datasets to weakly supervised web images, our method can benefit from sophisticated object recognition algorithms and overcome several typical problems found in webly-supervised learning. We consider the problem of fine-grained visual categorization, in which existing training resources are scarce, as our main research objective. Comprehensive experimentation and extensive analysis demonstrate encouraging performance of the proposed approach, which, at the same time, delivers a new pipeline for fine-grained visual categorization that is likely to be highly effective for real-world applications.

A real-time articulatory visual feedback approach with target presentation for second language pronunciation learning.

PubMed

Suemitsu, Atsuo; Dang, Jianwu; Ito, Takayuki; Tiede, Mark

2015-10-01

Articulatory information can support learning or remediating pronunciation of a second language (L2). This paper describes an electromagnetic articulometer-based visual-feedback approach using an articulatory target presented in real-time to facilitate L2 pronunciation learning. This approach trains learners to adjust articulatory positions to match targets for a L2 vowel estimated from productions of vowels that overlap in both L1 and L2. Training of Japanese learners for the American English vowel /æ/ that included visual training improved its pronunciation regardless of whether audio training was also included. Articulatory visual feedback is shown to be an effective method for facilitating L2 pronunciation learning.

Learning about Probability from Text and Tables: Do Color Coding and Labeling through an Interactive-User Interface Help?

ERIC Educational Resources Information Center

Clinton, Virginia; Morsanyi, Kinga; Alibali, Martha W.; Nathan, Mitchell J.

2016-01-01

Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly…

Web-Based Interactive 3D Visualization as a Tool for Improved Anatomy Learning

ERIC Educational Resources Information Center

Petersson, Helge; Sinkvist, David; Wang, Chunliang; Smedby, Orjan

2009-01-01

Despite a long tradition, conventional anatomy education based on dissection is declining. This study tested a new virtual reality (VR) technique for anatomy learning based on virtual contrast injection. The aim was to assess whether students value this new three-dimensional (3D) visualization method as a learning tool and what value they gain…

Fostering Creative Thinking Within the U.S. Army Command and General Staff Officers’ Course Curriculum

DTIC Science & Technology

2016-06-10

and complexity to their learning” that is not present in traditional teaching methods (James and Brookfield 2014, 4). In Engaging Imagination... method described is the use of visually based teaching and learning. James and Brookfield, delineate between looking and seeing (James and Brookfield...learning methods more applicable to some students as opposed to others. However, the exploration of visual teaching techniques through the use of pictures

Student-Generated Visualization as a Study Strategy for Science Concept Learning

ERIC Educational Resources Information Center

Hsieh, Yi-Chuan Jane; Cifuentes, Lauren

2006-01-01

Mixed methods were adopted to explore the effects of student-generated visualization on paper and on computers as a study strategy for middle school science concept learning. In a post-test-only-control-group design, scores were compared among a control-group (n=28), a group that was trained to visualize on paper (n=30), and a group that was…

Self-Taught Low-Rank Coding for Visual Learning.

PubMed

Li, Sheng; Li, Kang; Fu, Yun

2018-03-01

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

PubMed

Wu, Lin; Wang, Yang; Pan, Shirui

2017-12-01

It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

Automated estimation of image quality for coronary computed tomographic angiography using machine learning.

PubMed

Nakanishi, Rine; Sankaran, Sethuraman; Grady, Leo; Malpeso, Jenifer; Yousfi, Razik; Osawa, Kazuhiro; Ceponiene, Indre; Nazarat, Negin; Rahmani, Sina; Kissel, Kendall; Jayawardena, Eranthi; Dailing, Christopher; Zarins, Christopher; Koo, Bon-Kwon; Min, James K; Taylor, Charles A; Budoff, Matthew J

2018-03-23

Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA). The machine learning method was trained using 75 CCTA studies by mapping features (noise, contrast, misregistration scores, and un-interpretability index) to an IQ score based on manual ground truth data. The automated method was validated on a set of 50 CCTA studies and subsequently tested on a new set of 172 CCTA studies against visual IQ scores on a 5-point Likert scale. The area under the curve in the validation set was 0.96. In the 172 CCTA studies, our method yielded a Cohen's kappa statistic for the agreement between automated and visual IQ assessment of 0.67 (p < 0.01). In the group where good to excellent (n = 163), fair (n = 6), and poor visual IQ scores (n = 3) were graded, 155, 5, and 2 of the patients received an automated IQ score > 50 %, respectively. Fully automated assessment of the IQ of CCTA data sets by machine learning was reproducible and provided similar results compared with visual analysis within the limits of inter-operator variability. • The proposed method enables automated and reproducible image quality assessment. • Machine learning and visual assessments yielded comparable estimates of image quality. • Automated assessment potentially allows for more standardised image quality. • Image quality assessment enables standardization of clinical trial results across different datasets.

Computer-enhanced visual learning method: a paradigm to teach and document surgical skills.

PubMed

Maizels, Max; Mickelson, Jennie; Yerkes, Elizabeth; Maizels, Evelyn; Stork, Rachel; Young, Christine; Corcoran, Julia; Holl, Jane; Kaplan, William E

2009-09-01

Changes in health care are stimulating residency training programs to develop new methods for teaching surgical skills. We developed Computer-Enhanced Visual Learning (CEVL) as an innovative Internet-based learning and assessment tool. The CEVL method uses the educational procedures of deliberate practice and performance to teach and learn surgery in a stylized manner. CEVL is a learning and assessment tool that can provide students and educators with quantitative feedback on learning a specific surgical procedure. Methods involved examine quantitative data of improvement in surgical skills. Herein, we qualitatively describe the method and show how program directors (PDs) may implement this technique in their residencies. CEVL allows an operation to be broken down into teachable components. The process relies on feedback and remediation to improve performance, with a focus on learning that is applicable to the next case being performed. CEVL has been shown to be effective for teaching pediatric orchiopexy and is being adapted to additional adult and pediatric procedures and to office examination skills. The CEVL method is available to other residency training programs.

Computer-Enhanced Visual Learning Method: A Paradigm to Teach and Document Surgical Skills

PubMed Central

Maizels, Max; Mickelson, Jennie; Yerkes, Elizabeth; Maizels, Evelyn; Stork, Rachel; Young, Christine; Corcoran, Julia; Holl, Jane; Kaplan, William E.

2009-01-01

Innovation Changes in health care are stimulating residency training programs to develop new methods for teaching surgical skills. We developed Computer-Enhanced Visual Learning (CEVL) as an innovative Internet-based learning and assessment tool. The CEVL method uses the educational procedures of deliberate practice and performance to teach and learn surgery in a stylized manner. Aim of Innovation CEVL is a learning and assessment tool that can provide students and educators with quantitative feedback on learning a specific surgical procedure. Methods involved examine quantitative data of improvement in surgical skills. Herein, we qualitatively describe the method and show how program directors (PDs) may implement this technique in their residencies. Results CEVL allows an operation to be broken down into teachable components. The process relies on feedback and remediation to improve performance, with a focus on learning that is applicable to the next case being performed. CEVL has been shown to be effective for teaching pediatric orchiopexy and is being adapted to additional adult and pediatric procedures and to office examination skills. The CEVL method is available to other residency training programs. PMID:21975716

The Mediator Role of Perceived Stress in the Relationship between Academic Stress and Depressive Symptoms among E-Learning Students with Visual Impairments

ERIC Educational Resources Information Center

Lee, Soon Min; Oh, Yunjin

2017-01-01

Introduction: This study examined a mediator role of perceived stress on the prediction of the effects of academic stress on depressive symptoms among e-learning students with visual impairments. Methods: A convenience sample for this study was collected for three weeks from November to December in 2012 among students with visual impairments…

What Difference Does Curricular Integration Make? An Inquiry of Fifth Graders' Learning of History through the Use of Literacy and Visual Arts Skills

ERIC Educational Resources Information Center

Brugar, Kristy A.

2012-01-01

This is a quasi-experimental mixed methods study of a curriculum intervention focused on the interdisciplinary teaching of history, literacy, and the visual arts. In this study I address three questions: (1) How does students' learning in history change following their participation in an interdisciplinary history-literacy-visual arts…

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

3D Visualization of Machine Learning Algorithms with Astronomical Data

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2016-01-01

We present innovative machine learning (ML) methods using unsupervised clustering with minimum spanning trees (MSTs) to study 3D astronomical catalogs. Utilizing Python code to build trees based on galaxy catalogs, we can render the results with the visualization suite Blender to produce interactive 360 degree panoramic videos. The catalogs and their ML results can be explored in a 3D space using mobile devices, tablets or desktop browsers. We compare the statistics of the MST results to a number of machine learning methods relating to optimization and efficiency.

Deep imitation learning for 3D navigation tasks.

PubMed

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

MAVEN-SA: Model-Based Automated Visualization for Enhanced Situation Awareness

DTIC Science & Technology

2005-11-01

34 methods. But historically, as arts evolve, these how to methods become systematized and codified (e.g. the development and refinement of color theory ...schema (as necessary) 3. Draw inferences from new knowledge to support decision making process 33 Visual language theory suggests that humans process...informed by theories of learning. Over the years, many types of software have been developed to support student learning. The various types of

Physics Learning Strategies with Multi-touch Technology

NASA Astrophysics Data System (ADS)

Potter, Mark; Ilie, C.; Schofield, D.

2011-03-01

Advancements in technology have opened doorways to build new teaching and learning methods. Through conjunctive use of these technologies and methods, a classroom can be enriched to stimulate and improve student learning. The purpose of our research is to ascertain whether or not multi-touch technology enhances students' abilities to better comprehend and retain the knowledge taught in physics. At their basis, students learn via visual, aural, reading/writing, and kinesthetic styles. Labs provide for all but the aural style, while lectures lack kinesthetic learning. Pedagogical research indicates that kinesthetic learning is a fundamental, powerful, and ubiquitous learning style. By using multi-touch technology in lecture, not only can we accommodate kinesthetic learners, but we can also enrich the experiences of visual learners. Ushering to this wider array of students will hopefully lead to an increase in meaningful learning.

Hybrid image representation learning model with invariant features for basal cell carcinoma detection

NASA Astrophysics Data System (ADS)

Arevalo, John; Cruz-Roa, Angel; González, Fabio A.

2013-11-01

This paper presents a novel method for basal-cell carcinoma detection, which combines state-of-the-art methods for unsupervised feature learning (UFL) and bag of features (BOF) representation. BOF, which is a form of representation learning, has shown a good performance in automatic histopathology image classi cation. In BOF, patches are usually represented using descriptors such as SIFT and DCT. We propose to use UFL to learn the patch representation itself. This is accomplished by applying a topographic UFL method (T-RICA), which automatically learns visual invariance properties of color, scale and rotation from an image collection. These learned features also reveals these visual properties associated to cancerous and healthy tissues and improves carcinoma detection results by 7% with respect to traditional autoencoders, and 6% with respect to standard DCT representations obtaining in average 92% in terms of F-score and 93% of balanced accuracy.

Making Visual Arts Learning Visible in a Generalist Elementary School Classroom

ERIC Educational Resources Information Center

Wright, Susan; Watkins, Marnee; Grant, Gina

2017-01-01

This article presents the story of one elementary school teacher's shift in art praxis through her involvement in a research project aimed at facilitating participatory arts-based communities of practice. Qualitative methods and social constructivism informed Professional Learning Interventions (PLIs) involving: (1) a visual arts workshop, (2)…

Learning Sorting Algorithms through Visualization Construction

ERIC Educational Resources Information Center

Cetin, Ibrahim; Andrews-Larson, Christine

2016-01-01

Recent increased interest in computational thinking poses an important question to researchers: What are the best ways to teach fundamental computing concepts to students? Visualization is suggested as one way of supporting student learning. This mixed-method study aimed to (i) examine the effect of instruction in which students constructed…

Deep visual-semantic for crowded video understanding

NASA Astrophysics Data System (ADS)

Deng, Chunhua; Zhang, Junwen

2018-03-01

Visual-semantic features play a vital role for crowded video understanding. Convolutional Neural Networks (CNNs) have experienced a significant breakthrough in learning representations from images. However, the learning of visualsemantic features, and how it can be effectively extracted for video analysis, still remains a challenging task. In this study, we propose a novel visual-semantic method to capture both appearance and dynamic representations. In particular, we propose a spatial context method, based on the fractional Fisher vector (FV) encoding on CNN features, which can be regarded as our main contribution. In addition, to capture temporal context information, we also applied fractional encoding method on dynamic images. Experimental results on the WWW crowed video dataset demonstrate that the proposed method outperform the state of the art.

Detection of longitudinal visual field progression in glaucoma using machine learning.

PubMed

Yousefi, Siamak; Kiwaki, Taichi; Zheng, Yuhui; Suigara, Hiroki; Asaoka, Ryo; Murata, Hiroshi; Lemij, Hans; Yamanishi, Kenji

2018-06-16

Global indices of standard automated perimerty are insensitive to localized losses, while point-wise indices are sensitive but highly variable. Region-wise indices sit in between. This study introduces a machine-learning-based index for glaucoma progression detection that outperforms global, region-wise, and point-wise indices. Development and comparison of a prognostic index. Visual fields from 2085 eyes of 1214 subjects were used to identify glaucoma progression patterns using machine learning. Visual fields from 133 eyes of 71 glaucoma patients were collected 10 times over 10 weeks to provide a no-change, test-retest dataset. The parameters of all methods were identified using visual field sequences in the test-retest dataset to meet fixed 95% specificity. An independent dataset of 270 eyes of 136 glaucoma patients and survival analysis were utilized to compare methods. The time to detect progression in 25% of the eyes in the longitudinal dataset using global mean deviation (MD) was 5.2 years (95% confidence interval, 4.1 - 6.5 years); 4.5 years (4.0 - 5.5) using region-wise, 3.9 years (3.5 - 4.6) using point-wise, and 3.5 years (3.1 - 4.0) using machine learning analysis. The time until 25% of eyes showed subsequently confirmed progression after two additional visits were included were 6.6 years (5.6 - 7.4 years), 5.7 years (4.8 - 6.7), 5.6 years (4.7 - 6.5), and 5.1 years (4.5 - 6.0) for global, region-wise, point-wise, and machine learning analyses, respectively. Machine learning analysis detects progressing eyes earlier than other methods consistently, with or without confirmation visits. In particular, machine learning detects more slowly progressing eyes than other methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education

PubMed Central

Nilsson, Gunnar; Zary, Nabil

2014-01-01

Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data with possible future implications on healthcare education. It also opens a new direction in medical education informatics research. PMID:25469323

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education.

PubMed

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2014-01-01

Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data with possible future implications on healthcare education. It also opens a new direction in medical education informatics research.

Learning receptor positions from imperfectly known motions

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Mulligan, Jeffrey B.

1990-01-01

An algorithm is described for learning image interpolation functions for sensor arrays whose sensor positions are somewhat disordered. The learning is based on failures of translation invariance, so it does not require knowledge of the images being presented to the visual system. Previously reported implementations of the method assumed the visual system to have precise knowledge of the translations. It is demonstrated that translation estimates computed from the imperfectly interpolated images can have enough accuracy to allow the learning process to converge to a correct interpolation.

Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

ERIC Educational Resources Information Center

Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

2014-01-01

This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

English Language Learners: Experiences of Teachers of Students with Visual Impairments Who Work with This Population

ERIC Educational Resources Information Center

Topor, Irene; Rosenblum, L. Penny

2013-01-01

Introduction: This article presents a study that gathered data from 66 teachers of students with visual impairments about their preparation to work with children who are visually impaired and are learning English, and their knowledge of instructional strategies and methods of instruction. Methods: An online five-part survey was available to…

Retrieval evaluation and distance learning from perceived similarity between endomicroscopy videos.

PubMed

André, Barbara; Vercauteren, Tom; Buchner, Anna M; Wallace, Michael B; Ayache, Nicholas

2011-01-01

Evaluating content-based retrieval (CBR) is challenging because it requires an adequate ground-truth. When the available groundtruth is limited to textual metadata such as pathological classes, retrieval results can only be evaluated indirectly, for example in terms of classification performance. In this study we first present a tool to generate perceived similarity ground-truth that enables direct evaluation of endomicroscopic video retrieval. This tool uses a four-points Likert scale and collects subjective pairwise similarities perceived by multiple expert observers. We then evaluate against the generated ground-truth a previously developed dense bag-of-visual-words method for endomicroscopic video retrieval. Confirming the results of previous indirect evaluation based on classification, our direct evaluation shows that this method significantly outperforms several other state-of-the-art CBR methods. In a second step, we propose to improve the CBR method by learning an adjusted similarity metric from the perceived similarity ground-truth. By minimizing a margin-based cost function that differentiates similar and dissimilar video pairs, we learn a weight vector applied to the visual word signatures of videos. Using cross-validation, we demonstrate that the learned similarity distance is significantly better correlated with the perceived similarity than the original visual-word-based distance.

Investigating Verbal and Visual Auditory Learning After Conformal Radiation Therapy for Childhood Ependymoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di Pinto, Marcos; Conklin, Heather M.; Li Chenghong

Purpose: The primary objective of this study was to determine whether children with localized ependymoma experience a decline in verbal or visual-auditory learning after conformal radiation therapy (CRT). The secondary objective was to investigate the impact of age and select clinical factors on learning before and after treatment. Methods and Materials: Learning in a sample of 71 patients with localized ependymoma was assessed with the California Verbal Learning Test (CVLT-C) and the Visual-Auditory Learning Test (VAL). Learning measures were administered before CRT, at 6 months, and then yearly for a total of 5 years. Results: There was no significant declinemore » on measures of verbal or visual-auditory learning after CRT; however, younger age, more surgeries, and cerebrospinal fluid shunting did predict lower scores at baseline. There were significant longitudinal effects (improved learning scores after treatment) among older children on the CVLT-C and children that did not receive pre-CRT chemotherapy on the VAL. Conclusion: There was no evidence of global decline in learning after CRT in children with localized ependymoma. Several important implications from the findings include the following: (1) identification of and differentiation among variables with transient vs. long-term effects on learning, (2) demonstration that children treated with chemotherapy before CRT had greater risk of adverse visual-auditory learning performance, and (3) establishment of baseline and serial assessment as critical in ascertaining necessary sensitivity and specificity for the detection of modest effects.« less

Visual Thinking Strategies: Using Art to Deepen Learning across School Disciplines

ERIC Educational Resources Information Center

Yenawine, Philip

2013-01-01

"What's going on in this picture?" With this one question and a carefully chosen work of art, teachers can start their students down a path toward deeper learning and other skills now encouraged by the Common Core State Standards. The Visual Thinking Strategies (VTS) teaching method has been successfully implemented in schools,…

ICT Accessibility and Usability to Support Learning of Visually-Impaired Students in Tanzania

ERIC Educational Resources Information Center

Eligi, Innosencia; Mwantimwa, Kelefa

2017-01-01

The main objective of this study was to assess the accessibility and usability of Information and Communication Technology facilities to facilitate learning among visually-impaired students at the University of Dar es Salaam (UDSM). The study employed a mixed methods design in gathering, processing and analysing quantitative and qualitative data.…

Making a Case for Using Visual Inquiry Discussion in Preparing Elementary Social Studies Teachers

ERIC Educational Resources Information Center

Johnson, Cathy M.

2013-01-01

This dissertation research examines a teacher educator's instructional practices and preservice teachers' learning in two elementary social studies methods courses. As self-study, it focuses on learning to teach preservice teachers how to select and use visual images to teacher history and social studies. The research uses the Grossman Framework…

Visual Speech Perception in Children with Language Learning Impairments

ERIC Educational Resources Information Center

Knowland, Victoria C. P.; Evans, Sam; Snell, Caroline; Rosen, Stuart

2016-01-01

Purpose: The purpose of the study was to assess the ability of children with developmental language learning impairments (LLIs) to use visual speech cues from the talking face. Method: In this cross-sectional study, 41 typically developing children (mean age: 8 years 0 months, range: 4 years 5 months to 11 years 10 months) and 27 children with…

The Effect of Visual Variability on the Learning of Academic Concepts

ERIC Educational Resources Information Center

Bourgoyne, Ashley; Alt, Mary

2017-01-01

Purpose: The purpose of this study was to identify effects of variability of visual input on development of conceptual representations of academic concepts for college-age students with normal language (NL) and those with language-learning disabilities (LLD). Method: Students with NL (n = 11) and LLD (n = 11) participated in a computer-based…

Perceptions of Teachers of Students with Visual Impairments regarding Assistive Technology: A Follow-Up Study to a University Course

ERIC Educational Resources Information Center

Kamei-Hannan, Cheryl; Howe, Jon; Herrera, Robyn Rene; Erin, Jane N.

2012-01-01

Introduction: The study presented here examined the learning outcomes of graduate students in visual impairment who were enrolled in an assistive technology course in three university programs. Methods: The students' perceptions of learning were evaluated using pre- and posttests administered during the course. A follow-up questionnaire was…

Learning Styles of Medical Students - Implications in Education

PubMed Central

BUŞAN, ALINA-MIHAELA

2014-01-01

Background: The term “learning style” refers to the fact that each person has a different way of accumulating knowledge. While some prefer listening to learn better, others need to write or they only need to read the text or see a picture to later remember. According to Fleming and Mills the learning styles can be classified in Visual, Auditory and Kinesthetic. There is no evidence that teaching according to the learning style can help a person, yet this cannot be ignored. Subjects and methods: In this study, a number of 230 medical students were questioned in order to determine their learning style. Results: We determined that 73% of the students prefer one learning style, 22% prefer to learn using equally two learning style, while the rest prefer three learning styles. According to this study the distribution of the learning styles is as following: 33% visual, 26% auditory, 14% kinesthetic, 12% visual and auditory styles equally, 6% visual and kinesthetic, 4% auditory and kinesthetic and 5% all three styles. 32 % of the students that participated at this study are from UMF Craiova, 32% from UMF Carol Davila, 11% University of Medicine T Popa, Iasi, 9% UMF Cluj Iulius Hatieganu. Discussions: The way medical students learn is different from the general population. This is why it is important when teaching to considerate how the students learn in order to facilitate the learning PMID:25729590

Effectiveness of Program Visualization: A Case Study with the ViLLE Tool

ERIC Educational Resources Information Center

Rajala, Teemu; Laakso, Mikko-Jussi; Kaila, Erkki; Salakoski, Tapio

2008-01-01

Program visualization is one of the various methods developed over the years to aid novices with their difficulties in learning to program. It consists of different graphical--often animated--and textual objects, visualizing the execution of programs. The aim of program visualization is to enhance students' understanding of different areas of…

Top-Down Visual Saliency via Joint CRF and Dictionary Learning.

PubMed

Yang, Jimei; Yang, Ming-Hsuan

2017-03-01

Top-down visual saliency is an important module of visual attention. In this work, we propose a novel top-down saliency model that jointly learns a Conditional Random Field (CRF) and a visual dictionary. The proposed model incorporates a layered structure from top to bottom: CRF, sparse coding and image patches. With sparse coding as an intermediate layer, CRF is learned in a feature-adaptive manner; meanwhile with CRF as the output layer, the dictionary is learned under structured supervision. For efficient and effective joint learning, we develop a max-margin approach via a stochastic gradient descent algorithm. Experimental results on the Graz-02 and PASCAL VOC datasets show that our model performs favorably against state-of-the-art top-down saliency methods for target object localization. In addition, the dictionary update significantly improves the performance of our model. We demonstrate the merits of the proposed top-down saliency model by applying it to prioritizing object proposals for detection and predicting human fixations.

Analysis of the critical thinking process of junior high school students in solving geometric problems by utilizing the v-a-k learning styles model

NASA Astrophysics Data System (ADS)

Hananto, R. B.; Kusmayadi, T. A.; Riyadi

2018-05-01

The research aims to identify the critical thinking process of students in solving geometry problems. The geometry problem selected in this study was the building of flat side room (cube). The critical thinking process was implemented to visual, auditory and kinesthetic learning styles. This research was a descriptive analysis research using qualitative method. The subjects of this research were 3 students selected by purposive sampling consisting of visual, auditory, and kinesthetic learning styles. Data collection was done through test, interview, and observation. The results showed that the students' critical thinking process in identifying and defining steps for each learning style were similar in solving problems. The critical thinking differences were seen in enumerate, analyze, list, and self-correct steps. It was also found that critical thinking process of students with kinesthetic learning style was better than visual and auditory learning styles.

Good Features to Correlate for Visual Tracking

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Alatan, A. Aydin

2018-05-01

During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of trackers significantly affect the performance of visual tracking. The ultimate goal is to utilize robust features invariant to any kind of appearance change of the object, while predicting the object location as properly as in the case of no appearance change. As the deep learning based methods have emerged, the study of learning features for specific tasks has accelerated. For instance, discriminative visual tracking methods based on deep architectures have been studied with promising performance. Nevertheless, correlation filter based (CFB) trackers confine themselves to use the pre-trained networks which are trained for object classification problem. To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated. In order to learn the proposed model, a novel and efficient backpropagation algorithm is presented based on the loss function of the network. The proposed learning framework enables the network model to be flexible for a custom design. Moreover, it alleviates the dependency on the network trained for classification. Extensive performance analysis shows the efficacy of the proposed custom design in the CFB tracking framework. By fine-tuning the convolutional parts of a state-of-the-art network and integrating this model to a CFB tracker, which is the top performing one of VOT2016, 18% increase is achieved in terms of expected average overlap, and tracking failures are decreased by 25%, while maintaining the superiority over the state-of-the-art methods in OTB-2013 and OTB-2015 tracking datasets.

Learning style-based teaching harvests a superior comprehension of respiratory physiology.

PubMed

Anbarasi, M; Rajkumar, G; Krishnakumar, S; Rajendran, P; Venkatesan, R; Dinesh, T; Mohan, J; Venkidusamy, S

2015-09-01

Students entering medical college generally show vast diversity in their school education. It becomes the responsibility of teachers to motivate students and meet the needs of all diversities. One such measure is teaching students in their own preferred learning style. The present study was aimed to incorporate a learning style-based teaching-learning program for medical students and to reveal its significance and utility. Learning styles of students were assessed online using the visual-auditory-kinesthetic (VAK) learning style self-assessment questionnaire. When respiratory physiology was taught, students were divided into three groups, namely, visual (n = 34), auditory (n = 44), and kinesthetic (n = 28), based on their learning style. A fourth group (the traditional group; n = 40) was formed by choosing students randomly from the above three groups. Visual, auditory, and kinesthetic groups were taught following the appropriate teaching-learning strategies. The traditional group was taught via the routine didactic lecture method. The effectiveness of this intervention was evaluated by a pretest and two posttests, posttest 1 immediately after the intervention and posttest 2 after a month. In posttest 1, one-way ANOVA showed a significant statistical difference (P=0.005). Post hoc analysis showed significance between the kinesthetic group and traditional group (P=0.002). One-way ANOVA showed a significant difference in posttest 2 scores (P < 0.0001). Post hoc analysis showed significance between the three learning style-based groups compared with the traditional group [visual vs. traditional groups (p=0.002), auditory vs. traditional groups (p=0.03), and Kinesthetic vs. traditional groups (p=0.001)]. This study emphasizes that teaching methods tailored to students' style of learning definitely improve their understanding, performance, and retrieval of the subject. Copyright © 2015 The American Physiological Society.

Learning style preferences and their influence on students' problem solving in kinematics observed by eye-tracking method

NASA Astrophysics Data System (ADS)

Kekule, Martina

2017-01-01

The article presents eye-tracking method and its using for observing students when they solve problems from kinematics. Particularly, multiple-choice items in TUG-K test by Robert Beichner. Moreover, student's preference for visual way of learning as a possible influential aspect is proofed and discussed. Learning Style Inventory by Dunn, Dunn&Price was administered to students in order to find out their preferences. More than 20 high school and college students about 20 years old took part in the research. Preferred visual way of learning in contrast to the other ways of learning (audio, tactile, kinesthetic) shows very slight correlation with the total score of the test, none correlation with the average fixation duration and slight correlation with average fixation count on a task and average total visit duration on a task.

Nurses' learning styles: promoting better integration of theory into practice.

PubMed

Frankel, Andrew

In a climate where nurses' roles are expanding, underpinning knowledge is increasingly important. To explore staff preferences for learning and highlight the importance of recognising individual learning styles. A questionnaire was carried out with 61 nurses in an independent health and social care provider, achieving a response rate of 100%. Staff mainly prefer visual or kinaesthetic learning. This indicates the current training programme is not meeting their needs. The learning environment is recognised as having an impact in either encouraging or impeding a positive learning experience. A range of learning theories, concepts and approaches can be used to build and manage effective learning environments. Staff often prefer a visual learning style. Increased emphasis should be given to work-based learning rather than classroom-based teaching methods.

Yoga-teaching protocol adapted for children with visual impairment

PubMed Central

Mohanty, Soubhagyalaxmi; Hankey, Alex; Pradhan, Balaram; Ranjita, Rajashree

2016-01-01

Context: Childhood visual deficiency impairs children's neuro-psychomotor development, considerably affecting physical, mental, social, and emotional health. Yoga's multifaceted approach may help children with visual impairment (VI) to cope with their challenges. Aim: This study aimed to develop a special protocol for teaching yoga to children with VI, and to evaluate their preferred method of learning. Methods: The study was carried out at Ramana Maharishi Academy for the Blind, Bengaluru, South India. Forty-one students volunteered to learn yoga practices, and classes were held weekly 5 days, 1 hr per session for 16 weeks. The study introduced a new method using a sequence of five teaching steps: verbal instructions, tactile modeling, step-by-step teaching, learning in a group, and physical guidance. A questionnaire concerning the preferred steps of learning was then given to each student, and verbal answers were obtained. Results: A total of 33 (out of 41), aged 11.97 ± 1.94, 15 girls and 18 boys responded. Twenty-six (78.79%) chose physical guidance as their most favored learning mode. Conclusions: Specially designed protocol may pave the way to impart yoga in an exciting and comfortable way to children with VI. More studies are needed to further investigate the effectiveness of this new yoga protocol in similar settings. PMID:27512318

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

Implicit Statistical Learning and Language Skills in Bilingual Children

ERIC Educational Resources Information Center

Yim, Dongsun; Rudoy, John

2013-01-01

Purpose: Implicit statistical learning in 2 nonlinguistic domains (visual and auditory) was used to investigate (a) whether linguistic experience influences the underlying learning mechanism and (b) whether there are modality constraints in predicting implicit statistical learning with age and language skills. Method: Implicit statistical learning…

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

Discovery learning model with geogebra assisted for improvement mathematical visual thinking ability

NASA Astrophysics Data System (ADS)

Juandi, D.; Priatna, N.

2018-05-01

The main goal of this study is to improve the mathematical visual thinking ability of high school student through implementation the Discovery Learning Model with Geogebra Assisted. This objective can be achieved through study used quasi-experimental method, with non-random pretest-posttest control design. The sample subject of this research consist of 62 senior school student grade XI in one of school in Bandung district. The required data will be collected through documentation, observation, written tests, interviews, daily journals, and student worksheets. The results of this study are: 1) Improvement students Mathematical Visual Thinking Ability who obtain learning with applied the Discovery Learning Model with Geogebra assisted is significantly higher than students who obtain conventional learning; 2) There is a difference in the improvement of students’ Mathematical Visual Thinking ability between groups based on prior knowledge mathematical abilities (high, medium, and low) who obtained the treatment. 3) The Mathematical Visual Thinking Ability improvement of the high group is significantly higher than in the medium and low groups. 4) The quality of improvement ability of high and low prior knowledge is moderate category, in while the quality of improvement ability in the high category achieved by student with medium prior knowledge.

Enhanced HMAX model with feedforward feature learning for multiclass categorization.

PubMed

Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

2015-01-01

In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

Data Mining and Machine Learning Models for Predicting Drug Likeness and Their Disease or Organ Category.

PubMed

Yosipof, Abraham; Guedes, Rita C; García-Sosa, Alfonso T

2018-01-01

Data mining approaches can uncover underlying patterns in chemical and pharmacological property space decisive for drug discovery and development. Two of the most common approaches are visualization and machine learning methods. Visualization methods use dimensionality reduction techniques in order to reduce multi-dimension data into 2D or 3D representations with a minimal loss of information. Machine learning attempts to find correlations between specific activities or classifications for a set of compounds and their features by means of recurring mathematical models. Both models take advantage of the different and deep relationships that can exist between features of compounds, and helpfully provide classification of compounds based on such features or in case of visualization methods uncover underlying patterns in the feature space. Drug-likeness has been studied from several viewpoints, but here we provide the first implementation in chemoinformatics of the t-Distributed Stochastic Neighbor Embedding (t-SNE) method for the visualization and the representation of chemical space, and the use of different machine learning methods separately and together to form a new ensemble learning method called AL Boost. The models obtained from AL Boost synergistically combine decision tree, random forests (RF), support vector machine (SVM), artificial neural network (ANN), k nearest neighbors (kNN), and logistic regression models. In this work, we show that together they form a predictive model that not only improves the predictive force but also decreases bias. This resulted in a corrected classification rate of over 0.81, as well as higher sensitivity and specificity rates for the models. In addition, separation and good models were also achieved for disease categories such as antineoplastic compounds and nervous system diseases, among others. Such models can be used to guide decision on the feature landscape of compounds and their likeness to either drugs or other characteristics, such as specific or multiple disease-category(ies) or organ(s) of action of a molecule.

Degradation of learned skills. Static practice effectiveness for visual approach and landing skill retention

NASA Technical Reports Server (NTRS)

Sitterley, T. E.

1974-01-01

The effectivess of an improved static retraining method was evaluated for a simulated space vehicle approach and landing under instrument and visual flight conditions. Experienced pilots were trained and then tested after 4 months without flying to compare their performance using the improved method with three methods previously evaluated. Use of the improved static retraining method resulted in no practical or significant skill degradation and was found to be even more effective than methods using a dynamic presentation of visual cues. The results suggested that properly structured open loop methods of flight control task retraining are feasible.

Active and Passive Perceptual Learning in the Visually Impaired.

ERIC Educational Resources Information Center

Conrod, Beverley E.; And Others

1986-01-01

Active and passive perceptual training methods were tested with 30 macular degeneration patients to improve their residual vision. The main conclusion was that perceptual training may contribute to successful visual adjustment and that the effect of training is not limited to a particular level of visual impairment. (Author/CL)

Visual acuity and visual skills in Malaysian children with learning disabilities

PubMed Central

Muzaliha, Mohd-Nor; Nurhamiza, Buang; Hussein, Adil; Norabibas, Abdul-Rani; Mohd-Hisham-Basrun, Jaafar; Sarimah, Abdullah; Leo, Seo-Wei; Shatriah, Ismail

2012-01-01

Background: There is limited data in the literature concerning the visual status and skills in children with learning disabilities, particularly within the Asian population. This study is aimed to determine visual acuity and visual skills in children with learning disabilities in primary schools within the suburban Kota Bharu district in Malaysia. Methods: We examined 1010 children with learning disabilities aged between 8–12 years from 40 primary schools in the Kota Bharu district, Malaysia from January 2009 to March 2010. These children were identified based on their performance in a screening test known as the Early Intervention Class for Reading and Writing Screening Test conducted by the Ministry of Education, Malaysia. Complete ocular examinations and visual skills assessment included near point of convergence, amplitude of accommodation, accommodative facility, convergence break and recovery, divergence break and recovery, and developmental eye movement tests for all subjects. Results: A total of 4.8% of students had visual acuity worse than 6/12 (20/40), 14.0% had convergence insufficiency, 28.3% displayed poor accommodative amplitude, and 26.0% showed signs of accommodative infacility. A total of 12.1% of the students had poor convergence break, 45.7% displayed poor convergence recovery, 37.4% showed poor divergence break, and 66.3% were noted to have poor divergence recovery. The mean horizontal developmental eye movement was significantly prolonged. Conclusion: Although their visual acuity was satisfactory, nearly 30% of the children displayed accommodation problems including convergence insufficiency, poor accommodation, and accommodative infacility. Convergence and divergence recovery are the most affected visual skills in children with learning disabilities in Malaysia. PMID:23055674

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

Visual question answering using hierarchical dynamic memory networks

NASA Astrophysics Data System (ADS)

Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei

2018-04-01

Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.

Inferring Interaction Force from Visual Information without Using Physical Force Sensors.

PubMed

Hwang, Wonjun; Lim, Soo-Chul

2017-10-26

In this paper, we present an interaction force estimation method that uses visual information rather than that of a force sensor. Specifically, we propose a novel deep learning-based method utilizing only sequential images for estimating the interaction force against a target object, where the shape of the object is changed by an external force. The force applied to the target can be estimated by means of the visual shape changes. However, the shape differences in the images are not very clear. To address this problem, we formulate a recurrent neural network-based deep model with fully-connected layers, which models complex temporal dynamics from the visual representations. Extensive evaluations show that the proposed learning models successfully estimate the interaction forces using only the corresponding sequential images, in particular in the case of three objects made of different materials, a sponge, a PET bottle, a human arm, and a tube. The forces predicted by the proposed method are very similar to those measured by force sensors.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

PubMed

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

PubMed Central

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Transforming Clinical Imaging Data for Virtual Reality Learning Objects

ERIC Educational Resources Information Center

Trelease, Robert B.; Rosset, Antoine

2008-01-01

Advances in anatomical informatics, three-dimensional (3D) modeling, and virtual reality (VR) methods have made computer-based structural visualization a practical tool for education. In this article, the authors describe streamlined methods for producing VR "learning objects," standardized interactive software modules for anatomical sciences…

Generational Learning Style Preferences Based on Computer-Based Healthcare Training

ERIC Educational Resources Information Center

Knight, Michaelle H.

2016-01-01

Purpose. The purpose of this mixed-method study was to determine the degree of perceived differences for auditory, visual and kinesthetic learning styles of Traditionalist, Baby Boomers, Generation X and Millennial generational healthcare workers participating in technology-assisted healthcare training. Methodology. This mixed-method research…

Making perceptual learning practical to improve visual functions.

PubMed

Polat, Uri

2009-10-01

Task-specific improvement in performance after training is well established. The finding that learning is stimulus-specific and does not transfer well between different stimuli, between stimulus locations in the visual field, or between the two eyes has been used to support the notion that neurons or assemblies of neurons are modified at the earliest stage of cortical processing. However, a debate regarding the proposed mechanism underlying perceptual learning is an ongoing issue. Nevertheless, generalization of a trained task to other functions is an important key, for both understanding the neural mechanisms and the practical value of the training. This manuscript describes a structured perceptual learning method that previously used (amblyopia, myopia) and a novel technique and results that were applied for presbyopia. In general, subjects were trained for contrast detection of Gabor targets under lateral masking conditions. Training improved contrast sensitivity and diminished the lateral suppression when it existed (amblyopia). The improvement was transferred to unrelated functions such as visual acuity. The new results of presbyopia show substantial improvement of the spatial and temporal contrast sensitivity, leading to improved processing speed of target detection as well as reaction time. Consequently, the subjects, who were able to eliminate the need for reading glasses, benefited. Thus, here we show that the transfer of functions indicates that the specificity of improvement in the trained task can be generalized by repetitive practice of target detection, covering a sufficient range of spatial frequencies and orientations, leading to an improvement in unrelated visual functions. Thus, perceptual learning can be a practical method to improve visual functions in people with impaired or blurred vision.

Learning Rotation-Invariant Local Binary Descriptor.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors, such as local binary pattern and its variants, which require strong prior knowledge, local binary feature learning methods are more efficient and data-adaptive. Unlike existing learning-based local binary descriptors, such as compact binary face descriptor and simultaneous local binary feature learning and encoding, which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain RI-LBDs. As all the rotation variants of a patch belong to the same RBP, they are rotated into the same orientation and projected into the same binary descriptor. Then, we construct a codebook by a clustering method on the learned binary codes, and obtain a histogram feature for each image as the final representation. In order to exploit higher order statistical information, we extend our RI-LBD to the triple rotation-invariant co-occurrence local binary descriptor (TRICo-LBD) learning method, which learns a triple co-occurrence binary code for each local patch. Extensive experimental results on four different visual recognition tasks, including image patch matching, texture classification, face recognition, and scene classification, show that our RI-LBD and TRICo-LBD outperform most existing local descriptors.

Visual memories for perceived length are well preserved in older adults.

PubMed

Norman, J Farley; Holmin, Jessica S; Bartholomew, Ashley N

2011-09-15

Three experiments compared younger (mean age was 23.7years) and older (mean age was 72.1years) observers' ability to visually discriminate line length using both explicit and implicit standard stimuli. In Experiment 1, the method of constant stimuli (with an explicit standard) was used to determine difference thresholds, whereas the method of single stimuli (where the knowledge of the standard length was only implicit and learned from previous test stimuli) was used in Experiments 2 and 3. The study evaluated whether increases in age affect older observers' ability to learn, retain, and utilize effective implicit visual standards. Overall, the observers' length difference thresholds were 5.85% of the standard when the method of constant stimuli was used and improved to 4.39% of the standard for the method of single stimuli (a decrease of 25%). Both age groups performed similarly in all conditions. The results demonstrate that older observers retain the ability to create, remember, and utilize effective implicit standards from a series of visual stimuli. Copyright © 2011 Elsevier Ltd. All rights reserved.

Usage of stereoscopic visualization in the learning contents of rotational motion.

PubMed

Matsuura, Shu

2013-01-01

Rotational motion plays an essential role in physics even at an introductory level. In addition, the stereoscopic display of three-dimensional graphics includes is advantageous for the presentation of rotational motions, particularly for depth recognition. However, the immersive visualization of rotational motion has been known to lead to dizziness and even nausea for some viewers. Therefore, the purpose of this study is to examine the onset of nausea and visual fatigue when learning rotational motion through the use of a stereoscopic display. The findings show that an instruction method with intermittent exposure of the stereoscopic display and a simplification of its visual components reduced the onset of nausea and visual fatigue for the viewers, which maintained the overall effect of instantaneous spatial recognition.

Predicting Robust Learning with the Visual Form of the Moment-by-Moment Learning Curve

ERIC Educational Resources Information Center

Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M.

2013-01-01

We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…

An analysis of mathematical connection ability based on student learning style on visualization auditory kinesthetic (VAK) learning model with self-assessment

NASA Astrophysics Data System (ADS)

Apipah, S.; Kartono; Isnarto

2018-03-01

This research aims to analyze the quality of VAK learning with self-assessment toward the ability of mathematical connection performed by students and to analyze students’ mathematical connection ability based on learning styles in VAK learning model with self-assessment. This research applies mixed method type with concurrent embedded design. The subject of this research consists of VIII grade students from State Junior High School 9 Semarang who apply visual learning style, auditory learning style, and kinesthetic learning style. The data of learning style is collected by using questionnaires, the data of mathematical connection ability is collected by performing tests, and the data of self-assessment is collected by using assessment sheets. The quality of learning is qualitatively valued from planning stage, realization stage, and valuation stage. The result of mathematical connection ability test is analyzed quantitatively by mean test, conducting completeness test, mean differentiation test, and mean proportional differentiation test. The result of the research shows that VAK learning model results in well-qualified learning regarded from qualitative and quantitative sides. Students with visual learning style perform the highest mathematical connection ability, students with kinesthetic learning style perform average mathematical connection ability, and students with auditory learning style perform the lowest mathematical connection ability.

A visual tracking method based on improved online multiple instance learning

NASA Astrophysics Data System (ADS)

He, Xianhui; Wei, Yuxing

2016-09-01

Visual tracking is an active research topic in the field of computer vision and has been well studied in the last decades. The method based on multiple instance learning (MIL) was recently introduced into the tracking task, which can solve the problem that template drift well. However, MIL method has relatively poor performance in running efficiency and accuracy, due to its strong classifiers updating strategy is complicated, and the speed of the classifiers update is not always same with the change of the targets' appearance. In this paper, we present a novel online effective MIL (EMIL) tracker. A new update strategy for strong classifier was proposed to improve the running efficiency of MIL method. In addition, to improve the t racking accuracy and stability of the MIL method, a new dynamic mechanism for learning rate renewal of the classifier and variable search window were proposed. Experimental results show that our method performs good performance under the complex scenes, with strong stability and high efficiency.

The Learning Preferences among Nursing Students in the King Saud University in Saudi Arabia: A Cross-Sectional Survey

PubMed Central

Almutairi, Adel F.; Alhelih, Eyad M.; Alshehry, Abdualrahman S.

2017-01-01

Objective The present study aimed to identify the most common learning preferences among the nursing students in Saudi Arabia and to investigate the associations of certain demographic variables with the learning preferences. Methods All the undergraduate nursing students in the nursing college were requested to participate in this descriptive cross-sectional study. An Arabic version of the Felder-Silverman learning style model (FSLSM) questionnaire was used to examine the learning preferences among undergraduate nursing students. Results A total of 56 (43%) completed questionnaires were included in the final analysis. Results of the present study indicate that the most common learning preferences among the nursing students were visual (67.9%), followed by active (50%) and sequential (37.5%) learning preferences. The verbal style was the least common learning preference (3.6%) among the nursing students. There was no association between gender and learning preferences (p > .05). Conclusion The present study concluded that the visual, active, and sequential styles are the commonest learning preferences among the nursing students. The nursing educators should emphasize the use of this information in their teaching methods to improve learning skills among the nursing students. PMID:28630767

The Preference of Visualization in Teaching and Learning Absolute Value

ERIC Educational Resources Information Center

Konyalioglu, Alper Cihan; Aksu, Zeki; Senel, Esma Ozge

2012-01-01

Visualization is mostly despised although it complements and--sometimes--guides the analytical process. This study mainly investigates teachers' preferences concerning the use of the visualization method and determines the extent to which they encourage their students to make use of it within the problem-solving process. This study was conducted…

Small Private Online Research: A Proposal for A Numerical Methods Course Based on Technology Use and Blended Learning

ERIC Educational Resources Information Center

Cepeda, Francisco Javier Delgado

2017-01-01

This work presents a proposed model in blended learning for a numerical methods course evolved from traditional teaching into a research lab in scientific visualization. The blended learning approach sets a differentiated and flexible scheme based on a mobile setup and face to face sessions centered on a net of research challenges. Model is…

Kinespell: Kinesthetic Learning Activity and Assessment in a Digital Game-Based Learning Environment

NASA Astrophysics Data System (ADS)

Cariaga, Ada Angeli; Salvador, Jay Andrae; Solamo, Ma. Rowena; Feria, Rommel

Various approaches in learning are commonly classified into visual, auditory and kinesthetic (VAK) learning styles. One way of addressing the VAK learning styles is through game-based learning which motivates learners pursue knowledge holistically. The paper presents Kinespell, an unconventional method of learning through digital game-based learning. Kinespell is geared towards enhancing not only the learner’s spelling abilities but also the motor skills through utilizing wireless controllers. It monitors player’s performance through integrated assessment scheme. Results show that Kinespell may accommodate the VAK learning styles and is a promising alternative to established methods in learning and assessing students’ performance in Spelling.

Detecting Visually Observable Disease Symptoms from Faces.

PubMed

Wang, Kuan; Luo, Jiebo

2016-12-01

Recent years have witnessed an increasing interest in the application of machine learning to clinical informatics and healthcare systems. A significant amount of research has been done on healthcare systems based on supervised learning. In this study, we present a generalized solution to detect visually observable symptoms on faces using semi-supervised anomaly detection combined with machine vision algorithms. We rely on the disease-related statistical facts to detect abnormalities and classify them into multiple categories to narrow down the possible medical reasons of detecting. Our method is in contrast with most existing approaches, which are limited by the availability of labeled training data required for supervised learning, and therefore offers the major advantage of flagging any unusual and visually observable symptoms.

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

NASA Astrophysics Data System (ADS)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

Visual recognition and inference using dynamic overcomplete sparse learning.

PubMed

Murray, Joseph F; Kreutz-Delgado, Kenneth

2007-09-01

We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and expectation-driven segmentation. Using properties of biological vision for guidance, we posit a stochastic generative world model and from it develop a simplified world model (SWM) based on a tractable variational approximation that is designed to enforce sparse coding. Recent developments in computational methods for learning overcomplete representations (Lewicki & Sejnowski, 2000; Teh, Welling, Osindero, & Hinton, 2003) suggest that overcompleteness can be useful for visual tasks, and we use an overcomplete dictionary learning algorithm (Kreutz-Delgado, et al., 2003) as a preprocessing stage to produce accurate, sparse codings of images. Inference is performed by constructing a dynamic multilayer network with feedforward, feedback, and lateral connections, which is trained to approximate the SWM. Learning is done with a variant of the back-propagation-through-time algorithm, which encourages convergence to desired states within a fixed number of iterations. Vision tasks require large networks, and to make learning efficient, we take advantage of the sparsity of each layer to update only a small subset of elements in a large weight matrix at each iteration. Experiments on a set of rotated objects demonstrate various types of visual inference and show that increasing the degree of overcompleteness improves recognition performance in difficult scenes with occluded objects in clutter.

Local matrix learning in clustering and applications for manifold visualization.

PubMed

Arnonkijpanich, Banchar; Hasenfuss, Alexander; Hammer, Barbara

2010-05-01

Electronic data sets are increasing rapidly with respect to both, size of the data sets and data resolution, i.e. dimensionality, such that adequate data inspection and data visualization have become central issues of data mining. In this article, we present an extension of classical clustering schemes by local matrix adaptation, which allows a better representation of data by means of clusters with an arbitrary spherical shape. Unlike previous proposals, the method is derived from a global cost function. The focus of this article is to demonstrate the applicability of this matrix clustering scheme to low-dimensional data embedding for data inspection. The proposed method is based on matrix learning for neural gas and manifold charting. This provides an explicit mapping of a given high-dimensional data space to low dimensionality. We demonstrate the usefulness of this method for data inspection and manifold visualization. 2009 Elsevier Ltd. All rights reserved.

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

Enhanced learning of natural visual sequences in newborn chicks.

PubMed

Wood, Justin N; Prasad, Aditya; Goldman, Jason G; Wood, Samantha M W

2016-07-01

To what extent are newborn brains designed to operate over natural visual input? To address this question, we used a high-throughput controlled-rearing method to examine whether newborn chicks (Gallus gallus) show enhanced learning of natural visual sequences at the onset of vision. We took the same set of images and grouped them into either natural sequences (i.e., sequences showing different viewpoints of the same real-world object) or unnatural sequences (i.e., sequences showing different images of different real-world objects). When raised in virtual worlds containing natural sequences, newborn chicks developed the ability to recognize familiar images of objects. Conversely, when raised in virtual worlds containing unnatural sequences, newborn chicks' object recognition abilities were severely impaired. In fact, the majority of the chicks raised with the unnatural sequences failed to recognize familiar images of objects despite acquiring over 100 h of visual experience with those images. Thus, newborn chicks show enhanced learning of natural visual sequences at the onset of vision. These results indicate that newborn brains are designed to operate over natural visual input.

Implementation of dictionary pair learning algorithm for image quality improvement

NASA Astrophysics Data System (ADS)

Vimala, C.; Aruna Priya, P.

2018-04-01

This paper proposes an image denoising on dictionary pair learning algorithm. Visual information is transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmissions is often corrupted with noise. The received image needs processing before it can be used in applications. Image denoising involves the manipulation of the image data to produce a visually high quality image.

Adaptive low-rank subspace learning with online optimization for robust visual tracking.

PubMed

Liu, Risheng; Wang, Di; Han, Yuzhuo; Fan, Xin; Luo, Zhongxuan

2017-04-01

In recent years, sparse and low-rank models have been widely used to formulate appearance subspace for visual tracking. However, most existing methods only consider the sparsity or low-rankness of the coefficients, which is not sufficient enough for appearance subspace learning on complex video sequences. Moreover, as both the low-rank and the column sparse measures are tightly related to all the samples in the sequences, it is challenging to incrementally solve optimization problems with both nuclear norm and column sparse norm on sequentially obtained video data. To address above limitations, this paper develops a novel low-rank subspace learning with adaptive penalization (LSAP) framework for subspace based robust visual tracking. Different from previous work, which often simply decomposes observations as low-rank features and sparse errors, LSAP simultaneously learns the subspace basis, low-rank coefficients and column sparse errors to formulate appearance subspace. Within LSAP framework, we introduce a Hadamard production based regularization to incorporate rich generative/discriminative structure constraints to adaptively penalize the coefficients for subspace learning. It is shown that such adaptive penalization can significantly improve the robustness of LSAP on severely corrupted dataset. To utilize LSAP for online visual tracking, we also develop an efficient incremental optimization scheme for nuclear norm and column sparse norm minimizations. Experiments on 50 challenging video sequences demonstrate that our tracker outperforms other state-of-the-art methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of photography to support the learning process of science teachers of ninth through twelfth grades in the schools of Kuwait

NASA Astrophysics Data System (ADS)

Alenizi, Abdulaziz

The purpose of the study was to investigate the relevance of teachers in Kuwait when utilizing photographic aids in the classroom. Specifically, this study assessed learning outcomes of teachers amongst high school students in schools at Kuwait. The learning outcomes were then compared with teachers who are barred from using photographic aids. The research utilized a descriptive quantitative research design. The number of participants was limited to an acceptable number in the range of 250--300. Data were collected through a questionnaire and analyses were conducted using various types of statistical designs for interpretation, specifically Spearman correlation analysis. The study revealed that visual media such as images and photographs made it easy for the students to understand the concepts of science subjects, specifically biology, physics, and chemistry. Visual media should be included in the curriculum to enhance the comprehension level of students. The government of Kuwaiti, therefore, should to encourage the use of visual aids in schools to enhance learning. The research did not indicate a capacity of skills students and teachers can employ effectively when using visual aids. There also remains a gap between possessing the skills and applying them in the school. Benefits associated with visuals aids in teaching are evident in the study. With the adoption of audio-visual methods of learning, students are presented with opportunities to develop their own ideas and opinions, thus boosting their own interpersonal skills while at the same time questioning the authenticity and relevance of the concepts at hand. The major merit of audio-visual platforms in classroom learning is they cause students to break complex science concepts into finer components that can be easily understood.

Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex.

PubMed

Byers, Anna; Serences, John T

2014-09-01

Learning to better discriminate a specific visual feature (i.e., a specific orientation in a specific region of space) has been associated with plasticity in early visual areas (sensory modulation) and with improvements in the transmission of sensory information from early visual areas to downstream sensorimotor and decision regions (enhanced readout). However, in many real-world scenarios that require perceptual expertise, observers need to efficiently process numerous exemplars from a broad stimulus class as opposed to just a single stimulus feature. Some previous data suggest that perceptual learning leads to highly specific neural modulations that support the discrimination of specific trained features. However, the extent to which perceptual learning acts to improve the discriminability of a broad class of stimuli via the modulation of sensory responses in human visual cortex remains largely unknown. Here, we used functional MRI and a multivariate analysis method to reconstruct orientation-selective response profiles based on activation patterns in the early visual cortex before and after subjects learned to discriminate small offsets in a set of grating stimuli that were rendered in one of nine possible orientations. Behavioral performance improved across 10 training sessions, and there was a training-related increase in the amplitude of orientation-selective response profiles in V1, V2, and V3 when orientation was task relevant compared with when it was task irrelevant. These results suggest that generalized perceptual learning can lead to modified responses in the early visual cortex in a manner that is suitable for supporting improved discriminability of stimuli drawn from a large set of exemplars. Copyright © 2014 the American Physiological Society.

Matching Learning Style to Instructional Method: Effects on Comprehension

ERIC Educational Resources Information Center

Rogowsky, Beth A.; Calhoun, Barbara M.; Tallal, Paula

2015-01-01

While it is hypothesized that providing instruction based on individuals' preferred learning styles improves learning (i.e., reading for visual learners and listening for auditory learners, also referred to as the "meshing hypothesis"), after a critical review of the literature Pashler, McDaniel, Rohrer, and Bjork (2008) concluded that…

Using ICT-Supported Narratives in Teaching Science and Their Effects on Middle School Students

ERIC Educational Resources Information Center

Ekici, Fatma Taskin; Pekmezci, Sultan

2015-01-01

Effective and sustainable science education is enriched by the use of visuals, auditory, and tactile experiences. In order to provide effective learning, instruction needs to include multimodal approaches. Integrating ICT supported narrations into learning environments may provide effective and sustainable learning methods. Investigated in this…

Visual Thinking Routines: A Mixed Methods Approach Applied to Student Teachers at the American University in Dubai

ERIC Educational Resources Information Center

Gholam, Alain

2017-01-01

Visual thinking routines are principles based on several theories, approaches, and strategies. Such routines promote thinking skills, call for collaboration and sharing of ideas, and above all, make thinking and learning visible. Visual thinking routines were implemented in the teaching methodology graduate course at the American University in…

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

ERIC Educational Resources Information Center

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors…

Fostering First-Year Students' Engagement and Well-Being through Visual Narratives

ERIC Educational Resources Information Center

Everett, Michele C.

2017-01-01

This article reports on a qualitative study that explored the learning outcomes from an innovative instructional method, visual narratives, used in a first-year seminar. Fifty-three students enrolled in a mandatory first semester student success course were instructed to use visual images to tell the story of the first-year experience. Data…

Comprehensive Decision Tree Models in Bioinformatics

PubMed Central

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. Methods This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. Results The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. Conclusions The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics. PMID:22479449

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

PubMed

Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

2014-02-01

This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

The Effect of Visual of a Courseware towards Pre-University Students' Learning in Literature

NASA Astrophysics Data System (ADS)

Masri, Mazyrah; Wan Ahmad, Wan Fatimah; Nordin, Shahrina Md.; Sulaiman, Suziah

This paper highlights the effect of visual of a multimedia courseware, Black Cat Courseware (BC-C), developed for learning literature at a pre-university level in University Teknologi PETRONAS (UTP). The contents of the courseware are based on a Black Cat story which is covered in an English course at the university. The objective of this paper is to evaluate the usability and effectiveness of BC-C. A total of sixty foundation students were involved in the study. Quasi-experimental design was employed, forming two groups: experimental and control groups. The experimental group had to interact with BC-C as part of the learning activities while the control group used the conventional learning methods. The results indicate that the experimental group achieved a statistically significant compared to the control group in understanding the Black Cat story. The study result also proves that the effect of visual increases the students' performances in literature learning at a pre-university level.

Honeybees in a virtual reality environment learn unique combinations of colour and shape.

PubMed

Rusch, Claire; Roth, Eatai; Vinauger, Clément; Riffell, Jeffrey A

2017-10-01

Honeybees are well-known models for the study of visual learning and memory. Whereas most of our knowledge of learned responses comes from experiments using free-flying bees, a tethered preparation would allow fine-scale control of the visual stimuli as well as accurate characterization of the learned responses. Unfortunately, conditioning procedures using visual stimuli in tethered bees have been limited in their efficacy. In this study, using a novel virtual reality environment and a differential training protocol in tethered walking bees, we show that the majority of honeybees learn visual stimuli, and need only six paired training trials to learn the stimulus. We found that bees readily learn visual stimuli that differ in both shape and colour. However, bees learn certain components over others (colour versus shape), and visual stimuli are learned in a non-additive manner with the interaction of specific colour and shape combinations being crucial for learned responses. To better understand which components of the visual stimuli the bees learned, the shape-colour association of the stimuli was reversed either during or after training. Results showed that maintaining the visual stimuli in training and testing phases was necessary to elicit visual learning, suggesting that bees learn multiple components of the visual stimuli. Together, our results demonstrate a protocol for visual learning in restrained bees that provides a powerful tool for understanding how components of a visual stimulus elicit learned responses as well as elucidating how visual information is processed in the honeybee brain. © 2017. Published by The Company of Biologists Ltd.

Bag-of-features based medical image retrieval via multiple assignment and visual words weighting.

PubMed

Wang, Jingyan; Li, Yongping; Zhang, Ying; Wang, Chao; Xie, Honglan; Chen, Guoling; Gao, Xin

2011-11-01

Bag-of-features based approaches have become prominent for image retrieval and image classification tasks in the past decade. Such methods represent an image as a collection of local features, such as image patches and key points with scale invariant feature transform (SIFT) descriptors. To improve the bag-of-features methods, we first model the assignments of local descriptors as contribution functions, and then propose a novel multiple assignment strategy. Assuming the local features can be reconstructed by their neighboring visual words in a vocabulary, reconstruction weights can be solved by quadratic programming. The weights are then used to build contribution functions, resulting in a novel assignment method, called quadratic programming (QP) assignment. We further propose a novel visual word weighting method. The discriminative power of each visual word is analyzed by the sub-similarity function in the bin that corresponds to the visual word. Each sub-similarity function is then treated as a weak classifier. A strong classifier is learned by boosting methods that combine those weak classifiers. The weighting factors of the visual words are learned accordingly. We evaluate the proposed methods on medical image retrieval tasks. The methods are tested on three well-known data sets, i.e., the ImageCLEFmed data set, the 304 CT Set, and the basal-cell carcinoma image set. Experimental results demonstrate that the proposed QP assignment outperforms the traditional nearest neighbor assignment, the multiple assignment, and the soft assignment, whereas the proposed boosting based weighting strategy outperforms the state-of-the-art weighting methods, such as the term frequency weights and the term frequency-inverse document frequency weights.

Visualizing Science Dissections in 3D: Contextualizing Student Responses to Multidimensional Learning Materials in Science Dissections

NASA Astrophysics Data System (ADS)

Walker, Robin Annette

A series of dissection tasks was developed in this mixed-methods study of student self-explanations of their learning using actual and virtual multidimensional science dissections and visuo-spatial instruction. Thirty-five seventh-grade students from a science classroom (N = 20 Female/15 Male, Age =13 years) were assigned to three dissection environments instructing them to: (a) construct static paper designs of frogs, (b) perform active dissections with formaldehyde specimens, and (c) engage with interactive 3D frog visualizations and virtual simulations. This multi-methods analysis of student engagement with anchored dissection materials found learning gains on labeling exercises and lab assessments among most students. Data revealed that students who correctly utilized multimedia text and diagrams, individually and collaboratively, manipulated 3D tools more effectively and were better able to self-explain and complete their dissection work. Student questionnaire responses corroborated that they preferred learning how to dissect a frog using 3D multimedia instruction. The data were used to discuss the impact of 3D technologies, programs, and activities on student learning, spatial reasoning, and their interest in science. Implications were drawn regarding how to best integrate 3D visualizations into science curricula as innovative learning options for students, as instructional alternatives for teachers, and as mandated dissection choices for those who object to physical dissections in schools.

Effects of the Use of Two Visual Methods in Teaching College Chemistry to Non-Science Majors.

ERIC Educational Resources Information Center

Koechel, Loretta

This was a quantified study on the learning of certain theoretical topics in general chemistry as influenced by two methods of visual technique (single concept films, overhead projections). Four classes of chemistry students (non-science majors) registered in sections on a random basis, participated. Objective, multiple choice tests on each of the…

Detecting glaucomatous change in visual fields: Analysis with an optimization framework.

PubMed

Yousefi, Siamak; Goldbaum, Michael H; Varnousfaderani, Ehsan S; Belghith, Akram; Jung, Tzyy-Ping; Medeiros, Felipe A; Zangwill, Linda M; Weinreb, Robert N; Liebmann, Jeffrey M; Girkin, Christopher A; Bowd, Christopher

2015-12-01

Detecting glaucomatous progression is an important aspect of glaucoma management. The assessment of longitudinal series of visual fields, measured using Standard Automated Perimetry (SAP), is considered the reference standard for this effort. We seek efficient techniques for determining progression from longitudinal visual fields by formulating the problem as an optimization framework, learned from a population of glaucoma data. The longitudinal data from each patient's eye were used in a convex optimization framework to find a vector that is representative of the progression direction of the sample population, as a whole. Post-hoc analysis of longitudinal visual fields across the derived vector led to optimal progression (change) detection. The proposed method was compared to recently described progression detection methods and to linear regression of instrument-defined global indices, and showed slightly higher sensitivities at the highest specificities than other methods (a clinically desirable result). The proposed approach is simpler, faster, and more efficient for detecting glaucomatous changes, compared to our previously proposed machine learning-based methods, although it provides somewhat less information. This approach has potential application in glaucoma clinics for patient monitoring and in research centers for classification of study participants. Copyright © 2015 Elsevier Inc. All rights reserved.

Deep learning for neuroimaging: a validation study.

PubMed

Plis, Sergey M; Hjelm, Devon R; Salakhutdinov, Ruslan; Allen, Elena A; Bockholt, Henry J; Long, Jeffrey D; Johnson, Hans J; Paulsen, Jane S; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neuroimager's toolbox. Success of these methods is, in part, explained by the flexibility of deep learning models. However, this flexibility makes the process of porting to new areas a difficult parameter optimization problem. In this work we demonstrate our results (and feasible parameter ranges) in application of deep learning methods to structural and functional brain imaging data. These methods include deep belief networks and their building block the restricted Boltzmann machine. We also describe a novel constraint-based approach to visualizing high dimensional data. We use it to analyze the effect of parameter choices on data transformations. Our results show that deep learning methods are able to learn physiologically important representations and detect latent relations in neuroimaging data.

Visual Tracking Based on Extreme Learning Machine and Sparse Representation

PubMed Central

Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen

2015-01-01

The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. PMID:26506359

Using a visual programming language to bridge the cognitive gap between a novice's mental model and program code

NASA Astrophysics Data System (ADS)

Smith, Bryan J.

Current research suggests that many students do not know how to program very well at the conclusion of their introductory programming course. We believe that a reason novices have such difficulties learning programming is because engineering novices often learn through a lecture format where someone with programming knowledge lectures to novices, the novices attempt to absorb the content, and then reproduce it during exams. By primarily appealing to programming novices who prefer to understand visually, we research whether programming novices understand programming better if computer science concepts are presented using a visual programming language than if these programs are presented using a text-based programming language. This method builds upon previous research that suggests that most engineering students are visual learners, and we propose that using a flow-based visual programming language will address some of the most important and difficult topics to novices of programming. We use an existing flow-model tool, RAPTOR, to test this method, and share the program understanding results using this theory.

Reduced Mental Load in Learning a Motor Visual Task with Virtual 3D Method

ERIC Educational Resources Information Center

Dan, A.; Reiner, M.

2018-01-01

Distance learning is expanding rapidly, fueled by the novel technologies for shared recorded teaching sessions on the Web. Here, we ask whether 3D stereoscopic (3DS) virtual learning environment teaching sessions are more compelling than typical two-dimensional (2D) video sessions and whether this type of teaching results in superior learning. The…

Prose Learning in Children and Adults with Down Syndrome: The Use of Visual and Mental Image Strategies to Improve Recall

ERIC Educational Resources Information Center

de la Iglesia, Carmen J. F.; Buceta, M. Jose; Campos, Alfredo

2005-01-01

Background: Research indicates that the use of mental imagery is a rich source of possibilities for improving learning in participants with learning disabilities and intellectual disability. Method: We undertook two experiments designed to assess the effectiveness of using imagery in prose learning for participants with Down syndrome (DS). The…

[Which learning methods are expected for ultrasound training? Blended learning on trial].

PubMed

Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R

2014-10-01

Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (< 50%). A total of 176 trainees participated in this survey. Participants preferred an e-learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.

The Effects of Single and Dual Coded Multimedia Instructional Methods on Chinese Character Learning

ERIC Educational Resources Information Center

Wang, Ling

2013-01-01

Learning Chinese characters is a difficult task for adult English native speakers due to the significant differences between the Chinese and English writing system. The visuospatial properties of Chinese characters have inspired the development of instructional methods using both verbal and visual information based on the Dual Coding Theory. This…

The Keyword Method of Vocabulary Acquisition: An Experimental Evaluation.

ERIC Educational Resources Information Center

Griffith, Douglas

The keyword method of vocabulary acquisition is a two-step mnemonic technique for learning vocabulary terms. The first step, the acoustic link, generates a keyword based on the sound of the foreign word. The second step, the imagery link, ties the keyword to the meaning of the item to be learned, via an interactive visual image or other…

Comparing Analysis Frames for Visual Data Sets: Using Pupil Views Templates to Explore Perspectives of Learning

ERIC Educational Resources Information Center

Wall, Kate; Higgins, Steve; Remedios, Richard; Rafferty, Victoria; Tiplady, Lucy

2013-01-01

A key challenge of visual methodology is how to combine large-scale qualitative data sets with epistemologically acceptable and rigorous analysis techniques. The authors argue that a pragmatic approach drawing on ideas from mixed methods is helpful to open up the full potential of visual data. However, before one starts to "mix" the…

Comparative Effects of Seven Verbal-Visual Presentation Modes Upon Learning Tasks.

ERIC Educational Resources Information Center

Russell, Josiah Johnson, IV

A study was made of the comparative media effects upon teaching the component learning tasks of concept learning: classification, generalization, and application. The seven selected methods of presenting stimuli to the learners were: motion pictures with spoken verbal; motion pictures, silent; still pictures with spoken verbal; still pictures,…

Teaching and Learning with Computers! A Method for American Indian Bilingual Classrooms.

ERIC Educational Resources Information Center

Bennett, Ruth

Computer instruction can offer particular benefits to the Indian child. Computer use emphasizes the visual facets of learning, teaches language based skills needed for higher education and careers, and provides types of instruction proven effective with Indian children, such as private self-testing and cooperative learning. The Hupa, Yurok, Karuk,…

Dynamic visualizations as tools for supporting cosmological literacy

NASA Astrophysics Data System (ADS)

Buck, Zoe Elizabeth

My dissertation research is designed to improve access to STEM content through the development of cosmology visualizations that support all learners as they engage in cosmological sense-making. To better understand how to design visualizations that work toward breaking cycles of power and access in the sciences, I orient my work to following "meta-question": How might educators use visualizations to support diverse ways of knowing and learning in order to expand access to cosmology, and to science? In this dissertation, I address this meta-question from a pragmatic epistemological perspective, through a sociocultural lens, following three lines of inquiry: experimental methods (Creswell, 2003) with a focus on basic visualization design, activity analysis (Wells, 1996; Ash, 2001; Rahm, 2012) with a focus on culturally and linguistically diverse learners, and case study (Creswell, 2000) with a focus on expansive learning at a planetarium (Engestrom, 2001; Ash, 2014). My research questions are as follows, each of which corresponds to a self contained course of inquiry with its own design, data, analysis and results: 1) Can mediational cues like color affect the way learners interpret the content in a cosmology visualization? 2) How do cosmology visualizations support cosmological sense-making for diverse students? 3) What are the shared objects of dynamic networks of activity around visualization production and use in a large, urban planetarium and how do they affect learning? The result is a mixed-methods design (Sweetman, Badiee & Creswell, 2010) where both qualitative and quantitative data are used when appropriate to address my research goals. In the introduction I begin by establishing a theoretical framework for understanding visualizations within cultural historical activity theory (CHAT) and situating the chapters that follow within that framework. I also introduce the concept of cosmological literacy, which I define as the set of conceptual, semiotic and cognitive resources required to understand the scientific Universe on a cosmological scale. In the first chapter I use quantitative methods to investigate how 122 postsecondary learners relied on mediational cues like color to interpret dark matter in a cosmology visualization. My results show that color can have a profound effect on the way that audiences interpret a dynamic cosmology visualization, suggesting a closer look at learning activity. Thus in the second chapter I look at how the visualizations are used by small groups of community college students to make sense of cosmology visualizations. I present evidence that when we look past linguistic fluency, visualizations can scaffold cosmological sense-making, which I define as engaging in object-oriented learning activity mediated by concepts and practices associated with cosmological literacy. In the third chapter I present a case study of an urban planetarium trying to define its goals at a time of transition, during and after the development of a visualization-based planetarium show. My analysis reveals several historical contradictions that appear to impel a shift toward affective goals within the institution, and driving the implementation of visualizations, particularly in the context of immersive planetarium shows. I problematize this result by repositioning the shift toward affective goals in the context of equity and diversity. Finally in my conclusion I present broad recommendations for visualization design and implementation based on my findings.

Advocating for a Population-Specific Health Literacy for People With Visual Impairments.

PubMed

Harrison, Tracie; Lazard, Allison

2015-01-01

Health literacy, the ability to access, process, and understand health information, is enhanced by the visual senses among people who are typically sighted. Emotions, meaning, speed of knowledge transfer, level of attention, and degree of relevance are all manipulated by the visual design of health information when people can see. When consumers of health information are blind or visually impaired, they access, process, and understand their health information in a multitude of methods using a variety of accommodations depending upon their severity and type of impairment. They are taught, or they learn how, to accommodate their differences by using alternative sensory experiences and interpretations. In this article, we argue that due to the unique and powerful aspects of visual learning and due to the differences in knowledge creation when people are not visually oriented, health literacy must be considered a unique construct for people with visual impairment, which requires a distinctive theoretical basis for determining the impact of their mind-constructed representations of health.

"We Grew as We Grew": Visual Methods, Social Change and Collective Learning over Time

ERIC Educational Resources Information Center

Walsh, Shannon

2012-01-01

Educational research using visual methods has the power to transform the society in which we live and the communities in which we work. We must not naïvely imagine that having the desire to make change in people's lives will mean that it will happen, as sometimes there may be surprising, unintended negative repercussions as well. Other…

Max-margin multiattribute learning with low-rank constraint.

PubMed

Zhang, Qiang; Chen, Lin; Li, Baoxin

2014-07-01

Attribute learning has attracted a lot of interests in recent years for its advantage of being able to model high-level concepts with a compact set of midlevel attributes. Real-world objects often demand multiple attributes for effective modeling. Most existing methods learn attributes independently without explicitly considering their intrinsic relatedness. In this paper, we propose max margin multiattribute learning with low-rank constraint, which learns a set of attributes simultaneously, using only relative ranking of the attributes for the data. By learning all the attributes simultaneously through low-rank constraint, the proposed method is able to capture their intrinsic correlation for improved learning; by requiring only relative ranking, the method avoids restrictive binary labels of attributes that are often assumed by many existing techniques. The proposed method is evaluated on both synthetic data and real visual data including a challenging video data set. Experimental results demonstrate the effectiveness of the proposed method.

Auditory and Visual Working Memory Functioning in College Students with Attention-Deficit/Hyperactivity Disorder and/or Learning Disabilities.

PubMed

Liebel, Spencer W; Nelson, Jason M

2017-12-01

We investigated the auditory and visual working memory functioning in college students with attention-deficit/hyperactivity disorder, learning disabilities, and clinical controls. We examined the role attention-deficit/hyperactivity disorder subtype status played in working memory functioning. The unique influence that both domains of working memory have on reading and math abilities was investigated. A sample of 268 individuals seeking postsecondary education comprise four groups of the present study: 110 had an attention-deficit/hyperactivity disorder diagnosis only, 72 had a learning disability diagnosis only, 35 had comorbid attention-deficit/hyperactivity disorder and learning disability diagnoses, and 60 individuals without either of these disorders comprise a clinical control group. Participants underwent a comprehensive neuropsychological evaluation, and licensed psychologists employed a multi-informant, multi-method approach in obtaining diagnoses. In the attention-deficit/hyperactivity disorder only group, there was no difference between auditory and visual working memory functioning, t(100) = -1.57, p = .12. In the learning disability group, however, auditory working memory functioning was significantly weaker compared with visual working memory, t(71) = -6.19, p < .001, d = -0.85. Within the attention-deficit/hyperactivity disorder only group, there were no auditory or visual working memory functioning differences between participants with either a predominantly inattentive type or a combined type diagnosis. Visual working memory did not incrementally contribute to the prediction of academic achievement skills. Individuals with attention-deficit/hyperactivity disorder did not demonstrate significant working memory differences compared with clinical controls. Individuals with a learning disability demonstrated weaker auditory working memory than individuals in either the attention-deficit/hyperactivity or clinical control groups. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning.

PubMed

Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

2016-06-29

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images' spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines.

Mathematical disposition of junior high school students viewed from learning styles

NASA Astrophysics Data System (ADS)

Putra, Arief Karunia; Budiyono, Slamet, Isnandar

2017-08-01

The relevance of this study is the growth of character values for students in Indonesia. Mathematics is a subject that builds the character values for students. It can be seen from the students' confidence in answering mathematics problems, their persistent and resilience in mathematics task. In addition, students have a curiosity in mathematics and appreciate the usefulness of mathematics. In mathematics, it is called a mathematical disposition. One of the factors that can affect students' mathematical disposition is learning style. Each student has a dominant learning style. Three of the most popular ones are visual, auditory, and kinesthetic. The most important uses of learning styles is that it makes it easy for teachers to incorporate them into their teaching. The purpose of this study was to determine which one that gives better mathematical dispositions among students with learning styles of visual, auditory, or kinesthetic. The subjects were 150 students in Sleman regency. Data obtained through questionnaires. Based on data analysis that has been done with benchmark assessment method, it can be concluded that students with visual learning style has a mathematical disposition better than students with auditory and kinesthetic learning styles, while students with kinesthetic learning style has a mathematical disposition better than students with auditory learning style. These results can be used as a reference for students with individual learning styles to improve the mathematical positive disposition in the learning process of mathematics.

Visual management of large scale data mining projects.

PubMed

Shah, I; Hunter, L

2000-01-01

This paper describes a unified framework for visualizing the preparations for, and results of, hundreds of machine learning experiments. These experiments were designed to improve the accuracy of enzyme functional predictions from sequence, and in many cases were successful. Our system provides graphical user interfaces for defining and exploring training datasets and various representational alternatives, for inspecting the hypotheses induced by various types of learning algorithms, for visualizing the global results, and for inspecting in detail results for specific training sets (functions) and examples (proteins). The visualization tools serve as a navigational aid through a large amount of sequence data and induced knowledge. They provided significant help in understanding both the significance and the underlying biological explanations of our successes and failures. Using these visualizations it was possible to efficiently identify weaknesses of the modular sequence representations and induction algorithms which suggest better learning strategies. The context in which our data mining visualization toolkit was developed was the problem of accurately predicting enzyme function from protein sequence data. Previous work demonstrated that approximately 6% of enzyme protein sequences are likely to be assigned incorrect functions on the basis of sequence similarity alone. In order to test the hypothesis that more detailed sequence analysis using machine learning techniques and modular domain representations could address many of these failures, we designed a series of more than 250 experiments using information-theoretic decision tree induction and naive Bayesian learning on local sequence domain representations of problematic enzyme function classes. In more than half of these cases, our methods were able to perfectly discriminate among various possible functions of similar sequences. We developed and tested our visualization techniques on this application.

Learning Using Dynamic and Static Visualizations: Students' Comprehension, Prior Knowledge and Conceptual Status of a Biotechnological Method

ERIC Educational Resources Information Center

Yarden, Hagit; Yarden, Anat

2010-01-01

The importance of biotechnology education at the high-school level has been recognized in a number of international curriculum frameworks around the world. One of the most problematic issues in learning biotechnology has been found to be the biotechnological methods involved. Here, we examine the unique contribution of an animation of the…

Enhancing Learning Management Systems Utility for Blind Students: A Task-Oriented, User-Centered, Multi-Method Evaluation Technique

ERIC Educational Resources Information Center

Babu, Rakesh; Singh, Rahul

2013-01-01

This paper presents a novel task-oriented, user-centered, multi-method evaluation (TUME) technique and shows how it is useful in providing a more complete, practical and solution-oriented assessment of the accessibility and usability of Learning Management Systems (LMS) for blind and visually impaired (BVI) students. Novel components of TUME…

Effective Poster Teaching Strategy Towards Risk in Studying Fraud

ERIC Educational Resources Information Center

Aziz, Rozainun Haji Abdul; Jusoff, Kamaruzaman

2009-01-01

The aim of this paper is to present an alternative method and strategy in teaching and learning for the higher institution of learning. Poster presentation is an approach to introduce and deliver a lecture to create a different mood enticed by the visuals given. This poster presents a new approach of creativity as a method of teaching and learning…

Exploring Middle School Students' Representational Competence in Science: Development and Verification of a Framework for Learning with Visual Representations

NASA Astrophysics Data System (ADS)

Tippett, Christine Diane

Scientific knowledge is constructed and communicated through a range of forms in addition to verbal language. Maps, graphs, charts, diagrams, formulae, models, and drawings are just some of the ways in which science concepts can be represented. Representational competence---an aspect of visual literacy that focuses on the ability to interpret, transform, and produce visual representations---is a key component of science literacy and an essential part of science reading and writing. To date, however, most research has examined learning from representations rather than learning with representations. This dissertation consisted of three distinct projects that were related by a common focus on learning from visual representations as an important aspect of scientific literacy. The first project was the development of an exploratory framework that is proposed for use in investigations of students constructing and interpreting multimedia texts. The exploratory framework, which integrates cognition, metacognition, semiotics, and systemic functional linguistics, could eventually result in a model that might be used to guide classroom practice, leading to improved visual literacy, better comprehension of science concepts, and enhanced science literacy because it emphasizes distinct aspects of learning with representations that can be addressed though explicit instruction. The second project was a metasynthesis of the research that was previously conducted as part of the Explicit Literacy Instruction Embedded in Middle School Science project (Pacific CRYSTAL, http://www.educ.uvic.ca/pacificcrystal). Five overarching themes emerged from this case-to-case synthesis: the engaging and effective nature of multimedia genres, opportunities for differentiated instruction using multimodal strategies, opportunities for assessment, an emphasis on visual representations, and the robustness of some multimodal literacy strategies across content areas. The third project was a mixed-methods verification study that was conducted to refine and validate the theoretical framework. This study examined middle school students' representational competence and focused on students' creation of visual representations such as labelled diagrams, a form of representation commonly found in science information texts and textbooks. An analysis of the 31 Grade 6 participants' representations and semistructured interviews revealed five themes, each of which supports one or more dimensions of the exploratory framework: participants' use of color, participants' choice of representation (form and function), participants' method of planning for representing, participants' knowledge of conventions, and participants' selection of information to represent. Together, the results of these three projects highlight the need for further research on learning with rather than learning from representations.

Photovoice: Engaging Children with Autism and Their Teachers

ERIC Educational Resources Information Center

Carnahan, Christi R.

2006-01-01

Photovoice is an educational action research tool that embraces visual communication through photography and allows for individualization. In this article, the author describes how a visual teaching method known as photovoice led to improved engagement with peers and learning materials for two young boys with autism. The author also describes how…

Learning and Prediction of Slip from Visual Information

NASA Technical Reports Server (NTRS)

Angelova, Anelia; Matthies, Larry; Helmick, Daniel; Perona, Pietro

2007-01-01

This paper presents an approach for slip prediction from a distance for wheeled ground robots using visual information as input. Large amounts of slippage which can occur on certain surfaces, such as sandy slopes, will negatively affect rover mobility. Therefore, obtaining information about slip before entering such terrain can be very useful for better planning and avoiding these areas. To address this problem, terrain appearance and geometry information about map cells are correlated to the slip measured by the rover while traversing each cell. This relationship is learned from previous experience, so slip can be predicted remotely from visual information only. The proposed method consists of terrain type recognition and nonlinear regression modeling. The method has been implemented and tested offline on several off-road terrains including: soil, sand, gravel, and woodchips. The final slip prediction error is about 20%. The system is intended for improved navigation on steep slopes and rough terrain for Mars rovers.

Comparison on testability of visual acuity, stereo acuity and colour vision tests between children with learning disabilities and children without learning disabilities in government primary schools

PubMed Central

Abu Bakar, Nurul Farhana; Chen, Ai-Hong

2014-01-01

Context: Children with learning disabilities might have difficulties to communicate effectively and give reliable responses as required in various visual function testing procedures. Aims: The purpose of this study was to compare the testability of visual acuity using the modified Early Treatment Diabetic Retinopathy Study (ETDRS) and Cambridge Crowding Cards, stereo acuity using Lang Stereo test II and Butterfly stereo tests and colour perception using Colour Vision Test Made Easy (CVTME) and Ishihara's Test for Colour Deficiency (Ishihara Test) between children in mainstream classes and children with learning disabilities in special education classes in government primary schools. Materials and Methods: A total of 100 primary school children (50 children from mainstream classes and 50 children from special education classes) matched in age were recruited in this cross-sectional comparative study. The testability was determined by the percentage of children who were able to give reliable respond as required by the respective tests. ‘Unable to test’ was defined as inappropriate response or uncooperative despite best efforts of the screener. Results: The testability of the modified ETDRS, Butterfly stereo test and Ishihara test for respective visual function tests were found lower among children in special education classes (P < 0.001) but not in Cambridge Crowding Cards, Lang Stereo test II and CVTME. Conclusion: Non verbal or “matching” approaches were found to be more superior in testing visual functions in children with learning disabilities. Modifications of vision testing procedures are essential for children with learning disabilities. PMID:24008790

Visualizing the process of interaction in a 3D environment

NASA Astrophysics Data System (ADS)

Vaidya, Vivek; Suryanarayanan, Srikanth; Krishnan, Kajoli; Mullick, Rakesh

2007-03-01

As the imaging modalities used in medicine transition to increasingly three-dimensional data the question of how best to interact with and analyze this data becomes ever more pressing. Immersive virtual reality systems seem to hold promise in tackling this, but how individuals learn and interact in these environments is not fully understood. Here we will attempt to show some methods in which user interaction in a virtual reality environment can be visualized and how this can allow us to gain greater insight into the process of interaction/learning in these systems. Also explored is the possibility of using this method to improve understanding and management of ergonomic issues within an interface.

Learning To Recognize Visual Concepts: Development and Implementation of a Method for Texture Concept Acquisition Through Inductive Learning

DTIC Science & Technology

1993-01-01

Maria and My Parents, Helena and Andrzej IV ACKNOWLEDGMENTS I would like to first of all thank my advisor. Dr. Ryszard Michalski. who introduced...represent the current state of the art in machine learning methodology. The most popular method. the minimization of Bayes risk [ Duda and Hart. 1973]. is a...34 Pattern Recognition, Vol. 23, no. 3-4, pp. 291-309, 1990. Duda , O. and P. Hart, Pattern Classification and Scene Analysis, John Wiley & Sons. 1973

Drawing in nursing PBL.

PubMed

Chan, Zenobia C Y

2013-08-01

The implementation of art education in nursing is said to have positive effects on nursing students. Most studies applied visual art dialogues or object design, whereas the effectiveness of drawing as a teaching and learning method is rarely examined and discussed. This paper aimed to discuss the potential and effectiveness of drawing as a learning and teaching method. Four drawings which were created by Hong Kong nursing students are demonstrated and the students' perspectives of how drawing enhanced learning are shown in this paper. Topics on drawing as a fun teaching and learning method and the way it can enhance critical thinking and creativity are also discussed. In conclusion, the activity was a great success, and students enjoyed the learning process and reflected positive comments. However, we cannot conclude that drawing is an effective teaching and learning method based on a single paper, therefore more similar studies should be conducted to investigate this method. Copyright © 2012 Elsevier Ltd. All rights reserved.

Representational Distance Learning for Deep Neural Networks

PubMed Central

McClure, Patrick; Kriegeskorte, Nikolaus

2016-01-01

Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Representational spaces of the student and the teacher are characterized by representational distance matrices (RDMs). We propose representational distance learning (RDL), a stochastic gradient descent method that drives the RDMs of the student to approximate the RDMs of the teacher. We demonstrate that RDL is competitive with other transfer learning techniques for two publicly available benchmark computer vision datasets (MNIST and CIFAR-100), while allowing for architectural differences between student and teacher. By pulling the student's RDMs toward those of the teacher, RDL significantly improved visual classification performance when compared to baseline networks that did not use transfer learning. In the future, RDL may enable combined supervised training of deep neural networks using task constraints (e.g., images and category labels) and constraints from brain-activity measurements, so as to build models that replicate the internal representational spaces of biological brains. PMID:28082889

Representational Distance Learning for Deep Neural Networks.

PubMed

McClure, Patrick; Kriegeskorte, Nikolaus

2016-01-01

Deep neural networks (DNNs) provide useful models of visual representational transformations. We present a method that enables a DNN (student) to learn from the internal representational spaces of a reference model (teacher), which could be another DNN or, in the future, a biological brain. Representational spaces of the student and the teacher are characterized by representational distance matrices (RDMs). We propose representational distance learning (RDL), a stochastic gradient descent method that drives the RDMs of the student to approximate the RDMs of the teacher. We demonstrate that RDL is competitive with other transfer learning techniques for two publicly available benchmark computer vision datasets (MNIST and CIFAR-100), while allowing for architectural differences between student and teacher. By pulling the student's RDMs toward those of the teacher, RDL significantly improved visual classification performance when compared to baseline networks that did not use transfer learning. In the future, RDL may enable combined supervised training of deep neural networks using task constraints (e.g., images and category labels) and constraints from brain-activity measurements, so as to build models that replicate the internal representational spaces of biological brains.

Three visual techniques to enhance interprofessional learning.

PubMed

Parsell, G; Gibbs, T; Bligh, J

1998-07-01

Many changes in the delivery of healthcare in the UK have highlighted the need for healthcare professionals to learn to work together as teams for the benefit of patients. Whatever the profession or level, whether for postgraduate education and training, continuing professional development, or for undergraduates, learners should have an opportunity to learn about and with, other healthcare practitioners in a stimulating and exciting way. Learning to understand how people think, feel, and react, and the parts they play at work, both as professionals and individuals, can only be achieved through sensitive discussion and exchange of views. Teaching and learning methods must provide opportunities for this to happen. This paper describes three small-group teaching techniques which encourage a high level of learner collaboration and team-working. Learning content is focused on real-life health-care issues and strong visual images are used to stimulate lively discussion and debate. Each description includes the learning objectives of each exercise, basic equipment and resources, and learning outcomes.

Caudate nucleus reactivity predicts perceptual learning rate for visual feature conjunctions.

PubMed

Reavis, Eric A; Frank, Sebastian M; Tse, Peter U

2015-04-15

Useful information in the visual environment is often contained in specific conjunctions of visual features (e.g., color and shape). The ability to quickly and accurately process such conjunctions can be learned. However, the neural mechanisms responsible for such learning remain largely unknown. It has been suggested that some forms of visual learning might involve the dopaminergic neuromodulatory system (Roelfsema et al., 2010; Seitz and Watanabe, 2005), but this hypothesis has not yet been directly tested. Here we test the hypothesis that learning visual feature conjunctions involves the dopaminergic system, using functional neuroimaging, genetic assays, and behavioral testing techniques. We use a correlative approach to evaluate potential associations between individual differences in visual feature conjunction learning rate and individual differences in dopaminergic function as indexed by neuroimaging and genetic markers. We find a significant correlation between activity in the caudate nucleus (a component of the dopaminergic system connected to visual areas of the brain) and visual feature conjunction learning rate. Specifically, individuals who showed a larger difference in activity between positive and negative feedback on an unrelated cognitive task, indicative of a more reactive dopaminergic system, learned visual feature conjunctions more quickly than those who showed a smaller activity difference. This finding supports the hypothesis that the dopaminergic system is involved in visual learning, and suggests that visual feature conjunction learning could be closely related to associative learning. However, no significant, reliable correlations were found between feature conjunction learning and genotype or dopaminergic activity in any other regions of interest. Copyright © 2015 Elsevier Inc. All rights reserved.

Improving the performance of the amblyopic visual system

PubMed Central

Levi, Dennis M.; Li, Roger W.

2008-01-01

Experience-dependent plasticity is closely linked with the development of sensory function; however, there is also growing evidence for plasticity in the adult visual system. This review re-examines the notion of a sensitive period for the treatment of amblyopia in the light of recent experimental and clinical evidence for neural plasticity. One recently proposed method for improving the effectiveness and efficiency of treatment that has received considerable attention is ‘perceptual learning’. Specifically, both children and adults with amblyopia can improve their perceptual performance through extensive practice on a challenging visual task. The results suggest that perceptual learning may be effective in improving a range of visual performance and, importantly, the improvements may transfer to visual acuity. Recent studies have sought to explore the limits and time course of perceptual learning as an adjunct to occlusion and to investigate the neural mechanisms underlying the visual improvement. These findings, along with the results of new clinical trials, suggest that it might be time to reconsider our notions about neural plasticity in amblyopia. PMID:19008199

Visual memory and learning in extremely low-birth-weight/extremely preterm adolescents compared with controls: a geographic study.

PubMed

Molloy, Carly S; Wilson-Ching, Michelle; Doyle, Lex W; Anderson, Vicki A; Anderson, Peter J

2014-04-01

Contemporary data on visual memory and learning in survivors born extremely preterm (EP; <28 weeks gestation) or with extremely low birth weight (ELBW; <1,000 g) are lacking. Geographically determined cohort study of 298 consecutive EP/ELBW survivors born in 1991 and 1992, and 262 randomly selected normal-birth-weight controls. Visual learning and memory data were available for 221 (74.2%) EP/ELBW subjects and 159 (60.7%) controls. EP/ELBW adolescents exhibited significantly poorer performance across visual memory and learning variables compared with controls. Visual learning and delayed visual memory were particularly problematic and remained so after controlling for visual-motor integration and visual perception and excluding adolescents with neurosensory disability, and/or IQ <70. Male EP/ELBW adolescents or those treated with corticosteroids had poorer outcomes. EP/ELBW adolescents have poorer visual memory and learning outcomes compared with controls, which cannot be entirely explained by poor visual perceptual or visual constructional skills or intellectual impairment.

The role of visual representation in physics learning: dynamic versus static visualization

NASA Astrophysics Data System (ADS)

Suyatna, Agus; Anggraini, Dian; Agustina, Dina; Widyastuti, Dini

2017-11-01

This study aims to examine the role of visual representation in physics learning and to compare the learning outcomes of using dynamic and static visualization media. The study was conducted using quasi-experiment with Pretest-Posttest Control Group Design. The samples of this research are students of six classes at State Senior High School in Lampung Province. The experimental class received a learning using dynamic visualization and control class using static visualization media. Both classes are given pre-test and post-test with the same instruments. Data were tested with N-gain analysis, normality test, homogeneity test and mean difference test. The results showed that there was a significant increase of mean (N-Gain) learning outcomes (p <0.05) in both experimental and control classes. The averages of students’ learning outcomes who are using dynamic visualization media are significantly higher than the class that obtains learning by using static visualization media. It can be seen from the characteristics of visual representation; each visualization provides different understanding support for the students. Dynamic visual media is more suitable for explaining material related to movement or describing a process, whereas static visual media is appropriately used for non-moving physical phenomena and requires long-term observation.

Associative visual learning by tethered bees in a controlled visual environment.

PubMed

Buatois, Alexis; Pichot, Cécile; Schultheiss, Patrick; Sandoz, Jean-Christophe; Lazzari, Claudio R; Chittka, Lars; Avarguès-Weber, Aurore; Giurfa, Martin

2017-10-10

Free-flying honeybees exhibit remarkable cognitive capacities but the neural underpinnings of these capacities cannot be studied in flying insects. Conversely, immobilized bees are accessible to neurobiological investigation but display poor visual learning. To overcome this limitation, we aimed at establishing a controlled visual environment in which tethered bees walking on a spherical treadmill learn to discriminate visual stimuli video projected in front of them. Freely flying bees trained to walk into a miniature Y-maze displaying these stimuli in a dark environment learned the visual discrimination efficiently when one of them (CS+) was paired with sucrose and the other with quinine solution (CS-). Adapting this discrimination to the treadmill paradigm with a tethered, walking bee was successful as bees exhibited robust discrimination and preferred the CS+ to the CS- after training. As learning was better in the maze, movement freedom, active vision and behavioral context might be important for visual learning. The nature of the punishment associated with the CS- also affects learning as quinine and distilled water enhanced the proportion of learners. Thus, visual learning is amenable to a controlled environment in which tethered bees learn visual stimuli, a result that is important for future neurobiological studies in virtual reality.

On the Design and Development of a UML-Based Visual Environment for Novice Programmers

ERIC Educational Resources Information Center

Moor, Brian D.; Deek, Fadi P.

2006-01-01

Few beginners find learning to program easy. There are many factors at work in this phenomenon with some being simply inherent in the subject itself, while others have more to do with deficiencies in learning methods and resources. As a result, many programming environments, software applications, and learning tools have been developed to address…

Drawing in the blind and the sighted as a probe of cortical reorganization

NASA Astrophysics Data System (ADS)

Likova, Lora T.

2010-02-01

In contrast to other arts, such as music, there is a very little neuroimaging research on visual art and in particular - on drawing. Drawing - from artistic to technical - involves diverse aspects of spatial cognition, precise sensorimotor planning and control as well as a rich set of higher cognitive functions. A new method for learning the drawing skill in the blind that we have developed, and the technological advances of a multisensory MR-compatible drawing system, allowed us to run for the first time a comparative fMRI study on drawing in the blind and the sighted. In each population, we identified widely distributed cortical networks, extending from the occipital and temporal cortices, through the parietal to the frontal lobe. This is the first neuroimaging study of drawing in blind novices, as well as the first study on the learning to draw in either population. We sought to determine the cortical reorganization taking place as a result of learning to draw, despite the lack of visual input to the brains of the blind. Remarkably, we found massive recruitment of the visual cortex on learning to draw, although our subjects had no previous experience, but only a short training with our new drawing method. This finding implies a rapid, learning-based plasticity mechanism. We further proposed that the functional level of the brain reorganization in the blind may still differ from that in the sighted even in areas that overlap between the two populations, such as in the visual cortex. We tested this idea in the framework of saccadic suppression. A methodological innovation allowed us to estimate the retinotopic regions locations in the blind brain. Although the visual cortex of both groups was greatly recruited, only the sighted experienced dramatic suppression in hMT+ and V1, while there was no sign of an analogous process in the blind. This finding has important implications and suggests that the recruitment of the visual cortex in the blind does not assure a full functional parallel.

Self-development of visual space perception by learning from the hand

NASA Astrophysics Data System (ADS)

Chung, Jae-Moon; Ohnishi, Noboru

1998-10-01

Animals have been considered to develop ability for interpreting images captured on their retina by themselves gradually from their birth. For this they do not need external supervisor. We think that the visual function is obtained together with the development of hand reaching and grasping operations which are executed by active interaction with environment. On the viewpoint of hand teaches eye, this paper shows how visual space perception is developed in a simulated robot. The robot has simplified human-like structure used for hand-eye coordination. From the experimental results it may be possible to validate the method to describe how visual space perception of biological systems is developed. In addition the description gives a way to self-calibrate the vision of intelligent robot based on learn by doing manner without external supervision.

Repetitive Transcranial Direct Current Stimulation Induced Excitability Changes of Primary Visual Cortex and Visual Learning Effects-A Pilot Study.

PubMed

Sczesny-Kaiser, Matthias; Beckhaus, Katharina; Dinse, Hubert R; Schwenkreis, Peter; Tegenthoff, Martin; Höffken, Oliver

2016-01-01

Studies on noninvasive motor cortex stimulation and motor learning demonstrated cortical excitability as a marker for a learning effect. Transcranial direct current stimulation (tDCS) is a non-invasive tool to modulate cortical excitability. It is as yet unknown how tDCS-induced excitability changes and perceptual learning in visual cortex correlate. Our study aimed to examine the influence of tDCS on visual perceptual learning in healthy humans. Additionally, we measured excitability in primary visual cortex (V1). We hypothesized that anodal tDCS would improve and cathodal tDCS would have minor or no effects on visual learning. Anodal, cathodal or sham tDCS were applied over V1 in a randomized, double-blinded design over four consecutive days (n = 30). During 20 min of tDCS, subjects had to learn a visual orientation-discrimination task (ODT). Excitability parameters were measured by analyzing paired-stimulation behavior of visual-evoked potentials (ps-VEP) and by measuring phosphene thresholds (PTs) before and after the stimulation period of 4 days. Compared with sham-tDCS, anodal tDCS led to an improvement of visual discrimination learning (p < 0.003). We found reduced PTs and increased ps-VEP ratios indicating increased cortical excitability after anodal tDCS (PT: p = 0.002, ps-VEP: p = 0.003). Correlation analysis within the anodal tDCS group revealed no significant correlation between PTs and learning effect. For cathodal tDCS, no significant effects on learning or on excitability could be seen. Our results showed that anodal tDCS over V1 resulted in improved visual perceptual learning and increased cortical excitability. tDCS is a promising tool to alter V1 excitability and, hence, perceptual visual learning.

Deep learning with convolutional neural networks for EEG decoding and visualization

PubMed Central

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

An adult learning perspective on disability and microfinance: The case of Katureebe

PubMed Central

Nuwagaba, Ephraim L.

2016-01-01

Background Despite Uganda’s progress in promoting affirmative action for persons with disabilities and its strategy of using microfinance to fight poverty, access to microfinance services by persons with disabilities is still problematic due to barriers, characterised by discrepancies between policies and practices. Regarding education, the affirmative action in favour of learners with disabilities has not translated into actual learning opportunities due to personal and environmental barriers. Objectives The study on which this article is based investigated the non-formal and informal adult learning practices regarding microfinance that persons with disabilities engaged in. This article seeks to illuminate the barriers that a person with a visual impairment encountered while learning about and engaging with microfinance and the strategies that he developed to overcome them. Methods This was a case study, framed within the social model of disability and critical research paradigm. Data were collected through in-depth interviews of a person with visual impairment and observations of the environment in which adult learning and engagement with Savings and Credit Cooperative Organisations (SACCOs) occurred. Results Findings indicate that the person with a visual disability faced barriers to learning about microfinance services. He experienced barriers in an integrated manner and developed strategies to overcome these barriers. The barriers and strategies are theorised using the social model of disability. Conclusion The case of a person with visual impairment suggests that persons with disabilities face multiple barriers regarding microfinance, including social, psychological and educational. However, his own agency and attitudes were also of importance as they influenced his learning. Viewing these barriers as blockades can lead to non-participation in learning and engagement with microfinance whereas viewing them as surmountable hurdles can potentially motivate participants to succeed in learning about and engaging with microfinance. PMID:28730047

Electropalatographic Therapy for Children and Young People with Down's Syndrome

ERIC Educational Resources Information Center

Cleland, Joanne; Timmins, Claire; Wood, Sara E.; Hardcastle, William J.; Wishart, Jennifer G.

2009-01-01

Articulation disorders in Down's syndrome (DS) are prevalent and often intractable. Individuals with DS generally prefer visual to auditory methods of learning and may therefore find it beneficial to be given a visual model during speech intervention, such as that provided by electropalatography (EPG). In this study, participants with Down's…

What's Going on in This Picture? Visual Thinking Strategies and Adult Learning

ERIC Educational Resources Information Center

Landorf, Hilary

2006-01-01

The Visual Thinking Strategies (VTS) curriculum and teaching method uses art to help students think critically, listen attentively, communicate, and collaborate. VTS has been proven to enhance reading, writing, comprehension, and creative and analytical skills among students of all ages. The origins and procedures of the VTS curriculum are…

Visual Literacy: Does It Enhance Leadership Abilities Required for the Twenty-First Century?

ERIC Educational Resources Information Center

Bintz, Carol

2016-01-01

The twenty-first century hosts a well-established global economy, where leaders are required to have increasingly complex skills that include creativity, innovation, vision, relatability, critical thinking and well-honed communications methods. The experience gained by learning to be visually literate includes the ability to see, observe, analyze,…

Data Mining and Machine Learning Models for Predicting Drug Likeness and their Disease or Organ Category

NASA Astrophysics Data System (ADS)

Yosipof, Abraham; Guedes, Rita C.; García-Sosa, Alfonso T.

2018-05-01

Data mining approaches can uncover underlying patterns in chemical and pharmacological property space decisive for drug discovery and development. Two of the most common approaches are visualization and machine learning methods. Visualization methods use dimensionality reduction techniques in order to reduce multi-dimension data into 2D or 3D representations with a minimal loss of information. Machine learning attempts to find correlations between specific activities or classifications for a set of compounds and their features by means of recurring mathematical models. Both models take advantage of the different and deep relationships that can exist between features of compounds, and helpfully provide classification of compounds based on such features. Drug-likeness has been studied from several viewpoints, but here we provide the first implementation in chemoinformatics of the t-Distributed Stochastic Neighbor Embedding (t-SNE) method for the visualization and the representation of chemical space, and the use of different machine learning methods separately and together to form a new ensemble learning method called AL Boost. The models obtained from AL Boost synergistically combine decision tree, random forests (RF), support vector machine (SVM), artificial neuronal network (ANN), k nearest neighbors (kNN), and logistic regression models. In this work, we show that together they form a predictive model that not only improves the predictive force but also decreases bias. This resulted in a corrected classification rate of over 0.81, as well as higher sensitivity and specificity rates for the models. In addition, separation and good models were also achieved for disease categories such as antineoplastic compounds and nervous system diseases, among others. Such models can be used to guide decision on the feature landscape of compounds and their likeness to either drugs or other characteristics, such as specific or multiple disease-category(ies) or organ(s) of action of a molecule.

Visual discrimination transfer and modulation by biogenic amines in honeybees.

PubMed

Vieira, Amanda Rodrigues; Salles, Nayara; Borges, Marco; Mota, Theo

2018-05-10

For more than a century, visual learning and memory have been studied in the honeybee Apis mellifera using operant appetitive conditioning. Although honeybees show impressive visual learning capacities in this well-established protocol, operant training of free-flying animals cannot be combined with invasive protocols for studying the neurobiological basis of visual learning. In view of this, different attempts have been made to develop new classical conditioning protocols for studying visual learning in harnessed honeybees, though learning performance remains considerably poorer than that for free-flying animals. Here, we investigated the ability of honeybees to use visual information acquired during classical conditioning in a new operant context. We performed differential visual conditioning of the proboscis extension reflex (PER) followed by visual orientation tests in a Y-maze. Classical conditioning and Y-maze retention tests were performed using the same pair of perceptually isoluminant chromatic stimuli, to avoid the influence of phototaxis during free-flying orientation. Visual discrimination transfer was clearly observed, with pre-trained honeybees significantly orienting their flights towards the former positive conditioned stimulus (CS+), thus showing that visual memories acquired by honeybees are resistant to context changes between conditioning and the retention test. We combined this visual discrimination approach with selective pharmacological injections to evaluate the effect of dopamine and octopamine in appetitive visual learning. Both octopaminergic and dopaminergic antagonists impaired visual discrimination performance, suggesting that both these biogenic amines modulate appetitive visual learning in honeybees. Our study brings new insight into cognitive and neurobiological mechanisms underlying visual learning in honeybees. © 2018. Published by The Company of Biologists Ltd.

Visual and verbal learning deficits in Veterans with alcohol and substance use disorders.

PubMed

Bell, Morris D; Vissicchio, Nicholas A; Weinstein, Andrea J

2016-02-01

This study examined visual and verbal learning in the early phase of recovery for 48 Veterans with alcohol use (AUD) and substance use disorders (SUD, primarily cocaine and opiate abusers). Previous studies have demonstrated visual and verbal learning deficits in AUD, however little is known about the differences between AUD and SUD on these domains. Since the DSM-5 specifically identifies problems with learning in AUD and not in SUD, and problems with visual and verbal learning have been more prevalent in the literature for AUD than SUD, we predicted that people with AUD would be more impaired on measures of visual and verbal learning than people with SUD. Participants were enrolled in a comprehensive rehabilitation program and were assessed within the first 5 weeks of abstinence. Verbal learning was measured using the Hopkins Verbal Learning Test (HVLT) and visual learning was assessed using the Brief Visuospatial Memory Test (BVMT). Results indicated significantly greater decline in verbal learning on the HVLT across the three learning trials for AUD participants but not for SUD participants (F=4.653, df=48, p=0.036). Visual learning was less impaired than verbal learning across learning trials for both diagnostic groups (F=0.197, df=48, p=0.674); there was no significant difference between groups on visual learning (F=0.401, df=14, p=0.538). Older Veterans in the early phase of recovery from AUD may have difficulty learning new verbal information. Deficits in verbal learning may reduce the effectiveness of verbally-based interventions such as psycho-education. Published by Elsevier Ireland Ltd.

Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning

PubMed Central

Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

2016-01-01

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images’ spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines. PMID:27367703

Web-based interactive 3D visualization as a tool for improved anatomy learning.

PubMed

Petersson, Helge; Sinkvist, David; Wang, Chunliang; Smedby, Orjan

2009-01-01

Despite a long tradition, conventional anatomy education based on dissection is declining. This study tested a new virtual reality (VR) technique for anatomy learning based on virtual contrast injection. The aim was to assess whether students value this new three-dimensional (3D) visualization method as a learning tool and what value they gain from its use in reaching their anatomical learning objectives. Several 3D vascular VR models were created using an interactive segmentation tool based on the "virtual contrast injection" method. This method allows users, with relative ease, to convert computer tomography or magnetic resonance images into vivid 3D VR movies using the OsiriX software equipped with the CMIV CTA plug-in. Once created using the segmentation tool, the image series were exported in Quick Time Virtual Reality (QTVR) format and integrated within a web framework of the Educational Virtual Anatomy (EVA) program. A total of nine QTVR movies were produced encompassing most of the major arteries of the body. These movies were supplemented with associated information, color keys, and notes. The results indicate that, in general, students' attitudes towards the EVA-program were positive when compared with anatomy textbooks, but results were not the same with dissections. Additionally, knowledge tests suggest a potentially beneficial effect on learning.

Intellectual Innovation: A Paradigm Shift in Workforce Development

DTIC Science & Technology

2016-08-01

varying learning abilities and disabilities , and require vary­ ing lengths of time to learn and Although experienced employees need less training...training courses or objectives, organizations should develop a tailored plan that focuses on what each employee needs to learn . Time and effort are... learns in a different way, which can include the use of visual and/or audible as well as the hands­on method of instruc­ tion. Employees also have

Learning viewpoint invariant perceptual representations from cluttered images.

PubMed

Spratling, Michael W

2005-05-01

In order to perform object recognition, it is necessary to form perceptual representations that are sufficiently specific to distinguish between objects, but that are also sufficiently flexible to generalize across changes in location, rotation, and scale. A standard method for learning perceptual representations that are invariant to viewpoint is to form temporal associations across image sequences showing object transformations. However, this method requires that individual stimuli be presented in isolation and is therefore unlikely to succeed in real-world applications where multiple objects can co-occur in the visual input. This paper proposes a simple modification to the learning method that can overcome this limitation and results in more robust learning of invariant representations.

Implementing Vision Research in Special Needs Education

ERIC Educational Resources Information Center

Wilhelmsen, Gunvor Birkeland; Aanstad, Monica L.; Leirvik, Eva Iren B.

2015-01-01

This article presents experiences from vision research implemented in education and argues for the need for teachers with visual competence and insight into suitable methods for stimulation and learning. A new type of continuing professional development (CPD) focuses on the role of vision in children's learning and development, the consequences of…

LATUX: An Iterative Workflow for Designing, Validating, and Deploying Learning Analytics Visualizations

ERIC Educational Resources Information Center

Martinez-Maldonado, Roberto; Pardo, Abelardo; Mirriahi, Negin; Yacef, Kalina; Kay, Judy; Clayphan, Andrew

2015-01-01

Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now…

Quality knowledge of science through virtual laboratory as an element of visualization

NASA Astrophysics Data System (ADS)

Rizman Herga, Natasa

Doctoral dissertation discusses the use of virtual laboratory for learning and teaching chemical concepts at science classes in the seventh grade of primary school. The dissertation has got a two-part structure. In the first theoretical part presents a general platform of teaching science in elementary school, teaching forms and methods of teaching and among modern approaches we highlight experimental work. Particular emphasis was placed on the use of new technologies in education and virtual laboratories. Scientific findings on the importance of visualization of science concepts and their triple nature of their understanding are presented. These findings represent a fundamental foundation of empirical research presented in the second part of the doctoral dissertation, whose basic purpose was to examine the effectiveness of using virtual laboratory for teaching and learning chemical contents at science from students' point of view on knowledge and interest. We designed a didactic experiment in which 225 pupils participated. The work was conducted in the experimental and control group. Prior to its execution, the existing school practice among science and chemistry teachers was analysed in terms of: (1) inclusion of experimental work as a fundamental method of active learning chemical contents, (2) the use of visualization methods in the classroom and (3) the use of a virtual laboratory. The main findings of the empirical research, carried out in the school year 2012/2013, in which 48 science and chemistry participated, are that teachers often include experimental work when teaching chemical contents. Interviewed science teachers use a variety of visualization methods when presenting science concepts, in particular computer animation and simulation. Using virtual laboratory as a new strategy for teaching and learning chemical contents is not common because teachers lack special-didactic skills, enabling them to use virtual reality technology. Based on the didactic experiment, carried out over a period of two school years (2012/2013 and 2013/2014) in ten primary schools, the effectiveness of teaching carried out with the support of a virtual laboratory was analyzed. The obtained empirical findings reveal that the use of virtual laboratory has great impact on the pupils' knowledge and interest. At the end of the experiment, pupils in the experimental group had an advantage according to knowledge of chemical contents in science. Also, the use of virtual laboratory had an impact on the sustainability of the acquired knowledge of science contents and pupils' interest at the end of the experiment, because the pupils in the experimental group had a higher interest for learning science contents. The didactic experiment determined, that the use of virtual laboratory enables quality learning and teaching chemical contents of science, because it allows: (1) experimental work as an active learning method, (2) the visualization of abstract concepts and phenomena, (3) dynamic sub micro presentations (4) integration of all three levels of the chemical concept as a whole and (5) positively impacts pupils' interest, knowledge and sustainability of the acquired knowledge.

Public Computer Assisted Learning Facilities for Children with Visual Impairment: Universal Design for Inclusive Learning

ERIC Educational Resources Information Center

Siu, Kin Wai Michael; Lam, Mei Seung

2012-01-01

Although computer assisted learning (CAL) is becoming increasingly popular, people with visual impairment face greater difficulty in accessing computer-assisted learning facilities. This is primarily because most of the current CAL facilities are not visually impaired friendly. People with visual impairment also do not normally have access to…

Effects of Computer-Based Visual Representation on Mathematics Learning and Cognitive Load

ERIC Educational Resources Information Center

Yung, Hsin I.; Paas, Fred

2015-01-01

Visual representation has been recognized as a powerful learning tool in many learning domains. Based on the assumption that visual representations can support deeper understanding, we examined the effects of visual representations on learning performance and cognitive load in the domain of mathematics. An experimental condition with visual…

Developing Learning Tool of Control System Engineering Using Matrix Laboratory Software Oriented on Industrial Needs

NASA Astrophysics Data System (ADS)

Isnur Haryudo, Subuh; Imam Agung, Achmad; Firmansyah, Rifqi

2018-04-01

The purpose of this research is to develop learning media of control technique using Matrix Laboratory software with industry requirement approach. Learning media serves as a tool for creating a better and effective teaching and learning situation because it can accelerate the learning process in order to enhance the quality of learning. Control Techniques using Matrix Laboratory software can enlarge the interest and attention of students, with real experience and can grow independent attitude. This research design refers to the use of research and development (R & D) methods that have been modified by multi-disciplinary team-based researchers. This research used Computer based learning method consisting of computer and Matrix Laboratory software which was integrated with props. Matrix Laboratory has the ability to visualize the theory and analysis of the Control System which is an integration of computing, visualization and programming which is easy to use. The result of this instructional media development is to use mathematical equations using Matrix Laboratory software on control system application with DC motor plant and PID (Proportional-Integral-Derivative). Considering that manufacturing in the field of Distributed Control systems (DCSs), Programmable Controllers (PLCs), and Microcontrollers (MCUs) use PID systems in production processes are widely used in industry.

Threat captures attention but does not affect learning of contextual regularities.

PubMed

Yamaguchi, Motonori; Harwood, Sarah L

2017-04-01

Some of the stimulus features that guide visual attention are abstract properties of objects such as potential threat to one's survival, whereas others are complex configurations such as visual contexts that are learned through past experiences. The present study investigated the two functions that guide visual attention, threat detection and learning of contextual regularities, in visual search. Search arrays contained images of threat and non-threat objects, and their locations were fixed on some trials but random on other trials. Although they were irrelevant to the visual search task, threat objects facilitated attention capture and impaired attention disengagement. Search time improved for fixed configurations more than for random configurations, reflecting learning of visual contexts. Nevertheless, threat detection had little influence on learning of the contextual regularities. The results suggest that factors guiding visual attention are different from factors that influence learning to guide visual attention.

Degradation of learned skills: Effectiveness of practice methods on visual approach and landing skill retention

NASA Technical Reports Server (NTRS)

Sitterley, T. E.; Zaitzeff, L. P.; Berge, W. A.

1972-01-01

Flight control and procedural task skill degradation, and the effectiveness of retraining methods were evaluated for a simulated space vehicle approach and landing under instrument and visual flight conditions. Fifteen experienced pilots were trained and then tested after 4 months either without the benefits of practice or with static rehearsal, dynamic rehearsal or with dynamic warmup practice. Performance on both the flight control and procedure tasks degraded significantly after 4 months. The rehearsal methods effectively countered procedure task skill degradation, while dynamic rehearsal or a combination of static rehearsal and dynamic warmup practice was required for the flight control tasks. The quality of the retraining methods appeared to be primarily dependent on the efficiency of visual cue reinforcement.

Effectiveness of Video Demonstration over Conventional Methods in Teaching Osteology in Anatomy.

PubMed

Viswasom, Angela A; Jobby, Abraham

2017-02-01

Technology and its applications are the most happening things in the world. So, is it in the field of medical education. This study was an evaluation of whether the conventional methods can compete with the test of technology. A comparative study of traditional method of teaching osteology in human anatomy with an innovative visual aided method. The study was conducted on 94 students admitted to MBBS 2014 to 2015 batch of Travancore Medical College. The students were divided into two academically validated groups. They were taught using conventional and video demonstrational techniques in a systematic manner. Post evaluation tests were conducted. Analysis of the mark pattern revealed that the group taught using traditional method scored better when compared to the visual aided method. Feedback analysis showed that, the students were able to identify bony features better with clear visualisation and three dimensional view when taught using the video demonstration method. The students identified visual aided method as the more interesting one for learning which helped them in applying the knowledge gained. In most of the questions asked, the two methods of teaching were found to be comparable on the same scale. As the study ends, we discover that, no new technique can be substituted for time tested techniques of teaching and learning. The ideal method would be incorporating newer multimedia techniques into traditional classes.

Effects of Fasting During Ramadan Month on Cognitive Function in Muslim Athletes

PubMed Central

Tian, Ho-Heng; Aziz, Abdul-Rashid; Png, Weileen; Wahid, Mohamed Faizul; Yeo, Donald; Constance Png, Ai-Li

2011-01-01

Purpose Our study aimed to profile the effect of fasting during the Ramadan month on cognitive function in a group of healthy Muslim athletes. Methods Eighteen male athletes underwent computerized neuropsychological testing during (fasting) and after (non-fasting) Ramadan. Diet was standardized, and tests were performed at 0900h and 1600h to characterize potential time-of-day (TOD) interactions. Psychomotor function (processing speed), vigilance (visual attention), visual learning and memory, working memory (executive function), verbal learning and memory were examined. Capillary glucose, body temperature, urine specific gravity, and sleep volume were also recorded. Results Fasting effects were observed for psychomotor function (Cohen's d=1.3, P=0.01) and vigilance (d=0.6, P=0.004), with improved performance at 0900h during fasting; verbal learning and memory was poorer at 1600h (d=-0.8, P=0.03). A TOD effect was present for psychomotor function (d=-0.4, P<0.001), visual learning (d=-0.5, P=0.04), verbal learning and memory (d=-1.3, P=0.001), with poorer performances at 1600h. There was no significant fasting effect on visual learning and working memory. Conclusions Our results show that the effect of fasting on cognition is heterogeneous and domain-specific. Performance in functions requiring sustained rapid responses was better in the morning, declining in the late afternoon, whereas performance in non-speed dependent accuracy measures was more resilient. PMID:22375233

Perceptual Learning as a potential treatment for amblyopia: a mini-review

PubMed Central

Levi, Dennis M.; Li, Roger W.

2009-01-01

Amblyopia is a developmental abnormality that results from physiological alterations in the visual cortex and impairs form vision. It is a consequence of abnormal binocular visual experience during the “sensitive period” early in life. While amblyopia can often be reversed when treated early, conventional treatment is generally not undertaken in older children and adults. A number of studies over the last twelve years or so suggest that Perceptual Learning (PL) may provide an important new method for treating amblyopia. The aim of this mini-review is to provide a critical review and “meta-analysis” of perceptual learning in adults and children with amblyopia, with a view to extracting principles that might make PL more effective and efficient. Specifically we evaluate: What factors influence the outcome of perceptual learning?Specificity and generalization – two sides of the coin.Do the improvements last?How does PL improve visual function?Should PL be part of the treatment armamentarium? A review of the extant studies makes it clear that practicing a visual task results in a long-lasting improvement in performance in an amblyopic eye. The improvement is generally strongest for the trained eye, task, stimulus and orientation, but appears to have a broader spatial frequency bandwidth than in normal vision. Importantly, practicing on a variety of different tasks and stimuli seems to transfer to improved visual acuity. Perceptual learning operates via a reduction of internal neural noise and/or through more efficient use of the stimulus information by retuning the weighting of the information. The success of PL raises the question of whether it should become a standard part of the armamentarium for the clinical treatment of amblyopia, and suggests several important principles for effective perceptual learning in amblyopia. PMID:19250947

The Box-and-Dot Method: A Simple Strategy for Counting Significant Figures

NASA Astrophysics Data System (ADS)

Stephenson, W. Kirk

2009-08-01

A visual method for counting significant digits is presented. This easy-to-learn (and easy-to-teach) method, designated the box-and-dot method, uses the device of "boxing" significant figures based on two simple rules, then counting the number of digits in the boxes.

Lesion classification using clinical and visual data fusion by multiple kernel learning

NASA Astrophysics Data System (ADS)

Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf

2014-03-01

To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.

Design and outcomes of an acoustic data visualization seminar.

PubMed

Robinson, Philip W; Pätynen, Jukka; Haapaniemi, Aki; Kuusinen, Antti; Leskinen, Petri; Zan-Bi, Morley; Lokki, Tapio

2014-01-01

Recently, the Department of Media Technology at Aalto University offered a seminar entitled Applied Data Analysis and Visualization. The course used spatial impulse response measurements from concert halls as the context to explore high-dimensional data visualization methods. Students were encouraged to represent source and receiver positions, spatial aspects, and temporal development of sound fields, frequency characteristics, and comparisons between halls, using animations and interactive graphics. The primary learning objectives were for the students to translate their skills across disciplines and gain a working understanding of high-dimensional data visualization techniques. Accompanying files present examples of student-generated, animated and interactive visualizations.

Decomposition and extraction: a new framework for visual classification.

PubMed

Fang, Yuqiang; Chen, Qiang; Sun, Lin; Dai, Bin; Yan, Shuicheng

2014-08-01

In this paper, we present a novel framework for visual classification based on hierarchical image decomposition and hybrid midlevel feature extraction. Unlike most midlevel feature learning methods, which focus on the process of coding or pooling, we emphasize that the mechanism of image composition also strongly influences the feature extraction. To effectively explore the image content for the feature extraction, we model a multiplicity feature representation mechanism through meaningful hierarchical image decomposition followed by a fusion step. In particularly, we first propose a new hierarchical image decomposition approach in which each image is decomposed into a series of hierarchical semantical components, i.e, the structure and texture images. Then, different feature extraction schemes can be adopted to match the decomposed structure and texture processes in a dissociative manner. Here, two schemes are explored to produce property related feature representations. One is based on a single-stage network over hand-crafted features and the other is based on a multistage network, which can learn features from raw pixels automatically. Finally, those multiple midlevel features are incorporated by solving a multiple kernel learning task. Extensive experiments are conducted on several challenging data sets for visual classification, and experimental results demonstrate the effectiveness of the proposed method.

Correlation of the summary method with learning styles.

PubMed

Sarikcioglu, Levent; Senol, Yesim; Yildirim, Fatos B; Hizay, Arzu

2011-09-01

The summary is the last part of the lesson but one of the most important. We aimed to study the relationship between the preference of the summary method (video demonstration, question-answer, or brief review of slides) and learning styles. A total of 131 students were included in the present study. An inventory was prepared to understand the students' learning styles, and a satisfaction questionnaire was provided to determine the summary method selection. The questionnaire and inventory were collected and analyzed. A comparison of the data revealed that the summary method with video demonstration received the highest score among all the methods tested. Additionally, there were no significant differences between learning styles and summary method with video demonstration. We suggest that such a summary method should be incorporated into neuroanatomy lessons. Since anatomy has a large amount of visual material, we think that it is ideally suited for this summary method.

28 CFR 36.309 - Examinations and courses.

Code of Federal Regulations, 2012 CFR

2012-07-01

... include taped examinations, interpreters or other effective methods of making orally delivered materials... qualified readers for individuals with visual impairments or learning disabilities, transcribers for... and services required by this section may include taped texts, interpreters or other effective methods...

28 CFR 36.309 - Examinations and courses.

Code of Federal Regulations, 2013 CFR

2013-07-01

... include taped examinations, interpreters or other effective methods of making orally delivered materials... qualified readers for individuals with visual impairments or learning disabilities, transcribers for... and services required by this section may include taped texts, interpreters or other effective methods...

28 CFR 36.309 - Examinations and courses.

Code of Federal Regulations, 2014 CFR

2014-07-01

... include taped examinations, interpreters or other effective methods of making orally delivered materials... qualified readers for individuals with visual impairments or learning disabilities, transcribers for... and services required by this section may include taped texts, interpreters or other effective methods...

Colouring the Gaps in Learning Design: Aesthetics and the Visual in Learning

ERIC Educational Resources Information Center

Carroll, Fiona; Kop, Rita

2016-01-01

The visual is a dominant mode of information retrieval and understanding however, the focus on the visual dimension of Technology Enhanced Learning (TEL) is still quite weak in relation to its predominant focus on usability. To accommodate the future needs of the visual learner, designers of e-learning environments should advance the current…

Visual and Verbal Learning in a Genetic Metabolic Disorder

ERIC Educational Resources Information Center

Spilkin, Amy M.; Ballantyne, Angela O.; Trauner, Doris A.

2009-01-01

Visual and verbal learning in a genetic metabolic disorder (cystinosis) were examined in the following three studies. The goal of Study I was to provide a normative database and establish the reliability and validity of a new test of visual learning and memory (Visual Learning and Memory Test; VLMT) that was modeled after a widely used test of…

Why Color Matters: The Effect of Visual Cues on Learner's Interpretation of Dark Matter in a Cosmology Visualization

NASA Astrophysics Data System (ADS)

Buck, Z.

2013-04-01

As we turn more and more to high-end computing to understand the Universe at cosmological scales, visualizations of simulations will take on a vital role as perceptual and cognitive tools. In collaboration with the Adler Planetarium and University of California High-Performance AstroComputing Center (UC-HiPACC), I am interested in better understanding the use of visualizations to mediate astronomy learning across formal and informal settings. The aspect of my research that I present here uses quantitative methods to investigate how learners are relying on color to interpret dark matter in a cosmology visualization. The concept of dark matter is vital to our current understanding of the Universe, and yet we do not know how to effectively present dark matter visually to support learning. I employ an alternative treatment post-test only experimental design, in which members of an equivalent sample are randomly assigned to one of three treatment groups, followed by treatment and a post-test. Results indicate significant correlation (p < .05) between the color of dark matter in the visualization and survey responses, implying that aesthetic variations like color can have a profound effect on audience interpretation of a cosmology visualization.

A qualitative inquiry into the effects of visualization on high school chemistry students' learning process of molecular structure

NASA Astrophysics Data System (ADS)

Deratzou, Susan

This research studies the process of high school chemistry students visualizing chemical structures and its role in learning chemical bonding and molecular structure. Minimal research exists with high school chemistry students and more research is necessary (Gabel & Sherwood, 1980; Seddon & Moore, 1986; Seddon, Tariq, & Dos Santos Veiga, 1984). Using visualization tests (Ekstrom, French, Harman, & Dermen, 1990a), a learning style inventory (Brown & Cooper, 1999), and observations through a case study design, this study found visual learners performed better, but needed more practice and training. Statistically, all five pre- and post-test visualization test comparisons were highly significant in the two-tailed t-test (p > .01). The research findings are: (1) Students who tested high in the Visual (Language and/or Numerical) and Tactile Learning Styles (and Social Learning) had an advantage. Students who learned the chemistry concepts more effectively were better at visualizing structures and using molecular models to enhance their knowledge. (2) Students showed improvement in learning after visualization practice. Training in visualization would improve students' visualization abilities and provide them with a way to think about these concepts. (3) Conceptualization of concepts indicated that visualizing ability was critical and that it could be acquired. Support for this finding was provided by pre- and post-Visualization Test data with a highly significant t-test. (4) Various molecular animation programs and websites were found to be effective. (5) Visualization and modeling of structures encompassed both two- and three-dimensional space. The Visualization Test findings suggested that the students performed better with basic rotation of structures as compared to two- and three-dimensional objects. (6) Data from observations suggest that teaching style was an important factor in student learning of molecular structure. (7) Students did learn the chemistry concepts. Based on the Visualization Test results, which showed that most of the students performed better on the post-test, the visualization experience and the abstract nature of the content allowed them to transfer some of their chemical understanding and practice to non-chemical structures. Finally, implications for teaching of chemistry, students learning chemistry, curriculum, and research for the field of chemical education were discussed.

Coherent Image Layout using an Adaptive Visual Vocabulary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dillard, Scott E.; Henry, Michael J.; Bohn, Shawn J.

When querying a huge image database containing millions of images, the result of the query may still contain many thousands of images that need to be presented to the user. We consider the problem of arranging such a large set of images into a visually coherent layout, one that places similar images next to each other. Image similarity is determined using a bag-of-features model, and the layout is constructed from a hierarchical clustering of the image set by mapping an in-order traversal of the hierarchy tree into a space-filling curve. This layout method provides strong locality guarantees so we aremore » able to quantitatively evaluate performance using standard image retrieval benchmarks. Performance of the bag-of-features method is best when the vocabulary is learned on the image set being clustered. Because learning a large, discriminative vocabulary is a computationally demanding task, we present a novel method for efficiently adapting a generic visual vocabulary to a particular dataset. We evaluate our clustering and vocabulary adaptation methods on a variety of image datasets and show that adapting a generic vocabulary to a particular set of images improves performance on both hierarchical clustering and image retrieval tasks.« less

Role of Enhancing Visual Effects Education Delivery to Encounter Career Challenges in Malaysia

ERIC Educational Resources Information Center

Ng, Lynn-Sze

2017-01-01

Problem-based Learning (PBL) is one of the most effective methods of instruction that helps Visual Effects (VFX) students to be more adaptable at encountering career challenges in Malaysia. These challenges are; lack of several important requirements such as, the basic and fundamental knowledge of VFX concepts, the ability to understand real-world…

The Effects of Visualizations on Linguistically Diverse Students' Understanding of Energy and Matter in Life Science

ERIC Educational Resources Information Center

Ryoo, Kihyun; Bedell, Kristin

2017-01-01

Although extensive research has shown the educational value of different types of interactive visualizations on students' science learning in general, how such technologies can contribute to English learners' (ELs) understanding of complex scientific concepts has not been sufficiently explored to date. This mixed-methods study investigated how…

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

Creating visual explanations improves learning.

PubMed

Bobek, Eliza; Tversky, Barbara

2016-01-01

Many topics in science are notoriously difficult for students to learn. Mechanisms and processes outside student experience present particular challenges. While instruction typically involves visualizations, students usually explain in words. Because visual explanations can show parts and processes of complex systems directly, creating them should have benefits beyond creating verbal explanations. We compared learning from creating visual or verbal explanations for two STEM domains, a mechanical system (bicycle pump) and a chemical system (bonding). Both kinds of explanations were analyzed for content and learning assess by a post-test. For the mechanical system, creating a visual explanation increased understanding particularly for participants of low spatial ability. For the chemical system, creating both visual and verbal explanations improved learning without new teaching. Creating a visual explanation was superior and benefitted participants of both high and low spatial ability. Visual explanations often included crucial yet invisible features. The greater effectiveness of visual explanations appears attributable to the checks they provide for completeness and coherence as well as to their roles as platforms for inference. The benefits should generalize to other domains like the social sciences, history, and archeology where important information can be visualized. Together, the findings provide support for the use of learner-generated visual explanations as a powerful learning tool.

Drawing from Freirian empowerment methods to develop and use innovative learning maps: increasing enrollment of uninsured children on Detroit's eastside.

PubMed

Lopez, Ellen D S; Lichtenstein, Richard; Lewis, Alonzo; Banaszak-Holl, Jane; Lewis, Cheryl; Johnson, Penni; Riley, Scherry; Baum, Nancy M

2007-04-01

In 2001, virtually every child on Detroit's eastside was eligible for health coverage, yet approximately 3,000 children remained uninsured. The primary aim of the Eastside Access Partnership (EAP), a community-based participatory research collaboration, was to increase enrollment of uninsured children in state programs. To achieve this aim, one of the approaches that EAP is using is the innovative Learning Map titled Choosing the Healthy Path, which was developed in collaboration with Root Learning, Inc. Although Learning Maps were originally developed to assist corporations in implementing strategic change, their integration of visualization and interactive dialogue incorporates Freirian principles of empowerment education, making them a viable option for providing meaningful learning opportunities for community residents. This article presents the collaborative process involving the University of Michigan, local community-based organizations, community members, and Root Learning consultants to develop a visual map that enables community residents to understand and overcome the barriers that prevent them from obtaining health insurance for their children.

Students awareness of learning styles and their perceptions to a mixed method approach for learning.

PubMed

Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder

2015-08-01

Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning.

The influence of visual ability on learning and memory performance in 13 strains of mice.

PubMed

Brown, Richard E; Wong, Aimée A

2007-03-01

We calculated visual ability in 13 strains of mice (129SI/Sv1mJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, C57BL/6J, CAST/EiJ, DBA/2J, FVB/NJ, MOLF/EiJ, SJL/J, SM/J, and SPRET/EiJ) on visual detection, pattern discrimination, and visual acuity and tested these and other mice of the same strains in a behavioral test battery that evaluated visuo-spatial learning and memory, conditioned odor preference, and motor learning. Strain differences in visual acuity accounted for a significant proportion of the variance between strains in measures of learning and memory in the Morris water maze. Strain differences in motor learning performance were not influenced by visual ability. Conditioned odor preference was enhanced in mice with visual defects. These results indicate that visual ability must be accounted for when testing for strain differences in learning and memory in mice because differences in performance in many tasks may be due to visual deficits rather than differences in higher order cognitive functions. These results have significant implications for the search for the neural and genetic basis of learning and memory in mice.

Perceptual learning in children with visual impairment improves near visual acuity.

PubMed

Huurneman, Bianca; Boonstra, F Nienke; Cox, Ralf F A; van Rens, Ger; Cillessen, Antonius H N

2013-09-17

This study investigated whether visual perceptual learning can improve near visual acuity and reduce foveal crowding effects in four- to nine-year-old children with visual impairment. Participants were 45 children with visual impairment and 29 children with normal vision. Children with visual impairment were divided into three groups: a magnifier group (n = 12), a crowded perceptual learning group (n = 18), and an uncrowded perceptual learning group (n = 15). Children with normal vision also were divided in three groups, but were measured only at baseline. Dependent variables were single near visual acuity (NVA), crowded NVA, LH line 50% crowding NVA, number of trials, accuracy, performance time, amount of small errors, and amount of large errors. Children with visual impairment trained during six weeks, two times per week, for 30 minutes (12 training sessions). After training, children showed significant improvement of NVA in addition to specific improvements on the training task. The crowded perceptual learning group showed the largest acuity improvements (1.7 logMAR lines on the crowded chart, P < 0.001). Only the children in the crowded perceptual learning group showed improvements on all NVA charts. Children with visual impairment benefit from perceptual training. While task-specific improvements were observed in all training groups, transfer to crowded NVA was largest in the crowded perceptual learning group. To our knowledge, this is the first study to provide evidence for the improvement of NVA by perceptual learning in children with visual impairment. (http://www.trialregister.nl number, NTR2537.).

Visual Learning in Application of Integration

NASA Astrophysics Data System (ADS)

Bt Shafie, Afza; Barnachea Janier, Josefina; Bt Wan Ahmad, Wan Fatimah

Innovative use of technology can improve the way how Mathematics should be taught. It can enhance student's learning the concepts through visualization. Visualization in Mathematics refers to us of texts, pictures, graphs and animations to hold the attention of the learners in order to learn the concepts. This paper describes the use of a developed multimedia courseware as an effective tool for visual learning mathematics. The focus is on the application of integration which is a topic in Engineering Mathematics 2. The course is offered to the foundation students in the Universiti Teknologi of PETRONAS. Questionnaire has been distributed to get a feedback on the visual representation and students' attitudes towards using visual representation as a learning tool. The questionnaire consists of 3 sections: Courseware Design (Part A), courseware usability (Part B) and attitudes towards using the courseware (Part C). The results showed that students demonstrated the use of visual representation has benefited them in learning the topic.

Sketching Up New Geographies: Open Sourcing and Curriculum Development

ERIC Educational Resources Information Center

Boyd, William; Ellis, David

2013-01-01

The functionality of web 2.0 technologies has caused academics to rethink their development of teaching and learning methods and approaches. The editable, open access nature of web 2.0 encourages the innovative collaboration of ideas, the creation of equitable visual and tactile learning environments, and opportunity for academics to develop…

Concept Maps Provide a Window onto Preservice Elementary Teachers' Knowledge in the Teaching and Learning of Mathematics

ERIC Educational Resources Information Center

Chichekian, Tanya; Shore, Bruce M.

2013-01-01

This collaborative concept-mapping exercise was conducted in a second-year mathematics methods course. Teachers' visual representations of their mathematical content and pedagogical knowledge provided insight into their understanding of how students learn mathematics. We collected 28 preservice student teachers' concept maps and analyzed them by…

The Process and Product: Crafting Community Portraits with Young People in Flexible Learning Settings

ERIC Educational Resources Information Center

Baker, Alison M.

2016-01-01

Community-based alternative education is situated on the margins in relation to mainstream education. Young people attending these learning sites are often characterised as "disengaged learners", who have fallen through the cracks of the traditional schooling system. The aim of this project was to use participatory visual methods with…

Learning of grammar-like visual sequences by adults with and without language-learning disabilities.

PubMed

Aguilar, Jessica M; Plante, Elena

2014-08-01

Two studies examined learning of grammar-like visual sequences to determine whether a general deficit in statistical learning characterizes this population. Furthermore, we tested the hypothesis that difficulty in sustaining attention during the learning task might account for differences in statistical learning. In Study 1, adults with normal language (NL) or language-learning disability (LLD) were familiarized with the visual artificial grammar and then tested using items that conformed or deviated from the grammar. In Study 2, a 2nd sample of adults with NL and LLD were presented auditory word pairs with weak semantic associations (e.g., groom + clean) along with the visual learning task. Participants were instructed to attend to visual sequences and to ignore the auditory stimuli. Incidental encoding of these words would indicate reduced attention to the primary task. In Studies 1 and 2, both groups demonstrated learning and generalization of the artificial grammar. In Study 2, neither the NL nor the LLD group appeared to encode the words presented during the learning phase. The results argue against a general deficit in statistical learning for individuals with LLD and demonstrate that both NL and LLD learners can ignore extraneous auditory stimuli during visual learning.

Visual Learning Alters the Spontaneous Activity of the Resting Human Brain: An fNIRS Study

PubMed Central

Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

2014-01-01

Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning. PMID:25243168

Visual learning alters the spontaneous activity of the resting human brain: an fNIRS study.

PubMed

Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

2014-01-01

Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning.

Perceptual learning increases the strength of the earliest signals in visual cortex.

PubMed

Bao, Min; Yang, Lin; Rios, Cristina; He, Bin; Engel, Stephen A

2010-11-10

Training improves performance on most visual tasks. Such perceptual learning can modify how information is read out from, and represented in, later visual areas, but effects on early visual cortex are controversial. In particular, it remains unknown whether learning can reshape neural response properties in early visual areas independent from feedback arising in later cortical areas. Here, we tested whether learning can modify feedforward signals in early visual cortex as measured by the human electroencephalogram. Fourteen subjects were trained for >24 d to detect a diagonal grating pattern in one quadrant of the visual field. Training improved performance, reducing the contrast needed for reliable detection, and also reliably increased the amplitude of the earliest component of the visual evoked potential, the C1. Control orientations and locations showed smaller effects of training. Because the C1 arises rapidly and has a source in early visual cortex, our results suggest that learning can increase early visual area response through local receptive field changes without feedback from later areas.

Cognitive Strategies for Learning from Static and Dynamic Visuals.

ERIC Educational Resources Information Center

Lewalter, D.

2003-01-01

Studied the effects of including static or dynamic visuals in an expository text on a learning outcome and the use of learning strategies when working with these visuals. Results for 60 undergraduates for both types of illustration indicate different frequencies in the use of learning strategies relevant for the learning outcome. (SLD)

What Would a Graph Look Like in this Layout? A Machine Learning Approach to Large Graph Visualization.

PubMed

Kwon, Oh-Hyun; Crnovrsanin, Tarik; Ma, Kwan-Liu

2018-01-01

Using different methods for laying out a graph can lead to very different visual appearances, with which the viewer perceives different information. Selecting a "good" layout method is thus important for visualizing a graph. The selection can be highly subjective and dependent on the given task. A common approach to selecting a good layout is to use aesthetic criteria and visual inspection. However, fully calculating various layouts and their associated aesthetic metrics is computationally expensive. In this paper, we present a machine learning approach to large graph visualization based on computing the topological similarity of graphs using graph kernels. For a given graph, our approach can show what the graph would look like in different layouts and estimate their corresponding aesthetic metrics. An important contribution of our work is the development of a new framework to design graph kernels. Our experimental study shows that our estimation calculation is considerably faster than computing the actual layouts and their aesthetic metrics. Also, our graph kernels outperform the state-of-the-art ones in both time and accuracy. In addition, we conducted a user study to demonstrate that the topological similarity computed with our graph kernel matches perceptual similarity assessed by human users.

Vision improvement in pilots with presbyopia following perceptual learning.

PubMed

Sterkin, Anna; Levy, Yuval; Pokroy, Russell; Lev, Maria; Levian, Liora; Doron, Ravid; Yehezkel, Oren; Fried, Moshe; Frenkel-Nir, Yael; Gordon, Barak; Polat, Uri

2017-11-24

Israeli Air Force (IAF) pilots continue flying combat missions after the symptoms of natural near-vision deterioration, termed presbyopia, begin to be noticeable. Because modern pilots rely on the displays of the aircraft control and performance instruments, near visual acuity (VA) is essential in the cockpit. We aimed to apply a method previously shown to improve visual performance of presbyopes, and test whether presbyopic IAF pilots can overcome the limitation imposed by presbyopia. Participants were selected by the IAF aeromedical unit as having at least initial presbyopia and trained using a structured personalized perceptual learning method (GlassesOff application), based on detecting briefly presented low-contrast Gabor stimuli, under the conditions of spatial and temporal constraints, from a distance of 40 cm. Our results show that despite their initial visual advantage over age-matched peers, training resulted in robust improvements in various basic visual functions, including static and temporal VA, stereoacuity, spatial crowding, contrast sensitivity and contrast discrimination. Moreover, improvements generalized to higher-level tasks, such as sentence reading and aerial photography interpretation (specifically designed to reflect IAF pilots' expertise in analyzing noisy low-contrast input). In concert with earlier suggestions, gains in visual processing speed are plausible to account, at least partially, for the observed training-induced improvements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transferring and generalizing deep-learning-based neural encoding models across subjects.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-08-01

Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or encoding models), requires measuring cortical responses to large and diverse sets of natural visual stimuli from single subjects. This requirement limits prior studies to few subjects, making it difficult to generalize findings across subjects or for a population. In this study, we developed new methods to transfer and generalize encoding models across subjects. To train encoding models specific to a target subject, the models trained for other subjects were used as the prior models and were refined efficiently using Bayesian inference with a limited amount of data from the target subject. To train encoding models for a population, the models were progressively trained and updated with incremental data from different subjects. For the proof of principle, we applied these methods to functional magnetic resonance imaging (fMRI) data from three subjects watching tens of hours of naturalistic videos, while a deep residual neural network driven by image recognition was used to model visual cortical processing. Results demonstrate that the methods developed herein provide an efficient and effective strategy to establish both subject-specific and population-wide predictive models of cortical representations of high-dimensional and hierarchical visual features. Copyright © 2018 Elsevier Inc. All rights reserved.

The Box-and-Dot Method: A Simple Strategy for Counting Significant Figures

ERIC Educational Resources Information Center

Stephenson, W. Kirk

2009-01-01

A visual method for counting significant digits is presented. This easy-to-learn (and easy-to-teach) method, designated the box-and-dot method, uses the device of "boxing" significant figures based on two simple rules, then counting the number of digits in the boxes. (Contains 4 notes.)

Landmark Image Retrieval by Jointing Feature Refinement and Multimodal Classifier Learning.

PubMed

Zhang, Xiaoming; Wang, Senzhang; Li, Zhoujun; Ma, Shuai; Xiaoming Zhang; Senzhang Wang; Zhoujun Li; Shuai Ma; Ma, Shuai; Zhang, Xiaoming; Wang, Senzhang; Li, Zhoujun

2018-06-01

Landmark retrieval is to return a set of images with their landmarks similar to those of the query images. Existing studies on landmark retrieval focus on exploiting the geometries of landmarks for visual similarity matches. However, the visual content of social images is of large diversity in many landmarks, and also some images share common patterns over different landmarks. On the other side, it has been observed that social images usually contain multimodal contents, i.e., visual content and text tags, and each landmark has the unique characteristic of both visual content and text content. Therefore, the approaches based on similarity matching may not be effective in this environment. In this paper, we investigate whether the geographical correlation among the visual content and the text content could be exploited for landmark retrieval. In particular, we propose an effective multimodal landmark classification paradigm to leverage the multimodal contents of social image for landmark retrieval, which integrates feature refinement and landmark classifier with multimodal contents by a joint model. The geo-tagged images are automatically labeled for classifier learning. Visual features are refined based on low rank matrix recovery, and multimodal classification combined with group sparse is learned from the automatically labeled images. Finally, candidate images are ranked by combining classification result and semantic consistence measuring between the visual content and text content. Experiments on real-world datasets demonstrate the superiority of the proposed approach as compared to existing methods.

LinkWinds: An Approach to Visual Data Analysis

NASA Technical Reports Server (NTRS)

Jacobson, Allan S.

1992-01-01

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration and analysis system resulting from a NASA/JPL program of research into graphical methods for rapidly accessing, displaying and analyzing large multivariate multidisciplinary datasets. It is an integrated multi-application execution environment allowing the dynamic interconnection of multiple windows containing visual displays and/or controls through a data-linking paradigm. This paradigm, which results in a system much like a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but provides a highly intuitive, easy to learn user interface on top of the traditional graphical user interface.

Visual Aversive Learning Compromises Sensory Discrimination.

PubMed

Shalev, Lee; Paz, Rony; Avidan, Galia

2018-03-14

Aversive learning is thought to modulate perceptual thresholds, which can lead to overgeneralization. However, it remains undetermined whether this modulation is domain specific or a general effect. Moreover, despite the unique role of the visual modality in human perception, it is unclear whether this aspect of aversive learning exists in this modality. The current study was designed to examine the effect of visual aversive outcomes on the perception of basic visual and auditory features. We tested the ability of healthy participants, both males and females, to discriminate between neutral stimuli, before and after visual learning. In each experiment, neutral stimuli were associated with aversive images in an experimental group and with neutral images in a control group. Participants demonstrated a deterioration in discrimination (higher discrimination thresholds) only after aversive learning. This deterioration was measured for both auditory (tone frequency) and visual (orientation and contrast) features. The effect was replicated in five different experiments and lasted for at least 24 h. fMRI neural responses and pupil size were also measured during learning. We showed an increase in neural activations in the anterior cingulate cortex, insula, and amygdala during aversive compared with neutral learning. Interestingly, the early visual cortex showed increased brain activity during aversive compared with neutral context trials, with identical visual information. Our findings imply the existence of a central multimodal mechanism, which modulates early perceptual properties, following exposure to negative situations. Such a mechanism could contribute to abnormal responses that underlie anxiety states, even in new and safe environments. SIGNIFICANCE STATEMENT Using a visual aversive-learning paradigm, we found deteriorated discrimination abilities for visual and auditory stimuli that were associated with visual aversive stimuli. We showed increased neural activations in the anterior cingulate cortex, insula, and amygdala during aversive learning, compared with neutral learning. Importantly, similar findings were also evident in the early visual cortex during trials with aversive/neutral context, but with identical visual information. The demonstration of this phenomenon in the visual modality is important, as it provides support to the notion that aversive learning can influence perception via a central mechanism, independent of input modality. Given the dominance of the visual system in human perception, our findings hold relevance to daily life, as well as imply a potential etiology for anxiety disorders. Copyright © 2018 the authors 0270-6474/18/382766-14$15.00/0.

How actions shape perception: learning action-outcome relations and predicting sensory outcomes promote audio-visual temporal binding

PubMed Central

Desantis, Andrea; Haggard, Patrick

2016-01-01

To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events. PMID:27982063

How actions shape perception: learning action-outcome relations and predicting sensory outcomes promote audio-visual temporal binding.

PubMed

Desantis, Andrea; Haggard, Patrick

2016-12-16

To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events.

The Effect of Visual Variability on the Learning of Academic Concepts.

PubMed

Bourgoyne, Ashley; Alt, Mary

2017-06-10

The purpose of this study was to identify effects of variability of visual input on development of conceptual representations of academic concepts for college-age students with normal language (NL) and those with language-learning disabilities (LLD). Students with NL (n = 11) and LLD (n = 11) participated in a computer-based training for introductory biology course concepts. Participants were trained on half the concepts under a low-variability condition and half under a high-variability condition. Participants completed a posttest in which they were asked to identify and rate the accuracy of novel and trained visual representations of the concepts. We performed separate repeated measures analyses of variance to examine the accuracy of identification and ratings. Participants were equally accurate on trained and novel items in the high-variability condition, but were less accurate on novel items only in the low-variability condition. The LLD group showed the same pattern as the NL group; they were just less accurate. Results indicated that high-variability visual input may facilitate the acquisition of academic concepts in college students with NL and LLD. High-variability visual input may be especially beneficial for generalization to novel representations of concepts. Implicit learning methods may be harnessed by college courses to provide students with basic conceptual knowledge when they are entering courses or beginning new units.

Hierarchical extreme learning machine based reinforcement learning for goal localization

NASA Astrophysics Data System (ADS)

AlDahoul, Nouar; Zaw Htike, Zaw; Akmeliawati, Rini

2017-03-01

The objective of goal localization is to find the location of goals in noisy environments. Simple actions are performed to move the agent towards the goal. The goal detector should be capable of minimizing the error between the predicted locations and the true ones. Few regions need to be processed by the agent to reduce the computational effort and increase the speed of convergence. In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. The visual data, a set of images, is high dimensional unstructured data and needs to be represented efficiently to get a robust detector. Different deep Reinforcement models have already been used to localize a goal but most of them take long time to learn the model. This long learning time results from the weights fine tuning stage that is applied iteratively to find an accurate model. Hierarchical Extreme Learning Machine (H-ELM) was used as a fast deep model that doesn’t fine tune the weights. In other words, hidden weights are generated randomly and output weights are calculated analytically. H-ELM algorithm was used in this work to find good features for effective representation. This paper proposes a combination of Hierarchical Extreme learning machine and Reinforcement learning to find an optimal policy directly from visual input. This combination outperforms other methods in terms of accuracy and learning speed. The simulations and results were analysed by using MATLAB.

Learning to associate orientation with color in early visual areas by associative decoded fMRI neurofeedback

PubMed Central

Amano, Kaoru; Shibata, Kazuhisa; Kawato, Mitsuo; Sasaki, Yuka; Watanabe, Takeo

2016-01-01

Summary Associative learning is an essential brain process where the contingency of different items increases after training. Associative learning has been found to occur in many brain regions [1-4]. However, there is no clear evidence that associative learning of visual features occurs in early visual areas, although a number of studies have indicated that learning of a single visual feature (perceptual learning) involves early visual areas [5-8]. Here, via decoded functional magnetic resonance imaging (fMRI) neurofeedback, termed “DecNef” [9], we tested whether associative learning of color and orientation can be created in early visual areas. During three days' training, DecNef induced fMRI signal patterns that corresponded to a specific target color (red) mostly in early visual areas while a vertical achromatic grating was physically presented to participants. As a result, participants came to perceive “red” significantly more frequently than “green” in an achromatic vertical grating. This effect was also observed 3 to 5 months after the training. These results suggest that long-term associative learning of the two different visual features such as color and orientation was created most likely in early visual areas. This newly extended technique that induces associative learning is called “A(ssociative)-DecNef” and may be used as an important tool for understanding and modifying brain functions, since associations are fundamental and ubiquitous functions in the brain. PMID:27374335

Learning to Associate Orientation with Color in Early Visual Areas by Associative Decoded fMRI Neurofeedback.

PubMed

Amano, Kaoru; Shibata, Kazuhisa; Kawato, Mitsuo; Sasaki, Yuka; Watanabe, Takeo

2016-07-25

Associative learning is an essential brain process where the contingency of different items increases after training. Associative learning has been found to occur in many brain regions [1-4]. However, there is no clear evidence that associative learning of visual features occurs in early visual areas, although a number of studies have indicated that learning of a single visual feature (perceptual learning) involves early visual areas [5-8]. Here, via decoded fMRI neurofeedback termed "DecNef" [9], we tested whether associative learning of orientation and color can be created in early visual areas. During 3 days of training, DecNef induced fMRI signal patterns that corresponded to a specific target color (red) mostly in early visual areas while a vertical achromatic grating was physically presented to participants. As a result, participants came to perceive "red" significantly more frequently than "green" in an achromatic vertical grating. This effect was also observed 3-5 months after the training. These results suggest that long-term associative learning of two different visual features such as orientation and color was created, most likely in early visual areas. This newly extended technique that induces associative learning is called "A-DecNef," and it may be used as an important tool for understanding and modifying brain functions because associations are fundamental and ubiquitous functions in the brain. Copyright © 2016 Elsevier Ltd. All rights reserved.

Perceptual Learning Improves Adult Amblyopic Vision Through Rule-Based Cognitive Compensation

PubMed Central

Zhang, Jun-Yun; Cong, Lin-Juan; Klein, Stanley A.; Levi, Dennis M.; Yu, Cong

2014-01-01

Purpose. We investigated whether perceptual learning in adults with amblyopia could be enabled to transfer completely to an orthogonal orientation, which would suggest that amblyopic perceptual learning results mainly from high-level cognitive compensation, rather than plasticity in the amblyopic early visual brain. Methods. Nineteen adults (mean age = 22.5 years) with anisometropic and/or strabismic amblyopia were trained following a training-plus-exposure (TPE) protocol. The amblyopic eyes practiced contrast, orientation, or Vernier discrimination at one orientation for six to eight sessions. Then the amblyopic or nonamblyopic eyes were exposed to an orthogonal orientation via practicing an irrelevant task. Training was first performed at a lower spatial frequency (SF), then at a higher SF near the cutoff frequency of the amblyopic eye. Results. Perceptual learning was initially orientation specific. However, after exposure to the orthogonal orientation, learning transferred to an orthogonal orientation completely. Reversing the exposure and training order failed to produce transfer. Initial lower SF training led to broad improvement of contrast sensitivity, and later higher SF training led to more specific improvement at high SFs. Training improved visual acuity by 1.5 to 1.6 lines (P < 0.001) in the amblyopic eyes with computerized tests and a clinical E acuity chart. It also improved stereoacuity by 53% (P < 0.001). Conclusions. The complete transfer of learning suggests that perceptual learning in amblyopia may reflect high-level learning of rules for performing a visual discrimination task. These rules are applicable to new orientations to enable learning transfer. Therefore, perceptual learning may improve amblyopic vision mainly through rule-based cognitive compensation. PMID:24550359

Tiger salamanders' (Ambystoma tigrinum) response learning and usage of visual cues.

PubMed

Kundey, Shannon M A; Millar, Roberto; McPherson, Justin; Gonzalez, Maya; Fitz, Aleyna; Allen, Chadbourne

2016-05-01

We explored tiger salamanders' (Ambystoma tigrinum) learning to execute a response within a maze as proximal visual cue conditions varied. In Experiment 1, salamanders learned to turn consistently in a T-maze for reinforcement before the maze was rotated. All learned the initial task and executed the trained turn during test, suggesting that they learned to demonstrate the reinforced response during training and continued to perform it during test. In a second experiment utilizing a similar procedure, two visual cues were placed consistently at the maze junction. Salamanders were reinforced for turning towards one cue. Cue placement was reversed during test. All learned the initial task, but executed the trained turn rather than turning towards the visual cue during test, evidencing response learning. In Experiment 3, we investigated whether a compound visual cue could control salamanders' behaviour when it was the only cue predictive of reinforcement in a cross-maze by varying start position and cue placement. All learned to turn in the direction indicated by the compound visual cue, indicating that visual cues can come to control their behaviour. Following training, testing revealed that salamanders attended to stimuli foreground over background features. Overall, these results suggest that salamanders learn to execute responses over learning to use visual cues but can use visual cues if required. Our success with this paradigm offers the potential in future studies to explore salamanders' cognition further, as well as to shed light on how features of the tiger salamanders' life history (e.g. hibernation and metamorphosis) impact cognition.

Fine-grained temporal coding of visually-similar categories in the ventral visual pathway and prefrontal cortex

PubMed Central

Xu, Yang; D'Lauro, Christopher; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2013-01-01

Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned–with feedback–to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning we observed some degree of categorical discriminability and predictability in both prefrontal cortex and the ventral visual pathway. Predictability improved significantly above chance in the ventral visual pathway over the course of learning with the left inferior temporal and fusiform gyri showing the greatest improvement in predictability between 150 and 250 ms (M200) during category learning. In contrast, there was no comparable increase in discriminability in prefrontal cortex with the only significant post-learning effect being a decrease in predictability in the inferior frontal gyrus between 250 and 350 ms (M300). Thus, the ventral visual pathway appears to encode learned visual categories over the long term. At the same time these results add to our understanding of the cortical origins of previously reported signature temporal components associated with perceptual learning. PMID:24146656

Learning clinical procedures through Internet visual resources: a qualitative study amongst undergraduate students.

PubMed

Gao, X; Wong, L M; Chow, D Y S; Law, X J; Ching, L Y L

2015-02-01

Acquiring competency in performing clinical procedures is central to professional education of healthcare providers. Internet visual resources (IVR), defined as visual materials openly accessible on public websites, provides a new channel to learn clinical procedures. This qualitative study aimed to profile the experience and opinions of undergraduate students (in dentistry, medicine and nursing) in learning clinical procedures through IVR. From clinical degree programmes (Bachelor of Dental Surgery, Bachelor of Medicine, Bachelor of Surgery, and Bachelor of Nursing) of University of Hong Kong, 31 students were recruited to join six focus group discussions, which were transcribed and subjected to thematic analysis using inductive method, in which themes emerge from data. Students actively looked for IVRs through various means and used them for pre-clinical preparation, post-clinical revision, learning simple and advanced procedures, exploring alternative and updated techniques, and benchmarking against international peers. IVRs were valued for their visual stimulation, inclusion of a wide variety of real-life cases, convenience in access, user-friendliness and time-saving features. Students tended to share and discuss IVRs with their peers rather than with tutors, even when contents deviated from school teaching or faculty's e-learning materials. When doubts persisted, they chose to follow faculty guidelines for examination purpose. Students were frustrated sometimes by difficulties in judging the scientific quality, lack of immediate interactive discussions and loosely structured presentations in some IVRs. Teachers' attitudes towards IVR appeared to vary greatly. Despite the wide spectrum of experience and opinions, IVR was generally viewed by undergraduates from across clinical faculties as enhancing their clinical confidence and self-perceived competency, enriching their learning experience and serving as an important supplement to formal learning in the planned curriculum. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Aminergic neuromodulation of associative visual learning in harnessed honey bees.

PubMed

Mancini, Nino; Giurfa, Martin; Sandoz, Jean-Christophe; Avarguès-Weber, Aurore

2018-05-21

The honey bee Apis mellifera is a major insect model for studying visual cognition. Free-flying honey bees learn to associate different visual cues with a sucrose reward and may deploy sophisticated cognitive strategies to this end. Yet, the neural bases of these capacities cannot be studied in flying insects. Conversely, immobilized bees are accessible to neurobiological investigation but training them to respond appetitively to visual stimuli paired with sucrose reward is difficult. Here we succeeded in coupling visual conditioning in harnessed bees with pharmacological analyses on the role of octopamine (OA), dopamine (DA) and serotonin (5-HT) in visual learning. We also studied if and how these biogenic amines modulate sucrose responsiveness and phototaxis behaviour as intact reward and visual perception are essential prerequisites for appetitive visual learning. Our results suggest that both octopaminergic and dopaminergic signaling mediate either the appetitive sucrose signaling or the association between color and sucrose reward in the bee brain. Enhancing and inhibiting serotonergic signaling both compromised learning performances, probably via an impairment of visual perception. We thus provide a first analysis of the role of aminergic signaling in visual learning and retention in the honey bee and discuss further research trends necessary to understand the neural bases of visual cognition in this insect. Copyright © 2018 Elsevier Inc. All rights reserved.

Students awareness of learning styles and their perceptions to a mixed method approach for learning

PubMed Central

Bhagat, Anumeha; Vyas, Rashmi; Singh, Tejinder

2015-01-01

Background: Individualization of instructional method does not contribute significantly to learning outcomes although it is known that students have differing learning styles (LSs). Hence, in order to maximally enhance learning, one must try to use a mixed method approach. Hypothesis: Our hypothesis was that awareness of preferred LS and motivation to incorporate multiple learning strategies might enhance learning outcomes. Aim: Our aim was to determine the impact of awareness of LS among medical undergraduates and motivating students to use mixed methods of learning. Materials and Methods: Before awareness lecture, LS preferences were determined using Visual, Aural, Read/Write, and Kinesthetic (VARK) questionnaire. Awareness of LS was assessed using a validated questionnaire. Through a lecture, students were oriented to various LSs, impact of LS on their performance, and benefit of using mixed method approach for learning. Subsequently, group discussions were organized. After 3 months, VARK preferences and awareness of LSs were reassessed. Student narratives were collected. Qualitative analysis of the data was done. Results: There was a significant increase in the number of students who were aware of LS. The number of participants showing a change in VARK scores for various modalities of learning was also significant (P < 0.001). Conclusion: Thus, awareness of LSs motivated students to adapt other learning strategies and use mixed methods for learning. PMID:26380214

Large-scale weakly supervised object localization via latent category learning.

PubMed

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

A Field Study of a Standardized Tangible Symbol System for Learners Who Are Visually Impaired and Have Multiple Disabilities

ERIC Educational Resources Information Center

Trief, Ellen; Cascella, Paul W.; Bruce, Susan M.

2013-01-01

Introduction: The study reported in this article tracked the learning rate of 43 children with multiple disabilities and visual impairments who had limited to no verbal language across seven months of classroom-based intervention using a standardized set of tangible symbols. Methods: The participants were introduced to tangible symbols on a daily…

From Spoke to Hub: Transforming Organizational Vision and Strategy With Story and Visual Art

ERIC Educational Resources Information Center

Tyler, Jo A.

2015-01-01

This article reports on a case study at an inner-city nonprofit service agency that inquired into the ways integration of storytelling and visual art as a method of adult learning and way of knowing might influence the process of strategic visioning and planning in a nonprofit organization. The case study focuses on data collected through…

Integration of Audio Visual Multimedia for Special Education Pre-Service Teachers' Self Reflections in Developing Teaching Competencies

ERIC Educational Resources Information Center

Sediyani, Tri; Yufiarti; Hadi, Eko

2017-01-01

This study aims to develop a model of learning by integrating multimedia and audio-visual self-reflective learners. This multimedia was developed as a tool for prospective teachers as learners in the education of children with special needs to reflect on their teaching competencies before entering the world of education. Research methods to…

Visual one-shot learning as an 'anti-camouflage device': a novel morphing paradigm.

PubMed

Ishikawa, Tetsuo; Mogi, Ken

2011-09-01

Once people perceive what is in the hidden figure such as Dallenbach's cow and Dalmatian, they seldom seem to come back to the previous state when they were ignorant of the answer. This special type of learning process can be accomplished in a short time, with the effect of learning lasting for a long time (visual one-shot learning). Although it is an intriguing cognitive phenomenon, the lack of the control of difficulty of stimuli presented has been a problem in research. Here we propose a novel paradigm to create new hidden figures systematically by using a morphing technique. Through gradual changes from a blurred and binarized two-tone image to a blurred grayscale image of the original photograph including objects in a natural scene, spontaneous one-shot learning can occur at a certain stage of morphing when a sufficient amount of information is restored to the degraded image. A negative correlation between confidence levels and reaction times is observed, giving support to the fluency theory of one-shot learning. The correlation between confidence ratings and correct recognition rates indicates that participants had an accurate introspective ability (metacognition). The learning effect could be tested later by verifying whether or not the target object was recognized quicker in the second exposure. The present method opens a way for a systematic production of "good" hidden figures, which can be used to demystify the nature of visual one-shot learning.

The learning style preferences of chiropractic students: A cross-sectional study

PubMed Central

Whillier, Stephney; Lystad, Reidar P.; Abi-Arrage, David; McPhie, Christopher; Johnston, Samara; Williams, Christopher; Rice, Mark

2014-01-01

Objective The aims of our study were to measure the learning style preferences of chiropractic students and to assess whether they differ across the 5 years of chiropractic study. Methods A total of 407 (41.4% females) full-degree, undergraduate, and postgraduate students enrolled in an Australian chiropractic program agreed to participate in a cross-sectional survey comprised of basic demographic information and the Visual, Aural, Read/Write, Kinesthetic (VARK) questionnaire, which identifies learning preferences on four different subscales: visual, aural, reading/writing, and kinesthetic. Multivariate analysis of variance and the χ2 test were used to check for differences in continuous (VARK scores) and categorical (VARK category preference) outcome variables. Results The majority of chiropractic students (56.0%) were found to be multimodal learners. Compared to the other learning styles preferences, kinesthetic learning was preferred by a significantly greater proportion of students (65.4%, p < .001) and received a significantly greater mean VARK score (5.66 ± 2.47, p < .001). Conclusions To the best of our knowledge, this is the first time chiropractic students have been shown to be largely multimodal learners with a preference for kinesthetic learning. While this knowledge may be beneficial in the structuring of future curricula, more thorough research must be conducted to show any beneficial relationship between learning style preferences and teaching methods. PMID:24350945

Visual texture perception via graph-based semi-supervised learning

NASA Astrophysics Data System (ADS)

Zhang, Qin; Dong, Junyu; Zhong, Guoqiang

2018-04-01

Perceptual features, for example direction, contrast and repetitiveness, are important visual factors for human to perceive a texture. However, it needs to perform psychophysical experiment to quantify these perceptual features' scale, which requires a large amount of human labor and time. This paper focuses on the task of obtaining perceptual features' scale of textures by small number of textures with perceptual scales through a rating psychophysical experiment (what we call labeled textures) and a mass of unlabeled textures. This is the scenario that the semi-supervised learning is naturally suitable for. This is meaningful for texture perception research, and really helpful for the perceptual texture database expansion. A graph-based semi-supervised learning method called random multi-graphs, RMG for short, is proposed to deal with this task. We evaluate different kinds of features including LBP, Gabor, and a kind of unsupervised deep features extracted by a PCA-based deep network. The experimental results show that our method can achieve satisfactory effects no matter what kind of texture features are used.

Deep neural networks for modeling visual perceptual learning.

PubMed

Wenliang, Li; Seitz, Aaron R

2018-05-23

Understanding visual perceptual learning (VPL) has become increasingly more challenging as new phenomena are discovered with novel stimuli and training paradigms. While existing models aid our knowledge of critical aspects of VPL, the connections shown by these models between behavioral learning and plasticity across different brain areas are typically superficial. Most models explain VPL as readout from simple perceptual representations to decision areas and are not easily adaptable to explain new findings. Here, we show that a well-known instance of deep neural network (DNN), while not designed specifically for VPL, provides a computational model of VPL with enough complexity to be studied at many levels of analyses. After learning a Gabor orientation discrimination task, the DNN model reproduced key behavioral results, including increasing specificity with higher task precision, and also suggested that learning precise discriminations could asymmetrically transfer to coarse discriminations when the stimulus conditions varied. In line with the behavioral findings, the distribution of plasticity moved towards lower layers when task precision increased, and this distribution was also modulated by tasks with different stimulus types. Furthermore, learning in the network units demonstrated close resemblance to extant electrophysiological recordings in monkey visual areas. Altogether, the DNN fulfilled predictions of existing theories regarding specificity and plasticity, and reproduced findings of tuning changes in neurons of the primate visual areas. Although the comparisons were mostly qualitative, the DNN provides a new method of studying VPL and can serve as a testbed for theories and assist in generating predictions for physiological investigations. SIGNIFICANCE STATEMENT Visual perceptual learning (VPL) has been found to cause changes at multiple stages of the visual hierarchy. We found that training a deep neural network (DNN) on an orientation discrimination task produced similar behavioral and physiological patterns found in human and monkey experiments. Unlike existing VPL models, the DNN was pre-trained on natural images to reach high performance in object recognition but was not designed specifically for VPL, and yet it fulfilled predictions of existing theories regarding specificity and plasticity, and reproduced findings of tuning changes in neurons of the primate visual areas. When used with care, this unbiased and deep-hierarchical model can provide new ways of studying VPL from behavior to physiology. Copyright © 2018 the authors.

Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning

ERIC Educational Resources Information Center

Rau, Martina A.

2017-01-01

Visual representations play a critical role in enhancing science, technology, engineering, and mathematics (STEM) learning. Educational psychology research shows that adding visual representations to text can enhance students' learning of content knowledge, compared to text-only. But should students learn with a single type of visual…

Relationship between Learning Style and Academic Status of Babol Dental Students

PubMed Central

Nasiri, Zahra; Gharekhani, Samane; Ghasempour, Maryam

2016-01-01

Introduction Identifying and employing students’ learning styles could play an important role in selecting appropriate teaching methods in order to improve education. The aim of this study was to determine the relationship between the students’ final exam scores and the learning style preferences of dental students at Babol University of Medical Sciences. Methods This cross-sectional study was conducted on 88 dental students studying in their fourth, fifth, and sixth years using the visual–aural–reading/writing–kinesthetic (VARK) learning styles’ questionnaire. The data were analyzed with IBM SPSS, version 21, using the chi-squared test and the t-test. Results Of the 88 participants who responded to the questionnaire, 87 preferred multimodal learning styles. There was no significant difference between the mean of the final exam scores in students who did and did not prefer the aural learning style (p = 0.86), the reading/writing learning style (p = 0.20), and the kinesthetic learning style (p = 0.32). In addition, there was no significant difference between the scores on the final clinical course among the students who had different preferences for learning style. However, there was a significant difference between the mean of the final exam scores in students with and without visual learning style preference (p = 0.03), with the former having higher mean scores. There was no significant relationship between preferred learning styles and gender (p > 0.05). Conclusion The majority of dental students preferred multimodal learning styles, and there was a significant difference between the mean of the final exam scores for students with and without a preference for the visual learning style. In addition, there were no differences in the preferred learning styles between male and female students. PMID:27382442

Embodied attention and word learning by toddlers

PubMed Central

Yu, Chen; Smith, Linda B.

2013-01-01

Many theories of early word learning begin with the uncertainty inherent to learning a word from its co-occurrence with a visual scene. However, the relevant visual scene for infant word learning is neither from the adult theorist’s view nor the mature partner’s view, but is rather from the learner’s personal view. Here we show that when 18-month old infants interacted with objects in play with their parents, they created moments in which a single object was visually dominant. If parents named the object during these moments of bottom-up selectivity, later forced-choice tests showed that infants learned the name, but did not when naming occurred during a less visually selective moment. The momentary visual input for parents and toddlers was captured via head cameras placed low on each participant’s forehead as parents played with and named objects for their infant. Frame-by-frame analyses of the head camera images at and around naming moments were conducted to determine the visual properties at input that were associated with learning. The analyses indicated that learning occurred when bottom-up visual information was clean and uncluttered. The sensory-motor behaviors of infants and parents were also analyzed to determine how their actions on the objects may have created these optimal visual moments for learning. The results are discussed with respect to early word learning, embodied attention, and the social role of parents in early word learning. PMID:22878116

Understanding How to Build Long-Lived Learning Collaborators

DTIC Science & Technology

2016-03-16

discrimination in learning, and dynamic encoding strategies to improve visual encoding for learning via analogical generalization. We showed that spatial concepts...a 20,000 sketch corpus to examine the tradeoffs involved in visual representation and analogical generalization. 15. SUBJECT TERMS...strategies to improve visual encoding for learning via analogical generalization. We showed that spatial concepts can be learned via analogical

Changing viewer perspectives reveals constraints to implicit visual statistical learning.

PubMed

Jiang, Yuhong V; Swallow, Khena M

2014-10-07

Statistical learning-learning environmental regularities to guide behavior-likely plays an important role in natural human behavior. One potential use is in search for valuable items. Because visual statistical learning can be acquired quickly and without intention or awareness, it could optimize search and thereby conserve energy. For this to be true, however, visual statistical learning needs to be viewpoint invariant, facilitating search even when people walk around. To test whether implicit visual statistical learning of spatial information is viewpoint independent, we asked participants to perform a visual search task from variable locations around a monitor placed flat on a stand. Unbeknownst to participants, the target was more often in some locations than others. In contrast to previous research on stationary observers, visual statistical learning failed to produce a search advantage for targets in high-probable regions that were stable within the environment but variable relative to the viewer. This failure was observed even when conditions for spatial updating were optimized. However, learning was successful when the rich locations were referenced relative to the viewer. We conclude that changing viewer perspective disrupts implicit learning of the target's location probability. This form of learning shows limited integration with spatial updating or spatiotopic representations. © 2014 ARVO.

Comprehensive decision tree models in bioinformatics.

PubMed

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics.

Aural mapping of STEM concepts using literature mining

NASA Astrophysics Data System (ADS)

Bharadwaj, Venkatesh

Recent technological applications have made the life of people too much dependent on Science, Technology, Engineering, and Mathematics (STEM) and its applications. Understanding basic level science is a must in order to use and contribute to this technological revolution. Science education in middle and high school levels however depends heavily on visual representations such as models, diagrams, figures, animations and presentations etc. This leaves visually impaired students with very few options to learn science and secure a career in STEM related areas. Recent experiments have shown that small aural clues called Audemes are helpful in understanding and memorization of science concepts among visually impaired students. Audemes are non-verbal sound translations of a science concept. In order to facilitate science concepts as Audemes, for visually impaired students, this thesis presents an automatic system for audeme generation from STEM textbooks. This thesis describes the systematic application of multiple Natural Language Processing tools and techniques, such as dependency parser, POS tagger, Information Retrieval algorithm, Semantic mapping of aural words, machine learning etc., to transform the science concept into a combination of atomic-sounds, thus forming an audeme. We present a rule based classification method for all STEM related concepts. This work also presents a novel way of mapping and extracting most related sounds for the words being used in textbook. Additionally, machine learning methods are used in the system to guarantee the customization of output according to a user's perception. The system being presented is robust, scalable, fully automatic and dynamically adaptable for audeme generation.

Expanding the Caring Lens: Nursing and Medical Students Reflecting on Images of Older People.

PubMed

Brand, Gabrielle; Miller, Karen; Saunders, Rosemary; Dugmore, Helen; Etherton-Beer, Christopher

2016-01-01

In changing higher education environments, health profession's educators have been increasingly challenged to prepare future health professionals to care for aging populations. This article reports on an exploratory, mixed-method research study that used an innovative photo-elicitation technique and interprofessional small-group work in the classroom to enhance the reflective learning experience of medical and nursing students. Data were collected from pre- and postquestionnaires and focus groups to explore shifts in perceptions toward older persons following the reflective learning session. The qualitative data revealed how using visual images of older persons provides a valuable learning space for reflection. Students found meaning in their own learning by creating shared storylines that challenged their perceptions of older people and themselves as future health professionals. These data support the use of visual methodologies to enhance engagement, reflection, and challenge students to explore and deepen their understanding in gerontology.

Is the Recall of Verbal-Spatial Information from Working Memory Affected by Symptoms of ADHD?

ERIC Educational Resources Information Center

Caterino, Linda C.; Verdi, Michael P.

2012-01-01

Objective: The Kulhavy model for text learning using organized spatial displays proposes that learning will be increased when participants view visual images prior to related text. In contrast to previous studies, this study also included students who exhibited symptoms of ADHD. Method: Participants were presented with either a map-text or…

Curriculum Mapping: A Method to Assess and Refine Undergraduate Degree Programs

ERIC Educational Resources Information Center

Joyner-Melito, Helen S.

2016-01-01

Over the past several decades, there has been increasing interest in program- and university-level assessment and aligning learning outcomes to program content. Curriculum mapping is a tool that creates a visual map of all courses in the curriculum and how they relate to curriculum learning outcomes. Assessment tools/activities are often included…

The Use of Eye Movements in the Study of Multimedia Learning

ERIC Educational Resources Information Center

Hyona, Jukka

2010-01-01

This commentary focuses on the use of the eye-tracking methodology to study cognitive processes during multimedia learning. First, some general remarks are made about how the method is applied to investigate visual information processing, followed by a reflection on the eye movement measures employed in the studies published in this special issue.…

The Use of Graphic Organizers To Improve Comprehension of Learning Disabled Students in Social Studies.

ERIC Educational Resources Information Center

Doyle, Carole S.

This study examined the effectiveness of two approaches to enhancing the reading comprehension of learning disabled students in the social studies content area. An approach using the graphic organizer in the form of visual displays was compared to the traditional method in which students were presented content through lecture, text, and linear…

Ultrasound visual feedback treatment and practice variability for residual speech sound errors

PubMed Central

Preston, Jonathan L.; McCabe, Patricia; Rivera-Campos, Ahmed; Whittle, Jessica L.; Landry, Erik; Maas, Edwin

2014-01-01

Purpose The goals were to (1) test the efficacy of a motor-learning based treatment that includes ultrasound visual feedback for individuals with residual speech sound errors, and (2) explore whether the addition of prosodic cueing facilitates speech sound learning. Method A multiple baseline single subject design was used, replicated across 8 participants. For each participant, one sound context was treated with ultrasound plus prosodic cueing for 7 sessions, and another sound context was treated with ultrasound but without prosodic cueing for 7 sessions. Sessions included ultrasound visual feedback as well as non-ultrasound treatment. Word-level probes assessing untreated words were used to evaluate retention and generalization. Results For most participants, increases in accuracy of target sound contexts at the word level were observed with the treatment program regardless of whether prosodic cueing was included. Generalization between onset singletons and clusters was observed, as well as generalization to sentence-level accuracy. There was evidence of retention during post-treatment probes, including at a two-month follow-up. Conclusions A motor-based treatment program that includes ultrasound visual feedback can facilitate learning of speech sounds in individuals with residual speech sound errors. PMID:25087938

Problem solving of student with visual impairment related to mathematical literacy problem

NASA Astrophysics Data System (ADS)

Pratama, A. R.; Saputro, D. R. S.; Riyadi

2018-04-01

The student with visual impairment, total blind category depends on the sense of touch and hearing in obtaining information. In fact, the two senses can receive information less than 20%. Thus, students with visual impairment of the total blind categories in the learning process must have difficulty, including learning mathematics. This study aims to describe the problem-solving process of the student with visual impairment, total blind category on mathematical literacy issues based on Polya phase. This research using test method similar problems mathematical literacy in PISA and in-depth interviews. The subject of this study was a student with visual impairment, total blind category. Based on the result of the research, problem-solving related to mathematical literacy based on Polya phase is quite good. In the phase of understanding the problem, the student read about twice by brushing the text and assisted with information through hearing three times. The student with visual impairment in problem-solving based on the Polya phase, devising a plan by summoning knowledge and experience gained previously. At the phase of carrying out the plan, students with visual impairment implement the plan in accordance with pre-made. In the looking back phase, students with visual impairment need to check the answers three times but have not been able to find a way.

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

PubMed

Reavis, Eric A; Frank, Sebastian M; Greenlee, Mark W; Tse, Peter U

2016-06-01

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Dissociation of visual associative and motor learning in Drosophila at the flight simulator.

PubMed

Wang, Shunpeng; Li, Yan; Feng, Chunhua; Guo, Aike

2003-08-29

Ever since operant conditioning was studied experimentally, the relationship between associative learning and possible motor learning has become controversial. Although motor learning and its underlying neural substrates have been extensively studied in mammals, it is still poorly understood in invertebrates. The visual discriminative avoidance paradigm of Drosophila at the flight simulator has been widely used to study the flies' visual associative learning and related functions, but it has not been used to study the motor learning process. In this study, newly-designed data analysis was employed to examine the flies' solitary behavioural variable that was recorded at the flight simulator-yaw torque. Analysis was conducted to explore torque distributions of both wild-type and mutant flies in conditioning, with the following results: (1) Wild-type Canton-S flies had motor learning performance in conditioning, which was proved by modifications of the animal's behavioural mode in conditioning. (2) Repetition of training improved the motor learning performance of wild-type Canton-S flies. (3) Although mutant dunce(1) flies were defective in visual associative learning, they showed essentially normal motor learning performance in terms of yaw torque distribution in conditioning. Finally, we tentatively proposed that both visual associative learning and motor learning were involved in the visual operant conditioning of Drosophila at the flight simulator, that the two learning forms could be dissociated and they might have different neural bases.

Action-Driven Visual Object Tracking With Deep Reinforcement Learning.

PubMed

Yun, Sangdoo; Choi, Jongwon; Yoo, Youngjoon; Yun, Kimin; Choi, Jin Young

2018-06-01

In this paper, we propose an efficient visual tracker, which directly captures a bounding box containing the target object in a video by means of sequential actions learned using deep neural networks. The proposed deep neural network to control tracking actions is pretrained using various training video sequences and fine-tuned during actual tracking for online adaptation to a change of target and background. The pretraining is done by utilizing deep reinforcement learning (RL) as well as supervised learning. The use of RL enables even partially labeled data to be successfully utilized for semisupervised learning. Through the evaluation of the object tracking benchmark data set, the proposed tracker is validated to achieve a competitive performance at three times the speed of existing deep network-based trackers. The fast version of the proposed method, which operates in real time on graphics processing unit, outperforms the state-of-the-art real-time trackers with an accuracy improvement of more than 8%.

Studying Visual Displays: How to Instructionally Support Learning

ERIC Educational Resources Information Center

Renkl, Alexander; Scheiter, Katharina

2017-01-01

Visual displays are very frequently used in learning materials. Although visual displays have great potential to foster learning, they also pose substantial demands on learners so that the actual learning outcomes are often disappointing. In this article, we pursue three main goals. First, we identify the main difficulties that learners have when…

Template optimization and transfer in perceptual learning.

PubMed

Kurki, Ilmari; Hyvärinen, Aapo; Saarinen, Jussi

2016-08-01

We studied how learning changes the processing of a low-level Gabor stimulus, using a classification-image method (psychophysical reverse correlation) and a task where observers discriminated between slight differences in the phase (relative alignment) of a target Gabor in visual noise. The method estimates the internal "template" that describes how the visual system weights the input information for decisions. One popular idea has been that learning makes the template more like an ideal Bayesian weighting; however, the evidence has been indirect. We used a new regression technique to directly estimate the template weight change and to test whether the direction of reweighting is significantly different from an optimal learning strategy. The subjects trained the task for six daily sessions, and we tested the transfer of training to a target in an orthogonal orientation. Strong learning and partial transfer were observed. We tested whether task precision (difficulty) had an effect on template change and transfer: Observers trained in either a high-precision (small, 60° phase difference) or a low-precision task (180°). Task precision did not have an effect on the amount of template change or transfer, suggesting that task precision per se does not determine whether learning generalizes. Classification images show that training made observers use more task-relevant features and unlearn some irrelevant features. The transfer templates resembled partially optimized versions of templates in training sessions. The template change direction resembles ideal learning significantly but not completely. The amount of template change was highly correlated with the amount of learning.

Differential learning and memory performance in OEF/OIF veterans for verbal and visual material.

PubMed

Sozda, Christopher N; Muir, James J; Springer, Utaka S; Partovi, Diana; Cole, Michael A

2014-05-01

Memory complaints are particularly salient among veterans who experience combat-related mild traumatic brain injuries and/or trauma exposure, and represent a primary barrier to successful societal reintegration and everyday functioning. Anecdotally within clinical practice, verbal learning and memory performance frequently appears differentially reduced versus visual learning and memory scores. We sought to empirically investigate the robustness of a verbal versus visual learning and memory discrepancy and to explore potential mechanisms for a verbal/visual performance split. Participants consisted of 103 veterans with reported history of mild traumatic brain injuries returning home from U.S. military Operations Enduring Freedom and Iraqi Freedom referred for outpatient neuropsychological evaluation. Findings indicate that visual learning and memory abilities were largely intact while verbal learning and memory performance was significantly reduced in comparison, residing at approximately 1.1 SD below the mean for verbal learning and approximately 1.4 SD below the mean for verbal memory. This difference was not observed in verbal versus visual fluency performance, nor was it associated with estimated premorbid verbal abilities or traumatic brain injury history. In our sample, symptoms of depression, but not posttraumatic stress disorder, were significantly associated with reduced composite verbal learning and memory performance. Verbal learning and memory performance may benefit from targeted treatment of depressive symptomatology. Also, because visual learning and memory functions may remain intact, these might be emphasized when applying neurocognitive rehabilitation interventions to compensate for observed verbal learning and memory difficulties.

Age-related declines of stability in visual perceptual learning.

PubMed

Chang, Li-Hung; Shibata, Kazuhisa; Andersen, George J; Sasaki, Yuka; Watanabe, Takeo

2014-12-15

One of the biggest questions in learning is how a system can resolve the plasticity and stability dilemma. Specifically, the learning system needs to have not only a high capability of learning new items (plasticity) but also a high stability to retain important items or processing in the system by preventing unimportant or irrelevant information from being learned. This dilemma should hold true for visual perceptual learning (VPL), which is defined as a long-term increase in performance on a visual task as a result of visual experience. Although it is well known that aging influences learning, the effect of aging on the stability and plasticity of the visual system is unclear. To address the question, we asked older and younger adults to perform a task while a task-irrelevant feature was merely exposed. We found that older individuals learned the task-irrelevant features that younger individuals did not learn, both the features that were sufficiently strong for younger individuals to suppress and the features that were too weak for younger individuals to learn. At the same time, there was no plasticity reduction in older individuals within the task tested. These results suggest that the older visual system is less stable to unimportant information than the younger visual system. A learning problem with older individuals may be due to a decrease in stability rather than a decrease in plasticity, at least in VPL. Copyright © 2014 Elsevier Ltd. All rights reserved.

Single image super-resolution based on convolutional neural networks

NASA Astrophysics Data System (ADS)

Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

2018-03-01

We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

Improvement of The Ability of Junior High School Students Thinking Through Visual Learning Assisted Geo gbra Tutorial

NASA Astrophysics Data System (ADS)

Elvi, M.; Nurjanah

2017-02-01

This research is distributed on the issue of the lack of visual thinking ability is a must-have basic ability of students in learning geometry. The purpose of this research is to investigate and elucide: 1) the enhancement of visual thinking ability of students to acquire learning assisted with geogebra tutorial learning: 2) the increase in visual thinking ability of students who obtained a model of learning assisted with geogebra and students who obtained a regular study of KAM (high, medium, and low). This research population is grade VII in Bandung Junior High School. The instruments used to collect data in this study consisted of instruments of the test and the observation sheet. The data obtained were analyzed using the test average difference i.e. Test-t and ANOVA Test one line to two lines. The results showed that: 1) the attainment and enhancement of visual thinking ability of students to acquire learning assisted geogebra tutorial better than students who acquire learning; 2) there may be differences of visual upgrade thinking students who acquire the learning model assisted with geogebra tutorial earn regular learning of KAM (high, medium and low).

Learning Using Dynamic and Static Visualizations: Students' Comprehension, Prior Knowledge and Conceptual Status of a Biotechnological Method

NASA Astrophysics Data System (ADS)

Yarden, Hagit; Yarden, Anat

2010-05-01

The importance of biotechnology education at the high-school level has been recognized in a number of international curriculum frameworks around the world. One of the most problematic issues in learning biotechnology has been found to be the biotechnological methods involved. Here, we examine the unique contribution of an animation of the polymerase chain reaction (PCR) in promoting conceptual learning of the biotechnological method among 12th-grade biology majors. All of the students learned about the PCR using still images ( n = 83) or the animation ( n = 90). A significant advantage to the animation treatment was identified following learning. Students’ prior content knowledge was found to be an important factor for students who learned PCR using still images, serving as an obstacle to learning the PCR method in the case of low prior knowledge. Through analysing students’ discourse, using the framework of the conceptual status analysis, we found that students who learned about PCR using still images faced difficulties in understanding some mechanistic aspects of the method. On the other hand, using the animation gave the students an advantage in understanding those aspects.

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Teaching of Basic Posture Skills in Visually Impaired Individuals and Its Implementation under Aggravated Conditions

ERIC Educational Resources Information Center

Suveren-Erdogan, Ceren; Suveren, Sibel

2018-01-01

The aim of this study is to enable basic posture exercises to be included in the basic exercises of the visually impaired individuals as a step to learn more difficult movements, to guide the instructors in order to make efficient progress in a short time and to help more numbers of disabled individuals benefit from these studies. Method: 15…

Spelling: A Visual Skill.

ERIC Educational Resources Information Center

Hendrickson, Homer

1988-01-01

Spelling problems arise due to problems with form discrimination and inadequate visualization. A child's sequence of visual development involves learning motor control and coordination, with vision directing and monitoring the movements; learning visual comparison of size, shape, directionality, and solidity; developing visual memory or recall;…

The pedagogical toolbox: computer-generated visual displays, classroom demonstration, and lecture.

PubMed

Bockoven, Jerry

2004-06-01

This analogue study compared the effectiveness of computer-generated visual displays, classroom demonstration, and traditional lecture as methods of instruction used to teach neuronal structure and processes. Randomly assigned 116 undergraduate students participated in 1 of 3 classrooms in which they experienced the same content but different teaching approaches presented by 3 different student-instructors. Then participants completed a survey of their subjective reactions and a measure of factual information designed to evaluate objective learning outcomes. Participants repeated this factual measure 5 wk. later. Results call into question the use of classroom demonstration methods as well as the trend towards devaluing traditional lecture in favor of computer-generated visual display.

iSee: Teaching Visual Learning in an Organic Virtual Learning Environment

ERIC Educational Resources Information Center

Han, Hsiao-Cheng

2017-01-01

This paper presents a three-year participatory action research project focusing on the graduate level course entitled Visual Learning in 3D Animated Virtual Worlds. The purpose of this research was to understand "How the virtual world processes of observing and creating can best help students learn visual theories". The first cycle of…

Guided Discovery, Visualization, and Technology Applied to the New Curriculum for Secondary Mathematics.

ERIC Educational Resources Information Center

Smith, Karan B.

1996-01-01

Presents activities which highlight major concepts of linear programming. Demonstrates how technology allows students to solve linear programming problems using exploration prior to learning algorithmic methods. (DDR)

[Associative Learning between Orientation and Color in Early Visual Areas].

PubMed

Amano, Kaoru; Shibata, Kazuhisa; Kawato, Mitsuo; Sasaki, Yuka; Watanabe, Takeo

2017-08-01

Associative learning is an essential neural phenomenon where the contingency of different items increases after training. Although associative learning has been found to occur in many brain regions, there is no clear evidence that associative learning of visual features occurs in early visual areas. Here, we developed an associative decoded functional magnetic resonance imaging (fMRI) neurofeedback (A-DecNef) to determine whether associative learning of color and orientation can be induced in early visual areas. During the three days' training, A-DecNef induced fMRI signal patterns that corresponded to a specific target color (red) mostly in early visual areas while a vertical achromatic grating was simultaneously, physically presented to participants. Consequently, participants' perception of "red" was significantly more frequently than that of "green" in an achromatic vertical grating. This effect was also observed 3 to 5 months after training. These results suggest that long-term associative learning of two different visual features such as color and orientation, was induced most likely in early visual areas. This newly extended technique that induces associative learning may be used as an important tool for understanding and modifying brain function, since associations are fundamental and ubiquitous with respect to brain function.

Perceptual learning in visual search: fast, enduring, but non-specific.

PubMed

Sireteanu, R; Rettenbach, R

1995-07-01

Visual search has been suggested as a tool for isolating visual primitives. Elementary "features" were proposed to involve parallel search, while serial search is necessary for items without a "feature" status, or, in some cases, for conjunctions of "features". In this study, we investigated the role of practice in visual search tasks. We found that, under some circumstances, initially serial tasks can become parallel after a few hundred trials. Learning in visual search is far less specific than learning of visual discriminations and hyperacuity, suggesting that it takes place at another level in the central visual pathway, involving different neural circuits.

Learning sorting algorithms through visualization construction

NASA Astrophysics Data System (ADS)

Cetin, Ibrahim; Andrews-Larson, Christine

2016-01-01

Recent increased interest in computational thinking poses an important question to researchers: What are the best ways to teach fundamental computing concepts to students? Visualization is suggested as one way of supporting student learning. This mixed-method study aimed to (i) examine the effect of instruction in which students constructed visualizations on students' programming achievement and students' attitudes toward computer programming, and (ii) explore how this kind of instruction supports students' learning according to their self-reported experiences in the course. The study was conducted with 58 pre-service teachers who were enrolled in their second programming class. They expect to teach information technology and computing-related courses at the primary and secondary levels. An embedded experimental model was utilized as a research design. Students in the experimental group were given instruction that required students to construct visualizations related to sorting, whereas students in the control group viewed pre-made visualizations. After the instructional intervention, eight students from each group were selected for semi-structured interviews. The results showed that the intervention based on visualization construction resulted in significantly better acquisition of sorting concepts. However, there was no significant difference between the groups with respect to students' attitudes toward computer programming. Qualitative data analysis indicated that students in the experimental group constructed necessary abstractions through their engagement in visualization construction activities. The authors of this study argue that the students' active engagement in the visualization construction activities explains only one side of students' success. The other side can be explained through the instructional approach, constructionism in this case, used to design instruction. The conclusions and implications of this study can be used by researchers and instructors dealing with computational thinking.

Interface Metaphors for Interactive Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jasper, Robert J.; Blaha, Leslie M.

To promote more interactive and dynamic machine learn- ing, we revisit the notion of user-interface metaphors. User-interface metaphors provide intuitive constructs for supporting user needs through interface design elements. A user-interface metaphor provides a visual or action pattern that leverages a user’s knowledge of another domain. Metaphors suggest both the visual representations that should be used in a display as well as the interactions that should be afforded to the user. We argue that user-interface metaphors can also offer a method of extracting interaction-based user feedback for use in machine learning. Metaphors offer indirect, context-based information that can be usedmore » in addition to explicit user inputs, such as user-provided labels. Implicit information from user interactions with metaphors can augment explicit user input for active learning paradigms. Or it might be leveraged in systems where explicit user inputs are more challenging to obtain. Each interaction with the metaphor provides an opportunity to gather data and learn. We argue this approach is especially important in streaming applications, where we desire machine learning systems that can adapt to dynamic, changing data.« less

Motor-visual neurons and action recognition in social interactions.

PubMed

de la Rosa, Stephan; Bülthoff, Heinrich H

2014-04-01

Cook et al. suggest that motor-visual neurons originate from associative learning. This suggestion has interesting implications for the processing of socially relevant visual information in social interactions. Here, we discuss two aspects of the associative learning account that seem to have particular relevance for visual recognition of social information in social interactions - namely, context-specific and contingency based learning.

Implicit visual learning and the expression of learning.

PubMed

Haider, Hilde; Eberhardt, Katharina; Kunde, Alexander; Rose, Michael

2013-03-01

Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes. Copyright © 2012 Elsevier Inc. All rights reserved.

[The study of functional status in the perception of visual information depending on the method of technical color mixing on LCD and DLP projectors technology].

PubMed

Merkulova, A G; Osokina, E S; Bukhtiiarov, I V

2014-10-01

The case of compare two ways of projection color visual images, characterized by different spatial-temporal characteristics of visual stimuli, presents the methodology and the set of techniques. Received comparative data, identifying risks of regulation disorder of the functional state and development general, mental and visual fatigue during prolonged strenuous visual activity, according to two types of test tasks, which are the most typical for the use of modern projectors to work with the audience, both inthe process of implementation of learning technologies and the collective take responsible decisions by expert groups that control of complex technological processes.

Plastic Bags and Environmental Pollution

ERIC Educational Resources Information Center

Sang, Anita Ng Heung

2010-01-01

The "Hong Kong Visual Arts Curriculum Guide," covering Primary 1 to Secondary 3 grades (Curriculum Development Committee, 2003), points to three domains of learning in visual arts: (1) visual arts knowledge; (2) visual arts appreciation and criticism; and (3) visual arts making. The "Guide" suggests learning should develop…

Differential Effects of Music and Video Gaming During Breaks on Auditory and Visual Learning.

PubMed

Liu, Shuyan; Kuschpel, Maxim S; Schad, Daniel J; Heinz, Andreas; Rapp, Michael A

2015-11-01

The interruption of learning processes by breaks filled with diverse activities is common in everyday life. This study investigated the effects of active computer gaming and passive relaxation (rest and music) breaks on auditory versus visual memory performance. Young adults were exposed to breaks involving (a) open eyes resting, (b) listening to music, and (c) playing a video game, immediately after memorizing auditory versus visual stimuli. To assess learning performance, words were recalled directly after the break (an 8:30 minute delay) and were recalled and recognized again after 7 days. Based on linear mixed-effects modeling, it was found that playing the Angry Birds video game during a short learning break impaired long-term retrieval in auditory learning but enhanced long-term retrieval in visual learning compared with the music and rest conditions. These differential effects of video games on visual versus auditory learning suggest specific interference of common break activities on learning.

Time course influences transfer of visual perceptual learning across spatial location.

PubMed

Larcombe, S J; Kennard, C; Bridge, H

2017-06-01

Visual perceptual learning describes the improvement of visual perception with repeated practice. Previous research has established that the learning effects of perceptual training may be transferable to untrained stimulus attributes such as spatial location under certain circumstances. However, the mechanisms involved in transfer have not yet been fully elucidated. Here, we investigated the effect of altering training time course on the transferability of learning effects. Participants were trained on a motion direction discrimination task or a sinusoidal grating orientation discrimination task in a single visual hemifield. The 4000 training trials were either condensed into one day, or spread evenly across five training days. When participants were trained over a five-day period, there was transfer of learning to both the untrained visual hemifield and the untrained task. In contrast, when the same amount of training was condensed into a single day, participants did not show any transfer of learning. Thus, learning time course may influence the transferability of perceptual learning effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of Auditory/Visual and Visual/Motor Practice on the Spelling Accuracy of Learning Disabled Children.

ERIC Educational Resources Information Center

Aleman, Cheryl; And Others

1990-01-01

Compares auditory/visual practice to visual/motor practice in spelling with seven elementary school learning-disabled students enrolled in a resource room setting. Finds that the auditory/visual practice was superior to the visual/motor practice on the weekly spelling performance for all seven students. (MG)

Magnetic stimulation of visual cortex impairs perceptual learning.

PubMed

Baldassarre, Antonello; Capotosto, Paolo; Committeri, Giorgia; Corbetta, Maurizio

2016-12-01

The ability to learn and process visual stimuli more efficiently is important for survival. Previous neuroimaging studies have shown that perceptual learning on a shape identification task differently modulates activity in both frontal-parietal cortical regions and visual cortex (Sigman et al., 2005;Lewis et al., 2009). Specifically, fronto-parietal regions (i.e. intra parietal sulcus, pIPS) became less activated for trained as compared to untrained stimuli, while visual regions (i.e. V2d/V3 and LO) exhibited higher activation for familiar shape. Here, after the intensive training, we employed transcranial magnetic stimulation over both visual occipital and parietal regions, previously shown to be modulated, to investigate their causal role in learning the shape identification task. We report that interference with V2d/V3 and LO increased reaction times to learned stimuli as compared to pIPS and Sham control condition. Moreover, the impairment observed after stimulation over the two visual regions was positive correlated. These results strongly support the causal role of the visual network in the control of the perceptual learning. Copyright © 2016 Elsevier Inc. All rights reserved.

Visual Associative Learning in Restrained Honey Bees with Intact Antennae

PubMed Central

Dobrin, Scott E.; Fahrbach, Susan E.

2012-01-01

A restrained honey bee can be trained to extend its proboscis in response to the pairing of an odor with a sucrose reward, a form of olfactory associative learning referred to as the proboscis extension response (PER). Although the ability of flying honey bees to respond to visual cues is well-established, associative visual learning in restrained honey bees has been challenging to demonstrate. Those few groups that have documented vision-based PER have reported that removing the antennae prior to training is a prerequisite for learning. Here we report, for a simple visual learning task, the first successful performance by restrained honey bees with intact antennae. Honey bee foragers were trained on a differential visual association task by pairing the presentation of a blue light with a sucrose reward and leaving the presentation of a green light unrewarded. A negative correlation was found between age of foragers and their performance in the visual PER task. Using the adaptations to the traditional PER task outlined here, future studies can exploit pharmacological and physiological techniques to explore the neural circuit basis of visual learning in the honey bee. PMID:22701575

The Effect of Image Quality, Repeated Study, and Assessment Method on Anatomy Learning

ERIC Educational Resources Information Center

Fenesi, Barbara; Mackinnon, Chelsea; Cheng, Lucia; Kim, Joseph A.; Wainman, Bruce C.

2017-01-01

The use of two-dimensional (2D) images is consistently used to prepare anatomy students for handling real specimen. This study examined whether the quality of 2D images is a critical component in anatomy learning. The visual clarity and consistency of 2D anatomical images was systematically manipulated to produce low-quality and high-quality…

Evaluating the Ability of and Enabling a Blind Adult with Learning Disability to Sign a Tenancy Agreement

ERIC Educational Resources Information Center

Waight, Mary Philomena; Oldreive, Warren James

2012-01-01

This paper aims to describe the process undertaken by Speech and Language Therapy and Occupational Therapy to assess a gentleman with learning disabilities and visual impairment with regard to his capacity to sign a tenancy agreement. It describes the method used to assess the gentleman's mental capacity before exploring the system used to provide…

Pornographic image recognition and filtering using incremental learning in compressed domain

NASA Astrophysics Data System (ADS)

Zhang, Jing; Wang, Chao; Zhuo, Li; Geng, Wenhao

2015-11-01

With the rapid development and popularity of the network, the openness, anonymity, and interactivity of networks have led to the spread and proliferation of pornographic images on the Internet, which have done great harm to adolescents' physical and mental health. With the establishment of image compression standards, pornographic images are mainly stored with compressed formats. Therefore, how to efficiently filter pornographic images is one of the challenging issues for information security. A pornographic image recognition and filtering method in the compressed domain is proposed by using incremental learning, which includes the following steps: (1) low-resolution (LR) images are first reconstructed from the compressed stream of pornographic images, (2) visual words are created from the LR image to represent the pornographic image, and (3) incremental learning is adopted to continuously adjust the classification rules to recognize the new pornographic image samples after the covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic images. The experimental results show that the proposed pornographic image recognition method using incremental learning has a higher recognition rate as well as costing less recognition time in the compressed domain.

Cross-Sensory Transfer of Reference Frames in Spatial Memory

ERIC Educational Resources Information Center

Kelly, Jonathan W.; Avraamides, Marios N.

2011-01-01

Two experiments investigated whether visual cues influence spatial reference frame selection for locations learned through touch. Participants experienced visual cues emphasizing specific environmental axes and later learned objects through touch. Visual cues were manipulated and haptic learning conditions were held constant. Imagined perspective…

Learning style, judgements of learning, and learning of verbal and visual information.

PubMed

Knoll, Abby R; Otani, Hajime; Skeel, Reid L; Van Horn, K Roger

2017-08-01

The concept of learning style is immensely popular despite the lack of evidence showing that learning style influences performance. This study tested the hypothesis that the popularity of learning style is maintained because it is associated with subjective aspects of learning, such as judgements of learning (JOLs). Preference for verbal and visual information was assessed using the revised Verbalizer-Visualizer Questionnaire (VVQ). Then, participants studied a list of word pairs and a list of picture pairs, making JOLs (immediate, delayed, and global) while studying each list. Learning was tested by cued recall. The results showed that higher VVQ verbalizer scores were associated with higher immediate JOLs for words, and higher VVQ visualizer scores were associated with higher immediate JOLs for pictures. There was no association between VVQ scores and recall or JOL accuracy. As predicted, learning style was associated with subjective aspects of learning but not objective aspects of learning. © 2016 The British Psychological Society.

An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

ERIC Educational Resources Information Center

McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

2016-01-01

Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

Task-Appropriate Visualizations: Can the Very Same Visualization Format Either Promote or Hinder Learning Depending on the Task Requirements?

ERIC Educational Resources Information Center

Soemer, Alexander; Schwan, Stephan

2016-01-01

In a series of experiments, we tested a recently proposed hypothesis stating that the degree of alignment between the form of a mental representation resulting from learning with a particular visualization format and the specific requirements of a learning task determines learning performance (task-appropriateness). Groups of participants were…

Elements of Scenario-Based Learning on Suicidal Patient Care Using Real-Time Video.

PubMed

Lu, Chuehfen; Lee, Hueying; Hsu, Shuhui; Shu, Inmei

2016-01-01

This study aims understanding of students' learning experiences when receiving scenario-based learning combined with real-time video. Videos that recorded student nurses intervention with a suicidal standardized patient (SP) were replayed immediately as teaching materials. Videos clips and field notes from ten classes were analysed. Investigators and method triangulation were used to boost the robustness of the study. Three key elements, emotional involvement, concretizing of the teaching material and substitute learning were identified. Emotions were evoked among the SP, the student performer and the students who were observing, thus facilitating a learning effect. Concretizing of the teaching material refers to students were able to focus on the discussions using visual and verbal information. Substitute learning occurred when the students watching the videos, both the strengths and weaknesses represented were similar to those that would be likely to occur. These key elements explicate their learning experience and suggested a strategic teaching method.

Social Image Tag Ranking by Two-View Learning

NASA Astrophysics Data System (ADS)

Zhuang, Jinfeng; Hoi, Steven C. H.

Tags play a central role in text-based social image retrieval and browsing. However, the tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In order to solve this problem, researchers have proposed techniques to rank the annotated tags of a social image according to their relevance to the visual content of the image. In this paper, we aim to overcome the challenge of social image tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the conventional learning approaches that usually assumes some parametric models, our method is completely data-driven and makes no assumption about the underlying models, making the proposed solution practically more effective. We formulate our method as an optimization task and present an efficient algorithm to solve it. To evaluate the efficacy of our method, we conducted an extensive set of experiments by applying our technique to both text-based social image retrieval and automatic image annotation tasks. Our empirical results showed that the proposed method can be more effective than the conventional approaches.

Development of Visualization of Learning Outcomes Using Curriculum Mapping

ERIC Educational Resources Information Center

Ikuta, Takashi; Gotoh, Yasushi

2012-01-01

Niigata University has started to develop the Niigata University Bachelor Assessment System (NBAS). The objective is to have groups of teachers belonging to educational programs discuss whether visualized learning outcomes are comprehensible. Discussions based on teachers' subjective judgments showed in general that visualized learning outcomes…

Teaching for Different Learning Styles.

ERIC Educational Resources Information Center

Cropper, Carolyn

1994-01-01

This study examined learning styles in 137 high ability fourth-grade students. All students were administered two learning styles inventories. Characteristics of students with the following learning styles are summarized: auditory language, visual language, auditory numerical, visual numerical, tactile concrete, individual learning, group…

A diagram retrieval method with multi-label learning

NASA Astrophysics Data System (ADS)

Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

2015-01-01

In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

Learning Building Layouts with Non-geometric Visual Information: The Effects of Visual Impairment and Age

PubMed Central

Kalia, Amy A.; Legge, Gordon E.; Giudice, Nicholas A.

2009-01-01

Previous studies suggest that humans rely on geometric visual information (hallway structure) rather than non-geometric visual information (e.g., doors, signs and lighting) for acquiring cognitive maps of novel indoor layouts. This study asked whether visual impairment and age affect reliance on non-geometric visual information for layout learning. We tested three groups of participants—younger (< 50 years) normally sighted, older (50–70 years) normally sighted, and low vision (people with heterogeneous forms of visual impairment ranging in age from 18–67). Participants learned target locations in building layouts using four presentation modes: a desktop virtual environment (VE) displaying only geometric cues (Sparse VE), a VE displaying both geometric and non-geometric cues (Photorealistic VE), a Map, and a Real building. Layout knowledge was assessed by map drawing and by asking participants to walk to specified targets in the real space. Results indicate that low-vision and older normally-sighted participants relied on additional non-geometric information to accurately learn layouts. In conclusion, visual impairment and age may result in reduced perceptual and/or memory processing that makes it difficult to learn layouts without non-geometric visual information. PMID:19189732

Multisensory perceptual learning of temporal order: audiovisual learning transfers to vision but not audition.

PubMed

Alais, David; Cass, John

2010-06-23

An outstanding question in sensory neuroscience is whether the perceived timing of events is mediated by a central supra-modal timing mechanism, or multiple modality-specific systems. We use a perceptual learning paradigm to address this question. Three groups were trained daily for 10 sessions on an auditory, a visual or a combined audiovisual temporal order judgment (TOJ). Groups were pre-tested on a range TOJ tasks within and between their group modality prior to learning so that transfer of any learning from the trained task could be measured by post-testing other tasks. Robust TOJ learning (reduced temporal order discrimination thresholds) occurred for all groups, although auditory learning (dichotic 500/2000 Hz tones) was slightly weaker than visual learning (lateralised grating patches). Crossmodal TOJs also displayed robust learning. Post-testing revealed that improvements in temporal resolution acquired during visual learning transferred within modality to other retinotopic locations and orientations, but not to auditory or crossmodal tasks. Auditory learning did not transfer to visual or crossmodal tasks, and neither did it transfer within audition to another frequency pair. In an interesting asymmetry, crossmodal learning transferred to all visual tasks but not to auditory tasks. Finally, in all conditions, learning to make TOJs for stimulus onsets did not transfer at all to discriminating temporal offsets. These data present a complex picture of timing processes. The lack of transfer between unimodal groups indicates no central supramodal timing process for this task; however, the audiovisual-to-visual transfer cannot be explained without some form of sensory interaction. We propose that auditory learning occurred in frequency-tuned processes in the periphery, precluding interactions with more central visual and audiovisual timing processes. Functionally the patterns of featural transfer suggest that perceptual learning of temporal order may be optimised to object-centered rather than viewer-centered constraints.

Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Potter, Kristin C; Brunhart-Lupo, Nicholas J; Bush, Brian W

We have developed a framework for the exploration, design, and planning of energy systems that combines interactive visualization with machine-learning based approximations of simulations through a general purpose dataflow API. Our system provides a visual inter- face allowing users to explore an ensemble of energy simulations representing a subset of the complex input parameter space, and spawn new simulations to 'fill in' input regions corresponding to new enegery system scenarios. Unfortunately, many energy simula- tions are far too slow to provide interactive responses. To support interactive feedback, we are developing reduced-form models via machine learning techniques, which provide statistically soundmore » esti- mates of the full simulations at a fraction of the computational cost and which are used as proxies for the full-form models. Fast com- putation and an agile dataflow enhance the engagement with energy simulations, and allow researchers to better allocate computational resources to capture informative relationships within the system and provide a low-cost method for validating and quality-checking large-scale modeling efforts.« less

Visual-motor association learning in undergraduate students as a function of the autism-spectrum quotient.

PubMed

Parkington, Karisa B; Clements, Rebecca J; Landry, Oriane; Chouinard, Philippe A

2015-10-01

We examined how performance on an associative learning task changes in a sample of undergraduate students as a function of their autism-spectrum quotient (AQ) score. The participants, without any prior knowledge of the Japanese language, learned to associate hiragana characters with button responses. In the novel condition, 50 participants learned visual-motor associations without any prior exposure to the stimuli's visual attributes. In the familiar condition, a different set of 50 participants completed a session in which they first became familiar with the stimuli's visual appearance prior to completing the visual-motor association learning task. Participants with higher AQ scores had a clear advantage in the novel condition; the amount of training required reaching learning criterion correlated negatively with AQ. In contrast, participants with lower AQ scores had a clear advantage in the familiar condition; the amount of training required to reach learning criterion correlated positively with AQ. An examination of how each of the AQ subscales correlated with these learning patterns revealed that abilities in visual discrimination-which is known to depend on the visual ventral-stream system-may have afforded an advantage in the novel condition for the participants with the higher AQ scores, whereas abilities in attention switching-which are known to require mechanisms in the prefrontal cortex-may have afforded an advantage in the familiar condition for the participants with the lower AQ scores.

Learning invariance from natural images inspired by observations in the primary visual cortex.

PubMed

Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

"Visual Learning Is the Best Learning--It Lets You Be Creative while Learning": Exploring Ways to Begin Guided Writing in Second Language Learning through the Use of Comics

ERIC Educational Resources Information Center

Rossetto, Marietta; Chiera-Macchia, Antonella

2011-01-01

This study investigated the use of comics (Cary, 2004) in a guided writing experience in secondary school Italian language learning. The main focus of the peer group interaction task included the exploration of visual sequencing and visual integration (Bailey, O'Grady-Jones, & McGown, 1995) using image and text to create a comic strip narrative in…

Unsupervised and self-mapping category formation and semantic object recognition for mobile robot vision used in an actual environment

NASA Astrophysics Data System (ADS)

Madokoro, H.; Tsukada, M.; Sato, K.

2013-07-01

This paper presents an unsupervised learning-based object category formation and recognition method for mobile robot vision. Our method has the following features: detection of feature points and description of features using a scale-invariant feature transform (SIFT), selection of target feature points using one class support vector machines (OC-SVMs), generation of visual words using self-organizing maps (SOMs), formation of labels using adaptive resonance theory 2 (ART-2), and creation and classification of categories on a category map of counter propagation networks (CPNs) for visualizing spatial relations between categories. Classification results of dynamic images using time-series images obtained using two different-size robots and according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category formation of appearance changes of objects.

Electrophysiological evidence of heterogeneity in visual statistical learning in young children with ASD.

PubMed

Jeste, Shafali S; Kirkham, Natasha; Senturk, Damla; Hasenstab, Kyle; Sugar, Catherine; Kupelian, Chloe; Baker, Elizabeth; Sanders, Andrew J; Shimizu, Christina; Norona, Amanda; Paparella, Tanya; Freeman, Stephanny F N; Johnson, Scott P

2015-01-01

Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism spectrum disorder (ASD) using an event-related potential shape learning paradigm, and we examined the relation between visual statistical learning and cognitive function. Compared to typically developing (TD) controls, the ASD group as a whole showed reduced evidence of learning as defined by N1 (early visual discrimination) and P300 (attention to novelty) components. Upon further analysis, in the ASD group there was a positive correlation between N1 amplitude difference and non-verbal IQ, and a positive correlation between P300 amplitude difference and adaptive social function. Children with ASD and a high non-verbal IQ and high adaptive social function demonstrated a distinctive pattern of learning. This is the first study to identify electrophysiological markers of visual statistical learning in children with ASD. Through this work we have demonstrated heterogeneity in statistical learning in ASD that maps onto non-verbal cognition and adaptive social function. © 2014 John Wiley & Sons Ltd.

Visual Complexity in Orthographic Learning: Modeling Learning across Writing System Variations

ERIC Educational Resources Information Center

Chang, Li-Yun; Plaut, David C.; Perfetti, Charles A.

2016-01-01

The visual complexity of orthographies varies across writing systems. Prior research has shown that complexity strongly influences the initial stage of reading development: the perceptual learning of grapheme forms. This study presents a computational simulation that examines the degree to which visual complexity leads to grapheme learning…

English Orthographic Learning in Chinese-L1 Young EFL Beginners

ERIC Educational Resources Information Center

Cheng, Yu-Lin

2017-01-01

English orthographic learning, among Chinese-L1 children who were beginning to learn English as a foreign language, was documented when: (1) "only" visual memory was at their disposal, (2) visual memory and either "some" letter-sound knowledge or "some" semantic information was available, and (3) visual memory,…

jAMVLE, a New Integrated Molecular Visualization Learning Environment

ERIC Educational Resources Information Center

Bottomley, Steven; Chandler, David; Morgan, Eleanor; Helmerhorst, Erik

2006-01-01

A new computer-based molecular visualization tool has been developed for teaching, and learning, molecular structure. This java-based jmol Amalgamated Molecular Visualization Learning Environment (jAMVLE) is platform-independent, integrated, and interactive. It has an overall graphical user interface that is intuitive and easy to use. The…

Drawing Connections across Conceptually Related Visual Representations in Science

ERIC Educational Resources Information Center

Hansen, Janice

2013-01-01

This dissertation explored beliefs about learning from multiple related visual representations in science, and compared beliefs to learning outcomes. Three research questions were explored: 1) What beliefs do pre-service teachers, non-educators and children have about learning from visual representations? 2) What format of presenting those…

Practice makes it better: A psychophysical study of visual perceptual learning and its transfer effects on aging.

PubMed

Li, Xuan; Allen, Philip A; Lien, Mei-Ching; Yamamoto, Naohide

2017-02-01

Previous studies on perceptual learning, acquiring a new skill through practice, appear to stimulate brain plasticity and enhance performance (Fiorentini & Berardi, 1981). The present study aimed to determine (a) whether perceptual learning can be used to compensate for age-related declines in perceptual abilities, and (b) whether the effect of perceptual learning can be transferred to untrained stimuli and subsequently improve capacity of visual working memory (VWM). We tested both healthy younger and older adults in a 3-day training session using an orientation discrimination task. A matching-to-sample psychophysical method was used to measure improvements in orientation discrimination thresholds and reaction times (RTs). Results showed that both younger and older adults improved discrimination thresholds and RTs with similar learning rates and magnitudes. Furthermore, older adults exhibited a generalization of improvements to 3 untrained orientations that were close to the training orientation and benefited more compared with younger adults from the perceptual learning as they transferred learning effects to the VWM performance. We conclude that through perceptual learning, older adults can partially counteract age-related perceptual declines, generalize the learning effect to other stimulus conditions, and further overcome the limitation of using VWM capacity to perform a perceptual task. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Search for Patterns of Functional Specificity in the Brain: A Nonparametric Hierarchical Bayesian Model for Group fMRI Data

PubMed Central

Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2012-01-01

Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with perviously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. PMID:21884803

Optometric Child Vision Care and Guidance. A Series of Papers Released by the Optometric Extension Program to its Membership 1966-1967.

ERIC Educational Resources Information Center

Optometric Extension Program, Duncan, OK.

The diagnosis and treatment of early learning problems and their relation to visual development is the subject of a series of 12 articles. The optometric viewpoint expressed is that vision is learned. A child's method of organizing his world, and manifestations of his disorganized behavior, including poor early academic achievement, probably…

An Exploratory Study of a New Educational Method Using Live Animals and Visual Thinking Strategies for Natural Science Teaching in Museums

ERIC Educational Resources Information Center

Genovesi, Jacqueline Sue

2011-01-01

The earth is in an environmental crisis that can only be addressed by changing human conservation attitudes. People must have the scientific knowledge to make informed decisions. Research identifying new promising practices, for the use of live animals that incorporate new theories of learning and factors proven to impact learning, is critical. …

After Action Review Tools For Team Training with Chat Communications

DTIC Science & Technology

2009-11-01

collaborative learning environments. The most relevant work is being done by the CALO ( Cognitive Agent that Learns and Organizes) project, a joint...emoticons, and other common stylistic practices. To a lesser degree, some research has yielded methods and tools to analyze or visualize chat...information sources, and overall cognitive effort. AAR Challenges The most significant challenge to conducting an effective after action review of

Analysis and Visualization of Relations in eLearning

NASA Astrophysics Data System (ADS)

Dráždilová, Pavla; Obadi, Gamila; Slaninová, Kateřina; Martinovič, Jan; Snášel, Václav

The popularity of eLearning systems is growing rapidly; this growth is enabled by the consecutive development in Internet and multimedia technologies. Web-based education became wide spread in the past few years. Various types of learning management systems facilitate development of Web-based courses. Users of these courses form social networks through the different activities performed by them. This chapter focuses on searching the latent social networks in eLearning systems data. These data consist of students activity records wherein latent ties among actors are embedded. The social network studied in this chapter is represented by groups of students who have similar contacts and interact in similar social circles. Different methods of data clustering analysis can be applied to these groups, and the findings show the existence of latent ties among the group members. The second part of this chapter focuses on social network visualization. Graphical representation of social network can describe its structure very efficiently. It can enable social network analysts to determine the network degree of connectivity. Analysts can easily determine individuals with a small or large amount of relationships as well as the amount of independent groups in a given network. When applied to the field of eLearning, data visualization simplifies the process of monitoring the study activities of individuals or groups, as well as the planning of educational curriculum, the evaluation of study processes, etc.

Multisensory training can promote or impede visual perceptual learning of speech stimuli: visual-tactile vs. visual-auditory training.

PubMed

Eberhardt, Silvio P; Auer, Edward T; Bernstein, Lynne E

2014-01-01

In a series of studies we have been investigating how multisensory training affects unisensory perceptual learning with speech stimuli. Previously, we reported that audiovisual (AV) training with speech stimuli can promote auditory-only (AO) perceptual learning in normal-hearing adults but can impede learning in congenitally deaf adults with late-acquired cochlear implants. Here, impeder and promoter effects were sought in normal-hearing adults who participated in lipreading training. In Experiment 1, visual-only (VO) training on paired associations between CVCVC nonsense word videos and nonsense pictures demonstrated that VO words could be learned to a high level of accuracy even by poor lipreaders. In Experiment 2, visual-auditory (VA) training in the same paradigm but with the addition of synchronous vocoded acoustic speech impeded VO learning of the stimuli in the paired-associates paradigm. In Experiment 3, the vocoded AO stimuli were shown to be less informative than the VO speech. Experiment 4 combined vibrotactile speech stimuli with the visual stimuli during training. Vibrotactile stimuli were shown to promote visual perceptual learning. In Experiment 5, no-training controls were used to show that training with visual speech carried over to consonant identification of untrained CVCVC stimuli but not to lipreading words in sentences. Across this and previous studies, multisensory training effects depended on the functional relationship between pathways engaged during training. Two principles are proposed to account for stimulus effects: (1) Stimuli presented to the trainee's primary perceptual pathway will impede learning by a lower-rank pathway. (2) Stimuli presented to the trainee's lower rank perceptual pathway will promote learning by a higher-rank pathway. The mechanisms supporting these principles are discussed in light of multisensory reverse hierarchy theory (RHT).

Multisensory training can promote or impede visual perceptual learning of speech stimuli: visual-tactile vs. visual-auditory training

PubMed Central

Eberhardt, Silvio P.; Auer Jr., Edward T.; Bernstein, Lynne E.

2014-01-01

In a series of studies we have been investigating how multisensory training affects unisensory perceptual learning with speech stimuli. Previously, we reported that audiovisual (AV) training with speech stimuli can promote auditory-only (AO) perceptual learning in normal-hearing adults but can impede learning in congenitally deaf adults with late-acquired cochlear implants. Here, impeder and promoter effects were sought in normal-hearing adults who participated in lipreading training. In Experiment 1, visual-only (VO) training on paired associations between CVCVC nonsense word videos and nonsense pictures demonstrated that VO words could be learned to a high level of accuracy even by poor lipreaders. In Experiment 2, visual-auditory (VA) training in the same paradigm but with the addition of synchronous vocoded acoustic speech impeded VO learning of the stimuli in the paired-associates paradigm. In Experiment 3, the vocoded AO stimuli were shown to be less informative than the VO speech. Experiment 4 combined vibrotactile speech stimuli with the visual stimuli during training. Vibrotactile stimuli were shown to promote visual perceptual learning. In Experiment 5, no-training controls were used to show that training with visual speech carried over to consonant identification of untrained CVCVC stimuli but not to lipreading words in sentences. Across this and previous studies, multisensory training effects depended on the functional relationship between pathways engaged during training. Two principles are proposed to account for stimulus effects: (1) Stimuli presented to the trainee’s primary perceptual pathway will impede learning by a lower-rank pathway. (2) Stimuli presented to the trainee’s lower rank perceptual pathway will promote learning by a higher-rank pathway. The mechanisms supporting these principles are discussed in light of multisensory reverse hierarchy theory (RHT). PMID:25400566

Limited Rank Matrix Learning, discriminative dimension reduction and visualization.

PubMed

Bunte, Kerstin; Schneider, Petra; Hammer, Barbara; Schleif, Frank-Michael; Villmann, Thomas; Biehl, Michael

2012-02-01

We present an extension of the recently introduced Generalized Matrix Learning Vector Quantization algorithm. In the original scheme, adaptive square matrices of relevance factors parameterize a discriminative distance measure. We extend the scheme to matrices of limited rank corresponding to low-dimensional representations of the data. This allows to incorporate prior knowledge of the intrinsic dimension and to reduce the number of adaptive parameters efficiently. In particular, for very large dimensional data, the limitation of the rank can reduce computation time and memory requirements significantly. Furthermore, two- or three-dimensional representations constitute an efficient visualization method for labeled data sets. The identification of a suitable projection is not treated as a pre-processing step but as an integral part of the supervised training. Several real world data sets serve as an illustration and demonstrate the usefulness of the suggested method. Copyright © 2011 Elsevier Ltd. All rights reserved.

No evidence for visual context-dependency of olfactory learning in Drosophila

NASA Astrophysics Data System (ADS)

Yarali, Ayse; Mayerle, Moritz; Nawroth, Christian; Gerber, Bertram

2008-08-01

How is behaviour organised across sensory modalities? Specifically, we ask concerning the fruit fly Drosophila melanogaster how visual context affects olfactory learning and recall and whether information about visual context is getting integrated into olfactory memory. We find that changing visual context between training and test does not deteriorate olfactory memory scores, suggesting that these olfactory memories can drive behaviour despite a mismatch of visual context between training and test. Rather, both the establishment and the recall of olfactory memory are generally facilitated by light. In a follow-up experiment, we find no evidence for learning about combinations of odours and visual context as predictors for reinforcement even after explicit training in a so-called biconditional discrimination task. Thus, a ‘true’ interaction between visual and olfactory modalities is not evident; instead, light seems to influence olfactory learning and recall unspecifically, for example by altering motor activity, alertness or olfactory acuity.

Visual Place Learning in Drosophila melanogaster

PubMed Central

Ofstad, Tyler A.; Zuker, Charles S.; Reiser, Michael B.

2011-01-01

The ability of insects to learn and navigate to specific locations in the environment has fascinated naturalists for decades. While the impressive navigation abilities of ants, bees, wasps, and other insects clearly demonstrate that insects are capable of visual place learning1–4, little is known about the underlying neural circuits that mediate these behaviors. Drosophila melanogaster is a powerful model organism for dissecting the neural circuitry underlying complex behaviors, from sensory perception to learning and memory. Flies can identify and remember visual features such as size, color, and contour orientation5, 6. However, the extent to which they use vision to recall specific locations remains unclear. Here we describe a visual place-learning platform and demonstrate that Drosophila are capable of forming and retaining visual place memories to guide selective navigation. By targeted genetic silencing of small subsets of cells in the Drosophila brain we show that neurons in the ellipsoid body, but not in the mushroom bodies, are necessary for visual place learning. Together, these studies reveal distinct neuroanatomical substrates for spatial versus non-spatial learning, and substantiate Drosophila as a powerful model for the study of spatial memories. PMID:21654803

Modeling semantic aspects for cross-media image indexing.

PubMed

Monay, Florent; Gatica-Perez, Daniel

2007-10-01

To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content of an image set and the associated text captions, then allowing for the automatic creation of semantic indices for unannotated images. The task, however, remains unsolved. In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis model (PLSA) for annotated images, and evaluate their respective performance for automatic image indexing. Under the PLSA assumptions, an image is modeled as a mixture of latent aspects that generates both image features and text captions, and we investigate three ways to learn the mixture of aspects. We also propose a more discriminative image representation than the traditional Blob histogram, concatenating quantized local color information and quantized local texture descriptors. The first learning procedure of a PLSA model for annotated images is a standard EM algorithm, which implicitly assumes that the visual and the textual modalities can be treated equivalently. The other two models are based on an asymmetric PLSA learning, allowing to constrain the definition of the latent space on the visual or on the textual modality. We demonstrate that the textual modality is more appropriate to learn a semantically meaningful latent space, which translates into improved annotation performance. A comparison of our learning algorithms with respect to recent methods on a standard dataset is presented, and a detailed evaluation of the performance shows the validity of our framework.

Supporting Multimedia Learning with Visual Signalling and Animated Pedagogical Agent: Moderating Effects of Prior Knowledge

ERIC Educational Resources Information Center

Johnson, A. M.; Ozogul, G.; Reisslein, M.

2015-01-01

An experiment examined the effects of visual signalling to relevant information in multiple external representations and the visual presence of an animated pedagogical agent (APA). Students learned electric circuit analysis using a computer-based learning environment that included Cartesian graphs, equations and electric circuit diagrams. The…

How Spatial Abilities and Dynamic Visualizations Interplay When Learning Functional Anatomy with 3D Anatomical Models

ERIC Educational Resources Information Center

Berney, Sandra; Bétrancourt, Mireille; Molinari, Gaëlle; Hoyek, Nady

2015-01-01

The emergence of dynamic visualizations of three-dimensional (3D) models in anatomy curricula may be an adequate solution for spatial difficulties encountered with traditional static learning, as they provide direct visualization of change throughout the viewpoints. However, little research has explored the interplay between learning material…

Identification of Quality Visual-Based Learning Material for Technology Education

ERIC Educational Resources Information Center

Katsioloudis, Petros

2010-01-01

It is widely known that the use of visual technology enhances learning by providing a better understanding of the topic as well as motivating students. If all visual-based learning materials (tables, figures, photos, etc.) were equally effective in facilitating student achievement of all kinds of educational objectives, there would virtually be no…

A Visual Haptic System for Children with Learning Disabilities: Software and Hardware Design Considerations

ERIC Educational Resources Information Center

Subrahmaniyan, Neeraja; Krishnaswamy, Swetha; Chowriappa, Ashirwad; Srimathveeravalli, Govindarajan; Bisantz, Ann; Shriber, Linda; Kesavadas, Thenkurussi

2012-01-01

Research has shown that children with learning disabilities exhibit considerable challenges with visual motor integration. While there are specialized Occupational Therapy interventions aimed at visual motor integration, computer games and virtual toys have now become increasingly popular, forming an integral part of children's learning and play.…

Heterogeneous iris image hallucination using sparse representation on a learned heterogeneous patch dictionary

NASA Astrophysics Data System (ADS)

Li, Yung-Hui; Zheng, Bo-Ren; Ji, Dai-Yan; Tien, Chung-Hao; Liu, Po-Tsun

2014-09-01

Cross sensor iris matching may seriously degrade the recognition performance because of the sensor mis-match problem of iris images between the enrollment and test stage. In this paper, we propose two novel patch-based heterogeneous dictionary learning method to attack this problem. The first method applies the latest sparse representation theory while the second method tries to learn the correspondence relationship through PCA in heterogeneous patch space. Both methods learn the basic atoms in iris textures across different image sensors and build connections between them. After such connections are built, at test stage, it is possible to hallucinate (synthesize) iris images across different sensors. By matching training images with hallucinated images, the recognition rate can be successfully enhanced. The experimental results showed the satisfied results both visually and in terms of recognition rate. Experimenting with an iris database consisting of 3015 images, we show that the EER is decreased 39.4% relatively by the proposed method.

Experience with Using Multiple Types of Visual Educational Tools during Problem-Based Learning.

PubMed

Kang, Bong Jin

2012-06-01

This study describes the experience of using multiple types of visual educational tools in the setting of problem-based learning (PBL). The author intends to demonstrate their roles in diverse and efficient ways of clinical reasoning and problem solving. Visual educational tools were introduced in a lecture that included their various types, possible benefits, and some examples. Each group made one mechanistic case diagram per week, and each student designed one diagnostic schema or therapeutic algorithm per week, based on their learning issues. The students were also told to provide commentary, which was intended to give insights into their truthfulness. Subsequently, the author administered a questionnaire about the usefulness and weakness of visual educational tools and the difficulties with performing the work. Also, the qualities of the products were assessed by the author. There were many complaints about the adequacy of the introduction of visual educational tools, also revealed by the many initial inappropriate types of products. However, the exercise presentation in the first week improved the level of understanding regarding their purposes and the method of design. In general, students agreed on the benefits of their help in providing a deep understanding of the cases and the possibility of solving clinical problems efficiently. The commentary was helpful in evaluating the truthfulness of their efforts. Students gave suggestions for increasing the percentage of their scores, considering the efforts. Using multiple types of visual educational tools during PBL can be useful in understanding the diverse routes of clinical reasoning and clinical features.

Exploring the Engagement Effects of Visual Programming Language for Data Structure Courses

ERIC Educational Resources Information Center

Chang, Chih-Kai; Yang, Ya-Fei; Tsai, Yu-Tzu

2017-01-01

Previous research indicates that understanding the state of learning motivation enables researchers to deeply understand students' learning processes. Studies have shown that visual programming languages use graphical code, enabling learners to learn effectively, improve learning effectiveness, increase learning fun, and offering various other…

Differentiating for Struggling Readers and Writers: Improving Motivation and Metacognition through Multisensory Methods & Explicit Strategy Instruction

ERIC Educational Resources Information Center

Walet, Jennifer

2011-01-01

This paper examines the issue of struggling readers and writers, and offers suggestions to help teachers increase struggling students' motivation and metacognition. Suggestions include multisensory methods that make use of the visual, auditory and kinesthetic learning pathways, as well as explicit strategy instruction to improve students' ability…

An Evaluation of the Effectiveness of a Computer-Assisted Reading Intervention

ERIC Educational Resources Information Center

Messer, David; Nash, Gilly

2018-01-01

Background: A cost-effective method to address reading delays is to use computer-assisted learning, but these techniques are not always effective. Methods: We evaluated a commercially available computer system that uses visual mnemonics, in a randomised controlled trial with 78 English-speaking children (mean age 7 years) who their schools…

An Examination of the Effects of Argument Mapping on Students' Memory and Comprehension Performance

ERIC Educational Resources Information Center

Dwyer, Christopher P.; Hogan, Michael J.; Stewart, Ian

2013-01-01

Argument mapping (AM) is a method of visually diagramming arguments to allow for easy comprehension of core statements and relations. A series of three experiments compared argument map reading and construction with hierarchical outlining, text summarisation, and text reading as learning methods by examining subsequent memory and comprehension…

Perceptual learning in a non-human primate model of artificial vision

PubMed Central

Killian, Nathaniel J.; Vurro, Milena; Keith, Sarah B.; Kyada, Margee J.; Pezaris, John S.

2016-01-01

Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation. PMID:27874058

The 50s cliff: a decline in perceptuo-motor learning, not a deficit in visual motion perception.

PubMed

Ren, Jie; Huang, Shaochen; Zhang, Jiancheng; Zhu, Qin; Wilson, Andrew D; Snapp-Childs, Winona; Bingham, Geoffrey P

2015-01-01

Previously, we measured perceptuo-motor learning rates across the lifespan and found a sudden drop in learning rates between ages 50 and 60, called the "50s cliff." The task was a unimanual visual rhythmic coordination task in which participants used a joystick to oscillate one dot in a display in coordination with another dot oscillated by a computer. Participants learned to produce a coordination with a 90° relative phase relation between the dots. Learning rates for participants over 60 were half those of younger participants. Given existing evidence for visual motion perception deficits in people over 60 and the role of visual motion perception in the coordination task, it remained unclear whether the 50s cliff reflected onset of this deficit or a genuine decline in perceptuo-motor learning. The current work addressed this question. Two groups of 12 participants in each of four age ranges (20s, 50s, 60s, 70s) learned to perform a bimanual coordination of 90° relative phase. One group trained with only haptic information and the other group with both haptic and visual information about relative phase. Both groups were tested in both information conditions at baseline and post-test. If the 50s cliff was caused by an age dependent deficit in visual motion perception, then older participants in the visual group should have exhibited less learning than those in the haptic group, which should not exhibit the 50s cliff, and older participants in both groups should have performed less well when tested with visual information. Neither of these expectations was confirmed by the results, so we concluded that the 50s cliff reflects a genuine decline in perceptuo-motor learning with aging, not the onset of a deficit in visual motion perception.

Perception of medical undergraduate students about interactive lectures in an outcome-based integrated curriculum: A cross-sectional study

PubMed Central

Asad, Mohammad Rehan; Amir, Khwaja; Tadvi, Naser Ashraf; Afzal, Kamran; Sami, Waqas; Irfan, Abdul

2017-01-01

OBJECTIVE: The objective of this study is to explore the student's perspectives toward the interactive lectures as a teaching and learning method in an integrated curriculum. MATERIALS AND METHODS: This cross-sectional study was conducted among 1st, 2nd and 3rd year male medical students (n = 121). A self-administered questionnaire based on the Visual, Auditory, Reader, Kinesthetic learning styles, learning theories, and role of feedback in teaching and learning on five-point Likert rating scale was used. The questionnaire was constructed after extensive literature review. RESULTS: There was an 80% response rate in this study. The total number of undergraduate medical students responded in the study were n = 97, 34 students of 1st year, n = 30 students of 2nd year and n = 33 student were in 3rd year, the mean scores of the student responses were calculated using Independent samples Kruskal–Wallis. There was no significant difference in the responses of the students of different years except for the question “The Interactive lectures facilitate effective use of learning resources.” Which showed significant difference in the responses of the 3 years students by Independent samples Kruskal–Wallis test. No significant association was found between the year of study and items of the questionnaire except for the same item, “ The Interactive lectures facilitates effective use of learning resources” by Spearman rank correlation test. CONCLUSION: The students perceive interactive lecture as an effective tool for facilitating visual and auditory learning modes, and for achieving curricular strategies. The student find the feedback given during the interactive lectures is effective in modifying learning attitude and enhancing motivation toward learning. PMID:29296601

Distributed Fading Memory for Stimulus Properties in the Primary Visual Cortex

PubMed Central

Singer, Wolf; Maass, Wolfgang

2009-01-01

It is currently not known how distributed neuronal responses in early visual areas carry stimulus-related information. We made multielectrode recordings from cat primary visual cortex and applied methods from machine learning in order to analyze the temporal evolution of stimulus-related information in the spiking activity of large ensembles of around 100 neurons. We used sequences of up to three different visual stimuli (letters of the alphabet) presented for 100 ms and with intervals of 100 ms or larger. Most of the information about visual stimuli extractable by sophisticated methods of machine learning, i.e., support vector machines with nonlinear kernel functions, was also extractable by simple linear classification such as can be achieved by individual neurons. New stimuli did not erase information about previous stimuli. The responses to the most recent stimulus contained about equal amounts of information about both this and the preceding stimulus. This information was encoded both in the discharge rates (response amplitudes) of the ensemble of neurons and, when using short time constants for integration (e.g., 20 ms), in the precise timing of individual spikes (≤∼20 ms), and persisted for several 100 ms beyond the offset of stimuli. The results indicate that the network from which we recorded is endowed with fading memory and is capable of performing online computations utilizing information about temporally sequential stimuli. This result challenges models assuming frame-by-frame analyses of sequential inputs. PMID:20027205

A process-based approach to characterizing the effect of acute alprazolam challenge on visual paired associate learning and memory in healthy older adults.

PubMed

Pietrzak, Robert H; Scott, James Cobb; Harel, Brian T; Lim, Yen Ying; Snyder, Peter J; Maruff, Paul

2012-11-01

Alprazolam is a benzodiazepine that, when administered acutely, results in impairments in several aspects of cognition, including attention, learning, and memory. However, the profile (i.e., component processes) that underlie alprazolam-related decrements in visual paired associate learning has not been fully explored. In this double-blind, placebo-controlled, randomized cross-over study of healthy older adults, we used a novel, "process-based" computerized measure of visual paired associate learning to examine the effect of a single, acute 1-mg dose of alprazolam on component processes of visual paired associate learning and memory. Acute alprazolam challenge was associated with a large magnitude reduction in visual paired associate learning and memory performance (d = 1.05). Process-based analyses revealed significant increases in distractor, exploratory, between-search, and within-search error types. Analyses of percentages of each error type suggested that, relative to placebo, alprazolam challenge resulted in a decrease in the percentage of exploratory errors and an increase in the percentage of distractor errors, both of which reflect memory processes. Results of this study suggest that acute alprazolam challenge decreases visual paired associate learning and memory performance by reducing the strength of the association between pattern and location, which may reflect a general breakdown in memory consolidation, with less evidence of reductions in executive processes (e.g., working memory) that facilitate visual paired associate learning and memory. Copyright © 2012 John Wiley & Sons, Ltd.

Dual-learning systems during speech category learning

PubMed Central

Chandrasekaran, Bharath; Yi, Han-Gyol; Maddox, W. Todd

2013-01-01

Dual-systems models of visual category learning posit the existence of an explicit, hypothesis-testing ‘reflective’ system, as well as an implicit, procedural-based ‘reflexive’ system. The reflective and reflexive learning systems are competitive and neurally dissociable. Relatively little is known about the role of these domain-general learning systems in speech category learning. Given the multidimensional, redundant, and variable nature of acoustic cues in speech categories, our working hypothesis is that speech categories are learned reflexively. To this end, we examined the relative contribution of these learning systems to speech learning in adults. Native English speakers learned to categorize Mandarin tone categories over 480 trials. The training protocol involved trial-by-trial feedback and multiple talkers. Experiment 1 and 2 examined the effect of manipulating the timing (immediate vs. delayed) and information content (full vs. minimal) of feedback. Dual-systems models of visual category learning predict that delayed feedback and providing rich, informational feedback enhance reflective learning, while immediate and minimally informative feedback enhance reflexive learning. Across the two experiments, our results show feedback manipulations that targeted reflexive learning enhanced category learning success. In Experiment 3, we examined the role of trial-to-trial talker information (mixed vs. blocked presentation) on speech category learning success. We hypothesized that the mixed condition would enhance reflexive learning by not allowing an association between talker-related acoustic cues and speech categories. Our results show that the mixed talker condition led to relatively greater accuracies. Our experiments demonstrate that speech categories are optimally learned by training methods that target the reflexive learning system. PMID:24002965

The association between dopamine receptor (DRD4) gene polymorphisms and second language learning style and behavioral variability in undergraduate students in Turkey.

PubMed

Maras Atabay, Meltem; Safi Oz, Zehra; Kurtman, Elvan

2014-08-01

The dopamine D4 receptor gene (DRD4) encodes a receptor for dopamine, a chemical messenger used in the brain. One variant of the DRD4 gene, the 7R allele, is believed to be associated with attention deficit hyperactivity disorder (ADHD). The aim of this study was to investigate the relationships between repeat polymorphisms in dopamine DRD4 and second language learning styles such as visual (seeing), tactile (touching), auditory (hearing), kinesthetic (moving) and group/individual learning styles, as well as the relationships among DRD4 gene polymorphisms and ADHD in undergraduate students. A total of 227 students between the ages of 17-21 years were evaluated using the Wender Utah rating scale and DSM-IV diagnostic criteria for ADHD. Additionally, Reid's perceptual learning style questionnaire for second language learning style was applied. In addition, these students were evaluated for social distress factors using the list of Threatening Events (TLE); having had no TLE, having had just one TLE or having had two or more TLEs within the previous 6 months before the interview. For DRD4 gene polymorphisms, DNA was extracted from whole blood using the standard phenol/chloroform method and genotyped using polymerase chain reaction. Second language learners with the DRD4.7+ repeats showed kinaesthetic and auditory learning styles, while students with DRD4.7-repeats showed visual, tactile and group learning, and also preferred the more visual learning styles [Formula: see text]. We also demonstrated that the DRD4 polymorphism significantly affected the risk effect conferred by an increasing level of exposure to TLE.

Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition

PubMed Central

Cheng, Yujie; Zhou, Bo; Lu, Chen; Yang, Chao

2017-01-01

Fault diagnosis for rolling bearings has attracted increasing attention in recent years. However, few studies have focused on fault diagnosis for rolling bearings under variable conditions. This paper introduces a fault diagnosis method for rolling bearings under variable conditions based on visual cognition. The proposed method includes the following steps. First, the vibration signal data are transformed into a recurrence plot (RP), which is a two-dimensional image. Then, inspired by the visual invariance characteristic of the human visual system (HVS), we utilize speed up robust feature to extract fault features from the two-dimensional RP and generate a 64-dimensional feature vector, which is invariant to image translation, rotation, scaling variation, etc. Third, based on the manifold perception characteristic of HVS, isometric mapping, a manifold learning method that can reflect the intrinsic manifold embedded in the high-dimensional space, is employed to obtain a low-dimensional feature vector. Finally, a classical classification method, support vector machine, is utilized to realize fault diagnosis. Verification data were collected from Case Western Reserve University Bearing Data Center, and the experimental result indicates that the proposed fault diagnosis method based on visual cognition is highly effective for rolling bearings under variable conditions, thus providing a promising approach from the cognitive computing field. PMID:28772943

Audiovisual Association Learning in the Absence of Primary Visual Cortex.

PubMed

Seirafi, Mehrdad; De Weerd, Peter; Pegna, Alan J; de Gelder, Beatrice

2015-01-01

Learning audiovisual associations is mediated by the primary cortical areas; however, recent animal studies suggest that such learning can take place even in the absence of the primary visual cortex. Other studies have demonstrated the involvement of extra-geniculate pathways and especially the superior colliculus (SC) in audiovisual association learning. Here, we investigated such learning in a rare human patient with complete loss of the bilateral striate cortex. We carried out an implicit audiovisual association learning task with two different colors of red and purple (the latter color known to minimally activate the extra-genicular pathway). Interestingly, the patient learned the association between an auditory cue and a visual stimulus only when the unseen visual stimulus was red, but not when it was purple. The current study presents the first evidence showing the possibility of audiovisual association learning in humans with lesioned striate cortex. Furthermore, in line with animal studies, it supports an important role for the SC in audiovisual associative learning.

Techniques for Programming Visual Demonstrations.

ERIC Educational Resources Information Center

Gropper, George L.

Visual demonstrations may be used as part of programs to deliver both content objectives and process objectives. Research has shown that learning of concepts is easier, more accurate, and more broadly applied when it is accompanied by visual examples. The visual examples supporting content learning should emphasize both discrimination and…

The Effects of Realism in Learning with Dynamic Visualizations

ERIC Educational Resources Information Center

Scheiter, Katharina; Gerjets, Peter; Huk, Thomas; Imhof, Birgit; Kammerer, Yvonne

2009-01-01

Two experiments are reported that investigated the relative effectiveness of a realistic dynamic visualization as opposed to a schematic visualization for learning about cell replication (mitosis). In Experiment 1, 37 university students watched either realistic or schematic visualizations. Students' subjective task demands ratings as well as…

Using Visual Imagery in the Classroom.

ERIC Educational Resources Information Center

Grabow, Beverly

1981-01-01

The use of visual imagery, visualization, and guided and unguided fantasy has potential as a teaching tool for use with learning disabled children. Visualization utilized in a gamelike atmosphere can help the student learn new concepts, can positively effect social behaviors, and can help with emotional control. (SB)

Physics Learning Styles in Higher Education

NASA Astrophysics Data System (ADS)

Loos, Rebecca; Ward, James

2012-03-01

Students in Physics learn in a variety ways depending on backgrounds and interests. This study proposes to evaluate how students in Physics learn using Howard Gardner's Theory of Multiple Intelligences. Physics utilizes numbers, conceptualization of models, observations and visualization skills, and the ability to understand and reflect on specific information. The main objective is to evaluate how Physics students learn specifically using spatial, visual and sequential approaches. This will be assessed by conducting a learning style survey provided by North Carolina State University (NCSU). The survey is completed online by the student after which the results are sent to NCSU. Students will print out the completed survey analysis for further evaluation. The NCSU results categorize students within five of ten learning styles. After the evaluation of Howard Gardner's Theory of Multiple Intelligences and the NCSU definitions of the ten learning styles, the NCSU sensing and visual learning styles will be defined as the Gardener's spatial, visual learning styles. NCSU's sequential learning style will be looked at separately. With the survey results, it can be determined if Physics students fall within the hypothesized learning styles.

Using transfer learning to detect galaxy mergers

NASA Astrophysics Data System (ADS)

Ackermann, Sandro; Schawinksi, Kevin; Zhang, Ce; Weigel, Anna K.; Turp, M. Dennis

2018-05-01

We investigate the use of deep convolutional neural networks (deep CNNs) for automatic visual detection of galaxy mergers. Moreover, we investigate the use of transfer learning in conjunction with CNNs, by retraining networks first trained on pictures of everyday objects. We test the hypothesis that transfer learning is useful for improving classification performance for small training sets. This would make transfer learning useful for finding rare objects in astronomical imaging datasets. We find that these deep learning methods perform significantly better than current state-of-the-art merger detection methods based on nonparametric systems like CAS and GM20. Our method is end-to-end and robust to image noise and distortions; it can be applied directly without image preprocessing. We also find that transfer learning can act as a regulariser in some cases, leading to better overall classification accuracy (p = 0.02). Transfer learning on our full training set leads to a lowered error rate from 0.0381 down to 0.0321, a relative improvement of 15%. Finally, we perform a basic sanity-check by creating a merger sample with our method, and comparing with an already existing, manually created merger catalogue in terms of colour-mass distribution and stellar mass function.

Mapping students' ideas to understand learning in a collaborative programming environment

NASA Astrophysics Data System (ADS)

Harlow, Danielle Boyd; Leak, Anne Emerson

2014-07-01

Recent studies in learning programming have largely focused on high school and college students; less is known about how young children learn to program. From video data of 20 students using a graphical programming interface, we identified ideas that were shared and evolved through an elementary school classroom. In mapping these ideas and their resulting changes in programs and outputs, we were able to identify the contextual features which contributed to how ideas moved through the classroom as students learned. We suggest this process of idea mapping in visual programming environments as a viable method for understanding collaborative, constructivist learning as well as a context under which experiences can be developed to improve student learning.

Adapting Art Instruction for Students with Disabilities.

ERIC Educational Resources Information Center

Platt, Jennifer M.; Janeczko, Donna

1991-01-01

This article presents adaptations for teaching art to students with disabilities. Various techniques, methods, and materials are described by category of disability, including students with mental disabilities, visual impairments, hearing impairments, learning disabilities, emotional disabilities, and physical disabilities. (JDD)

[E-Learning in radiology; the practical use of the content management system ILIAS].

PubMed

Schütze, B; Mildenberger, P; Kämmerer, M

2006-05-01

Due to the possibility of using different kinds of visualization, e-learning has the advantage of allowing individualized learning. A check should be performed to determine whether the use of the web-based content management system ILIAS simplifies the writing and production of electronic learning modules in radiology. Internet-based e-learning provides access to existing learning modules regardless of time and location, since fast Internet connections are readily available. Web Content Management Systems (WCMS) are suitable platforms for imparting radiology-related information (visual abilities like the recognition of patterns as well as interdisciplinary specialized knowledge). The open source product ILIAS is a free WCMS. It is used by many universities and is accepted by both students and lecturers. Its modular and object-oriented software architecture makes it easy to adapt and enlarge the platform. The employment of e-learning standards such as LOM and SCORM within ILIAS makes it possible to reuse contents, even if the platform has to be changed. ILIAS renders it possible to provide students with texts, images, or files of any other kind within a learning context which is defined by the lecturer. Students can check their acquired knowledge via online testing and receive direct performance feedback. The significant interest that students have shown in ILIAS proves that e-learning can be a useful addition to conventional learning methods.

Behavioral Training as New Treatment for Adult Amblyopia: A Meta-Analysis and Systematic Review.

PubMed

Tsirlin, Inna; Colpa, Linda; Goltz, Herbert C; Wong, Agnes M F

2015-06-01

New behavioral treatment methods, including dichoptic training, perceptual learning, and video gaming, have been proposed to improve visual function in adult amblyopia. Here, we conducted a meta-analysis of these methods to investigate the factors involved in amblyopia recovery and their clinical significance. Mean and individual participant data meta-analyses were performed on 24 studies using the new behavioral methods in adults. Studies were identified using PubMed, Google Scholar, and published reviews. The new methods yielded a mean improvement in visual acuity of 0.17 logMAR with 32% participants achieving gains ≥ 0.2 logMAR, and a mean improvement in stereo sensitivity of 0.01 arcsec-1 with 42% of participants improving ≥2 octaves. The most significant predictor of treatment outcome was visual acuity at the onset of treatment. Participants with more severe amblyopia improved more on visual acuity and less on stereo sensitivity than those with milder amblyopia. Better initial stereo sensitivity was a predictor of greater gains in stereo sensitivity following treatment. Treatment type, amblyopia type, age, and training duration did not have any significant influence on visual and stereo acuity outcomes. Our analyses showed that some participants may benefit from the new treatments; however, clinical trials are required to confirm these findings. Despite the diverse nature of the new behavioral methods, the lack of significant differences in visual and stereo sensitivity outcomes among them suggests that visual attention-a common element among the varied treatment methods-may play an important role in amblyopia recovery.

Focus-on-form instructional methods promote deaf college students' improvement in English grammar.

PubMed

Berent, Gerald P; Kelly, Ronald R; Aldersley, Stephen; Schmitz, Kathryn L; Khalsa, Baldev Kaur; Panara, John; Keenan, Susan

2007-01-01

Focus-on-form English teaching methods are designed to facilitate second-language learners' noticing of target language input, where "noticing" is an acquisitional prerequisite for the comprehension, processing, and eventual integration of new grammatical knowledge. While primarily designed for teaching hearing second-language learners, many focus-on-form methods lend themselves to visual presentation. This article reports the results of classroom research on the visually based implementation of focus-on-form methods with deaf college students learning English. Two of 3 groups of deaf students received focus-on-form instruction during a 10-week remedial grammar course; a third control group received grammatical instruction that did not involve focus-on-form methods. The 2 experimental groups exhibited significantly greater improvement in English grammatical knowledge relative to the control group. These results validate the efficacy of visually based focus-on-form English instruction for deaf students of English and set the stage for the continual search for innovative and effective English teaching methodologies.

Microelectrode Recordings Validate the Clinical Visualization of Subthalamic-Nucleus Based on 7T Magnetic Resonance Imaging and Machine Learning for Deep Brain Stimulation Surgery.

PubMed

Shamir, Reuben R; Duchin, Yuval; Kim, Jinyoung; Patriat, Remi; Marmor, Odeya; Bergman, Hagai; Vitek, Jerrold L; Sapiro, Guillermo; Bick, Atira; Eliahou, Ruth; Eitan, Renana; Israel, Zvi; Harel, Noam

2018-05-24

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a proven and effective therapy for the management of the motor symptoms of Parkinson's disease (PD). While accurate positioning of the stimulating electrode is critical for success of this therapy, precise identification of the STN based on imaging can be challenging. We developed a method to accurately visualize the STN on a standard clinical magnetic resonance imaging (MRI). The method incorporates a database of 7-Tesla (T) MRIs of PD patients together with machine-learning methods (hereafter 7 T-ML). To validate the clinical application accuracy of the 7 T-ML method by comparing it with identification of the STN based on intraoperative microelectrode recordings. Sixteen PD patients who underwent microelectrode-recordings guided STN DBS were included in this study (30 implanted leads and electrode trajectories). The length of the STN along the electrode trajectory and the position of its contacts to dorsal, inside, or ventral to the STN were compared using microelectrode-recordings and the 7 T-ML method computed based on the patient's clinical 3T MRI. All 30 electrode trajectories that intersected the STN based on microelectrode-recordings, also intersected it when visualized with the 7 T-ML method. STN trajectory average length was 6.2 ± 0.7 mm based on microelectrode recordings and 5.8 ± 0.9 mm for the 7 T-ML method. We observed a 93% agreement regarding contact location between the microelectrode-recordings and the 7 T-ML method. The 7 T-ML method is highly consistent with microelectrode-recordings data. This method provides a reliable and accurate patient-specific prediction for targeting the STN.

Students using visual thinking to learn science in a Web-based environment

NASA Astrophysics Data System (ADS)

Plough, Jean Margaret

United States students' science test scores are low, especially in problem solving, and traditional science instruction could be improved. Consequently, visual thinking, constructing science structures, and problem solving in a web-based environment may be valuable strategies for improving science learning. This ethnographic study examined the science learning of fifteen fourth grade students in an after school computer club involving diverse students at an inner city school. The investigation was done from the perspective of the students, and it described the processes of visual thinking, web page construction, and problem solving in a web-based environment. The study utilized informal group interviews, field notes, Visual Learning Logs, and student web pages, and incorporated a Standards-Based Rubric which evaluated students' performance on eight science and technology standards. The Visual Learning Logs were drawings done on the computer to represent science concepts related to the Food Chain. Students used the internet to search for information on a plant or animal of their choice. Next, students used this internet information, with the information from their Visual Learning Logs, to make web pages on their plant or animal. Later, students linked their web pages to form Science Structures. Finally, students linked their Science Structures with the structures of other students, and used these linked structures as models for solving problems. Further, during informal group interviews, students answered questions about visual thinking, problem solving, and science concepts. The results of this study showed clearly that (1) making visual representations helped students understand science knowledge, (2) making links between web pages helped students construct Science Knowledge Structures, and (3) students themselves said that visual thinking helped them learn science. In addition, this study found that when using Visual Learning Logs, the main overall ideas of the science concepts were usually represented accurately. Further, looking for information on the internet may cause new problems in learning. Likewise, being absent, starting late, and/or dropping out all may negatively influence students' proficiency on the standards. Finally, the way Science Structures are constructed and linked may provide insights into the way individual students think and process information.

Interactive Learning System "VisMis" for Scientific Visualization Course

ERIC Educational Resources Information Center

Zhu, Xiaoming; Sun, Bo; Luo, Yanlin

2018-01-01

Now visualization courses have been taught at universities around the world. Keeping students motivated and actively engaged in this course can be a challenging task. In this paper we introduce our developed interactive learning system called VisMis (Visualization and Multi-modal Interaction System) for postgraduate scientific visualization course…

How Temporal and Spatial Aspects of Presenting Visualizations Affect Learning about Locomotion Patterns

ERIC Educational Resources Information Center

Imhof, Birgit; Scheiter, Katharina; Edelmann, Jorg; Gerjets, Peter

2012-01-01

Two studies investigated the effectiveness of dynamic and static visualizations for a perceptual learning task (locomotion pattern classification). In Study 1, seventy-five students viewed either dynamic, static-sequential, or static-simultaneous visualizations. For tasks of intermediate difficulty, dynamic visualizations led to better…

Learning about Locomotion Patterns from Visualizations: Effects of Presentation Format and Realism

ERIC Educational Resources Information Center

Imhof, Birgit; Scheiter, Katharina; Gerjets, Peter

2011-01-01

The rapid development of computer graphics technology has made possible an easy integration of dynamic visualizations into computer-based learning environments. This study examines the relative effectiveness of dynamic visualizations, compared either to sequentially or simultaneously presented static visualizations. Moreover, the degree of realism…

Drawing Connections Across Conceptually Related Visual Representations in Science

NASA Astrophysics Data System (ADS)

Hansen, Janice

This dissertation explored beliefs about learning from multiple related visual representations in science, and compared beliefs to learning outcomes. Three research questions were explored: 1) What beliefs do pre-service teachers, non-educators and children have about learning from visual representations? 2) What format of presenting those representations is most effective for learning? And, 3) Can children's ability to process conceptually related science diagrams be enhanced with added support? Three groups of participants, 89 pre-service teachers, 211 adult non-educators, and 385 middle school children, were surveyed about whether they felt related visual representations presented serially or simultaneously would lead to better learning outcomes. Two experiments, one with adults and one with child participants, explored the validity of these beliefs. Pre-service teachers did not endorse either serial or simultaneous related visual representations for their own learning. They were, however, significantly more likely to indicate that children would learn better from serially presented diagrams. In direct contrast to the educators, middle school students believed they would learn better from related visual representations presented simultaneously. Experimental data indicated that the beliefs adult non-educators held about their own learning needs matched learning outcomes. These participants endorsed simultaneous presentation of related diagrams for their own learning. When comparing learning from related diagrams presented simultaneously to learning from the same diagrams presented serially indicate that those in the simultaneously condition were able to create more complex mental models. A second experiment compared children's learning from related diagrams across four randomly-assigned conditions: serial, simultaneous, simultaneous with signaling, and simultaneous with structure mapping support. Providing middle school students with simultaneous related diagrams with support for structure mapping led to a lessened reliance on surface features, and a better understanding of the science concepts presented. These findings suggest that presenting diagrams serially in an effort to reduce cognitive load may not be preferable for learning if making connections across representations, and by extension across science concepts, is desired. Instead, providing simultaneous diagrams with structure mapping support may result in greater attention to the salient relationships between related visual representations as well as between the representations and the science concepts they depict.

Distance Metric Learning Using Privileged Information for Face Verification and Person Re-Identification.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong

2015-12-01

In this paper, we propose a new approach to improve face verification and person re-identification in the RGB images by leveraging a set of RGB-D data, in which we have additional depth images in the training data captured using depth cameras such as Kinect. In particular, we extract visual features and depth features from the RGB images and depth images, respectively. As the depth features are available only in the training data, we treat the depth features as privileged information, and we formulate this task as a distance metric learning with privileged information problem. Unlike the traditional face verification and person re-identification tasks that only use visual features, we further employ the extra depth features in the training data to improve the learning of distance metric in the training process. Based on the information-theoretic metric learning (ITML) method, we propose a new formulation called ITML with privileged information (ITML+) for this task. We also present an efficient algorithm based on the cyclic projection method for solving the proposed ITML+ formulation. Extensive experiments on the challenging faces data sets EUROCOM and CurtinFaces for face verification as well as the BIWI RGBD-ID data set for person re-identification demonstrate the effectiveness of our proposed approach.

Promoting Visualization Skills through Deconstruction Using Physical Models and a Visualization Activity Intervention

NASA Astrophysics Data System (ADS)

Schiltz, Holly Kristine

Visualization skills are important in learning chemistry, as these skills have been shown to correlate to high ability in problem solving. Students' understanding of visual information and their problem-solving processes may only ever be accessed indirectly: verbalization, gestures, drawings, etc. In this research, deconstruction of complex visual concepts was aligned with the promotion of students' verbalization of visualized ideas to teach students to solve complex visual tasks independently. All instructional tools and teaching methods were developed in accordance with the principles of the theoretical framework, the Modeling Theory of Learning: deconstruction of visual representations into model components, comparisons to reality, and recognition of students' their problemsolving strategies. Three physical model systems were designed to provide students with visual and tangible representations of chemical concepts. The Permanent Reflection Plane Demonstration provided visual indicators that students used to support or invalidate the presence of a reflection plane. The 3-D Coordinate Axis system provided an environment that allowed students to visualize and physically enact symmetry operations in a relevant molecular context. The Proper Rotation Axis system was designed to provide a physical and visual frame of reference to showcase multiple symmetry elements that students must identify in a molecular model. Focus groups of students taking Inorganic chemistry working with the physical model systems demonstrated difficulty documenting and verbalizing processes and descriptions of visual concepts. Frequently asked student questions were classified, but students also interacted with visual information through gestures and model manipulations. In an effort to characterize how much students used visualization during lecture or recitation, we developed observation rubrics to gather information about students' visualization artifacts and examined the effect instructors' modeled visualization artifacts had on students. No patterns emerged from the passive observation of visualization artifacts in lecture or recitation, but the need to elicit visual information from students was made clear. Deconstruction proved to be a valuable method for instruction and assessment of visual information. Three strategies for using deconstruction in teaching were distilled from the lessons and observations of the student focus groups: begin with observations of what is given in an image and what it's composed of, identify the relationships between components to find additional operations in different environments about the molecule, and deconstructing steps of challenging questions can reveal mistakes. An intervention was developed to teach students to use deconstruction and verbalization to analyze complex visualization tasks and employ the principles of the theoretical framework. The activities were scaffolded to introduce increasingly challenging concepts to students, but also support them as they learned visually demanding chemistry concepts. Several themes were observed in the analysis of the visualization activities. Students used deconstruction by documenting which parts of the images were useful for interpretation of the visual. Students identified valid patterns and rules within the images, which signified understanding of arrangement of information presented in the representation. Successful strategy communication was identified when students documented personal strategies that allowed them to complete the activity tasks. Finally, students demonstrated the ability to extend symmetry skills to advanced applications they had not previously seen. This work shows how the use of deconstruction and verbalization may have a great impact on how students master difficult topics and combined, they offer students a powerful strategy to approach visually demanding chemistry problems and to the instructor a unique insight to mentally constructed strategies.

Selective transfer of visual working memory training on Chinese character learning.

PubMed

Opitz, Bertram; Schneiders, Julia A; Krick, Christoph M; Mecklinger, Axel

2014-01-01

Previous research has shown a systematic relationship between phonological working memory capacity and second language proficiency for alphabetic languages. However, little is known about the impact of working memory processes on second language learning in a non-alphabetic language such as Mandarin Chinese. Due to the greater complexity of the Chinese writing system we expect that visual working memory rather than phonological working memory exerts a unique influence on learning Chinese characters. This issue was explored in the present experiment by comparing visual working memory training with an active (auditory working memory training) control condition and a passive, no training control condition. Training induced modulations in language-related brain networks were additionally examined using functional magnetic resonance imaging in a pretest-training-posttest design. As revealed by pre- to posttest comparisons and analyses of individual differences in working memory training gains, visual working memory training led to positive transfer effects on visual Chinese vocabulary learning compared to both control conditions. In addition, we found sustained activation after visual working memory training in the (predominantly visual) left infero-temporal cortex that was associated with behavioral transfer. In the control conditions, activation either increased (active control condition) or decreased (passive control condition) without reliable behavioral transfer effects. This suggests that visual working memory training leads to more efficient processing and more refined responses in brain regions involved in visual processing. Furthermore, visual working memory training boosted additional activation in the precuneus, presumably reflecting mental image generation of the learned characters. We, therefore, suggest that the conjoint activity of the mid-fusiform gyrus and the precuneus after visual working memory training reflects an interaction of working memory and imagery processes with complex visual stimuli that fosters the coherent synthesis of a percept from a complex visual input in service of enhanced Chinese character learning. © 2013 Published by Elsevier Ltd.

Classifying Acute Ischemic Stroke Onset Time using Deep Imaging Features

PubMed Central

Ho, King Chung; Speier, William; El-Saden, Suzie; Arnold, Corey W.

2017-01-01

Models have been developed to predict stroke outcomes (e.g., mortality) in attempt to provide better guidance for stroke treatment. However, there is little work in developing classification models for the problem of unknown time-since-stroke (TSS), which determines a patient’s treatment eligibility based on a clinical defined cutoff time point (i.e., <4.5hrs). In this paper, we construct and compare machine learning methods to classify TSS<4.5hrs using magnetic resonance (MR) imaging features. We also propose a deep learning model to extract hidden representations from the MR perfusion-weighted images and demonstrate classification improvement by incorporating these additional imaging features. Finally, we discuss a strategy to visualize the learned features from the proposed deep learning model. The cross-validation results show that our best classifier achieved an area under the curve of 0.68, which improves significantly over current clinical methods (0.58), demonstrating the potential benefit of using advanced machine learning methods in TSS classification. PMID:29854156

Learning Programming Technique through Visual Programming Application as Learning Media with Fuzzy Rating

ERIC Educational Resources Information Center

Buditjahjanto, I. G. P. Asto; Nurlaela, Luthfiyah; Ekohariadi; Riduwan, Mochamad

2017-01-01

Programming technique is one of the subjects at Vocational High School in Indonesia. This subject contains theory and application of programming utilizing Visual Programming. Students experience some difficulties to learn textual learning. Therefore, it is necessary to develop media as a tool to transfer learning materials. The objectives of this…

Visual paired-associate learning: in search of material-specific effects in adult patients who have undergone temporal lobectomy.

PubMed

Smith, Mary Lou; Bigel, Marla; Miller, Laurie A

2011-02-01

The mesial temporal lobes are important for learning arbitrary associations. It has previously been demonstrated that left mesial temporal structures are involved in learning word pairs, but it is not yet known whether comparable lesions in the right temporal lobe impair visually mediated associative learning. Patients who had undergone left (n=16) or right (n=18) temporal lobectomy for relief of intractable epilepsy and healthy controls (n=13) were administered two paired-associate learning tasks assessing their learning and memory of pairs of abstract designs or pairs of symbols in unique locations. Both patient groups had deficits in learning the designs, but only the right temporal group was impaired in recognition. For the symbol location task, differences were not found in learning, but again a recognition deficit was found for the right temporal group. The findings implicate the mesial temporal structures in relational learning. They support a material-specific effect for recognition but not for learning and recall of arbitrary visual and visual-spatial associative information. Copyright © 2010 Elsevier Inc. All rights reserved.

Individual personality differences in goats predict their performance in visual learning and non-associative cognitive tasks.

PubMed

Nawroth, Christian; Prentice, Pamela M; McElligott, Alan G

2017-01-01

Variation in common personality traits, such as boldness or exploration, is often associated with risk-reward trade-offs and behavioural flexibility. To date, only a few studies have examined the effects of consistent behavioural traits on both learning and cognition. We investigated whether certain personality traits ('exploration' and 'sociability') of individuals were related to cognitive performance, learning flexibility and learning style in a social ungulate species, the goat (Capra hircus). We also investigated whether a preference for feature cues rather than impaired learning abilities can explain performance variation in a visual discrimination task. We found that personality scores were consistent across time and context. Less explorative goats performed better in a non-associative cognitive task, in which subjects had to follow the trajectory of a hidden object (i.e. testing their ability for object permanence). We also found that less sociable subjects performed better compared to more sociable goats in a visual discrimination task. Good visual learning performance was associated with a preference for feature cues, indicating personality-dependent learning strategies in goats. Our results suggest that personality traits predict the outcome in visual discrimination and non-associative cognitive tasks in goats and that impaired performance in a visual discrimination tasks does not necessarily imply impaired learning capacities, but rather can be explained by a varying preference for feature cues. Copyright © 2016 Elsevier B.V. All rights reserved.

Changes in Visual Object Recognition Precede the Shape Bias in Early Noun Learning

PubMed Central

Yee, Meagan; Jones, Susan S.; Smith, Linda B.

2012-01-01

Two of the most formidable skills that characterize human beings are language and our prowess in visual object recognition. They may also be developmentally intertwined. Two experiments, a large sample cross-sectional study and a smaller sample 6-month longitudinal study of 18- to 24-month-olds, tested a hypothesized developmental link between changes in visual object representation and noun learning. Previous findings in visual object recognition indicate that children’s ability to recognize common basic level categories from sparse structural shape representations of object shape emerges between the ages of 18 and 24 months, is related to noun vocabulary size, and is lacking in children with language delay. Other research shows in artificial noun learning tasks that during this same developmental period, young children systematically generalize object names by shape, that this shape bias predicts future noun learning, and is lacking in children with language delay. The two experiments examine the developmental relation between visual object recognition and the shape bias for the first time. The results show that developmental changes in visual object recognition systematically precede the emergence of the shape bias. The results suggest a developmental pathway in which early changes in visual object recognition that are themselves linked to category learning enable the discovery of higher-order regularities in category structure and thus the shape bias in novel noun learning tasks. The proposed developmental pathway has implications for understanding the role of specific experience in the development of both visual object recognition and the shape bias in early noun learning. PMID:23227015

A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee

PubMed Central

Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R.

2017-01-01

Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee (Bombus terrestris) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. PMID:28978727

A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee.

PubMed

Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R; Chittka, Lars; Perry, Clint J

2017-10-11

Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee ( Bombus terrestris ) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. © 2017 The Authors.

Learning style preferences: A study of pre-clinical medical students in Barbados

PubMed Central

OJEH, NKEMCHO; SOBERS-GRANNUM, NATASHA; GAUR, UMA; UDUPA, ALAYA; MAJUMDER, MD.ANWARUL AZIM

2017-01-01

Introduction: Educators need to be aware of different learning styles to effectively tailor instructional strategies and methods to cater to the students’ learning needs and support a conductive learning environment. The VARK [an acronym for visual (V), aural (A), read/write (R) and kinesthetic (K)] instrument is a useful model to assess learning styles. The aim of this study was to use the VARK questionnaire to determine the learning styles of pre-clinical medical students in order to compare the perceived and assessed learning style preferences, assess gender differences in learning style preferences, and determine whether any relationships exists between awareness of learning styles and academic grades, age, gender and learning modality. Methods: The VARK questionnaire was administered to pre-clinical students taking a variety of courses in the first three years of the undergraduate MB BS degree programme at the Faculty of Medical Sciences, The University of the West Indies, Cave Hill Campus, Barbados in 2014. Results: The majority of the students were multimodal learners with no differences observed between males (59.5%) and females (60.0%), with tetramodal being the most common. Read/write (33.8%) followed by kinesthetic (32.5%) were the most common learning style preferences. The sensory modality preference for females was read/write (34.2%) and for males it was kinesthetic (40.5%). Significant differences were observed between the perceived and assessed learning style preferences with a majority of visual and read/write learners correctly matching their perceived to their actual learning styles. Awareness of learning styles was associated with learning modality but not with academic performance, age or gender. Overall, 60.7% of high achievers used multimodal learning compared to 56.9% low achievers. Conclusion: The findings from this study indicated that the VARK tool was useful in gathering information about different learning styles, and might assist educators in designing blended teaching strategies to cater to the students’ needs as well as help the students in becoming aware of their learning style preferences to enhance learning. PMID:28979913

Learning Human Actions by Combining Global Dynamics and Local Appearance.

PubMed

Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

Learning to See the Infinite: Measuring Visual Literacy Skills in a 1st-Year Seminar Course

ERIC Educational Resources Information Center

Palmer, Michael S.; Matthews, Tatiana

2015-01-01

Visual literacy was a stated learning objective for the fall 2009 iteration of a first-year seminar course. To help students develop visual literacy skills, they received formal instruction throughout the semester and completed a series of carefully designed learning activities. The effects of these interventions were measured using a one-group…

Learning Program for Enhancing Visual Literacy for Non-Design Students Using a CMS to Share Outcomes

ERIC Educational Resources Information Center

Ariga, Taeko; Watanabe, Takashi; Otani, Toshio; Masuzawa, Toshimitsu

2016-01-01

This study proposes a basic learning program for enhancing visual literacy using an original Web content management system (Web CMS) to share students' outcomes in class as a blog post. It seeks to reinforce students' understanding and awareness of the design of visual content. The learning program described in this research focuses on to address…

Phoneme Awareness, Visual-Verbal Paired-Associate Learning, and Rapid Automatized Naming as Predictors of Individual Differences in Reading Ability

ERIC Educational Resources Information Center

Warmington, Meesha; Hulme, Charles

2012-01-01

This study examines the concurrent relationships between phoneme awareness, visual-verbal paired-associate learning, rapid automatized naming (RAN), and reading skills in 7- to 11-year-old children. Path analyses showed that visual-verbal paired-associate learning and RAN, but not phoneme awareness, were unique predictors of word recognition,…

Graphical Technique to Support the Teaching/Learning Process of Software Process Reference Models

NASA Astrophysics Data System (ADS)

Espinosa-Curiel, Ismael Edrein; Rodríguez-Jacobo, Josefina; Fernández-Zepeda, José Alberto

In this paper, we propose a set of diagrams to visualize software process reference models (PRM). The diagrams, called dimods, are the combination of some visual and process modeling techniques such as rich pictures, mind maps, IDEF and RAD diagrams. We show the use of this technique by designing a set of dimods for the Mexican Software Industry Process Model (MoProSoft). Additionally, we perform an evaluation of the usefulness of dimods. The result of the evaluation shows that dimods may be a support tool that facilitates the understanding, memorization, and learning of software PRMs in both, software development organizations and universities. The results also show that dimods may have advantages over the traditional description methods for these types of models.

SIGKit: a New Data-based Software for Learning Introductory Geophysics

NASA Astrophysics Data System (ADS)

Zhang, Y.; Kruse, S.; George, O.; Esmaeili, S.; Papadimitrios, K. S.; Bank, C. G.; Cadmus, A.; Kenneally, N.; Patton, K.; Brusher, J.

2016-12-01

Students of diverse academic backgrounds take introductory geophysics courses to learn the theory of a variety of measurement and analysis methods with the expectation to be able to apply their basic knowledge to real data. Ideally, such data is collected in field courses and also used in lecture-based courses because they provide a critical context for better learning and understanding of geophysical methods. Each method requires a separate software package for the data processing steps, and the complexity and variety of professional software makes the path through data processing to data interpretation a strenuous learning process for students and a challenging teaching task for instructors. SIGKit (Student Investigation of Geophysics Toolkit) being developed as a collaboration between the University of South Florida, the University of Toronto, and MathWorks intends to address these shortcomings by showing the most essential processing steps and allowing students to visualize the underlying physics of the various methods. It is based on MATLAB software and offered as an easy-to-use graphical user interface and packaged so it can run as an executable in the classroom and the field even on computers without MATLAB licenses. An evaluation of the software based on student feedback from focus-group interviews and think-aloud observations helps drive its development and refinement. The toolkit provides a logical gateway into the more sophisticated and costly software students will encounter later in their training and careers by combining essential visualization, modeling, processing, and analysis steps for seismic, GPR, magnetics, gravity, resistivity, and electromagnetic data.

The Effect of Concept Mapping on Student Understanding and Correlation with Student Learning Styles

NASA Astrophysics Data System (ADS)

Mosley, William G.

This study investigated the use of concept mapping as a pedagogical strategy to promote change in the learning styles of pre-nursing students. Students' individual learning styles revealed two subsets of students; those who demonstrated a learning style that favors abstract conceptualization and those who demonstrated a learning style that favors concrete experience. Students in the experimental groups performed concept mapping activities designed to facilitate an integrative understanding of interactions between various organ systems of the body while the control group received a traditional didactic instruction without performing concept mapping activities. Both qualitative and quantitative data were collected in order to measure differences in student achievement. Analysis of the quantitative data revealed no significant change in the learning styles of students in either the control or experimental groups. Learning style groups were analyzed qualitatively for recurring or emergent themes that students identified as facilitating their learning. An analysis of qualitative data revealed that most students in the pre-nursing program were able to identify concepts within the class based upon visual cues, and a majority of these students exhibited the learning style of abstract conceptualization. As the laboratory experience for the course involves an examination of the anatomical structures of the human body, a visual identification of these structures seemed to be the most logical method to measure students' ability to identify anatomical structures.

The Possibility of Learning Curved Mirrors' Structure by a Normal Blind Inborn Students

ERIC Educational Resources Information Center

Bulbul, M. Sahin

2009-01-01

To take a physics course blind students must be assisted using teaching methods and aids adapted to their own perception capabilities. Touchable objects are very important for them because they have huge difficulties to visualize the third spatial dimension. However, appropriate resources and methods for blind students are not yet available. In…

Enhancing Learning Using 3D Printing: An Alternative to Traditional Student Project Methods

ERIC Educational Resources Information Center

McGahern, Patricia; Bosch, Frances; Poli, DorothyBelle

2015-01-01

Student engagement during the development of a three-dimensional visual aid or teaching model can vary for a number of reasons. Some students report that they are not "creative" or "good at art," often as an excuse to justify less professional outcomes. Student engagement can be low when using traditional methods to produce a…

How to Help Students Conceptualize the Rigorous Definition of the Limit of a Sequence

ERIC Educational Resources Information Center

Roh, Kyeong Hah

2010-01-01

This article suggests an activity, called the epsilon-strip activity, as an instructional method for conceptualization of the rigorous definition of the limit of a sequence via visualization. The article also describes the learning objectives of each instructional step of the activity, and then provides detailed instructional methods to guide…

Integrating concept ontology and multitask learning to achieve more effective classifier training for multilevel image annotation.

PubMed

Fan, Jianping; Gao, Yuli; Luo, Hangzai

2008-03-01

In this paper, we have developed a new scheme for achieving multilevel annotations of large-scale images automatically. To achieve more sufficient representation of various visual properties of the images, both the global visual features and the local visual features are extracted for image content representation. To tackle the problem of huge intraconcept visual diversity, multiple types of kernels are integrated to characterize the diverse visual similarity relationships between the images more precisely, and a multiple kernel learning algorithm is developed for SVM image classifier training. To address the problem of huge interconcept visual similarity, a novel multitask learning algorithm is developed to learn the correlated classifiers for the sibling image concepts under the same parent concept and enhance their discrimination and adaptation power significantly. To tackle the problem of huge intraconcept visual diversity for the image concepts at the higher levels of the concept ontology, a novel hierarchical boosting algorithm is developed to learn their ensemble classifiers hierarchically. In order to assist users on selecting more effective hypotheses for image classifier training, we have developed a novel hyperbolic framework for large-scale image visualization and interactive hypotheses assessment. Our experiments on large-scale image collections have also obtained very positive results.

Learning-based saliency model with depth information.

PubMed

Ma, Chih-Yao; Hang, Hsueh-Ming

2015-01-01

Most previous studies on visual saliency focused on two-dimensional (2D) scenes. Due to the rapidly growing three-dimensional (3D) video applications, it is very desirable to know how depth information affects human visual attention. In this study, we first conducted eye-fixation experiments on 3D images. Our fixation data set comprises 475 3D images and 16 subjects. We used a Tobii TX300 eye tracker (Tobii, Stockholm, Sweden) to track the eye movement of each subject. In addition, this database contains 475 computed depth maps. Due to the scarcity of public-domain 3D fixation data, this data set should be useful to the 3D visual attention research community. Then, a learning-based visual attention model was designed to predict human attention. In addition to the popular 2D features, we included the depth map and its derived features. The results indicate that the extra depth information can enhance the saliency estimation accuracy specifically for close-up objects hidden in a complex-texture background. In addition, we examined the effectiveness of various low-, mid-, and high-level features on saliency prediction. Compared with both 2D and 3D state-of-the-art saliency estimation models, our methods show better performance on the 3D test images. The eye-tracking database and the MATLAB source codes for the proposed saliency model and evaluation methods are available on our website.

You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention.

PubMed

Feldmann-Wüstefeld, Tobias; Uengoer, Metin; Schubö, Anna

2015-11-01

Besides visual salience and observers' current intention, prior learning experience may influence deployment of visual attention. Associative learning models postulate that observers pay more attention to stimuli previously experienced as reliable predictors of specific outcomes. To investigate the impact of learning experience on deployment of attention, we combined an associative learning task with a visual search task and measured event-related potentials of the EEG as neural markers of attention deployment. In the learning task, participants categorized stimuli varying in color/shape with only one dimension being predictive of category membership. In the search task, participants searched a shape target while disregarding irrelevant color distractors. Behavioral results showed that color distractors impaired performance to a greater degree when color rather than shape was predictive in the learning task. Neurophysiological results show that the amplified distraction was due to differential attention deployment (N2pc). Experiment 2 showed that when color was predictive for learning, color distractors captured more attention in the search task (ND component) and more suppression of color distractor was required (PD component). The present results thus demonstrate that priority in visual attention is biased toward predictive stimuli, which allows learning experience to shape selection. We also show that learning experience can overrule strong top-down control (blocked tasks, Experiment 3) and that learning experience has a longer-term effect on attention deployment (tasks on two successive days, Experiment 4). © 2015 Society for Psychophysiological Research.

The cerebellum and visual perceptual learning: evidence from a motion extrapolation task.

PubMed

Deluca, Cristina; Golzar, Ashkan; Santandrea, Elisa; Lo Gerfo, Emanuele; Eštočinová, Jana; Moretto, Giuseppe; Fiaschi, Antonio; Panzeri, Marta; Mariotti, Caterina; Tinazzi, Michele; Chelazzi, Leonardo

2014-09-01

Visual perceptual learning is widely assumed to reflect plastic changes occurring along the cerebro-cortical visual pathways, including at the earliest stages of processing, though increasing evidence indicates that higher-level brain areas are also involved. Here we addressed the possibility that the cerebellum plays an important role in visual perceptual learning. Within the realm of motor control, the cerebellum supports learning of new skills and recalibration of motor commands when movement execution is consistently perturbed (adaptation). Growing evidence indicates that the cerebellum is also involved in cognition and mediates forms of cognitive learning. Therefore, the obvious question arises whether the cerebellum might play a similar role in learning and adaptation within the perceptual domain. We explored a possible deficit in visual perceptual learning (and adaptation) in patients with cerebellar damage using variants of a novel motion extrapolation, psychophysical paradigm. Compared to their age- and gender-matched controls, patients with focal damage to the posterior (but not the anterior) cerebellum showed strongly diminished learning, in terms of both rate and amount of improvement over time. Consistent with a double-dissociation pattern, patients with focal damage to the anterior cerebellum instead showed more severe clinical motor deficits, indicative of a distinct role of the anterior cerebellum in the motor domain. The collected evidence demonstrates that a pure form of slow-incremental visual perceptual learning is crucially dependent on the intact cerebellum, bearing the notion that the human cerebellum acts as a learning device for motor, cognitive and perceptual functions. We interpret the deficit in terms of an inability to fine-tune predictive models of the incoming flow of visual perceptual input over time. Moreover, our results suggest a strong dissociation between the role of different portions of the cerebellum in motor versus non-motor functions, with only the posterior lobe being responsible for learning in the perceptual domain. Copyright © 2014. Published by Elsevier Ltd.

Does learning style preferences influence academic performance among dental students in Isfahan, Iran?

PubMed Central

2018-01-01

Purpose The present study aimed to identify the learning preferences of dental students and to characterize their relationship with academic performance at a dental school in Isfahan, Iran. Methods This cross-sectional descriptive study included 200 undergraduate dental students from October to November 2016. Data were collected using a 2-part questionnaire. The first part included demographic data, and the second part was a Persian-language version of the visual, aural, read/write, and kinesthetic questionnaire. Data analysis was conducted with the chi-square test, 1-way analysis of variance, and multiple linear regression. Results The response rate was 86.6%. Approximately half of the students (51.5%) had multimodal learning preferences. Among the unimodal group (48.5%), the most common mode was aural (24.0%), followed by kinesthetic (15.5%), reading-writing (8.0%), and visual (1.0%). There was a significant association between academic performance and the reading/writing learning style preference (P< 0.01). Conclusion Multimodal learning styles were the most preferred. Among single-mode learning styles, the aural style was most common, followed by the kinesthetic style. Students with a reading/writing preference had better academic performance. The results of this study provide useful information for preparing a more problem-based curriculum with active learning strategies. PMID:29575848

Multi-channel feature dictionaries for RGB-D object recognition

NASA Astrophysics Data System (ADS)

Lan, Xiaodong; Li, Qiming; Chong, Mina; Song, Jian; Li, Jun

2018-04-01

Hierarchical matching pursuit (HMP) is a popular feature learning method for RGB-D object recognition. However, the feature representation with only one dictionary for RGB channels in HMP does not capture sufficient visual information. In this paper, we propose multi-channel feature dictionaries based feature learning method for RGB-D object recognition. The process of feature extraction in the proposed method consists of two layers. The K-SVD algorithm is used to learn dictionaries in sparse coding of these two layers. In the first-layer, we obtain features by performing max pooling on sparse codes of pixels in a cell. And the obtained features of cells in a patch are concatenated to generate patch jointly features. Then, patch jointly features in the first-layer are used to learn the dictionary and sparse codes in the second-layer. Finally, spatial pyramid pooling can be applied to the patch jointly features of any layer to generate the final object features in our method. Experimental results show that our method with first or second-layer features can obtain a comparable or better performance than some published state-of-the-art methods.

Visual research in clinical education.

PubMed

Bezemer, Jeff

2017-01-01

The aim of this paper is to explore what might be gained from collecting and analysing visual data, such as photographs, scans, drawings, video and screen recordings, in clinical educational research. Its focus is on visual research that looks at teaching and learning 'as it naturally occurs' in the work place, in simulation centres and other sites, and also involves the collection and analysis of visual learning materials circulating in these sites. With the ubiquity of digital recording devices, video data and visual learning materials are now relatively cheap to collect. Compared to other domains of education research visual materials are not widely used in clinical education research. The paper sets out to identify and reflect on the possibilities for visual research using examples from an ethnographic study on surgical and inter-professional learning in the operating theatres of a London hospital. The paper shows how visual research enables recognition, analysis and critical evaluation of (1) the hidden curriculum, such as the meanings implied by embodied, visible actions of clinicians; (2) the ways in which clinical teachers design multimodal learning environments using a range of modes of communication available to them, combining, for instance, gesture and speech; (3) the informal assessment of clinical skills, and the intricate relation between trainee performance and supervisor feedback; (4) the potentialities and limitations of different visual learning materials, such as textbooks and videos, for representing medical knowledge. The paper concludes with theoretical and methodological reflections on what can be made visible, and therefore available for analysis, explanation and evaluation if visual materials are used for clinical education research, and what remains unaccounted for if written language remains the dominant mode in the research cycle. Opportunities for quantitative analysis and ethical implications are also discussed. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Classroom Interpreting and Visual Information Processing in Mainstream Education for Deaf Students: Live or Memorex®?

PubMed Central

Marschark, Marc; Pelz, Jeff B.; Convertino, Carol; Sapere, Patricia; Arndt, Mary Ellen; Seewagen, Rosemarie

2006-01-01

This study examined visual information processing and learning in classrooms including both deaf and hearing students. Of particular interest were the effects on deaf students’ learning of live (three-dimensional) versus video-recorded (two-dimensional) sign language interpreting and the visual attention strategies of more and less experienced deaf signers exposed to simultaneous, multiple sources of visual information. Results from three experiments consistently indicated no differences in learning between three-dimensional and two-dimensional presentations among hearing or deaf students. Analyses of students’ allocation of visual attention and the influence of various demographic and experimental variables suggested considerable flexibility in deaf students’ receptive communication skills. Nevertheless, the findings also revealed a robust advantage in learning in favor of hearing students. PMID:16628250

Efficacy of Simulation-Based Learning of Electronics Using Visualization and Manipulation

ERIC Educational Resources Information Center

Chen, Yu-Lung; Hong, Yu-Ru; Sung, Yao-Ting; Chang, Kuo-En

2011-01-01

Software for simulation-based learning of electronics was implemented to help learners understand complex and abstract concepts through observing external representations and exploring concept models. The software comprises modules for visualization and simulative manipulation. Differences in learning performance of using the learning software…

Effects of Visual Feedback-Induced Variability on Motor Learning of Handrim Wheelchair Propulsion

PubMed Central

Leving, Marika T.; Vegter, Riemer J. K.; Hartog, Johanneke; Lamoth, Claudine J. C.; de Groot, Sonja; van der Woude, Lucas H. V.

2015-01-01

Background It has been suggested that a higher intra-individual variability benefits the motor learning of wheelchair propulsion. The present study evaluated whether feedback-induced variability on wheelchair propulsion technique variables would also enhance the motor learning process. Learning was operationalized as an improvement in mechanical efficiency and propulsion technique, which are thought to be closely related during the learning process. Methods 17 Participants received visual feedback-based practice (feedback group) and 15 participants received regular practice (natural learning group). Both groups received equal practice dose of 80 min, over 3 weeks, at 0.24 W/kg at a treadmill speed of 1.11 m/s. To compare both groups the pre- and post-test were performed without feedback. The feedback group received real-time visual feedback on seven propulsion variables with instruction to manipulate the presented variable to achieve the highest possible variability (1st 4-min block) and optimize it in the prescribed direction (2nd 4-min block). To increase motor exploration the participants were unaware of the exact variable they received feedback on. Energy consumption and the propulsion technique variables with their respective coefficient of variation were calculated to evaluate the amount of intra-individual variability. Results The feedback group, which practiced with higher intra-individual variability, improved the propulsion technique between pre- and post-test to the same extent as the natural learning group. Mechanical efficiency improved between pre- and post-test in the natural learning group but remained unchanged in the feedback group. Conclusion These results suggest that feedback-induced variability inhibited the improvement in mechanical efficiency. Moreover, since both groups improved propulsion technique but only the natural learning group improved mechanical efficiency, it can be concluded that the improvement in mechanical efficiency and propulsion technique do not always appear simultaneously during the motor learning process. Their relationship is most likely modified by other factors such as the amount of the intra-individual variability. PMID:25992626

[Learning how to learn for specialist further education].

PubMed

Breuer, G; Lütcke, B; St Pierre, M; Hüttl, S

2017-02-01

The world of medicine is becoming from year to year more complex. This necessitates efficient learning processes, which incorporate the principles of adult education but with unchanged periods of further education. The subject matter must be processed, organized, visualized, networked and comprehended. The learning process should be voluntary and self-driven with the aim of learning the profession and becoming an expert in a specialist field. Learning is an individual process. Despite this, the constantly cited learning styles are nowadays more controversial. An important factor is a healthy mixture of blended learning methods, which also use new technical possibilities. These include a multitude of e‑learning options and simulations, which partly enable situative learning in a "shielded" environment. An exemplary role model of the teacher and feedback for the person in training also remain core and sustainable aspects in medical further education.

Orthopaedic resident preparedness for closed reduction and pinning of pediatric supracondylar fractures is improved by e-learning: a multisite randomized controlled study.

PubMed

Hearty, Thomas; Maizels, Max; Pring, Maya; Mazur, John; Liu, Raymond; Sarwark, John; Janicki, Joseph

2013-09-04

There is a need to provide more efficient surgical training methods for orthopaedic residents. E-learning could possibly increase resident surgical preparedness, confidence, and comfort for surgery. Using closed reduction and pinning of pediatric supracondylar humeral fractures as the index case, we hypothesized that e-learning could increase resident knowledge acquisition for case preparation in the operating room. An e-learning surgical training module was created on the Computer Enhanced Visual Learning platform. The module provides a detailed and focused road map of the procedure utilizing a multimedia format. A multisite prospective randomized controlled study design compared residents who used a textbook for case preparation (control group) with residents who used the same textbook plus completed the e-learning module (test group). All subjects completed a sixty-question test on the theory and methods of the case. After completion of the test, the control group then completed the module as well. All subjects were surveyed on their opinion regarding the effectiveness of the module after performing an actual surgical case. Twenty-eight subjects with no previous experience in this surgery were enrolled at four academic centers. Subjects were randomized into two equal groups. The test group scored significantly better (p < 0.001) and demonstrated competence on the test compared with the control group; the mean correct test score (and standard deviation) was 90.9% ± 6.8% for the test group and 73.5% ± 6.4% for the control group. All residents surveyed (n = 27) agreed that the module is a useful supplement to traditional methods for case preparation and twenty-two of twenty-seven residents agreed that it reduced their anxiety during the case and improved their attention to surgical detail. E-learning using the Computer Enhanced Visual Learning platform significantly improved preparedness, confidence, and comfort with percutaneous closed reduction and pinning of a pediatric supracondylar humeral fracture. We believe that adapting such methods into residency training programs will improve efficiency in surgical training.

H2Oh!: Classroom demonstrations and activities for improving student learning of water concepts

NASA Astrophysics Data System (ADS)

Chan-Hilton, A.; Neupauer, R. M.; Burian, S. J.; Lauer, J. W.; Mathisen, P. P.; Mays, D. C.; Olson, M. S.; Pomeroy, C. A.; Ruddell, B. L.; Sciortino, A.

2012-12-01

Research has shown that the use of demonstrations and hands-on activities in the classroom enhances student learning. Students learn more and enjoy classes more when visual and active learning are incorporated into the lecture. Most college-aged students prefer visual modes of learning, while most instruction is conducted in a lecture, or auditory, format. The use of classroom demonstrations provides opportunities for incorporating visual and active learning into the classroom environment. However, while most instructors acknowledge the benefits of these teaching methods, they typically do not have the time and resources to develop and test such activities and to develop plans to incorporate them into their lectures. Members of the Excellence in Water Resources Education Task Committee of the Environmental and Water Resources Institute (EWRI) of the American Society of Civil Engineers (ASCE) have produced a publication that contains a collection of activities aimed to foster excellence in water resources and hydrology education and improve student learning of principles. The book contains forty-five demonstrations and activities that can be used in water-related classes with topics in fluid mechanics, hydraulics, surface water hydrology, groundwater hydrology, and water quality. We present examples of these activities, including topics such as conservation of momentum, buoyancy, Bernoulli's principle, drag force, pipe flow, watershed delineation, reservoir networks, head distribution in aquifers, and molecular diffusion in a porous medium. Unlike full laboratory exercises, these brief demonstrations and activities (most of which take less than fifteen minutes) can be easily incorporated into classroom lectures. For each demonstration, guidance for preparing and conducting the activity, along with a brief overview of the principles that are demonstrated, is provided. The target audience of the activities is undergraduate students, although the activities also may be used in K-12 and graduate classes.

Exploring the role of task performance and learning style on prefrontal hemodynamics during a working memory task.

PubMed

Anderson, Afrouz A; Parsa, Kian; Geiger, Sydney; Zaragoza, Rachel; Kermanian, Riley; Miguel, Helga; Dashtestani, Hadis; Chowdhry, Fatima A; Smith, Elizabeth; Aram, Siamak; Gandjbakhche, Amir H

2018-01-01

Existing literature outlines the quality and location of activation in the prefrontal cortex (PFC) during working memory (WM) tasks. However, the effects of individual differences on the underlying neural process of WM tasks are still unclear. In this functional near infrared spectroscopy study, we administered a visual and auditory n-back task to examine activation in the PFC while considering the influences of task performance, and preferred learning strategy (VARK score). While controlling for age, results indicated that high performance (HP) subjects (accuracy > 90%) showed task dependent lower activation compared to normal performance subjects in PFC region Specifically HP groups showed lower activation in left dorsolateral PFC (DLPFC) region during performance of auditory task whereas during visual task they showed lower activation in the right DLPFC. After accounting for learning style, we found a correlation between visual and aural VARK score and level of activation in the PFC. Subjects with higher visual VARK scores displayed lower activation during auditory task in left DLPFC, while those with higher visual scores exhibited higher activation during visual task in bilateral DLPFC. During performance of auditory task, HP subjects had higher visual VARK scores compared to NP subjects indicating an effect of learning style on the task performance and activation. The results of this study show that learning style and task performance can influence PFC activation, with applications toward neurological implications of learning style and populations with deficits in auditory or visual processing.

Exploring the role of task performance and learning style on prefrontal hemodynamics during a working memory task

PubMed Central

Anderson, Afrouz A.; Parsa, Kian; Geiger, Sydney; Zaragoza, Rachel; Kermanian, Riley; Miguel, Helga; Chowdhry, Fatima A.; Smith, Elizabeth; Aram, Siamak; Gandjbakhche, Amir H.

2018-01-01

Existing literature outlines the quality and location of activation in the prefrontal cortex (PFC) during working memory (WM) tasks. However, the effects of individual differences on the underlying neural process of WM tasks are still unclear. In this functional near infrared spectroscopy study, we administered a visual and auditory n-back task to examine activation in the PFC while considering the influences of task performance, and preferred learning strategy (VARK score). While controlling for age, results indicated that high performance (HP) subjects (accuracy > 90%) showed task dependent lower activation compared to normal performance subjects in PFC region Specifically HP groups showed lower activation in left dorsolateral PFC (DLPFC) region during performance of auditory task whereas during visual task they showed lower activation in the right DLPFC. After accounting for learning style, we found a correlation between visual and aural VARK score and level of activation in the PFC. Subjects with higher visual VARK scores displayed lower activation during auditory task in left DLPFC, while those with higher visual scores exhibited higher activation during visual task in bilateral DLPFC. During performance of auditory task, HP subjects had higher visual VARK scores compared to NP subjects indicating an effect of learning style on the task performance and activation. The results of this study show that learning style and task performance can influence PFC activation, with applications toward neurological implications of learning style and populations with deficits in auditory or visual processing. PMID:29870536

Perceptual Learning Improves Stereoacuity in Amblyopia

PubMed Central

Xi, Jie; Jia, Wu-Li; Feng, Li-Xia; Lu, Zhong-Lin; Huang, Chang-Bing

2014-01-01

Purpose. Amblyopia is a developmental disorder that results in both monocular and binocular deficits. Although traditional treatment in clinical practice (i.e., refractive correction, or occlusion by patching and penalization of the fellow eye) is effective in restoring monocular visual acuity, there is little information on how binocular function, especially stereopsis, responds to traditional amblyopia treatment. We aim to evaluate the effects of perceptual learning on stereopsis in observers with amblyopia in the current study. Methods. Eleven observers (21.1 ± 5.1 years, six females) with anisometropic or ametropic amblyopia were trained to judge depth in 10 to 13 sessions. Red–green glasses were used to present three different texture anaglyphs with different disparities but a fixed exposure duration. Stereoacuity was assessed with the Fly Stereo Acuity Test and visual acuity was assessed with the Chinese Tumbling E Chart before and after training. Results. Averaged across observers, training significantly reduced disparity threshold from 776.7″ to 490.4″ (P < 0.01) and improved stereoacuity from 200.3″ to 81.6″ (P < 0.01). Interestingly, visual acuity also significantly improved from 0.44 to 0.35 logMAR (approximately 0.9 lines, P < 0.05) in the amblyopic eye after training. Moreover, the learning effects in two of the three retested observers were largely retained over a 5-month period. Conclusions. Perceptual learning is effective in improving stereo vision in observers with amblyopia. These results, together with previous evidence, suggest that structured monocular and binocular training might be necessary to fully recover degraded visual functions in amblyopia. Chinese Abstract PMID:24508791

Incidental Auditory Category Learning

PubMed Central

Gabay, Yafit; Dick, Frederic K.; Zevin, Jason D.; Holt, Lori L.

2015-01-01

Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in one of four possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from one of four distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning. PMID:26010588

Motor learning and working memory in children born preterm: a systematic review.

PubMed

Jongbloed-Pereboom, Marjolein; Janssen, Anjo J W M; Steenbergen, Bert; Nijhuis-van der Sanden, Maria W G

2012-04-01

Children born preterm have a higher risk for developing motor, cognitive, and behavioral problems. Motor problems can occur in combination with working memory problems, and working memory is important for explicit learning of motor skills. The relation between motor learning and working memory has never been reviewed. The goal of this review was to provide an overview of motor learning, visual working memory and the role of working memory on motor learning in preterm children. A systematic review conducted in four databases identified 38 relevant articles, which were evaluated for methodological quality. Only 4 of 38 articles discussed motor learning in preterm children. Thirty-four studies reported on visual working memory; preterm birth affected performance on visual working memory tests. Information regarding motor learning and the role of working memory on the different components of motor learning was not available. Future research should address this issue. Insight in the relation between motor learning and visual working memory may contribute to the development of evidence based intervention programs for children born preterm. Copyright © 2012 Elsevier Ltd. All rights reserved.

The use of interactive technology in the classroom.

PubMed

Kresic, P

1999-01-01

This article discusses the benefits that clinical laboratory science students and instructors experienced through the use of and integration of computer technology, microscopes, and digitizing cameras. Patient specimens were obtained from the participating clinical affiliates, slides stained or wet mounts prepared, images viewed under the microscope, digitized, and after labeling, stored into an appropriate folder. The individual folders were labeled as Hematology, Microbiology, Chemistry, or Urinalysis. Students, after obtaining the necessary specimens and pertinent data, created case study presentations for class discussions. After two semesters of utilizing videomicroscopy/computer technology in the classroom, students and instructors realized the potential associated with the technology, namely, the vast increase in the amount of organized visual and scientific information accessible and the availability of collaborative and interactive learning to complement individualized instruction. The instructors, on the other hand, were able to provide a wider variety of visual information on individual bases. In conclusion, the appropriate use of technology can enhance students' learning and participation. Increased student involvement through the use of videomicroscopy and computer technology heightened their sense of pride and ownership in providing suitable information in case study presentations. Also, visualization provides students and educators with alternative methods of teaching/learning and increased retention of information.

The Effects of Online Interactions on the Relationship between Learning-Related Anxiety and Intention to Persist among E-Learning Students with Visual Impairment

ERIC Educational Resources Information Center

Oh, Yunjin; Lee, Soon Min

2016-01-01

This study explored whether learning-related anxiety would negatively affect intention to persist with e-learning among students with visual impairment, and examined the roles of three online interactions in the relationship between learning-related anxiety and intention to persist with e-learning. For this study, a convenience sample of…

Technologies That Capitalize on Study Skills with Learning Style Strengths

ERIC Educational Resources Information Center

Howell, Dusti D.

2008-01-01

This article addresses the tools available in the rapidly changing digital learning environment and offers a variety of approaches for how they can assist students with visual, auditory, or kinesthetic learning strengths. Teachers can use visual, auditory, and kinesthetic assessment tests to identify learning preferences and then recommend…

Using Visualization to Motivate Student Participation in Collaborative Online Learning Environments

ERIC Educational Resources Information Center

Jin, Sung-Hee

2017-01-01

Online participation in collaborative online learning environments is instrumental in motivating students to learn and promoting their learning satisfaction, but there has been little research on the technical supports for motivating students' online participation. The purpose of this study was to develop a visualization tool to motivate learners…

Visual learning in drosophila: application on a roving robot and comparisons

NASA Astrophysics Data System (ADS)

Arena, P.; De Fiore, S.; Patané, L.; Termini, P. S.; Strauss, R.

2011-05-01

Visual learning is an important aspect of fly life. Flies are able to extract visual cues from objects, like colors, vertical and horizontal distributedness, and others, that can be used for learning to associate a meaning to specific features (i.e. a reward or a punishment). Interesting biological experiments show trained stationary flying flies avoiding flying towards specific visual objects, appearing on the surrounding environment. Wild-type flies effectively learn to avoid those objects but this is not the case for the learning mutant rutabaga defective in the cyclic AMP dependent pathway for plasticity. A bio-inspired architecture has been proposed to model the fly behavior and experiments on roving robots were performed. Statistical comparisons have been considered and mutant-like effect on the model has been also investigated.

Changes of the Prefrontal EEG (Electroencephalogram) Activities According to the Repetition of Audio-Visual Learning.

ERIC Educational Resources Information Center

Kim, Yong-Jin; Chang, Nam-Kee

2001-01-01

Investigates the changes of neuronal response according to a four time repetition of audio-visual learning. Obtains EEG data from the prefrontal (Fp1, Fp2) lobe from 20 subjects at the 8th grade level. Concludes that the habituation of neuronal response shows up in repetitive audio-visual learning and brain hemisphericity can be changed by…

From a Gloss to a Learning Tool: Does Visual Aids Enhance Better Sentence Comprehension?

ERIC Educational Resources Information Center

Sato, Takeshi; Suzuki, Akio

2012-01-01

The aim of this study is to optimize CALL environments as a learning tool rather than a gloss, focusing on the learning of polysemous words which refer to spatial relationship between objects. A lot of research has already been conducted to examine the efficacy of visual glosses while reading L2 texts and has reported that visual glosses can be…

Bayesian learning of visual chunks by human observers

PubMed Central

Orbán, Gergő; Fiser, József; Aslin, Richard N.; Lengyel, Máté

2008-01-01

Efficient and versatile processing of any hierarchically structured information requires a learning mechanism that combines lower-level features into higher-level chunks. We investigated this chunking mechanism in humans with a visual pattern-learning paradigm. We developed an ideal learner based on Bayesian model comparison that extracts and stores only those chunks of information that are minimally sufficient to encode a set of visual scenes. Our ideal Bayesian chunk learner not only reproduced the results of a large set of previous empirical findings in the domain of human pattern learning but also made a key prediction that we confirmed experimentally. In accordance with Bayesian learning but contrary to associative learning, human performance was well above chance when pair-wise statistics in the exemplars contained no relevant information. Thus, humans extract chunks from complex visual patterns by generating accurate yet economical representations and not by encoding the full correlational structure of the input. PMID:18268353

A delivery mode study: The effect of self-paced video learning on first-year college students' achievement in calculus

NASA Astrophysics Data System (ADS)

Oktaviyanthi, Rina; Herman, Tatang

2016-10-01

In this paper, the effect of two different modes of deliver are proposed. The use of self-paced video learning and conventional learning methods in mathematics are compared. The research design classified as a quasi-experiment. The participants were 80 students in the first-year college and divided into two groups. One group as an experiment class received self-paced video learning method and the other group as a control group taught by conventional learning method. Pre and posttest were employed to measure the students' achievement, while questionnaire and interviews were applied to support the pre and posttest data. Statistical analysis included the independent samples t-test showed differences (p < 0.05) in posttest between the experimental and control groups, it means that the use of self-paced video contributed on students' achievement and students' attitudes. In addition, related to corresponding to the students' answer, there are five positive gains in using self-paced video in learning Calculus, such as appropriate learning for both audio and visual of students' characteristics, useful to learn Calculus, assisting students to be more engaging and paying attention in learning, helping students in making the concepts of Calculus are visible, interesting media and motivating students to learn independently.

Impact of self-assessment questions and learning styles in Web-based learning: a randomized, controlled, crossover trial.

PubMed

Cook, David A; Thompson, Warren G; Thomas, Kris G; Thomas, Matthew R; Pankratz, V Shane

2006-03-01

To determine the effect of self-assessment questions on learners' knowledge and format preference in a Web-based course, and investigate associations between learning styles and outcomes. The authors conducted a randomized, controlled, crossover trial in the continuity clinics of the Mayo-Rochester internal medicine residency program during the 2003-04 academic year. Case-based self-assessment questions were added to Web-based modules covering topics in ambulatory internal medicine. Participants completed two modules with questions and two modules without questions, with sequence randomly assigned. Outcomes included knowledge assessed after each module, format preference, and learning style assessed using the Index of Learning Styles. A total of 121 of 146 residents (83%) consented. Residents had higher test scores when using the question format (mean +/- standard error, 78.9% +/- 1.0) than when using the standard format (76.2% +/- 1.0, p = .006). Residents preferring the question format scored higher (79.7% +/- 1.1) than those preferring standard (69.5% +/- 2.3, p < .001). Learning styles did not affect scores except that visual-verbal "intermediate" learners (80.6% +/- 1.4) and visual learners (77.5% +/- 1.3) did better than verbal learners (70.9% +/- 3.0, p = .003 and p = .033, respectively). Sixty-five of 78 residents (83.3%, 95% CI 73.2-90.8%) preferred the question format. Learning styles were not associated with preference (p > .384). Although the question format took longer than the standard format (60.4 +/- 3.6 versus 44.3 +/- 3.3 minutes, p < .001), 55 of 77 residents (71.4%, 60.0-81.2%) reported that it was more efficient. Instructional methods that actively engage learners improve learning outcomes. These findings hold implications for both Web-based learning and "traditional" educational activities. Future research, in both Web-based learning and other teaching modalities, should focus on further defining the effectiveness of selected instructional methods in specific learning contexts.

English Orthographic Learning in Chinese-L1 Young EFL Beginners.

PubMed

Cheng, Yu-Lin

2017-12-01

English orthographic learning, among Chinese-L1 children who were beginning to learn English as a foreign language, was documented when: (1) only visual memory was at their disposal, (2) visual memory and either some letter-sound knowledge or some semantic information was available, and (3) visual memory, some letter-sound knowledge and some semantic information were all available. When only visual memory was available, orthographic learning (measured via an orthographic choice test) was meagre. Orthographic learning was significant when either semantic information or letter-sound knowledge supplemented visual memory, with letter-sound knowledge generating greater significance. Although the results suggest that letter-sound knowledge plays a more important role than semantic information, letter-sound knowledge alone does not suffice to achieve perfect orthographic learning, as orthographic learning was greatest when letter-sound knowledge and semantic information were both available. The present findings are congruent with a view that the orthography of a foreign language drives its orthographic learning more than L1 orthographic learning experience, thus extending Share's (Cognition 55:151-218, 1995) self-teaching hypothesis to include non-alphabetic L1 children's orthographic learning of an alphabetic foreign language. The little letter-sound knowledge development observed in the experiment-I control group indicates that very little letter-sound knowledge develops in the absence of dedicated letter-sound training. Given the important role of letter-sound knowledge in English orthographic learning, dedicated letter-sound instruction is highly recommended.

A color fusion method of infrared and low-light-level images based on visual perception

NASA Astrophysics Data System (ADS)

Han, Jing; Yan, Minmin; Zhang, Yi; Bai, Lianfa

2014-11-01

The color fusion images can be obtained through the fusion of infrared and low-light-level images, which will contain both the information of the two. The fusion images can help observers to understand the multichannel images comprehensively. However, simple fusion may lose the target information due to inconspicuous targets in long-distance infrared and low-light-level images; and if targets extraction is adopted blindly, the perception of the scene information will be affected seriously. To solve this problem, a new fusion method based on visual perception is proposed in this paper. The extraction of the visual targets ("what" information) and parallel processing mechanism are applied in traditional color fusion methods. The infrared and low-light-level color fusion images are achieved based on efficient typical targets learning. Experimental results show the effectiveness of the proposed method. The fusion images achieved by our algorithm can not only improve the detection rate of targets, but also get rich natural information of the scenes.

Learning Science Using AR Book: A Preliminary Study on Visual Needs of Deaf Learners

NASA Astrophysics Data System (ADS)

Megat Mohd. Zainuddin, Norziha; Badioze Zaman, Halimah; Ahmad, Azlina

Augmented Reality (AR) is a technology that is projected to have more significant role in teaching and learning, particularly in visualising abstract concepts in the learning process. AR is a technology is based on visually oriented technique. Thus, it is suitable for deaf learners since they are generally classified as visual learners. Realising the importance of visual learning style for deaf learners in learning Science, this paper reports on a preliminary study of on an ongoing research on problems faced by deaf learners in learning the topic on Microorganisms. Being visual learners, they have problems with current text books that are more text-based that graphic based. In this preliminary study, a qualitative approach using the ethnographic observational technique was used so that interaction with three deaf learners who are participants throughout this study (they are also involved actively in the design and development of the AR Book). An interview with their teacher and doctor were also conducted to identify their learning and medical problems respectively. Preliminary findings have confirmed the need to design and develop a special Augmented Reality Book called AR-Science for Deaf Learners (AR-SiD).

Both memory and attention systems contribute to visual search for targets cued by implicitly learned context

PubMed Central

Giesbrecht, Barry; Sy, Jocelyn L.; Guerin, Scott A.

2012-01-01

Environmental context learned without awareness can facilitate visual processing of goal-relevant information. According to one view, the benefit of implicitly learned context relies on the neural systems involved in spatial attention and hippocampus-mediated memory. While this view has received empirical support, it contradicts traditional models of hippocampal function. The purpose of the present work was to clarify the influence of spatial context on visual search performance and on brain structures involved memory and attention. Event-related functional magnetic resonance imaging revealed that activity in the hippocampus as well as in visual and parietal cortex was modulated by learned visual context even though participants’ subjective reports and performance on a post-experiment recognition task indicated no explicit knowledge of the learned context. Moreover, the magnitude of the initial selective hippocampus response predicted the magnitude of the behavioral benefit due to context observed at the end of the experiment. The results suggest that implicit contextual learning is mediated by attention and memory and that these systems interact to support search of our environment. PMID:23099047

Dynamic functional brain networks involved in simple visual discrimination learning.

PubMed

Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

2014-10-01

Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Cross-modal interaction between visual and olfactory learning in Apis cerana.

PubMed

Zhang, Li-Zhen; Zhang, Shao-Wu; Wang, Zi-Long; Yan, Wei-Yu; Zeng, Zhi-Jiang

2014-10-01

The power of the small honeybee brain carrying out behavioral and cognitive tasks has been shown repeatedly to be highly impressive. The present study investigates, for the first time, the cross-modal interaction between visual and olfactory learning in Apis cerana. To explore the role and molecular mechanisms of cross-modal learning in A. cerana, the honeybees were trained and tested in a modified Y-maze with seven visual and five olfactory stimulus, where a robust visual threshold for black/white grating (period of 2.8°-3.8°) and relatively olfactory threshold (concentration of 50-25%) was obtained. Meanwhile, the expression levels of five genes (AcCREB, Acdop1, Acdop2, Acdop3, Actyr1) related to learning and memory were analyzed under different training conditions by real-time RT-PCR. The experimental results indicate that A. cerana could exhibit cross-modal interactions between visual and olfactory learning by reducing the threshold level of the conditioning stimuli, and that these genes may play important roles in the learning process of honeybees.

Dual Low-Rank Pursuit: Learning Salient Features for Saliency Detection.

PubMed

Lang, Congyan; Feng, Jiashi; Feng, Songhe; Wang, Jingdong; Yan, Shuicheng

2016-06-01

Saliency detection is an important procedure for machines to understand visual world as humans do. In this paper, we consider a specific saliency detection problem of predicting human eye fixations when they freely view natural images, and propose a novel dual low-rank pursuit (DLRP) method. DLRP learns saliency-aware feature transformations by utilizing available supervision information and constructs discriminative bases for effectively detecting human fixation points under the popular low-rank and sparsity-pursuit framework. Benefiting from the embedded high-level information in the supervised learning process, DLRP is able to predict fixations accurately without performing the expensive object segmentation as in the previous works. Comprehensive experiments clearly show the superiority of the proposed DLRP method over the established state-of-the-art methods. We also empirically demonstrate that DLRP provides stronger generalization performance across different data sets and inherits the advantages of both the bottom-up- and top-down-based saliency detection methods.

Communicating Science Concepts to Individuals with Visual Impairments Using Short Learning Modules

ERIC Educational Resources Information Center

Stender, Anthony S.; Newell, Ryan; Villarreal, Eduardo; Swearer, Dayne F.; Bianco, Elisabeth; Ringe, Emilie

2016-01-01

Of the 6.7 million individuals in the United States who are visually impaired, 63% are unemployed, and 59% have not attained an education beyond a high school diploma. Providing a basic science education to children and adults with visual disabilities can be challenging because most scientific learning relies on visual demonstrations. Creating…

Application of Frameworks in the Analysis and (Re)design of Interactive Visual Learning Tools

ERIC Educational Resources Information Center

Liang, Hai-Ning; Sedig, Kamran

2009-01-01

Interactive visual learning tools (IVLTs) are software environments that encode and display information visually and allow learners to interact with the visual information. This article examines the application and utility of frameworks in the analysis and design of IVLTs at the micro level. Frameworks play an important role in any design. They…

The challenges of studying visual expertise in medical image diagnosis.

PubMed

Gegenfurtner, Andreas; Kok, Ellen; van Geel, Koos; de Bruin, Anique; Jarodzka, Halszka; Szulewski, Adam; van Merriënboer, Jeroen Jg

2017-01-01

Visual expertise is the superior visual skill shown when executing domain-specific visual tasks. Understanding visual expertise is important in order to understand how the interpretation of medical images may be best learned and taught. In the context of this article, we focus on the visual skill of medical image diagnosis and, more specifically, on the methodological set-ups routinely used in visual expertise research. We offer a critique of commonly used methods and propose three challenges for future research to open up new avenues for studying characteristics of visual expertise in medical image diagnosis. The first challenge addresses theory development. Novel prospects in modelling visual expertise can emerge when we reflect on cognitive and socio-cultural epistemologies in visual expertise research, when we engage in statistical validations of existing theoretical assumptions and when we include social and socio-cultural processes in expertise development. The second challenge addresses the recording and analysis of longitudinal data. If we assume that the development of expertise is a long-term phenomenon, then it follows that future research can engage in advanced statistical modelling of longitudinal expertise data that extends the routine use of cross-sectional material through, for example, animations and dynamic visualisations of developmental data. The third challenge addresses the combination of methods. Alternatives to current practices can integrate qualitative and quantitative approaches in mixed-method designs, embrace relevant yet underused data sources and understand the need for multidisciplinary research teams. Embracing alternative epistemological and methodological approaches for studying visual expertise can lead to a more balanced and robust future for understanding superior visual skills in medical image diagnosis as well as other medical fields. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

TOPICAL REVIEW: Prosthetic interfaces with the visual system: biological issues

NASA Astrophysics Data System (ADS)

Cohen, Ethan D.

2007-06-01

The design of effective visual prostheses for the blind represents a challenge for biomedical engineers and neuroscientists. Significant progress has been made in the miniaturization and processing power of prosthesis electronics; however development lags in the design and construction of effective machine brain interfaces with visual system neurons. This review summarizes what has been learned about stimulating neurons in the human and primate retina, lateral geniculate nucleus and visual cortex. Each level of the visual system presents unique challenges for neural interface design. Blind patients with the retinal degenerative disease retinitis pigmentosa (RP) are a common population in clinical trials of visual prostheses. The visual performance abilities of normals and RP patients are compared. To generate pattern vision in blind patients, the visual prosthetic interface must effectively stimulate the retinotopically organized neurons in the central visual field to elicit patterned visual percepts. The development of more biologically compatible methods of stimulating visual system neurons is critical to the development of finer spatial percepts. Prosthesis electrode arrays need to adapt to different optimal stimulus locations, stimulus patterns, and patient disease states.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

Using ICT at an Open Distance Learning (ODL) Institution in South Africa: The Learning Experiences of Students with Visual Impairments

ERIC Educational Resources Information Center

Mokiwa, S. A.; Phasha, T. N.

2012-01-01

For students with visual impairments, Information and Communication Technology (ICT) has become an important means through which they can learn and access learning materials at various levels of education. However, their learning experiences in using such form of technologies have been rarely documented, thus suggests society's lack of…

Visual Literacy Skills of Students in College-Level Biology: Learning Outcomes Following Digital or Hand-Drawing Activities

ERIC Educational Resources Information Center

Bell, Justine C.

2014-01-01

To test the claim that digital learning tools enhance the acquisition of visual literacy in this generation of biology students, a learning intervention was carried out with 33 students enrolled in an introductory college biology course. This study compared learning outcomes following two types of learning tools: a traditional drawing activity, or…

Improving the Students' Activity and Learning Outcomes on Social Sciences Subject Using Round Table and Rally Coach of Cooperative Learning Model

ERIC Educational Resources Information Center

Ningsih; Soetjipto, Budi Eko; Sumarmi

2017-01-01

The purpose of this study was: (1) to analyze increasing students' learning activity and learning outcomes. Student activities which were observed include the visual, verbal, listening, writing and mental visual activity; (2) to analyze the improvement of student learning outcomes using "Round Table" and "Rally Coach" Model of…

Mobility scooter driving ability in visually impaired individuals.

PubMed

Cordes, Christina; Heutink, Joost; Brookhuis, Karel A; Brouwer, Wiebo H; Melis-Dankers, Bart J M

2018-06-01

To investigate how well visually impaired individuals can learn to use mobility scooters and which parts of the driving task deserve special attention. A mobility scooter driving skill test was developed to compare driving skills (e.g. reverse driving, turning) between 48 visually impaired (very low visual acuity = 14, low visual acuity = 10, peripheral field defects = 11, multiple visual impairments = 13) and 37 normal-sighted controls without any prior experience with mobility scooters. Performance on this test was rated on a three-point scale. Furthermore, the number of extra repetitions on the different elements were noted. Results showed that visually impaired participants were able to gain sufficient driving skills to be able to use mobility scooters. Participants with visual field defects combined with low visual acuity showed most problems learning different skills and needed more training. Reverse driving and stopping seemed to be most difficult. The present findings suggest that visually impaired individuals are able to learn to drive mobility scooters. Mobility scooter allocators should be aware that these individuals might need more training on certain elements of the driving task. Implications for rehabilitation Visual impairments do not necessarily lead to an inability to acquire mobility scooter driving skills. Individuals with peripheral field defects (especially in combination with reduced visual acuity) need more driving ability training compared to normal-sighted people - especially to accomplish reversing. Individual assessment of visually impaired people is recommended, since participants in this study showed a wide variation in ability to learn driving a mobility scooter.

Building Reflection with Word Clouds for Online RN to BSN Students.

PubMed

Volkert, Delene R

Reflection allows students to integrate learning with their personal context, developing deeper knowledge and promoting critical thinking. Word clouds help students develop themes/concepts beyond traditional methods, introducing visual aspects to an online learning environment. Students created word clouds and captions, then responded to those created by peers for a weekly discussion assignment. Students indicated overwhelming support for the use of word clouds to develop deeper understanding of the subject matter. This reflection assignment could be utilized in asynchronous, online undergraduate nursing courses for creative methods of building reflection and developing knowledge for the undergraduate RN to BSN student.

Visual Hybrid Development Learning System (VHDLS) framework for children with autism.

PubMed

Banire, Bilikis; Jomhari, Nazean; Ahmad, Rodina

2015-10-01

The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework.

Mirror reversal and visual rotation are learned and consolidated via separate mechanisms: recalibrating or learning de novo?

PubMed

Telgen, Sebastian; Parvin, Darius; Diedrichsen, Jörn

2014-10-08

Motor learning tasks are often classified into adaptation tasks, which involve the recalibration of an existing control policy (the mapping that determines both feedforward and feedback commands), and skill-learning tasks, requiring the acquisition of new control policies. We show here that this distinction also applies to two different visuomotor transformations during reaching in humans: Mirror-reversal (left-right reversal over a mid-sagittal axis) of visual feedback versus rotation of visual feedback around the movement origin. During mirror-reversal learning, correct movement initiation (feedforward commands) and online corrections (feedback responses) were only generated at longer latencies. The earliest responses were directed into a nonmirrored direction, even after two training sessions. In contrast, for visual rotation learning, no dependency of directional error on reaction time emerged, and fast feedback responses to visual displacements of the cursor were immediately adapted. These results suggest that the motor system acquires a new control policy for mirror reversal, which initially requires extra processing time, while it recalibrates an existing control policy for visual rotations, exploiting established fast computational processes. Importantly, memory for visual rotation decayed between sessions, whereas memory for mirror reversals showed offline gains, leading to better performance at the beginning of the second session than in the end of the first. With shifts in time-accuracy tradeoff and offline gains, mirror-reversal learning shares common features with other skill-learning tasks. We suggest that different neuronal mechanisms underlie the recalibration of an existing versus acquisition of a new control policy and that offline gains between sessions are a characteristic of latter. Copyright © 2014 the authors 0270-6474/14/3413768-12$15.00/0.

Contextual cueing: implicit learning and memory of visual context guides spatial attention.

PubMed

Chun, M M; Jiang, Y

1998-06-01

Global context plays an important, but poorly understood, role in visual tasks. This study demonstrates that a robust memory for visual context exists to guide spatial attention. Global context was operationalized as the spatial layout of objects in visual search displays. Half of the configurations were repeated across blocks throughout the entire session, and targets appeared within consistent locations in these arrays. Targets appearing in learned configurations were detected more quickly. This newly discovered form of search facilitation is termed contextual cueing. Contextual cueing is driven by incidentally learned associations between spatial configurations (context) and target locations. This benefit was obtained despite chance performance for recognizing the configurations, suggesting that the memory for context was implicit. The results show how implicit learning and memory of visual context can guide spatial attention towards task-relevant aspects of a scene.

Learning Enhances Sensory and Multiple Non-sensory Representations in Primary Visual Cortex

PubMed Central

Poort, Jasper; Khan, Adil G.; Pachitariu, Marius; Nemri, Abdellatif; Orsolic, Ivana; Krupic, Julija; Bauza, Marius; Sahani, Maneesh; Keller, Georg B.; Mrsic-Flogel, Thomas D.; Hofer, Sonja B.

2015-01-01

Summary We determined how learning modifies neural representations in primary visual cortex (V1) during acquisition of a visually guided behavioral task. We imaged the activity of the same layer 2/3 neuronal populations as mice learned to discriminate two visual patterns while running through a virtual corridor, where one pattern was rewarded. Improvements in behavioral performance were closely associated with increasingly distinguishable population-level representations of task-relevant stimuli, as a result of stabilization of existing and recruitment of new neurons selective for these stimuli. These effects correlated with the appearance of multiple task-dependent signals during learning: those that increased neuronal selectivity across the population when expert animals engaged in the task, and those reflecting anticipation or behavioral choices specifically in neuronal subsets preferring the rewarded stimulus. Therefore, learning engages diverse mechanisms that modify sensory and non-sensory representations in V1 to adjust its processing to task requirements and the behavioral relevance of visual stimuli. PMID:26051421

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Image segmentation evaluation for very-large datasets

NASA Astrophysics Data System (ADS)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Drawing enhances cross-modal memory plasticity in the human brain: a case study in a totally blind adult

PubMed Central

Likova, Lora T.

2012-01-01

In a memory-guided drawing task under blindfolded conditions, we have recently used functional Magnetic Resonance Imaging (fMRI) to demonstrate that the primary visual cortex (V1) may operate as the visuo-spatial buffer, or “sketchpad,” for working memory. The results implied, however, a modality-independent or amodal form of its operation. In the present study, to validate the role of V1 in non-visual memory, we eliminated not only the visual input but all levels of visual processing by replicating the paradigm in a congenitally blind individual. Our novel Cognitive-Kinesthetic method was used to train this totally blind subject to draw complex images guided solely by tactile memory. Control tasks of tactile exploration and memorization of the image to be drawn, and memory-free scribbling were also included. FMRI was run before training and after training. Remarkably, V1 of this congenitally blind individual, which before training exhibited noisy, immature, and non-specific responses, after training produced full-fledged response time-courses specific to the tactile-memory drawing task. The results reveal the operation of a rapid training-based plasticity mechanism that recruits the resources of V1 in the process of learning to draw. The learning paradigm allowed us to investigate for the first time the evolution of plastic re-assignment in V1 in a congenitally blind subject. These findings are consistent with a non-visual memory involvement of V1, and specifically imply that the observed cortical reorganization can be empowered by the process of learning to draw. PMID:22593738

Drawing enhances cross-modal memory plasticity in the human brain: a case study in a totally blind adult.

PubMed

Likova, Lora T

2012-01-01

In a memory-guided drawing task under blindfolded conditions, we have recently used functional Magnetic Resonance Imaging (fMRI) to demonstrate that the primary visual cortex (V1) may operate as the visuo-spatial buffer, or "sketchpad," for working memory. The results implied, however, a modality-independent or amodal form of its operation. In the present study, to validate the role of V1 in non-visual memory, we eliminated not only the visual input but all levels of visual processing by replicating the paradigm in a congenitally blind individual. Our novel Cognitive-Kinesthetic method was used to train this totally blind subject to draw complex images guided solely by tactile memory. Control tasks of tactile exploration and memorization of the image to be drawn, and memory-free scribbling were also included. FMRI was run before training and after training. Remarkably, V1 of this congenitally blind individual, which before training exhibited noisy, immature, and non-specific responses, after training produced full-fledged response time-courses specific to the tactile-memory drawing task. The results reveal the operation of a rapid training-based plasticity mechanism that recruits the resources of V1 in the process of learning to draw. The learning paradigm allowed us to investigate for the first time the evolution of plastic re-assignment in V1 in a congenitally blind subject. These findings are consistent with a non-visual memory involvement of V1, and specifically imply that the observed cortical reorganization can be empowered by the process of learning to draw.

Dichoptic training in adults with amblyopia: Additional stereoacuity gains over monocular training.

PubMed

Liu, Xiang-Yun; Zhang, Jun-Yun

2017-08-04

Dichoptic training is a recent focus of research on perceptual learning in adults with amblyopia, but whether and how dichoptic training is superior to traditional monocular training is unclear. Here we investigated whether dichoptic training could further boost visual acuity and stereoacuity in monocularly well-trained adult amblyopic participants. During dichoptic training the participants used the amblyopic eye to practice a contrast discrimination task, while a band-filtered noise masker was simultaneously presented in the non-amblyopic fellow eye. Dichoptic learning was indexed by the increase of maximal tolerable noise contrast for successful contrast discrimination in the amblyopic eye. The results showed that practice tripled maximal tolerable noise contrast in 13 monocularly well-trained amblyopic participants. Moreover, the training further improved stereoacuity by 27% beyond the 55% gain from previous monocular training, but unchanged visual acuity of the amblyopic eyes. Therefore our dichoptic training method may produce extra gains of stereoacuity, but not visual acuity, in adults with amblyopia after monocular training. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visual Perceptual Echo Reflects Learning of Regularities in Rapid Luminance Sequences.

PubMed

Chang, Acer Y-C; Schwartzman, David J; VanRullen, Rufin; Kanai, Ryota; Seth, Anil K

2017-08-30

A novel neural signature of active visual processing has recently been described in the form of the "perceptual echo", in which the cross-correlation between a sequence of randomly fluctuating luminance values and occipital electrophysiological signals exhibits a long-lasting periodic (∼100 ms cycle) reverberation of the input stimulus (VanRullen and Macdonald, 2012). As yet, however, the mechanisms underlying the perceptual echo and its function remain unknown. Reasoning that natural visual signals often contain temporally predictable, though nonperiodic features, we hypothesized that the perceptual echo may reflect a periodic process associated with regularity learning. To test this hypothesis, we presented subjects with successive repetitions of a rapid nonperiodic luminance sequence, and examined the effects on the perceptual echo, finding that echo amplitude linearly increased with the number of presentations of a given luminance sequence. These data suggest that the perceptual echo reflects a neural signature of regularity learning.Furthermore, when a set of repeated sequences was followed by a sequence with inverted luminance polarities, the echo amplitude decreased to the same level evoked by a novel stimulus sequence. Crucially, when the original stimulus sequence was re-presented, the echo amplitude returned to a level consistent with the number of presentations of this sequence, indicating that the visual system retained sequence-specific information, for many seconds, even in the presence of intervening visual input. Altogether, our results reveal a previously undiscovered regularity learning mechanism within the human visual system, reflected by the perceptual echo. SIGNIFICANCE STATEMENT How the brain encodes and learns fast-changing but nonperiodic visual input remains unknown, even though such visual input characterizes natural scenes. We investigated whether the phenomenon of "perceptual echo" might index such learning. The perceptual echo is a long-lasting reverberation between a rapidly changing visual input and evoked neural activity, apparent in cross-correlations between occipital EEG and stimulus sequences, peaking in the alpha (∼10 Hz) range. We indeed found that perceptual echo is enhanced by repeatedly presenting the same visual sequence, indicating that the human visual system can rapidly and automatically learn regularities embedded within fast-changing dynamic sequences. These results point to a previously undiscovered regularity learning mechanism, operating at a rate defined by the alpha frequency. Copyright © 2017 the authors 0270-6474/17/378486-12$15.00/0.

Exploring MEDLINE Space with Random Indexing and Pathfinder Networks

PubMed Central

Cohen, Trevor

2008-01-01

The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search. PMID:18999236

Exploring MEDLINE space with random indexing and pathfinder networks.

PubMed

Cohen, Trevor

2008-11-06

The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search.

Effects of Multimodal Information on Learning Performance and Judgment of Learning

ERIC Educational Resources Information Center

Chen, Gongxiang; Fu, Xiaolan

2003-01-01

Two experiments were conducted to investigate the effects of multimodal information on learning performance and judgment of learning (JOL). Experiment 1 examined the effects of representation type (word-only versus word-plus-picture) and presentation channel (visual-only versus visual-plus-auditory) on recall and immediate-JOL in fixed-rate…

The Role of Visual Learning in Improving Students' High-Order Thinking Skills

ERIC Educational Resources Information Center

Raiyn, Jamal

2016-01-01

Various concepts have been introduced to improve students' analytical thinking skills based on problem based learning (PBL). This paper introduces a new concept to increase student's analytical thinking skills based on a visual learning strategy. Such a strategy has three fundamental components: a teacher, a student, and a learning process. The…

Promoting Positive Emotion in Multimedia Learning Using Visual Illustrations

ERIC Educational Resources Information Center

Park, Sanghoon; Lim, Jung

2007-01-01

The purpose of this paper was to explore the concept of interest, one of the critical positive emotions in learning contexts and to investigate the effects of different types of visual illustrations on learning interest, achievement, and motivation in multimedia learning. The concept of interest was explored in light of positive emotion; an…

Electrophysiological Evidence of Heterogeneity in Visual Statistical Learning in Young Children with ASD

ERIC Educational Resources Information Center

Jeste, Shafali S.; Kirkham, Natasha; Senturk, Damla; Hasenstab, Kyle; Sugar, Catherine; Kupelian, Chloe; Baker, Elizabeth; Sanders, Andrew J.; Shimizu, Christina; Norona, Amanda; Paparella, Tanya; Freeman, Stephanny F. N.; Johnson, Scott P.

2015-01-01

Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism…

Pre-Service Visual Art Teachers' Perceptions of Assessment in Online Learning

ERIC Educational Resources Information Center

Allen, Jeanne Maree; Wright, Suzie; Innes, Maureen

2014-01-01

This paper reports on a study conducted into how one cohort of Master of Teaching pre-service visual art teachers perceived their learning in a fully online learning environment. Located in an Australian urban university, this qualitative study provided insights into a number of areas associated with higher education online learning, including…

Gesture helps learners learn, but not merely by guiding their visual attention.

PubMed

Wakefield, Elizabeth; Novack, Miriam A; Congdon, Eliza L; Franconeri, Steven; Goldin-Meadow, Susan

2018-04-16

Teaching a new concept through gestures-hand movements that accompany speech-facilitates learning above-and-beyond instruction through speech alone (e.g., Singer & Goldin-Meadow, ). However, the mechanisms underlying this phenomenon are still under investigation. Here, we use eye tracking to explore one often proposed mechanism-gesture's ability to direct visual attention. Behaviorally, we replicate previous findings: Children perform significantly better on a posttest after learning through Speech+Gesture instruction than through Speech Alone instruction. Using eye tracking measures, we show that children who watch a math lesson with gesture do allocate their visual attention differently from children who watch a math lesson without gesture-they look more to the problem being explained, less to the instructor, and are more likely to synchronize their visual attention with information presented in the instructor's speech (i.e., follow along with speech) than children who watch the no-gesture lesson. The striking finding is that, even though these looking patterns positively predict learning outcomes, the patterns do not mediate the effects of training condition (Speech Alone vs. Speech+Gesture) on posttest success. We find instead a complex relation between gesture and visual attention in which gesture moderates the impact of visual looking patterns on learning-following along with speech predicts learning for children in the Speech+Gesture condition, but not for children in the Speech Alone condition. Gesture's beneficial effects on learning thus come not merely from its ability to guide visual attention, but also from its ability to synchronize with speech and affect what learners glean from that speech. © 2018 John Wiley & Sons Ltd.

Training haptic stiffness discrimination: time course of learning with or without visual information and knowledge of results.

PubMed

Teodorescu, Kinneret; Bouchigny, Sylvain; Korman, Maria

2013-08-01

In this study, we explored the time course of haptic stiffness discrimination learning and how it was affected by two experimental factors, the addition of visual information and/or knowledge of results (KR) during training. Stiffness perception may integrate both haptic and visual modalities. However, in many tasks, the visual field is typically occluded, forcing stiffness perception to be dependent exclusively on haptic information. No studies to date addressed the time course of haptic stiffness perceptual learning. Using a virtual environment (VE) haptic interface and a two-alternative forced-choice discrimination task, the haptic stiffness discrimination ability of 48 participants was tested across 2 days. Each day included two haptic test blocks separated by a training block Additional visual information and/or KR were manipulated between participants during training blocks. Practice repetitions alone induced significant improvement in haptic stiffness discrimination. Between days, accuracy was slightly improved, but decision time performance was deteriorated. The addition of visual information and/or KR had only temporary effects on decision time, without affecting the time course of haptic discrimination learning. Learning in haptic stiffness discrimination appears to evolve through at least two distinctive phases: A single training session resulted in both immediate and latent learning. This learning was not affected by the training manipulations inspected. Training skills in VE in spaced sessions can be beneficial for tasks in which haptic perception is critical, such as surgery procedures, when the visual field is occluded. However, training protocols for such tasks should account for low impact of multisensory information and KR.

Learning styles of medical students - implications in education.

PubMed

Buşan, Alina-Mihaela

2014-01-01

The term "learning style" refers to the fact that each person has a different way of accumulating knowledge. While some prefer listening to learn better, others need to write or they only need to read the text or see a picture to later remember. According to Fleming and Mills the learning styles can be classified in Visual, Auditory and Kinesthetic. There is no evidence that teaching according to the learning style can help a person, yet this cannot be ignored. In this study, a number of 230 medical students were questioned in order to determine their learning style. We determined that 73% of the students prefer one learning style, 22% prefer to learn using equally two learning style, while the rest prefer three learning styles. According to this study the distribution of the learning styles is as following: 33% visual, 26% auditory, 14% kinesthetic, 12% visual and auditory styles equally, 6% visual and kinesthetic, 4% auditory and kinesthetic and 5% all three styles. 32 % of the students that participated at this study are from UMF Craiova, 32% from UMF Carol Davila, 11% University of Medicine T Popa, Iasi, 9% UMF Cluj Iulius Hatieganu. The way medical students learn is different from the general population. This is why it is important when teaching to considerate how the students learn in order to facilitate the learning.

Building effective learning experiences around visualizations: NASA Eyes on the Solar System and Infiniscope

NASA Astrophysics Data System (ADS)

Tamer, A. J. J.; Anbar, A. D.; Elkins-Tanton, L. T.; Klug Boonstra, S.; Mead, C.; Swann, J. L.; Hunsley, D.

2017-12-01

Advances in scientific visualization and public access to data have transformed science outreach and communication, but have yet to realize their potential impacts in the realm of education. Computer-based learning is a clear bridge between visualization and education, but creating high-quality learning experiences that leverage existing visualizations requires close partnerships among scientists, technologists, and educators. The Infiniscope project is working to foster such partnerships in order to produce exploration-driven learning experiences around NASA SMD data and images, leveraging the principles of ETX (Education Through eXploration). The visualizations inspire curiosity, while the learning design promotes improved reasoning skills and increases understanding of space science concepts. Infiniscope includes both a web portal to host these digital learning experiences, as well as a teaching network of educators using and modifying these experiences. Our initial efforts to enable student discovery through active exploration of the concepts associated with Small Worlds, Kepler's Laws, and Exoplanets led us to develop our own visualizations at Arizona State University. Other projects focused on Astrobiology and Mars geology led us to incorporate an immersive Virtual Field Trip platform into the Infiniscope portal in support of virtual exploration of scientifically significant locations. Looking to apply ETX design practices with other visualizations, our team at Arizona State partnered with the Jet Propulsion Lab to integrate the web-based version of NASA Eyes on the Eclipse within Smart Sparrow's digital learning platform in a proof-of-concept focused on the 2017 Eclipse. This goes a step beyond the standard features of "Eyes" by wrapping guided exploration, focused on a specific learning goal into standards-aligned lesson built around the visualization, as well as its distribution through Infiniscope and it's digital teaching network. Experience from this development effort has laid the groundwork to explore future integrations with JPL and other NASA partners.

The influence of learning styles, enrollment status and gender on academic performance of optometry undergraduates.

PubMed

Prajapati, Bhavna; Dunne, Mark; Bartlett, Hannah; Cubbidge, Robert

2011-01-01

This cross-sectional study was designed to determine whether the academic performance of optometry undergraduates is influenced by enrollment status, learning style or gender. Three hundred and sixty undergraduates in all 3 years of the optometry degree course at Aston University during 2008-2009 were asked for their informed consent to participate in this study. Enrollment status was known from admissions records. An Index of Learning Styles (http://www4.nscu.edu/unity/lockers/users/f/felder/public/Learning-Styles.html) determined learning style preference with respect to four different learning style axes; active-reflective, sensing-intuitive, visual-verbal and sequential-global. The influence of these factors on academic performance was investigated. Two hundred and seventy students agreed to take part (75% of the cohort). 63% of the sample was female. There were 213 home non-graduates (entrants from the UK or European Union without a bachelor's degree or higher), 14 home graduates (entrants from the UK or European Union with a bachelor's degree or higher), 28 international non-graduates (entrants from outside the UK or European Union without a bachelor's degree or higher) and 15 international graduates (entrants from outside the UK or European Union with a bachelor's degree or higher). The majority of students were balanced learners (between 48% and 64% across four learning style axes). Any preferences were towards active, sensing, visual and sequential learning styles. Of the factors investigated in this study, learning styles were influenced by gender; females expressed a disproportionate preference for the reflective and visual learning styles. Academic performance was influenced by enrollment status; international graduates (95% confidence limits: 64-72%) outperformed all other student groups (home non graduates, 60-62%; international non graduates, 55-63%) apart from home graduates (57-69%). Our research has shown that the majority of optometry students have balanced learning styles and, from the factors studied, academic performance is only influenced by enrollment status. Although learning style questionnaires offer suggestions on how to improve learning efficacy, our findings indicate that current teaching methods do not need to be altered to suit varying learning style preferences as balanced learning styles can easily adapt to any teaching style (Learning Styles and Pedagogy in Post-16 Learning: A Systematic and Critical Review. London, UK: Learning and Skills Research Centre, 2004). © 2010 The College of Optometrists.

Visual Saliency Detection Based on Multiscale Deep CNN Features.

PubMed

Guanbin Li; Yizhou Yu

2016-11-01

Visual saliency is a fundamental problem in both cognitive and computational sciences, including computer vision. In this paper, we discover that a high-quality visual saliency model can be learned from multiscale features extracted using deep convolutional neural networks (CNNs), which have had many successes in visual recognition tasks. For learning such saliency models, we introduce a neural network architecture, which has fully connected layers on top of CNNs responsible for feature extraction at three different scales. The penultimate layer of our neural network has been confirmed to be a discriminative high-level feature vector for saliency detection, which we call deep contrast feature. To generate a more robust feature, we integrate handcrafted low-level features with our deep contrast feature. To promote further research and evaluation of visual saliency models, we also construct a new large database of 4447 challenging images and their pixelwise saliency annotations. Experimental results demonstrate that our proposed method is capable of achieving the state-of-the-art performance on all public benchmarks, improving the F-measure by 6.12% and 10%, respectively, on the DUT-OMRON data set and our new data set (HKU-IS), and lowering the mean absolute error by 9% and 35.3%, respectively, on these two data sets.

Effects of kinesthetic and cutaneous stimulation during the learning of a viscous force field.

PubMed

Rosati, Giulio; Oscari, Fabio; Pacchierotti, Claudio; Prattichizzo, Domenico

2014-01-01

Haptic stimulation can help humans learn perceptual motor skills, but the precise way in which it influences the learning process has not yet been clarified. This study investigates the role of the kinesthetic and cutaneous components of haptic feedback during the learning of a viscous curl field, taking also into account the influence of visual feedback. We present the results of an experiment in which 17 subjects were asked to make reaching movements while grasping a joystick and wearing a pair of cutaneous devices. Each device was able to provide cutaneous contact forces through a moving platform. The subjects received visual feedback about joystick's position. During the experiment, the system delivered a perturbation through (1) full haptic stimulation, (2) kinesthetic stimulation alone, (3) cutaneous stimulation alone, (4) altered visual feedback, or (5) altered visual feedback plus cutaneous stimulation. Conditions 1, 2, and 3 were also tested with the cancellation of the visual feedback of position error. Results indicate that kinesthetic stimuli played a primary role during motor adaptation to the viscous field, which is a fundamental premise to motor learning and rehabilitation. On the other hand, cutaneous stimulation alone appeared not to bring significant direct or adaptation effects, although it helped in reducing direct effects when used in addition to kinesthetic stimulation. The experimental conditions with visual cancellation of position error showed slower adaptation rates, indicating that visual feedback actively contributes to the formation of internal models. However, modest learning effects were detected when the visual information was used to render the viscous field.

Anodal tDCS to V1 blocks visual perceptual learning consolidation.

PubMed

Peters, Megan A K; Thompson, Benjamin; Merabet, Lotfi B; Wu, Allan D; Shams, Ladan

2013-06-01

This study examined the effects of visual cortex transcranial direct current stimulation (tDCS) on visual processing and learning. Participants performed a contrast detection task on two consecutive days. Each session consisted of a baseline measurement followed by measurements made during active or sham stimulation. On the first day, one group received anodal stimulation to primary visual cortex (V1), while another received cathodal stimulation. Stimulation polarity was reversed for these groups on the second day. The third (control) group of subjects received sham stimulation on both days. No improvements or decrements in contrast sensitivity relative to the same-day baseline were observed during real tDCS, nor was any within-session learning trend observed. However, task performance improved significantly from Day 1 to Day 2 for the participants who received cathodal tDCS on Day 1 and for the sham group. No such improvement was found for the participants who received anodal stimulation on Day 1, indicating that anodal tDCS blocked overnight consolidation of visual learning, perhaps through engagement of inhibitory homeostatic plasticity mechanisms or alteration of the signal-to-noise ratio within stimulated cortex. These results show that applying tDCS to the visual cortex can modify consolidation of visual learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Soaring with Science.

ERIC Educational Resources Information Center

Tamarkin, Cali; Bourne, Barbara

1995-01-01

Presents an integrated unit on aerodynamics for a diverse group of 4th grade students. Students work with readily available, inexpensive materials to devise methods to answer questions about aerodynamics. High-interest activities include balloon rocketry and paper-airplane design and address visual, auditory, and kinesthetic learning styles. The…

Sounds and Sense-Abilities: Science for All

ERIC Educational Resources Information Center

Plourde, Lee A.; Klemm, E. Barbara

2004-01-01

Activities-oriented instruction offers multi modal opportunities for learning science. How do college students in elementary pre-service teacher preparation programs describe science lab activities in terms of visual, kinesthetic, auditory and motor characteristics? Research with elementary science methods students shows that the Levels of…

The Challenges of Educating the Visually Impaired and Quality Assurance in Tertiary Institutions of Learning in Nigeria

ERIC Educational Resources Information Center

Omede, Andrew A.

2015-01-01

This paper focused on the challenges in educating the visually impaired and modalities for ensuring quality assurance in tertiary institutions of learning in Nigeria. It examined the global challenges in the higher educational system and made it clear that the visually impaired are those with visual problems be it partial, low vision, or total…

Treatment of amblyopia in the adult: insights from a new rodent model of visual perceptual learning.

PubMed

Bonaccorsi, Joyce; Berardi, Nicoletta; Sale, Alessandro

2014-01-01

Amblyopia is the most common form of impairment of visual function affecting one eye, with a prevalence of about 1-5% of the total world population. Amblyopia usually derives from conditions of early functional imbalance between the two eyes, owing to anisometropia, strabismus, or congenital cataract, and results in a pronounced reduction of visual acuity and severe deficits in contrast sensitivity and stereopsis. It is widely accepted that, due to a lack of sufficient plasticity in the adult brain, amblyopia becomes untreatable after the closure of the critical period in the primary visual cortex. However, recent results obtained both in animal models and in clinical trials have challenged this view, unmasking a previously unsuspected potential for promoting recovery even in adulthood. In this context, non invasive procedures based on visual perceptual learning, i.e., the improvement in visual performance on a variety of simple visual tasks following practice, emerge as particularly promising to rescue discrimination abilities in adult amblyopic subjects. This review will survey recent work regarding the impact of visual perceptual learning on amblyopia, with a special focus on a new experimental model of perceptual learning in the amblyopic rat.

Treatment of amblyopia in the adult: insights from a new rodent model of visual perceptual learning

PubMed Central

Bonaccorsi, Joyce; Berardi, Nicoletta; Sale, Alessandro

2014-01-01

Amblyopia is the most common form of impairment of visual function affecting one eye, with a prevalence of about 1–5% of the total world population. Amblyopia usually derives from conditions of early functional imbalance between the two eyes, owing to anisometropia, strabismus, or congenital cataract, and results in a pronounced reduction of visual acuity and severe deficits in contrast sensitivity and stereopsis. It is widely accepted that, due to a lack of sufficient plasticity in the adult brain, amblyopia becomes untreatable after the closure of the critical period in the primary visual cortex. However, recent results obtained both in animal models and in clinical trials have challenged this view, unmasking a previously unsuspected potential for promoting recovery even in adulthood. In this context, non invasive procedures based on visual perceptual learning, i.e., the improvement in visual performance on a variety of simple visual tasks following practice, emerge as particularly promising to rescue discrimination abilities in adult amblyopic subjects. This review will survey recent work regarding the impact of visual perceptual learning on amblyopia, with a special focus on a new experimental model of perceptual learning in the amblyopic rat. PMID:25076874

Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop.

PubMed

Legg, Philip A; Chung, David H S; Parry, Matthew L; Bown, Rhodri; Jones, Mark W; Griffiths, Iwan W; Chen, Min

2013-12-01

Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there may be a lack of suitable training data, and the search requirements of the user may frequently change for different tasks. In this work, we develop a visual analytics systems that overcomes the shortcomings of the traditional approach. We make use of a sketch-based interface to enable users to specify search requirement in a flexible manner without depending on semantic annotation. We employ active machine learning to train different analytical models for different types of search requirements. We use visualization to facilitate knowledge discovery at the different stages of visual analytics. This includes visualizing the parameter space of the trained model, visualizing the search space to support interactive browsing, visualizing candidature search results to support rapid interaction for active learning while minimizing watching videos, and visualizing aggregated information of the search results. We demonstrate the system for searching spatiotemporal attributes from sports video to identify key instances of the team and player performance.

Bioorthogonal Metabolic Labeling of Nascent RNA in Neurons Improves the Sensitivity of Transcriptome-Wide Profiling.

PubMed

Zajaczkowski, Esmi L; Zhao, Qiong-Yi; Zhang, Zong Hong; Li, Xiang; Wei, Wei; Marshall, Paul R; Leighton, Laura J; Nainar, Sarah; Feng, Chao; Spitale, Robert C; Bredy, Timothy W

2018-06-15

Transcriptome-wide expression profiling of neurons has provided important insights into the underlying molecular mechanisms and gene expression patterns that transpire during learning and memory formation. However, there is a paucity of tools for profiling stimulus-induced RNA within specific neuronal cell populations. A bioorthogonal method to chemically label nascent (i.e., newly transcribed) RNA in a cell-type-specific and temporally controlled manner, which is also amenable to bioconjugation via click chemistry, was recently developed and optimized within conventional immortalized cell lines. However, its value within a more fragile and complicated cellular system such as neurons, as well as for transcriptome-wide expression profiling, has yet to be demonstrated. Here, we report the visualization and sequencing of activity-dependent nascent RNA derived from neurons using this labeling method. This work has important implications for improving transcriptome-wide expression profiling and visualization of nascent RNA in neurons, which has the potential to provide valuable insights into the mechanisms underlying neural plasticity, learning, and memory.

Two Trees: Migrating Fault Trees to Decision Trees for Real Time Fault Detection on International Space Station

NASA Technical Reports Server (NTRS)

Lee, Charles; Alena, Richard L.; Robinson, Peter

2004-01-01

We started from ISS fault trees example to migrate to decision trees, presented a method to convert fault trees to decision trees. The method shows that the visualizations of root cause of fault are easier and the tree manipulating becomes more programmatic via available decision tree programs. The visualization of decision trees for the diagnostic shows a format of straight forward and easy understands. For ISS real time fault diagnostic, the status of the systems could be shown by mining the signals through the trees and see where it stops at. The other advantage to use decision trees is that the trees can learn the fault patterns and predict the future fault from the historic data. The learning is not only on the static data sets but also can be online, through accumulating the real time data sets, the decision trees can gain and store faults patterns in the trees and recognize them when they come.

Learning Science Through Visualization

NASA Technical Reports Server (NTRS)

Chaudhury, S. Raj

2005-01-01

In the context of an introductory physical science course for non-science majors, I have been trying to understand how scientific visualizations of natural phenomena can constructively impact student learning. I have also necessarily been concerned with the instructional and assessment approaches that need to be considered when focusing on learning science through visually rich information sources. The overall project can be broken down into three distinct segments : (i) comparing students' abilities to demonstrate proportional reasoning competency on visual and verbal tasks (ii) decoding and deconstructing visualizations of an object falling under gravity (iii) the role of directed instruction to elicit alternate, valid scientific visualizations of the structure of the solar system. Evidence of student learning was collected in multiple forms for this project - quantitative analysis of student performance on written, graded assessments (tests and quizzes); qualitative analysis of videos of student 'think aloud' sessions. The results indicate that there are significant barriers for non-science majors to succeed in mastering the content of science courses, but with informed approaches to instruction and assessment, these barriers can be overcome.

Neuromorphic audio-visual sensor fusion on a sound-localizing robot.

PubMed

Chan, Vincent Yue-Sek; Jin, Craig T; van Schaik, André

2012-01-01

This paper presents the first robotic system featuring audio-visual (AV) sensor fusion with neuromorphic sensors. We combine a pair of silicon cochleae and a silicon retina on a robotic platform to allow the robot to learn sound localization through self motion and visual feedback, using an adaptive ITD-based sound localization algorithm. After training, the robot can localize sound sources (white or pink noise) in a reverberant environment with an RMS error of 4-5° in azimuth. We also investigate the AV source binding problem and an experiment is conducted to test the effectiveness of matching an audio event with a corresponding visual event based on their onset time. Despite the simplicity of this method and a large number of false visual events in the background, a correct match can be made 75% of the time during the experiment.

Functional Contour-following via Haptic Perception and Reinforcement Learning.

PubMed

Hellman, Randall B; Tekin, Cem; van der Schaar, Mihaela; Santos, Veronica J

2018-01-01

Many tasks involve the fine manipulation of objects despite limited visual feedback. In such scenarios, tactile and proprioceptive feedback can be leveraged for task completion. We present an approach for real-time haptic perception and decision-making for a haptics-driven, functional contour-following task: the closure of a ziplock bag. This task is challenging for robots because the bag is deformable, transparent, and visually occluded by artificial fingertip sensors that are also compliant. A deep neural net classifier was trained to estimate the state of a zipper within a robot's pinch grasp. A Contextual Multi-Armed Bandit (C-MAB) reinforcement learning algorithm was implemented to maximize cumulative rewards by balancing exploration versus exploitation of the state-action space. The C-MAB learner outperformed a benchmark Q-learner by more efficiently exploring the state-action space while learning a hard-to-code task. The learned C-MAB policy was tested with novel ziplock bag scenarios and contours (wire, rope). Importantly, this work contributes to the development of reinforcement learning approaches that account for limited resources such as hardware life and researcher time. As robots are used to perform complex, physically interactive tasks in unstructured or unmodeled environments, it becomes important to develop methods that enable efficient and effective learning with physical testbeds.

Effects of Image-Based and Text-Based Active Learning Exercises on Student Examination Performance in a Musculoskeletal Anatomy Course

ERIC Educational Resources Information Center

Gross, M. Melissa; Wright, Mary C.; Anderson, Olivia S.

2017-01-01

Research on the benefits of visual learning has relied primarily on lecture-based pedagogy, but the potential benefits of combining active learning strategies with visual and verbal materials on learning anatomy has not yet been explored. In this study, the differential effects of text-based and image-based active learning exercises on examination…

Training for cervical cancer prevention programs in low-resource settings: focus on visual inspection with acetic acid and cryotherapy.

PubMed

Blumenthal, P D; Lauterbach, M; Sellors, J W; Sankaranarayanan, R

2005-05-01

The modern approach to cervical cancer prevention, characterized by use of cytology and multiple visits for diagnosis and treatment, has frequently proven challenging and unworkable in low-resource settings. Because of this, the Alliance for Cervical Cancer Prevention (ACCP) has made it a priority to investigate and assess alternative approaches, particularly the use of visual screening methods, such as visual inspection with acetic acid (VIA) and visual inspection with Lugol's iodine (VILI), for precancer and cancer detection and the use of cryotherapy as a precancer treatment method. As a result of ACCP experience in providing training to nurses and doctors in these techniques, it is now widely agreed that training should be competency based, combining both didactic and hands-on approaches, and should be done in a clinical setting that resembles the service-delivery conditions at the program site. This article reviews ACCP experiences and perceptions about the essentials of training in visual inspection and cryotherapy and presents some lessons learned with regard to training in these techniques in low-resource settings.

Implementation of ICARE learning model using visualization animation on biotechnology course

NASA Astrophysics Data System (ADS)

Hidayat, Habibi

2017-12-01

ICARE is a learning model that directly ensure the students to actively participate in the learning process using animation media visualization. ICARE have five key elements of learning experience from children and adult that is introduction, connection, application, reflection and extension. The use of Icare system to ensure that participants have opportunity to apply what have been they learned. So that, the message delivered by lecture to students can be understood and recorded by students in a long time. Learning model that was deemed capable of improving learning outcomes and interest to learn in following learning process Biotechnology with applying the ICARE learning model using visualization animation. This learning model have been giving motivation to participate in the learning process and learning outcomes obtained becomes more increased than before. From the results of student learning in subjects Biotechnology by applying the ICARE learning model using Visualization Animation can improving study results of student from the average value of middle test amounted to 70.98 with the percentage of 75% increased value of final test to be 71.57 with the percentage of 68.63%. The interest to learn from students more increasing visits of student activities at each cycle, namely the first cycle obtained average value by 33.5 with enough category. The second cycle is obtained an average value of 36.5 to good category and third cycle the average value of 36.5 with a student activity to good category.

Estimating the implicit component of visuomotor rotation learning by constraining movement preparation time.

PubMed

Leow, Li-Ann; Gunn, Reece; Marinovic, Welber; Carroll, Timothy J

2017-08-01

When sensory feedback is perturbed, accurate movement is restored by a combination of implicit processes and deliberate reaiming to strategically compensate for errors. Here, we directly compare two methods used previously to dissociate implicit from explicit learning on a trial-by-trial basis: 1 ) asking participants to report the direction that they aim their movements, and contrasting this with the directions of the target and the movement that they actually produce, and 2 ) manipulating movement preparation time. By instructing participants to reaim without a sensory perturbation, we show that reaiming is possible even with the shortest possible preparation times, particularly when targets are narrowly distributed. Nonetheless, reaiming is effortful and comes at the cost of increased variability, so we tested whether constraining preparation time is sufficient to suppress strategic reaiming during adaptation to visuomotor rotation with a broad target distribution. The rate and extent of error reduction under preparation time constraints were similar to estimates of implicit learning obtained from self-report without time pressure, suggesting that participants chose not to apply a reaiming strategy to correct visual errors under time pressure. Surprisingly, participants who reported aiming directions showed less implicit learning according to an alternative measure, obtained during trials performed without visual feedback. This suggests that the process of reporting can affect the extent or persistence of implicit learning. The data extend existing evidence that restricting preparation time can suppress explicit reaiming and provide an estimate of implicit visuomotor rotation learning that does not require participants to report their aiming directions. NEW & NOTEWORTHY During sensorimotor adaptation, implicit error-driven learning can be isolated from explicit strategy-driven reaiming by subtracting self-reported aiming directions from movement directions, or by restricting movement preparation time. Here, we compared the two methods. Restricting preparation times did not eliminate reaiming but was sufficient to suppress reaiming during adaptation with widely distributed targets. The self-report method produced a discrepancy in implicit learning estimated by subtracting aiming directions and implicit learning measured in no-feedback trials. Copyright © 2017 the American Physiological Society.

Visual learning with reduced adaptation is eccentricity-specific.

PubMed

Harris, Hila; Sagi, Dov

2018-01-12

Visual learning is known to be specific to the trained target location, showing little transfer to untrained locations. Recently, learning was shown to transfer across equal-eccentricity retinal-locations when sensory adaptation due to repetitive stimulation was minimized. It was suggested that learning transfers to previously untrained locations when the learned representation is location invariant, with sensory adaptation introducing location-dependent representations, thus preventing transfer. Spatial invariance may also fail when the trained and tested locations are at different distance from the center of gaze (different retinal eccentricities), due to differences in the corresponding low-level cortical representations (e.g. allocated cortical area decreases with eccentricity). Thus, if learning improves performance by better classifying target-dependent early visual representations, generalization is predicted to fail when locations of different retinal eccentricities are trained and tested in the absence sensory adaptation. Here, using the texture discrimination task, we show specificity of learning across different retinal eccentricities (4-8°) using reduced adaptation training. The existence of generalization across equal-eccentricity locations but not across different eccentricities demonstrates that learning accesses visual representations preceding location independent representations, with specificity of learning explained by inhomogeneous sensory representation.

Sighted and visually impaired students’ perspectives of illustrations, diagrams and drawings in school science

PubMed Central

McDonald, Celia; Rodrigues, Susan

2016-01-01

Background: In this paper we report on the views of students with and without visual impairments on the use of illustrations, diagrams and drawings (IDD) in science lessons. Method: Our findings are based on data gathered through a brief questionnaire completed by a convenience sample of students prior to trialling new resource material. The questionnaire sought to understand the students’ views about using IDD in science lessons. The classes involved in the study included one class from a primary school, five classes from a secondary school and one class from a school for visually impaired students. Results: Approximately 20% of the participants thought that the diagrams were boring and just under half (48%) of the total sample (regardless of whether they were sighted or visually impaired) did not think diagrams were easy to use. Only 14% of the participants felt that repeated encounters with the same diagrams made the diagrams easy to understand. Unlike sighted students who can ‘flit’ across diagrams, a visually impaired student may only see or touch a small part of the diagram at a time so for them ‘fliting’ could result in loss of orientation with the diagram. Conclusions: Treating sighted and visually impaired pupils equally is different to treating them identically. Sighted students incidentally learn how to interpret visual information from a young age. Students who acquire sight loss need to learn the different rules associated with reading tactile diagrams, or large print and those who are congenitally blind do not have visual memories to rely upon. PMID:27918598

Learned face-voice pairings facilitate visual search.

PubMed

Zweig, L Jacob; Suzuki, Satoru; Grabowecky, Marcia

2015-04-01

Voices provide a rich source of information that is important for identifying individuals and for social interaction. During search for a face in a crowd, voices often accompany visual information, and they facilitate localization of the sought-after individual. However, it is unclear whether this facilitation occurs primarily because the voice cues the location of the face or because it also increases the salience of the associated face. Here we demonstrate that a voice that provides no location information nonetheless facilitates visual search for an associated face. We trained novel face-voice associations and verified learning using a two-alternative forced choice task in which participants had to correctly match a presented voice to the associated face. Following training, participants searched for a previously learned target face among other faces while hearing one of the following sounds (localized at the center of the display): a congruent learned voice, an incongruent but familiar voice, an unlearned and unfamiliar voice, or a time-reversed voice. Only the congruent learned voice speeded visual search for the associated face. This result suggests that voices facilitate the visual detection of associated faces, potentially by increasing their visual salience, and that the underlying crossmodal associations can be established through brief training.

The primate amygdala represents the positive and negative value of visual stimuli during learning

PubMed Central

Paton, Joseph J.; Belova, Marina A.; Morrison, Sara E.; Salzman, C. Daniel

2008-01-01

Visual stimuli can acquire positive or negative value through their association with rewards and punishments, a process called reinforcement learning. Although we now know a great deal about how the brain analyses visual information, we know little about how visual representations become linked with values. To study this process, we turned to the amygdala, a brain structure implicated in reinforcement learning1–5. We recorded the activity of individual amygdala neurons in monkeys while abstract images acquired either positive or negative value through conditioning. After monkeys had learned the initial associations, we reversed image value assignments. We examined neural responses in relation to these reversals in order to estimate the relative contribution to neural activity of the sensory properties of images and their conditioned values. Here we show that changes in the values of images modulate neural activity, and that this modulation occurs rapidly enough to account for, and correlates with, monkeys’ learning. Furthermore, distinct populations of neurons encode the positive and negative values of visual stimuli. Behavioural and physiological responses to visual stimuli may therefore be based in part on the plastic representation of value provided by the amygdala. PMID:16482160

Perceptual learning and adult cortical plasticity.

PubMed

Gilbert, Charles D; Li, Wu; Piech, Valentin

2009-06-15

The visual cortex retains the capacity for experience-dependent changes, or plasticity, of cortical function and cortical circuitry, throughout life. These changes constitute the mechanism of perceptual learning in normal visual experience and in recovery of function after CNS damage. Such plasticity can be seen at multiple stages in the visual pathway, including primary visual cortex. The manifestation of the functional changes associated with perceptual learning involve both long term modification of cortical circuits during the course of learning, and short term dynamics in the functional properties of cortical neurons. These dynamics are subject to top-down influences of attention, expectation and perceptual task. As a consequence, each cortical area is an adaptive processor, altering its function in accordance to immediate perceptual demands.

Learning from Balance Sheet Visualization

ERIC Educational Resources Information Center

Tanlamai, Uthai; Soongswang, Oranuj

2011-01-01

This exploratory study examines alternative visuals and their effect on the level of learning of balance sheet users. Executive and regular classes of graduate students majoring in information technology in business were asked to evaluate the extent of acceptance and enhanced capability of these alternative visuals toward their learning…

The Effects of Verbal Elaboration and Visual Elaboration on Student Learning.

ERIC Educational Resources Information Center

Chanlin, Lih-Juan

1997-01-01

This study examined: (1) the effectiveness of integrating verbal elaboration (metaphors) and different visual presentation strategies (still and animated graphics) in learning biotechnology concepts; (2) whether the use of verbal elaboration with different visual presentation strategies facilitates cognitive processes; and (3) how students employ…

Using a Teaching Intervention and Calibrated Peer Review™ Diagnostics to Improve Visual Communication Skills.

PubMed

Saterbak, Ann; Moturu, Anoosha; Volz, Tracy

2018-03-01

Rice University's bioengineering department incorporates written, oral, and visual communication instruction into its undergraduate curriculum to aid student learning and to prepare students to communicate their knowledge and discoveries precisely and persuasively. In a tissue culture lab course, we used a self- and peer-review tool called Calibrated Peer Review™ (CPR) to diagnose student learning gaps in visual communication skills on a poster assignment. We then designed an active learning intervention that required students to practice the visual communication skills that needed improvement and used CPR to measure the changes. After the intervention, we observed that students performed significantly better in their ability to develop high quality graphs and tables that represent experimental data. Based on these outcomes, we conclude that guided task practice, collaborative learning, and calibrated peer review can be used to improve engineering students' visual communication skills.

Posttraining transcranial magnetic stimulation of striate cortex disrupts consolidation early in visual skill learning.

PubMed

De Weerd, Peter; Reithler, Joel; van de Ven, Vincent; Been, Marin; Jacobs, Christianne; Sack, Alexander T

2012-02-08

Practice-induced improvements in skilled performance reflect "offline " consolidation processes extending beyond daily training sessions. According to visual learning theories, an early, fast learning phase driven by high-level areas is followed by a late, asymptotic learning phase driven by low-level, retinotopic areas when higher resolution is required. Thus, low-level areas would not contribute to learning and offline consolidation until late learning. Recent studies have challenged this notion, demonstrating modified responses to trained stimuli in primary visual cortex (V1) and offline activity after very limited training. However, the behavioral relevance of modified V1 activity for offline consolidation of visual skill memory in V1 after early training sessions remains unclear. Here, we used neuronavigated transcranial magnetic stimulation (TMS) directed to a trained retinotopic V1 location to test for behaviorally relevant consolidation in human low-level visual cortex. Applying TMS to the trained V1 location within 45 min of the first or second training session strongly interfered with learning, as measured by impaired performance the next day. The interference was conditional on task context and occurred only when training in the location targeted by TMS was followed by training in a second location before TMS. In this condition, high-level areas may become coupled to the second location and uncoupled from the previously trained low-level representation, thereby rendering consolidation vulnerable to interference. Our data show that, during the earliest phases of skill learning in the lowest-level visual areas, a behaviorally relevant form of consolidation exists of which the robustness is controlled by high-level, contextual factors.

Learning by E-Learning for Visually Impaired Students: Opportunities or Again Marginalisation?

ERIC Educational Resources Information Center

Kharade, Kalpana; Peese, Hema

2012-01-01

In recent years, e-learning has become a valuable tool for an increasing number of visually impaired (VI) learners. The benefits of this technology include: (1) remote learning for VI students; (2) the possibility for teachers living far from schools or universities to provide remote instructional assistance to VI students; and (3) continuing…

Tracing Trajectories of Audio-Visual Learning in the Infant Brain

ERIC Educational Resources Information Center

Kersey, Alyssa J.; Emberson, Lauren L.

2017-01-01

Although infants begin learning about their environment before they are born, little is known about how the infant brain changes during learning. Here, we take the initial steps in documenting how the neural responses in the brain change as infants learn to associate audio and visual stimuli. Using functional near-infrared spectroscopy (fNRIS) to…

Visual and Auditory Learning Processes in Normal Children and Children with Specific Learning Disabilities. Final Report.

ERIC Educational Resources Information Center

McGrady, Harold J.; Olson, Don A.

To describe and compare the psychosensory functioning of normal children and children with specific learning disabilities, 62 learning disabled and 68 normal children were studied. Each child was given a battery of thirteen subtests on an automated psychosensory system representing various combinations of auditory and visual intra- and…

Teachers' Reasoning: Classroom Visual Representational Practices in the Context of Introductory Chemical Bonding

ERIC Educational Resources Information Center

Patron, Emelie; Wikman, Susanne; Edfors, Inger; Johansson-Cederblad, Brita; Linder, Cedric

2017-01-01

Visual representations are essential for communication and meaning-making in chemistry, and thus the representational practices play a vital role in the teaching and learning of chemistry. One powerful contemporary model of classroom learning, the variation theory of learning, posits that the way an object of learning gets handled is another vital…

Exploring Antecedents of Performance Differences on Visual and Verbal Test Items: Learning Styles versus Aptitude

ERIC Educational Resources Information Center

Bacon, Donald R.; Hartley, Steven W.

2015-01-01

Many educators and researchers have suggested that some students learn more effectively with visual stimuli (e.g., pictures, graphs), whereas others learn more effectively with verbal information (e.g., text) (Felder & Brent, 2005). In two studies, the present research seeks to improve popular self-reported (indirect) learning style measures…

Mobile Learning and the Visual Web, Oh My! Nutrition Education in the 21st Century

ERIC Educational Resources Information Center

Schuster, Ellen

2012-01-01

Technology is rapidly changing how our program participants learn in school and for their personal improvement. Extension educators who deliver nutrition program will want to be aware of the technology trends that are driving these changes. Blended learning, mobile learning, the visual Web, and the gamification of health are approaches to consider…

Reduction in the retinotopic early visual cortex with normal aging and magnitude of perceptual learning.

PubMed

Chang, Li-Hung; Yotsumoto, Yuko; Salat, David H; Andersen, George J; Watanabe, Takeo; Sasaki, Yuka

2015-01-01

Although normal aging is known to reduce cortical structures globally, the effects of aging on local structures and functions of early visual cortex are less understood. Here, using standard retinotopic mapping and magnetic resonance imaging morphologic analyses, we investigated whether aging affects areal size of the early visual cortex, which were retinotopically localized, and whether those morphologic measures were associated with individual performance on visual perceptual learning. First, significant age-associated reduction was found in the areal size of V1, V2, and V3. Second, individual ability of visual perceptual learning was significantly correlated with areal size of V3 in older adults. These results demonstrate that aging changes local structures of the early visual cortex, and the degree of change may be associated with individual visual plasticity. Copyright © 2015 Elsevier Inc. All rights reserved.

Chinese children's early knowledge about writing.

PubMed

Zhang, Lan; Yin, Li; Treiman, Rebecca

2017-09-01

Much research on literacy development has focused on learners of alphabetic writing systems. Researchers have hypothesized that children learn about the formal characteristics of writing before they learn about the relations between units of writing and units of speech. We tested this hypothesis by examining young Chinese children's understanding of writing. Mandarin-speaking 2- to 5-year-olds completed a graphic task, which tapped their knowledge about the formal characteristics of writing, and a phonological task, which tapped their knowledge about the correspondence between Chinese characters and syllables. The 3- to 5-year-olds performed better on the graphic task than the phonological task, indicating that learning how writing appears visually begins earlier than learning that writing corresponds to linguistic units, even in a writing system in which written units correspond to syllables. Statement of contribution What is already known on this subject? Learning about writing's visual form, how it looks, is an important part of emergent literacy. Knowledge of how writing symbolizes linguistic units may emerge later. What does this study add? We test the hypothesis that Chinese children learn about writing's visual form earlier than its symbolic nature. Chinese 3- to 5- year-olds know more about visual features than character-syllable links. Results show learning of the visual appearance of a notation system is developmentally precocious. © 2016 The British Psychological Society.

Imprinting modulates processing of visual information in the visual wulst of chicks.

PubMed

Maekawa, Fumihiko; Komine, Okiru; Sato, Katsushige; Kanamatsu, Tomoyuki; Uchimura, Motoaki; Tanaka, Kohichi; Ohki-Hamazaki, Hiroko

2006-11-14

Imprinting behavior is one form of learning and memory in precocial birds. With the aim of elucidating of the neural basis for visual imprinting, we focused on visual information processing. A lesion in the visual wulst, which is similar functionally to the mammalian visual cortex, caused anterograde amnesia in visual imprinting behavior. Since the color of an object was one of the important cues for imprinting, we investigated color information processing in the visual wulst. Intrinsic optical signals from the visual wulst were detected in the early posthatch period and the peak regions of responses to red, green, and blue were spatially organized from the caudal to the nasal regions in dark-reared chicks. This spatial representation of color recognition showed plastic changes, and the response pattern along the antero-posterior axis of the visual wulst altered according to the color the chick was imprinted to. These results indicate that the thalamofugal pathway is critical for learning the imprinting stimulus and that the visual wulst shows learning-related plasticity and may relay processed visual information to indicate the color of the imprint stimulus to the memory storage region, e.g., the intermediate medial mesopallium.

Imprinting modulates processing of visual information in the visual wulst of chicks

PubMed Central

Maekawa, Fumihiko; Komine, Okiru; Sato, Katsushige; Kanamatsu, Tomoyuki; Uchimura, Motoaki; Tanaka, Kohichi; Ohki-Hamazaki, Hiroko

2006-01-01

Background Imprinting behavior is one form of learning and memory in precocial birds. With the aim of elucidating of the neural basis for visual imprinting, we focused on visual information processing. Results A lesion in the visual wulst, which is similar functionally to the mammalian visual cortex, caused anterograde amnesia in visual imprinting behavior. Since the color of an object was one of the important cues for imprinting, we investigated color information processing in the visual wulst. Intrinsic optical signals from the visual wulst were detected in the early posthatch period and the peak regions of responses to red, green, and blue were spatially organized from the caudal to the nasal regions in dark-reared chicks. This spatial representation of color recognition showed plastic changes, and the response pattern along the antero-posterior axis of the visual wulst altered according to the color the chick was imprinted to. Conclusion These results indicate that the thalamofugal pathway is critical for learning the imprinting stimulus and that the visual wulst shows learning-related plasticity and may relay processed visual information to indicate the color of the imprint stimulus to the memory storage region, e.g., the intermediate medial mesopallium. PMID:17101060

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

Differentiating Visual from Response Sequencing during Long-term Skill Learning.

PubMed

Lynch, Brighid; Beukema, Patrick; Verstynen, Timothy

2017-01-01

The dual-system model of sequence learning posits that during early learning there is an advantage for encoding sequences in sensory frames; however, it remains unclear whether this advantage extends to long-term consolidation. Using the serial RT task, we set out to distinguish the dynamics of learning sequential orders of visual cues from learning sequential responses. On each day, most participants learned a new mapping between a set of symbolic cues and responses made with one of four fingers, after which they were exposed to trial blocks of either randomly ordered cues or deterministic ordered cues (12-item sequence). Participants were randomly assigned to one of four groups (n = 15 per group): Visual sequences (same sequence of visual cues across training days), Response sequences (same order of key presses across training days), Combined (same serial order of cues and responses on all training days), and a Control group (a novel sequence each training day). Across 5 days of training, sequence-specific measures of response speed and accuracy improved faster in the Visual group than any of the other three groups, despite no group differences in explicit awareness of the sequence. The two groups that were exposed to the same visual sequence across days showed a marginal improvement in response binding that was not found in the other groups. These results indicate that there is an advantage, in terms of rate of consolidation across multiple days of training, for learning sequences of actions in a sensory representational space, rather than as motoric representations.

The Relationship among Beginning and Advanced American Sign Language Students and Credentialed Interpreters across Two Domains of Visual Imagery: Vividness and Manipulation

ERIC Educational Resources Information Center

Stauffer, Linda K.

2010-01-01

Given the visual-gestural nature of ASL it is reasonable to assume that visualization abilities may be one predictor of aptitude for learning ASL. This study tested a hypothesis that visualization abilities are a foundational aptitude for learning a signed language and that measurements of these skills will increase as students progress from…

An Issue of Learning: The Effect of Visual Split Attention in Classes for Deaf and Hard of Hearing Students

ERIC Educational Resources Information Center

Mather, Susan M.; Clark, M. Diane

2012-01-01

One of the ongoing challenges teachers of students who are deaf or hard of hearing face is managing the visual split attention implicit in multimedia learning. When a teacher presents various types of visual information at the same time, visual learners have no choice but to divide their attention among those materials and the teacher and…

Mayday - integrative analytics for expression data

PubMed Central

2010-01-01

Background DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files. Results We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved. Conclusions We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org. PMID:20214778

Basic Visual Processes and Learning Disability.

ERIC Educational Resources Information Center

Leisman, Gerald

Representatives of a variety of disciplines concerned with either clinical or research problems in vision and learning disabilities present reviews and reports of relevant research and clinical approaches. Contributions are organized into four broad sections: basic processes, specific disorders, diagnosis of visually based problems in learning,…

Exploring Visuospatial Thinking in Chemistry Learning

ERIC Educational Resources Information Center

Wu, Hsin-Kai; Shah, Priti

2004-01-01

In this article, we examine the role of visuospatial cognition in chemistry learning. We review three related kinds of literature: correlational studies of spatial abilities and chemistry learning, students' conceptual errors and difficulties understanding visual representations, and visualization tools that have been designed to help overcome…

The effect of haptic guidance and visual feedback on learning a complex tennis task.

PubMed

Marchal-Crespo, Laura; van Raai, Mark; Rauter, Georg; Wolf, Peter; Riener, Robert

2013-11-01

While haptic guidance can improve ongoing performance of a motor task, several studies have found that it ultimately impairs motor learning. However, some recent studies suggest that the haptic demonstration of optimal timing, rather than movement magnitude, enhances learning in subjects trained with haptic guidance. Timing of an action plays a crucial role in the proper accomplishment of many motor skills, such as hitting a moving object (discrete timing task) or learning a velocity profile (time-critical tracking task). The aim of the present study is to evaluate which feedback conditions-visual or haptic guidance-optimize learning of the discrete and continuous elements of a timing task. The experiment consisted in performing a fast tennis forehand stroke in a virtual environment. A tendon-based parallel robot connected to the end of a racket was used to apply haptic guidance during training. In two different experiments, we evaluated which feedback condition was more adequate for learning: (1) a time-dependent discrete task-learning to start a tennis stroke and (2) a tracking task-learning to follow a velocity profile. The effect that the task difficulty and subject's initial skill level have on the selection of the optimal training condition was further evaluated. Results showed that the training condition that maximizes learning of the discrete time-dependent motor task depends on the subjects' initial skill level. Haptic guidance was especially suitable for less-skilled subjects and in especially difficult discrete tasks, while visual feedback seems to benefit more skilled subjects. Additionally, haptic guidance seemed to promote learning in a time-critical tracking task, while visual feedback tended to deteriorate the performance independently of the task difficulty and subjects' initial skill level. Haptic guidance outperformed visual feedback, although additional studies are needed to further analyze the effect of other types of feedback visualization on motor learning of time-critical tasks.

Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

PubMed

Ngo, Tuan Anh; Lu, Zhi; Carneiro, Gustavo

2017-01-01

We introduce a new methodology that combines deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance (MR) data. This combination is relevant for segmentation problems, where the visual object of interest presents large shape and appearance variations, but the annotated training set is small, which is the case for various medical image analysis applications, including the one considered in this paper. In particular, level set methods are based on shape and appearance terms that use small training sets, but present limitations for modelling the visual object variations. Deep learning methods can model such variations using relatively small amounts of annotated training, but they often need to be regularised to produce good generalisation. Therefore, the combination of these methods brings together the advantages of both approaches, producing a methodology that needs small training sets and produces accurate segmentation results. We test our methodology on the MICCAI 2009 left ventricle segmentation challenge database (containing 15 sequences for training, 15 for validation and 15 for testing), where our approach achieves the most accurate results in the semi-automated problem and state-of-the-art results for the fully automated challenge. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Curriculum for Young Deaf Children.

ERIC Educational Resources Information Center

Restaino, Lillian C. R.; And Others

Presented is a curriculum designed to provide the teacher of the young deaf child with learning disabilities with a description of developmental objectives and methods for fulfilling these objectives in the areas of gross motor development, sensory motor integration, visual analysis, attention and memory, and conceptualization. The objectives are…

Measuring Quadriceps strength in adults with severe or moderate intellectual and visual disabilities: Feasibility and reliability.

PubMed

Dijkhuizen, Annemarie; Douma, Rob K; Krijnen, Wim P; van der Schans, Cees P; Waninge, Aly

2018-05-30

A feasible and reliable instrument to measure strength in persons with severe intellectual and visual disabilities (SIVD) is lacking. The aim of our study was to determine feasibility, learning period and reliability of three strength tests. Twenty-nine participants with SIVD performed the Minimum Sit-to-Stand Height test (MSST), the Leg Extension test (LE) and the 30 seconds Chair-Stand test (30sCS), once per week for 5 weeks. Feasibility was determined by the percentage of successful measurements; learning effect by using paired t test between two consecutive measurements; test-retest reliability by intraclass correlation coefficient and Limits of Agreement and, correlations by Pearson correlations. A sufficient feasibility and learning period of the tests was shown. The methods had sufficient test-retest reliability and moderate-to-sufficient correlations. The MSST, the LE, and the 30sCS are feasible tests for measuring muscle strength in persons with SIVD, having sufficient test re-test reliability. © 2018 John Wiley & Sons Ltd.

Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications.

PubMed

Vieira, Sandra; Pinaya, Walter H L; Mechelli, Andrea

2017-03-01

Deep learning (DL) is a family of machine learning methods that has gained considerable attention in the scientific community, breaking benchmark records in areas such as speech and visual recognition. DL differs from conventional machine learning methods by virtue of its ability to learn the optimal representation from the raw data through consecutive nonlinear transformations, achieving increasingly higher levels of abstraction and complexity. Given its ability to detect abstract and complex patterns, DL has been applied in neuroimaging studies of psychiatric and neurological disorders, which are characterised by subtle and diffuse alterations. Here we introduce the underlying concepts of DL and review studies that have used this approach to classify brain-based disorders. The results of these studies indicate that DL could be a powerful tool in the current search for biomarkers of psychiatric and neurologic disease. We conclude our review by discussing the main promises and challenges of using DL to elucidate brain-based disorders, as well as possible directions for future research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Visual Cues, Verbal Cues and Child Development

ERIC Educational Resources Information Center

Valentini, Nadia

2004-01-01

In this article, the author discusses two strategies--visual cues (modeling) and verbal cues (short, accurate phrases) which are related to teaching motor skills in maximizing learning in physical education classes. Both visual and verbal cues are strong influences in facilitating and promoting day-to-day learning. Both strategies reinforce…

Learning from Chemical Visualizations: Comparing Generation and Selection

ERIC Educational Resources Information Center

Zhang, Zhihui Helen; Linn, Marcia C.

2013-01-01

Dynamic visualizations can make unseen phenomena such as chemical reactions visible but students need guidance to benefit from them. This study explores the value of generating drawings versus selecting among alternatives to guide students to learn chemical reactions from a dynamic visualization of hydrogen combustion as part of an online inquiry…

Contextual Cueing: Implicit Learning and Memory of Visual Context Guides Spatial Attention.

ERIC Educational Resources Information Center

Chun, Marvin M.; Jiang, Yuhong

1998-01-01

Six experiments involving a total of 112 college students demonstrate that a robust memory for visual context exists to guide spatial attention. Results show how implicit learning and memory of visual context can guide spatial attention toward task-relevant aspects of a scene. (SLD)

Construction of a VISUAL (VIdeo-SUpported Active Learning) Resource.

ERIC Educational Resources Information Center

Nicolson, Roderick I.; And Others

1994-01-01

Discussion of interactive video for educational purposes focuses on the development of a video-supported active learning (VISUAL) resource on voice disorders that used digitized video and an Apple Macintosh computer. User evaluations are reported, and potential applications for VISUAL resources are suggested. (Contains five references.) (LRW)

Attentional Modulation in Visual Cortex Is Modified during Perceptual Learning

ERIC Educational Resources Information Center

Bartolucci, Marco; Smith, Andrew T.

2011-01-01

Practicing a visual task commonly results in improved performance. Often the improvement does not transfer well to a new retinal location, suggesting that it is mediated by changes occurring in early visual cortex, and indeed neuroimaging and neurophysiological studies both demonstrate that perceptual learning is associated with altered activity…

A description of the verbal behavior of students during two reading instruction methods

PubMed Central

Daly, Patricia M.

1987-01-01

The responses of students during two reading methods, the language experience approach and two Mastery Learning programs, were analyzed using verbal operants. A description of student responding was generated for these methods. The purpose of the study was to answer the questions: What are the major controlling variables determining student reading behavior during the language experience approach and two Mastery Learning programs, and how do these controlling variables change across story reading sessions and across stories in the first method? Student responses by verbal operant were compared for both reading methods. Findings indicated higher frequencies of textual operants occurred in responses during the Mastery Learning programs. A greater reliance on intraverbal control was evident in responses during the language experience approach. It is suggested that students who can generate strong intraverbal responses and who may have visual discrimination problems during early reading instruction may benefit from use of the language experience approach at this stage. ImagesFigure 2Figure 3 PMID:22477535