Commercial Foods and Culinary Arts. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains one module for completing a course in commercial foods and culinary arts. It is designed especially for use in secondary schools in Palm Beach County, Florida. The module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities keyed to resources, information…

Machine Shop. Student Learning Guide.

ERIC Educational Resources Information Center

Palm Beach County Board of Public Instruction, West Palm Beach, FL.

This student learning guide contains eight modules for completing a course in machine shop. It is designed especially for use in Palm Beach County, Florida. Each module covers one task, and consists of a purpose, performance objective, enabling objectives, learning activities and resources, information sheets, student self-check with answer key,…

Quality Assurance for Digital Learning Object Repositories: Issues for the Metadata Creation Process

ERIC Educational Resources Information Center

Currier, Sarah; Barton, Jane; O'Beirne, Ronan; Ryan, Ben

2004-01-01

Metadata enables users to find the resources they require, therefore it is an important component of any digital learning object repository. Much work has already been done within the learning technology community to assure metadata quality, focused on the development of metadata standards, specifications and vocabularies and their implementation…

Does Artificial Tutoring Foster Inquiry Based Learning?

ERIC Educational Resources Information Center

Schmoelz, Alexander; Swertz, Christian; Forstner, Alexandra; Barberi, Alessandro

2014-01-01

This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based…

Building High Performance Learning: A Focus on Career Results and the Bottom Line.

ERIC Educational Resources Information Center

Ingram, Hadyn; Sandelands, Eric; Teare, Richard

2001-01-01

Discusses how action learning can be targeted to business objectives and how electronically enabled action learning can increase productivity. Provides examples of personal learning aligned with organizational goals, including a certificate of management studies course, prior learning experiences, and an advanced diploma in virtual learning. (SK)

Spatial Object Recognition Enables Endogenous LTD that Curtails LTP in the Mouse Hippocampus

PubMed Central

Goh, Jinzhong Jeremy

2013-01-01

Although synaptic plasticity is believed to comprise the cellular substrate for learning and memory, limited direct evidence exists that hippocampus-dependent learning actually triggers synaptic plasticity. It is likely, however, that long-term potentiation (LTP) works in concert with its counterpart, long-term depression (LTD) in the creation of spatial memory. It has been reported in rats that weak synaptic plasticity is facilitated into persistent plasticity if afferent stimulation is coupled with a novel spatial learning event. It is not known if this phenomenon also occurs in other species. We recorded from the hippocampal CA1 of freely behaving mice and observed that novel spatial learning triggers endogenous LTD. Specifically, we observed that LTD is enabled when test-pulse afferent stimulation is given during the learning of object constellations or during a spatial object recognition task. Intriguingly, LTP is significantly impaired by the same tasks, suggesting that LTD is the main cellular substrate for this type of learning. These data indicate that learning-facilitated plasticity is not exclusive to rats and that spatial learning leads to endogenous LTD in the hippocampus, suggesting an important role for this type of synaptic plasticity in the creation of hippocampus-dependent memory. PMID:22510536

Undergraduate College Students, Laptop Computers, and Lifelong Learning

ERIC Educational Resources Information Center

Tan, Chong Leng; Morris, John S.

2006-01-01

Many universities and colleges list the development of lifelong learning skills as a curriculum objective and have adopted laptop programs that may enable lifelong learning. The purpose of this research is to address the effectiveness of a technology-based and computer-mediated learning environment in achieving lifelong learning skills from the…

Pre-Service Elementary School Teachers' Ability to Account for the Operation of Simple Physical Systems Using the Energy Conservation Law

ERIC Educational Resources Information Center

Papadouris, Nicos; Hadjigeorgiou, Angela; Constantinou, Constantinos P.

2014-01-01

Energy is recognized as a core idea in science and, hence, a significant learning objective of science education. The effective promotion of this learning objective posits that teachers themselves possess sound conceptual understanding. This is needed for enabling them to organize effective learning environments for their students. In this study,…

Digital Rights Management Implemented by RDF Graph Approach

ERIC Educational Resources Information Center

Yang, Jin Tan; Horng, Huai-Chien

2006-01-01

This paper proposes a design framework for constructing Digital Rights Management (DRM) that enables learning objects in legal usage. The central theme of this framework is that any design of a DRM must have theories as foundations to make the maintenance, extension or interoperability easy. While a learning objective consists of learning…

Teaching/Learning Guide: Level I.

ERIC Educational Resources Information Center

Carbon - Lehigh Intermediate Unit, Schnecksville, PA.

The manual presents sequences of skills designed for use as guides to teaching/learning objectives and as a basis for evaluating and recording special education students' progress. It is explained that the goal of the first level of objectives (sequenced in this document) is to enable the student to function at a motor/psychomotor state of…

Ontology-Based Annotation of Learning Object Content

ERIC Educational Resources Information Center

Gasevic, Dragan; Jovanovic, Jelena; Devedzic, Vladan

2007-01-01

The paper proposes a framework for building ontology-aware learning object (LO) content. Previously ontologies were exclusively employed for enriching LOs' metadata. Although such an approach is useful, as it improves retrieval of relevant LOs from LO repositories, it does not enable one to reuse components of a LO, nor to incorporate an explicit…

Participatory Learning in Residential Weekends: Benefit or Barrier to Learning for the International Student?

ERIC Educational Resources Information Center

Robson, Fiona; Forster, Gillian; Powell, Lynne

2016-01-01

The context for this research is a residential learning weekend which is embedded into all postgraduate programmes at Newcastle Business School via a management development module entitled "Developing Self". The objective of this study was to identify and explore how participatory learning in multicultural groups enables international…

Using Dual Eye-Tracking Measures to Differentiate between Collaboration on Procedural and Conceptual Learning Activities

ERIC Educational Resources Information Center

Belenky, Daniel; Ringenberg, Michael; Olsen, Jennifer; Aleven, Vincent; Rummel, Nikol

2013-01-01

Dual eye-tracking measures enable novel ways to test predictions about collaborative learning. For example, the research project we are engaging in uses measures of gaze recurrence to help understand how collaboration may differ when students are completing various learning activities focused on different learning objectives. Specifically, we…

Distributed learning or medical tourism? A Canadian residency program's experience in global health.

PubMed

Kelly, Kate; McCarthy, Anne; McLean, Laurie

2015-01-01

Global health experiences (GHEs) are becoming increasingly prevalent in surgical residency education. Although it may seem intuitive that participation in GHEs develops CanMEDS competencies, this has not been studied in depth in surgery. The purpose of this study is (1) to explore if and how otolaryngology-head and neck surgery (OHNS) resident participation in GHEs facilitates the development of CanMEDS competencies and (2) to develop an OHNS GHE tool to facilitate the integration of CanMEDS into GHE participation and evaluation. An online survey explored the GHEs of current and past OHNS residents in Canada. Based on the data collected and a literature review, a foundational tool was then created to (1) enable OHNS residents to structure their GHEs into CanMEDS-related learning objectives and (2) enable OHNS program directors to more effectively evaluate residents' GHEs with respect to CanMEDS competencies. Participants' GHEs varied widely. These experiences often contributed informally to the development of several CanMEDS competencies. However, few residents had concrete objectives, rarely were CanMEDS roles clearly incorporated, and most residents were not formally evaluated during their experience. Residents felt they achieved greater learning when predeparture objectives and postexperience reflections were integrated into their GHEs. Although GHEs vary widely, they can serve as valuable forums for developing CanMEDS competencies among participating residents. Without clear objectives that adhere to the CanMEDS framework or formal assessment methods however, residents in GHEs risk becoming medical tourists. The use of an objective and evaluation tool may facilitate the creation of predeparture learning objectives, encourage self-reflection on their GHE, and better enable program directors to evaluate residents participating in GHEs. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Computer-Assisted Language Learning (CALL) in Support of (Re)-Learning Native Languages: The Case of Runyakitara

ERIC Educational Resources Information Center

Katushemererwe, Fridah; Nerbonne, John

2015-01-01

This study presents the results from a computer-assisted language learning (CALL) system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue deficiencies to enhance their knowledge of grammar and acquire writing skills in Runyakitara. The system…

Where’s Waldo? How perceptual, cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene

PubMed Central

Chang, Hung-Cheng; Grossberg, Stephen; Cao, Yongqiang

2014-01-01

The Where’s Waldo problem concerns how individuals can rapidly learn to search a scene to detect, attend, recognize, and look at a valued target object in it. This article develops the ARTSCAN Search neural model to clarify how brain mechanisms across the What and Where cortical streams are coordinated to solve the Where’s Waldo problem. The What stream learns positionally-invariant object representations, whereas the Where stream controls positionally-selective spatial and action representations. The model overcomes deficiencies of these computationally complementary properties through What and Where stream interactions. Where stream processes of spatial attention and predictive eye movement control modulate What stream processes whereby multiple view- and positionally-specific object categories are learned and associatively linked to view- and positionally-invariant object categories through bottom-up and attentive top-down interactions. Gain fields control the coordinate transformations that enable spatial attention and predictive eye movements to carry out this role. What stream cognitive-emotional learning processes enable the focusing of motivated attention upon the invariant object categories of desired objects. What stream cognitive names or motivational drives can prime a view- and positionally-invariant object category of a desired target object. A volitional signal can convert these primes into top-down activations that can, in turn, prime What stream view- and positionally-specific categories. When it also receives bottom-up activation from a target, such a positionally-specific category can cause an attentional shift in the Where stream to the positional representation of the target, and an eye movement can then be elicited to foveate it. These processes describe interactions among brain regions that include visual cortex, parietal cortex, inferotemporal cortex, prefrontal cortex (PFC), amygdala, basal ganglia (BG), and superior colliculus (SC). PMID:24987339

"Notice of Violation of IEEE Publication Principles" Multiobjective Reinforcement Learning: A Comprehensive Overview.

PubMed

Liu, Chunming; Xu, Xin; Hu, Dewen

2013-04-29

Reinforcement learning is a powerful mechanism for enabling agents to learn in an unknown environment, and most reinforcement learning algorithms aim to maximize some numerical value, which represents only one long-term objective. However, multiple long-term objectives are exhibited in many real-world decision and control problems; therefore, recently, there has been growing interest in solving multiobjective reinforcement learning (MORL) problems with multiple conflicting objectives. The aim of this paper is to present a comprehensive overview of MORL. In this paper, the basic architecture, research topics, and naive solutions of MORL are introduced at first. Then, several representative MORL approaches and some important directions of recent research are reviewed. The relationships between MORL and other related research are also discussed, which include multiobjective optimization, hierarchical reinforcement learning, and multi-agent reinforcement learning. Finally, research challenges and open problems of MORL techniques are highlighted.

Toward Self-Referential Autonomous Learning of Object and Situation Models.

PubMed

Damerow, Florian; Knoblauch, Andreas; Körner, Ursula; Eggert, Julian; Körner, Edgar

2016-01-01

Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach.

Using Voice Boards: Pedagogical Design, Technological Implementation, Evaluation and Reflections

ERIC Educational Resources Information Center

Yaneske, Elisabeth; Oates, Briony

2011-01-01

We present a case study to evaluate the use of a Wimba Voice Board to support asynchronous audio discussion. We discuss the learning strategy and pedagogic rationale when a Voice Board was implemented within an MA module for language learners, enabling students to create learning objects and facilitating peer-to-peer learning. Previously students…

Using Voice Boards: Pedagogical Design, Technological Implementation, Evaluation and Reflections

ERIC Educational Resources Information Center

Yaneske, Elisabeth; Oates, Briony

2010-01-01

We present a case study to evaluate the use of a Wimba Voice Board to support asynchronous audio discussion. We discuss the learning strategy and pedagogic rationale when a Voice Board was implemented within an MA module for language learners, enabling students to create learning objects and facilitating peer-to-peer learning. Previously students…

Development of a short-form Learning Organization Survey: the LOS-27.

PubMed

Singer, Sara J; Moore, Scott C; Meterko, Mark; Williams, Sandra

2012-08-01

Despite urgent need for innovation, adaptation, and change in health care, few tools enable researchers or practitioners to assess the extent to which health care facilities perform as learning organizations or the effects of initiatives that require learning. This study's objective was to develop and test a short-form Learning Organization Survey to fill this gap. The authors applied exploratory factor analysis and confirmatory factor analysis to data from Veterans Health Administration personnel to derive a short-form survey and then conducted further confirmatory factor analysis and factor invariance testing on additional Veterans Health Administration data to evaluate the short form. Results suggest that a 27-item, 7-factor survey (2 environmental factors, 1 on leadership, and 4 on concrete learning processes and practices) reliably measures key features of organizational learning, allowing researchers to evaluate theoretical propositions about organizational learning, its antecedents, and outcomes and enabling managers to assess and enhance organizations' learning capabilities and performance.

Learning the 3-D structure of objects from 2-D views depends on shape, not format

PubMed Central

Tian, Moqian; Yamins, Daniel; Grill-Spector, Kalanit

2016-01-01

Humans can learn to recognize new objects just from observing example views. However, it is unknown what structural information enables this learning. To address this question, we manipulated the amount of structural information given to subjects during unsupervised learning by varying the format of the trained views. We then tested how format affected participants' ability to discriminate similar objects across views that were rotated 90° apart. We found that, after training, participants' performance increased and generalized to new views in the same format. Surprisingly, the improvement was similar across line drawings, shape from shading, and shape from shading + stereo even though the latter two formats provide richer depth information compared to line drawings. In contrast, participants' improvement was significantly lower when training used silhouettes, suggesting that silhouettes do not have enough information to generate a robust 3-D structure. To test whether the learned object representations were format-specific or format-invariant, we examined if learning novel objects from example views transfers across formats. We found that learning objects from example line drawings transferred to shape from shading and vice versa. These results have important implications for theories of object recognition because they suggest that (a) learning the 3-D structure of objects does not require rich structural cues during training as long as shape information of internal and external features is provided and (b) learning generates shape-based object representations independent of the training format. PMID:27153196

The Implementation of Medical Informatics in the National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM).

PubMed

Behrends, Marianne; Steffens, Sandra; Marschollek, Michael

2017-01-01

The National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) describes medical skills and attitudes without being ordered by subjects or organs. Thus, the NKLM enables systematic curriculum mapping and supports curricular transparency. In this paper we describe where learning objectives related to Medical Informatics (MI) in Hannover coincide with other subjects and where they are taught exclusively in MI. An instance of the web-based MERLIN-database was used for the mapping process. In total 52 learning objectives overlapping with 38 other subjects could be allocated to MI. No overlap exists for six learning objectives describing explicitly topics of information technology or data management for scientific research. Most of the overlap was found for learning objectives relating to documentation and aspects of data privacy. The identification of numerous shared learning objectives with other subjects does not mean that other subjects teach the same content as MI. Identifying common learning objectives rather opens up the possibility for teaching cooperations which could lead to an important exchange and hopefully an improvement in medical education. Mapping of a whole medical curriculum offers the opportunity to identify common ground between MI and other medical subjects. Furthermore, in regard to MI, the interaction with other medical subjects can strengthen its role in medical education.

Boundary Interaction: Towards Developing a Mobile Technology-Enabled Science Curriculum to Integrate Learning in the Informal Spaces

ERIC Educational Resources Information Center

Sun, Daner; Looi, Chee-Kit

2018-01-01

This paper explores the crossover between formal learning and learning in informal spaces supported by mobile technology, and proposes design principles for educators to carry out a science curriculum, namely Boundary Activity-based Science Curriculum (BAbSC). The conceptualization of the boundary object, and the principles of boundary activity as…

An innovative approach to developing the reflective skills of medical students

PubMed Central

Henderson, Penny; Johnson, Martin H

2002-01-01

Background Development of the reflective skills of medical students is an acknowledged objective of medical education. Description Description of an educational exercise which uses an email-based process for developing the reflective skills of undergraduate medical students. Student quotations illustrate learning outcomes qualitatively. Discussion The process described is immediate, direct, linked to learning objectives, enables rapid responses to be given to the students individually, and is followed by group sharing of learning. It provides a rigorous and robust feedback loop for students. It is relatively economic for teachers and incidentally benefits curriculum design and evolution. The approach supports development of a reflective approach to learning. PMID:12003640

Journal Writing and Learning: Reading between the Structural, Holistic, and Post-Structural Lines.

ERIC Educational Resources Information Center

Mannion, Greg

2001-01-01

Structural approaches to journal writing enable learners to manage subjectivity while seeking "objective truth." Holistic approaches attempt to synthesize ways of learning, giving a false sense of completion and inclusion. Poststructuralism places journal text in the context of discourses; through reflection and deconstruction, the…

Designing an Educator Toolkit for the Mobile Learning Age

ERIC Educational Resources Information Center

Burden, Kevin; Kearney, Matthew

2018-01-01

Mobile technologies have been described as 'boundary' objects which enable teachers and learners to transcend many of the barriers such as rigid schedules and spaces which have hitherto characterised traditional forms of education. However, educators need to better understand how to design learning scenarios which genuinely exploit the unique…

Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

PubMed Central

Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

2014-01-01

The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations. PMID:25538637

Representing Energy. II. Energy Tracking Representations

ERIC Educational Resources Information Center

Scherr, Rachel E.; Close, Hunter G.; Close, Eleanor W.; Vokos, Stamatis

2012-01-01

The Energy Project at Seattle Pacific University has developed representations that embody the substance metaphor and support learners in conserving and tracking energy as it flows from object to object and changes form. Such representations enable detailed modeling of energy dynamics in complex physical processes. We assess student learning by…

Algorithm Building and Learning Programming Languages Using a New Educational Paradigm

NASA Astrophysics Data System (ADS)

Jain, Anshul K.; Singhal, Manik; Gupta, Manu Sheel

2011-08-01

This research paper presents a new concept of using a single tool to associate syntax of various programming languages, algorithms and basic coding techniques. A simple framework has been programmed in Python that helps students learn skills to develop algorithms, and implement them in various programming languages. The tool provides an innovative and a unified graphical user interface for development of multimedia objects, educational games and applications. It also aids collaborative learning amongst students and teachers through an integrated mechanism based on Remote Procedure Calls. The paper also elucidates an innovative method for code generation to enable students to learn the basics of programming languages using drag-n-drop methods for image objects.

Exploring educational needs and design aspects of internet-enabled patient education for persons with diabetes: a qualitative interview study

PubMed Central

Jafari, Javad; Karimi Moonaghi, Hosein; Zary, Nabil; Masiello, Italo

2016-01-01

Objective The objective of this article is to explore the educational needs and design aspects of personalised internet-enabled education for patients with diabetes in Iran. Design Data were collected using semistructured interviews and then qualitatively analysed using inductive content analysis. Participants 9 patients with type 2 diabetes were included. Inclusion criteria were access to and knowledge on how to use the internet. The selection ensured representation based on gender, age, occupation and educational background. Setting The sample population was patients with diabetes who were admitted to an outpatient diabetes clinic in Mashhad, a large city of Iran with about 3 million inhabitants. Results 4 core categories emerged from the data: (1) seeking knowledge about diabetes, including specific knowledge acquisition, patient's interactions and learning requirements; (2) teaching and learning, including using different teaching methods and different ways to learn about the disease; (3) facilitators, including internet and mobile phone use to learn about the disease; and (4) barriers, including lack of internet access, uncertainty of access to the internet and lack of website in the local language and also perceived cultural barriers, such as patients' fears of the internet, lack of time and awareness. Conclusions This study provides a better understanding of the patient's educational expectations and technical needs in relation to internet-enabled education. This knowledge will inform the development of functional mock-ups in the next research phase using a design-based research approach in order to design internet-enabled patient education for self-management of diabetes. PMID:27799245

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

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

Leading the Charge for SoTL--Embracing Collaboration

ERIC Educational Resources Information Center

Cassard, Anita; Sloboda, Brian

2014-01-01

The scholarship of teaching and learning (SoTL) enables colleges and universities to assess student learning and measure the outcomes by engaging in meaningful research, and to disseminate this research. The objective of this paper is to give a snapshot of and assess the current thinking behind this scholarship by presenting examples of SoTL, and…

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%.

Assuring the Quality of Agricultural Learning Repositories: Issues for the Learning Object Metadata Creation Process of the CGIAR

NASA Astrophysics Data System (ADS)

Zschocke, Thomas; Beniest, Jan

The Consultative Group on International Agricultural Re- search (CGIAR) has established a digital repository to share its teaching and learning resources along with descriptive educational information based on the IEEE Learning Object Metadata (LOM) standard. As a critical component of any digital repository, quality metadata are critical not only to enable users to find more easily the resources they require, but also for the operation and interoperability of the repository itself. Studies show that repositories have difficulties in obtaining good quality metadata from their contributors, especially when this process involves many different stakeholders as is the case with the CGIAR as an international organization. To address this issue the CGIAR began investigating the Open ECBCheck as well as the ISO/IEC 19796-1 standard to establish quality protocols for its training. The paper highlights the implications and challenges posed by strengthening the metadata creation workflow for disseminating learning objects of the CGIAR.

Learning Activity Packets for High School Social Studies, American Studies, American History and Low Achieving Students. Course I.

ERIC Educational Resources Information Center

Seif, Elliott

The document presents student learning packets designed to provide an alternative social studies experience for high school students. The objective is to enable students to better understand themselves and their environment and other individuals and groups. Written at a junior high school reading level, the packets are intended to be used with low…

Supporting Self-Improvement in Teaching, Literacy, Language and Numeracy. Tools for Staff Development. Module 4: Teaching and Learning Approaches

ERIC Educational Resources Information Center

Basic Skills Agency, 2007

2007-01-01

This module provides teachers with practical tools to improve the quality of teaching and learning activities and enable learners to achieve their objectives in literacy, language and numeracy. Unit 1 explores approaches that are particularly appropriate to adult learners, developing thinking skills and involving them in decision making and…

Evolving autonomous learning in cognitive networks.

PubMed

Sheneman, Leigh; Hintze, Arend

2017-12-01

There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. These methods have been previously combined, particularly in artificial neural networks using an external objective feedback mechanism. We adapt this approach to Markov Brains, which are evolvable networks of probabilistic and deterministic logic gates. Prior to this work MB could only adapt from one generation to the other, so we introduce feedback gates which augment their ability to learn during their lifetime. We show that Markov Brains can incorporate these feedback gates in such a way that they do not rely on an external objective feedback signal, but instead can generate internal feedback that is then used to learn. This results in a more biologically accurate model of the evolution of learning, which will enable us to study the interplay between evolution and learning and could be another step towards autonomously learning machines.

Incrementally learning objects by touch: online discriminative and generative models for tactile-based recognition.

PubMed

Soh, Harold; Demiris, Yiannis

2014-01-01

Human beings not only possess the remarkable ability to distinguish objects through tactile feedback but are further able to improve upon recognition competence through experience. In this work, we explore tactile-based object recognition with learners capable of incremental learning. Using the sparse online infinite Echo-State Gaussian process (OIESGP), we propose and compare two novel discriminative and generative tactile learners that produce probability distributions over objects during object grasping/palpation. To enable iterative improvement, our online methods incorporate training samples as they become available. We also describe incremental unsupervised learning mechanisms, based on novelty scores and extreme value theory, when teacher labels are not available. We present experimental results for both supervised and unsupervised learning tasks using the iCub humanoid, with tactile sensors on its five-fingered anthropomorphic hand, and 10 different object classes. Our classifiers perform comparably to state-of-the-art methods (C4.5 and SVM classifiers) and findings indicate that tactile signals are highly relevant for making accurate object classifications. We also show that accurate "early" classifications are possible using only 20-30 percent of the grasp sequence. For unsupervised learning, our methods generate high quality clusterings relative to the widely-used sequential k-means and self-organising map (SOM), and we present analyses into the differences between the approaches.

Endogenous hippocampal LTD that is enabled by spatial object recognition requires activation of NMDA receptors and the metabotropic glutamate receptor, mGlu5.

PubMed

Goh, Jinzhong Jeremy; Manahan-Vaughan, Denise

2013-02-01

Learning-facilitated synaptic plasticity describes the ability of hippocampal synapses to respond with persistent plasticity to afferent stimulation when coupled with a spatial learning event, whereby the afferent stimulation normally produces short-term plasticity or no change in synaptic strength if given in the absence of novel learning. Recently, it was reported that in the mouse hippocampus intrinsic long-term depression (LTD > 24 h) occurs when test-pulse afferent stimulation is coupled with a novel spatial learning. It is not known to what extent this phenomenon shares molecular properties with synaptic plasticity that is typically induced by means of patterned electrical afferent stimulation. In previous work, we showed that a novel spatial object recognition task facilitates LTD at the Schaffer collateral-CA1 synapse of freely behaving adult mice, whereas reexposure to the familiar spatial configuration ∼24 h later elicited no such facilitation. Here we report that treatment with the NMDA receptor antagonist, (±)-3-(2-Carboxypiperazin-4-yl)-propanephosphonic acid (CPP), or antagonism of metabotropic glutamate (mGlu) receptor, mGlu5, using 2-methyl-6-(phenylethynyl) pyridine (MPEP), completely prevented LTD under the novel learning conditions. Behavioral assessment during re-exposure after application of the antagonists revealed that the animals did not remember the object during novel exposure and treated them as if they were novel. Under these circumstances, where the acquisition of novel spatial information was involved, LTD was facilitated. Our data support that the endogenous LTD that is enabled through novel spatial learning in adult mice is critically dependent on the activation of both the NMDA receptors and mGlu5. Copyright © 2012 Wiley Periodicals, Inc.

NASA SMD STEM Activation: Enabling NASA Science Experts and Content into the Learning Environment

NASA Astrophysics Data System (ADS)

Hasan, Hashima; Erickson, Kristen

2018-01-01

The NASA Science Mission Directorate (SMD) restructured its efforts to enhance learning in science, technology, engineering, and mathematics (STEM) content areas through a cooperative agreement notice issued in 2015. This effort resulted in the competitive selection of 27 organizations to implement a strategic approach that leverages SMD’s unique assets. Three of these are exclusively directed towards Astrophysics. These unique assets include SMD’s science and engineering content and Science Discipline Subject Matter Experts. Awardees began their work during 2016 and span all areas of Earth and space science and the audiences NASA SMD intends to reach. The goal of the restructured STEM Activation program is to further enable NASA science experts and content into the learning environment more effectively and efficiently with learners of all ages. The objectives are to enable STEM education, improve US scientific literacy, advance national educational goals, and leverage efforts through partnerships. This presentation will provide an overview of the NASA SMD STEM Activation landscape and its commitment to meeting user needs.

Object Design: Twelve Concepts to Know, Understand and Apply

ERIC Educational Resources Information Center

Marschalek, Douglas G.

2005-01-01

Some art teachers say that art is all around us when they actually mean that "design" is all around us. The everyday objects we view, purchase, and use are designed. Some are well designed, others are poorly designed, and many are in-between. Teachers need to develop learning strategies that enable their students to understand how design is part…

A Theory of How Columns in the Neocortex Enable Learning the Structure of the World

PubMed Central

Hawkins, Jeff; Ahmad, Subutai; Cui, Yuwei

2017-01-01

Neocortical regions are organized into columns and layers. Connections between layers run mostly perpendicular to the surface suggesting a columnar functional organization. Some layers have long-range excitatory lateral connections suggesting interactions between columns. Similar patterns of connectivity exist in all regions but their exact role remain a mystery. In this paper, we propose a network model composed of columns and layers that performs robust object learning and recognition. Each column integrates its changing input over time to learn complete predictive models of observed objects. Excitatory lateral connections across columns allow the network to more rapidly infer objects based on the partial knowledge of adjacent columns. Because columns integrate input over time and space, the network learns models of complex objects that extend well beyond the receptive field of individual cells. Our network model introduces a new feature to cortical columns. We propose that a representation of location relative to the object being sensed is calculated within the sub-granular layers of each column. The location signal is provided as an input to the network, where it is combined with sensory data. Our model contains two layers and one or more columns. Simulations show that using Hebbian-like learning rules small single-column networks can learn to recognize hundreds of objects, with each object containing tens of features. Multi-column networks recognize objects with significantly fewer movements of the sensory receptors. Given the ubiquity of columnar and laminar connectivity patterns throughout the neocortex, we propose that columns and regions have more powerful recognition and modeling capabilities than previously assumed. PMID:29118696

Team-Based Learning in US Colleges and Schools of Pharmacy

PubMed Central

Copeland, Jeffrey; Franks, Andrea S.; Karimi, Reza; McCollum, Marianne; Riese, David J.; Lin, Anne Y.F.

2013-01-01

Objective. To characterize the use of team-based learning (TBL) in US colleges and schools of pharmacy, including factors that may affect implementation and perceptions of faculty members regarding the impact of TBL on educational outcomes. Methods. Respondents identified factors that inhibit or enable TBL use and its impact on student learning. Results were stratified by type of institution (public/private), class size, and TBL experience. Results. Sixty-nine of 100 faculty members (69%) representing 43 (86%) institutions responded. Major factors considered to enable TBL implementation included a single campus and student and administration buy-in. Inhibiting factors included distant campuses, faculty resistance, and lack of training. Compared with traditional lectures, TBL is perceived to enhance student engagement, improve students’ preparation for class, and promote achievement of course outcomes. In addition, TBL is perceived to be more effective than lectures at fostering learning in all 6 domains of Bloom’s Taxonomy. Conclusions. Despite potential implementation challenges, faculty members perceive that TBL improves student engagement and learning. PMID:23966718

Aversive Learning Modulates Cortical Representations of Object Categories

PubMed Central

Dunsmoor, Joseph E.; Kragel, Philip A.; Martin, Alex; LaBar, Kevin S.

2014-01-01

Experimental studies of conditioned learning reveal activity changes in the amygdala and unimodal sensory cortex underlying fear acquisition to simple stimuli. However, real-world fears typically involve complex stimuli represented at the category level. A consequence of category-level representations of threat is that aversive experiences with particular category members may lead one to infer that related exemplars likewise pose a threat, despite variations in physical form. Here, we examined the effect of category-level representations of threat on human brain activation using 2 superordinate categories (animals and tools) as conditioned stimuli. Hemodynamic activity in the amygdala and category-selective cortex was modulated by the reinforcement contingency, leading to widespread fear of different exemplars from the reinforced category. Multivariate representational similarity analyses revealed that activity patterns in the amygdala and object-selective cortex were more similar among exemplars from the threat versus safe category. Learning to fear animate objects was additionally characterized by enhanced functional coupling between the amygdala and fusiform gyrus. Finally, hippocampal activity co-varied with object typicality and amygdala activation early during training. These findings provide novel evidence that aversive learning can modulate category-level representations of object concepts, thereby enabling individuals to express fear to a range of related stimuli. PMID:23709642

Computerized training management system

DOEpatents

Rice, H.B.; McNair, R.C.; White, K.; Maugeri, T.

1998-08-04

A Computerized Training Management System (CTMS) is disclosed for providing a procedurally defined process that is employed to develop accreditable performance based training programs for job classifications that are sensitive to documented regulations and technical information. CTMS is a database that links information needed to maintain a five-phase approach to training-analysis, design, development, implementation, and evaluation independent of training program design. CTMS is designed using R-Base{trademark}, an-SQL compliant software platform. Information is logically entered and linked in CTMS. Each task is linked directly to a performance objective, which, in turn, is linked directly to a learning objective; then, each enabling objective is linked to its respective test items. In addition, tasks, performance objectives, enabling objectives, and test items are linked to their associated reference documents. CTMS keeps all information up to date since it automatically sorts, files and links all data; CTMS includes key word and reference document searches. 18 figs.

Computerized training management system

DOEpatents

Rice, Harold B.; McNair, Robert C.; White, Kenneth; Maugeri, Terry

1998-08-04

A Computerized Training Management System (CTMS) for providing a procedurally defined process that is employed to develop accreditable performance based training programs for job classifications that are sensitive to documented regulations and technical information. CTMS is a database that links information needed to maintain a five-phase approach to training-analysis, design, development, implementation, and evaluation independent of training program design. CTMS is designed using R-Base.RTM., an-SQL compliant software platform. Information is logically entered and linked in CTMS. Each task is linked directly to a performance objective, which, in turn, is linked directly to a learning objective; then, each enabling objective is linked to its respective test items. In addition, tasks, performance objectives, enabling objectives, and test items are linked to their associated reference documents. CTMS keeps all information up to date since it automatically sorts, files and links all data; CTMS includes key word and reference document searches.

Energy Sector Security through a System for Intelligent, Learning Network Configuration Monitoring and Management (“Essence”)

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

Miller, Craig; Larmouth, Robert

The project was conceived and executed with the overarching objective to provide cost effective tools to cooperative utilities that enabled them to quickly detect, characterize and take remediative action against cyber attacks.

Determining the benefits and objectives of a child health residency program for Canadian rural family physicians: An international qualitative research study

PubMed Central

Keegan, David; Bannister, Susan

2010-01-01

OBJECTIVES: To clarify the need for an advanced child health training program for Canadian rural family physicians, and to determine the key learning objectives to enable graduates to become community leaders in child and youth health care. DESIGN: Qualitative educational research study. Setting: Canada and Australia. METHODS: To gather data, the authors carried out semistructured interviews and focus groups with child care consultants, Canadian rural family physicians, child patients and parents, family medicine residents and Australian rural family physicians. Standards of qualitative methodology were applied to identify themes and subthemes. RESULTS: It was determined that a family medicine child health program would provide the following benefits: enhanced care by family physicians, improved access to child care, increased attractiveness of family medicine as a career and reduced ‘specialty burden’. Five key learning objectives for graduates were identified: the ability to provide child-centred care, to care for acutely or critically ill children, to care for children with complex needs, to recognize and act on ‘red flags’, and to provide behavioural and mental health care. The Australian general practitioners confirmed that their training provided most of these benefits, and enabled them to achieve the objectives identified. CONCLUSION: The present study showed that multiple stakeholders believed that advanced training in child health for rural family physicians would provide better care for children. The study also identified key learning objectives for the program. The present research led to the establishment of a Family Medicine Child Health Residency Program (www.familymedicineuwo.ca/PostGrad/PGY3/ChildHealth.aspx) at The University of Western Ontario (London, Ontario). PMID:21731414

Perspectives on Advanced Learning Technologies and Learning Networks and Future Aerospace Workforce Environments

NASA Technical Reports Server (NTRS)

Noor, Ahmed K. (Compiler)

2003-01-01

An overview of the advanced learning technologies is given in this presentation along with a brief description of their impact on future aerospace workforce development. The presentation is divided into five parts (see Figure 1). In the first part, a brief historical account of the evolution of learning technologies is given. The second part describes the current learning activities. The third part describes some of the future aerospace systems, as examples of high-tech engineering systems, and lists their enabling technologies. The fourth part focuses on future aerospace research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on learning technologies and learning networks.

Learning About Causes From People: Observational Causal Learning in 24-Month-Old Infants

PubMed Central

Meltzoff, Andrew N.; Waismeyer, Anna; Gopnik, Alison

2013-01-01

How do infants and young children learn about the causal structure of the world around them? In 4 experiments we investigate whether young children initially give special weight to the outcomes of goal-directed interventions they see others perform and use this to distinguish correlations from genuine causal relations—observational causal learning. In a new 2-choice procedure, 2- to 4-year-old children saw 2 identical objects (potential causes). Activation of 1 but not the other triggered a spatially remote effect. Children systematically intervened on the causal object and predictively looked to the effect. Results fell to chance when the cause and effect were temporally reversed, so that the events were merely associated but not causally related. The youngest children (24- to 36-month-olds) were more likely to make causal inferences when covariations were the outcome of human interventions than when they were not. Observational causal learning may be a fundamental learning mechanism that enables infants to abstract the causal structure of the world. PMID:22369335

A Study on Markerless AR-Based Infant Education System Using CBIR

NASA Astrophysics Data System (ADS)

Lim, Ji-Hoon; Kim, Seoksoo

Block play is widely known to be effective to help a child develop emotionally and physically based on learning by a sense of sight and touch. But block play can not expect to have learning effects through a sense of hearing. Therefore, in this study, such limitations are overcome by a method that recognizes an object made up of blocks, not a marker-based method generally used for an AR environment, a matching technology enabling an object to be perceived in every direction, and a technology combining images of the real world with 2D/3D images/pictures/sounds of a similar object. Also, an education system for children aged 3~5 is designed to implement markerless AR with the CBIR method.

Multi-sensory learning and learning to read.

PubMed

Blomert, Leo; Froyen, Dries

2010-09-01

The basis of literacy acquisition in alphabetic orthographies is the learning of the associations between the letters and the corresponding speech sounds. In spite of this primacy in learning to read, there is only scarce knowledge on how this audiovisual integration process works and which mechanisms are involved. Recent electrophysiological studies of letter-speech sound processing have revealed that normally developing readers take years to automate these associations and dyslexic readers hardly exhibit automation of these associations. It is argued that the reason for this effortful learning may reside in the nature of the audiovisual process that is recruited for the integration of in principle arbitrarily linked elements. It is shown that letter-speech sound integration does not resemble the processes involved in the integration of natural audiovisual objects such as audiovisual speech. The automatic symmetrical recruitment of the assumedly uni-sensory visual and auditory cortices in audiovisual speech integration does not occur for letter and speech sound integration. It is also argued that letter-speech sound integration only partly resembles the integration of arbitrarily linked unfamiliar audiovisual objects. Letter-sound integration and artificial audiovisual objects share the necessity of a narrow time window for integration to occur. However, they differ from these artificial objects, because they constitute an integration of partly familiar elements which acquire meaning through the learning of an orthography. Although letter-speech sound pairs share similarities with audiovisual speech processing as well as with unfamiliar, arbitrary objects, it seems that letter-speech sound pairs develop into unique audiovisual objects that furthermore have to be processed in a unique way in order to enable fluent reading and thus very likely recruit other neurobiological learning mechanisms than the ones involved in learning natural or arbitrary unfamiliar audiovisual associations. Copyright 2010 Elsevier B.V. All rights reserved.

The origins of word learning: Brain responses of 3-month-olds indicate their rapid association of objects and words.

PubMed

Friedrich, Manuela; Friederici, Angela D

2017-03-01

The present study explored the origins of word learning in early infancy. Using event-related potentials (ERP) we monitored the brain activity of 3-month-old infants when they were repeatedly exposed to several initially novel words paired consistently with each the same initially novel objects or inconsistently with different objects. Our results provide strong evidence that these young infants extract statistic regularities in the distribution of the co-occurrences of objects and words extremely quickly. The data suggest that this ability is based on the rapid formation of associations between the neural representations of objects and words, but that the new associations are not retained in long-term memory until the next day. The type of brain response moreover indicates that, unlike in older infants, in 3-month-olds a semantic processing stage is not involved. Their ability to combine words with meaningful information is caused by a primary learning mechanism that enables the formation of proto-words and acts as a precursor for the acquisition of genuine words. © 2015 John Wiley & Sons Ltd.

A Web-Enabled Graduate Course: Two Perspectives.

ERIC Educational Resources Information Center

Penrod, James; Perry, Barbara A.

This paper describes a World Wide Web-enhanced graduate course at the University of Memphis (Tennessee) called "IT [Information Technology] Trends and Issues in Higher and Adult Education." Topics covered include the course objectives, technology used, course activities, and assignments. Four prevalent learning styles are summarized…

How does the brain rapidly learn and reorganize view-invariant and position-invariant object representations in the inferotemporal cortex?

PubMed

Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey

2011-12-01

All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is predicted to prevent the reset of spatial attention, which would otherwise keep the representations of multiple objects from being combined by learning. Li and DiCarlo (2008) have presented neurophysiological data from monkeys showing how unsupervised natural experience in a target swapping experiment can rapidly alter object representations in IT. The model quantitatively simulates the swapping data by showing how the swapping procedure fools the spatial attention mechanism. More generally, the model provides a unifying framework, and testable predictions in both monkeys and humans, for understanding object learning data using neurophysiological methods in monkeys, and spatial attention, episodic learning, and memory retrieval data using functional imaging methods in humans. Copyright © 2011 Elsevier Ltd. All rights reserved.

Ecological literacy and beyond: Problem-based learning for future professionals.

PubMed

Lewinsohn, Thomas M; Attayde, José Luiz; Fonseca, Carlos Roberto; Ganade, Gislene; Jorge, Leonardo Ré; Kollmann, Johannes; Overbeck, Gerhard E; Prado, Paulo Inácio; Pillar, Valério D; Popp, Daniela; da Rocha, Pedro L B; Silva, Wesley Rodrigues; Spiekermann, Annette; Weisser, Wolfgang W

2015-03-01

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

Bayesian Analogy with Relational Transformations

ERIC Educational Resources Information Center

Lu, Hongjing; Chen, Dawn; Holyoak, Keith J.

2012-01-01

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy…

Integration of Problem-based Learning and Innovative Technology Into a Self-Care Course

PubMed Central

2013-01-01

Objective. To assess the integration of problem-based learning and technology into a self-care course. Design. Problem-based learning (PBL) activities were developed and implemented in place of lectures in a self-care course. Students used technology, such as computer-generated virtual patients and iPads, during the PBL sessions. Assessments. Students’ scores on post-case quizzes were higher than on pre-case quizzes used to assess baseline knowledge. Student satisfaction with problem-based learning and the use of technology in the course remained consistent throughout the semester. Conclusion. Integrating problem-based learning and technology into a self-care course enabled students to become active learners. PMID:23966730

Involving a young person in the development of a digital resource in nurse education.

PubMed

Fenton, Gaynor

2014-01-01

Health policies across western societies have embedded the need for service user and carer perspectives in service design and delivery of educational programmes. There is a growing recognition of the need to include the perspectives of children and young people as service users in the design and delivery of child focused educational programmes. Digital storytelling provides a strategy for student nurses to gain insight into the lived experiences of children and young people. Engaging with these stories enables students to develop an understanding of a young persons' experience of healthcare. This paper outlines a project that developed a digital learning object based upon a young person's experience of cancer and student evaluations of the digital learning object as a teaching and learning strategy. Over 80% of students rated the digital learning object as interesting and were motivated to explore its content. In addition, the evaluation highlighted that listening to the young person's experiences of her treatment regimes was informative and assisted understanding of a patients' perspective of care delivery. Copyright © 2013 Elsevier Ltd. All rights reserved.

An Evaluation of New After-Action Review Tools in Exercise Black Skies 10 & Exercise Black Skies 12

DTIC Science & Technology

2013-10-01

impacting on participant learning . AWAR also enabled an objective ground truth to be readily available to learners, to overcome the shortcomings of...memory of historical events in a training mission. AWAR also appeared to enhance the opportunity for less experienced participants to learn through...human- machine interaction, team performance, and team training. Dr. Best is Science Team Leader for the collective training component of DSTO task AIR

Collective behaviour across animal species.

PubMed

DeLellis, Pietro; Polverino, Giovanni; Ustuner, Gozde; Abaid, Nicole; Macrì, Simone; Bollt, Erik M; Porfiri, Maurizio

2014-01-16

We posit a new geometric perspective to define, detect, and classify inherent patterns of collective behaviour across a variety of animal species. We show that machine learning techniques, and specifically the isometric mapping algorithm, allow the identification and interpretation of different types of collective behaviour in five social animal species. These results offer a first glimpse at the transformative potential of machine learning for ethology, similar to its impact on robotics, where it enabled robots to recognize objects and navigate the environment.

Developing Modular and Adaptable Courseware Using TeachML.

ERIC Educational Resources Information Center

Wehner, Frank; Lorz, Alexander

This paper presents the use of an XML grammar for two complementary projects--CHAMELEON (Cooperative Hypermedia Adaptive MultimEdia Learning Objects) and EIT (Enabling Informal Teamwork). Areas of applications are modular courseware documents and the collaborative authoring process of didactical units. A number of requirements for a suitable…

Cognitive Training and Initial Use of Referential Speech.

ERIC Educational Resources Information Center

Kahn, James V.

1984-01-01

Profoundly retarded 3-10 year olds (N=24) were divided into three groups: two cognitive training programs--object permanence or means-end--and language only. Results of pre- and posttests revealed that the cognitive training approaches were successful in enabling the majority of Ss to learn to use speech. (CL)

Lifelong Learning: Skills and Online Resources

ERIC Educational Resources Information Center

Lim, Russell F.; Hsiung, Bob C.; Hales, Deborah J.

2006-01-01

Objective: Advances in information technology enable the practicing psychiatrist's quest to keep up-to-date with new discoveries in psychiatry, as well as to meet recertification requirements. However, physicians' computer skills do not always keep up with technology, nor do they take advantage of online search and continuing education services.…

Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

PubMed Central

Feng, Di

2018-01-01

Reusing the tactile knowledge of some previously-explored objects (prior objects) helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT), and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10% when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20%. The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer). PMID:29466300

Indexing and retrieval of multimedia objects at different levels of granularity

NASA Astrophysics Data System (ADS)

Faudemay, Pascal; Durand, Gwenael; Seyrat, Claude; Tondre, Nicolas

1998-10-01

Intelligent access to multimedia databases for `naive user' should probably be based on queries formulation by `intelligent agents'. These agents should `understand' the semantics of the contents, learn user preferences and deliver to the user a subset of the source contents, for further navigation. The goal of such systems should be to enable `zero-command' access to the contents, while keeping the freedom of choice of the user. Such systems should interpret multimedia contents in terms of multiple audiovisual objects (from video to visual or audio object), and on actions and scenarios.

Student perceptions of independent versus facilitated small group learning approaches to compressed medical anatomy education.

PubMed

Whelan, Alexander; Leddy, John J; Mindra, Sean; Matthew Hughes, J D; El-Bialy, Safaa; Ramnanan, Christopher J

2016-01-01

The purpose of this study was to compare student perceptions regarding two, small group learning approaches to compressed (46.5 prosection-based laboratory hours), integrated anatomy education at the University of Ottawa medical program. In the facilitated active learning (FAL) approach, tutors engage students and are expected to enable and balance both active learning and progression through laboratory objectives. In contrast, the emphasized independent learning (EIL) approach stresses elements from the "flipped classroom" educational model: prelaboratory preparation, independent laboratory learning, and limited tutor involvement. Quantitative (Likert-style questions) and qualitative data (independent thematic analysis of open-ended commentary) from a survey of students who had completed the preclerkship curriculum identified strengths from the EIL (promoting student collaboration and communication) and FAL (successful progression through objectives) approaches. However, EIL led to student frustration related to a lack of direction and impaired completion of objectives, whereas active learning opportunities in FAL were highly variable and dependent on tutor teaching style. A "hidden curriculum" was also identified, where students (particularly EIL and clerkship students) commonly compared their compressed anatomy education or their anatomy learning environment with other approaches. Finally, while both groups highly regarded the efficiency of prosection-based learning and expressed value for cadaveric-based learning, student commentary noted that the lack of grade value dedicated to anatomy assessment limited student accountability. This study revealed critical insights into small group learning in compressed anatomy education, including the need to balance student active learning opportunities with appropriate direction and feedback (including assessment). © 2015 American Association of Anatomists.

Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

DTIC Science & Technology

2008-09-01

Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

Collective behaviour across animal species

PubMed Central

DeLellis, Pietro; Polverino, Giovanni; Ustuner, Gozde; Abaid, Nicole; Macrì, Simone; Bollt, Erik M.; Porfiri, Maurizio

2014-01-01

We posit a new geometric perspective to define, detect, and classify inherent patterns of collective behaviour across a variety of animal species. We show that machine learning techniques, and specifically the isometric mapping algorithm, allow the identification and interpretation of different types of collective behaviour in five social animal species. These results offer a first glimpse at the transformative potential of machine learning for ethology, similar to its impact on robotics, where it enabled robots to recognize objects and navigate the environment. PMID:24430561

Visual object recognition for mobile tourist information systems

NASA Astrophysics Data System (ADS)

Paletta, Lucas; Fritz, Gerald; Seifert, Christin; Luley, Patrick; Almer, Alexander

2005-03-01

We describe a mobile vision system that is capable of automated object identification using images captured from a PDA or a camera phone. We present a solution for the enabling technology of outdoors vision based object recognition that will extend state-of-the-art location and context aware services towards object based awareness in urban environments. In the proposed application scenario, tourist pedestrians are equipped with GPS, W-LAN and a camera attached to a PDA or a camera phone. They are interested whether their field of view contains tourist sights that would point to more detailed information. Multimedia type data about related history, the architecture, or other related cultural context of historic or artistic relevance might be explored by a mobile user who is intending to learn within the urban environment. Learning from ambient cues is in this way achieved by pointing the device towards the urban sight, capturing an image, and consequently getting information about the object on site and within the focus of attention, i.e., the users current field of view.

Data Mining Student Answers with Moodle to Investigate Learning Pathways in an Introductory Geohazards Course

NASA Astrophysics Data System (ADS)

Sit, S. M.; Brudzinski, M. R.; Colella, H. V.

2012-12-01

The recent growth of online learning in higher education is primarily motivated by a desire to (a) increase the availability of learning experiences for learners who cannot, or choose not, to attend traditional face-to-face offerings, (b) assemble and disseminate instructional content more cost-efficiently, or (c) enable instructors to handle more students while maintaining a learning outcome quality that is equivalent to that of comparable face-to-face instruction. However, a less recognized incentive is that online learning also provides an opportunity for data mining, or efficient discovery of non-obvious valuable patterns from a large collection of data, that can be used to investigate learning pathways as opposed to focusing solely on assessing student outcomes. Course management systems that enable online courses provide a means to collect a vast amount of information to analyze students' behavior and the learning process in general. One of the most commonly used is Moodle (modular object-oriented developmental learning environment), a free learning management system that enables creation of powerful, flexible, and engaging online courses and experiences. In order to examine student learning pathways, the online learning modules we are constructing take advantage of Moodle capabilities to provide immediate formative feedback, verifying answers as correct or incorrect and elaborating on knowledge components to guide students towards the correct answer. By permitting multiple attempts in which credit is diminished for each incorrect answer, we provide opportunities to use data mining strategies to assess thousands of students' actions for evidence of problem solving strategies and mastery of concepts. We will show preliminary results from application of this approach to a ~90 student introductory geohazard course that is migrating toward online instruction. We hope more continuous assessment of students' performances will help generate cognitive models that can inform instructional redesign, improve overall efficiency of student learning, and, potentially, be used to create an intelligent tutoring system.

Reality-Based Learning: Outbreak, an Engaging Introductory Course in Public Health and Epidemiology

ERIC Educational Resources Information Center

Calonge, David Santandreu; Grando, Danilla

2013-01-01

Objective: To develop a totally online reality-based course that engages students and enables the development of enhanced teamwork and report-writing skills. Setting: Outbreaks of infectious diseases impacts upon commerce, trade and tourism as well as placing strains on healthcare systems. A general course introducing university students to…

The Lom Approach--a Call for Concern?

ERIC Educational Resources Information Center

Armitage, Nicholas; Bowerman, Chris

2005-01-01

The LOM (Learning Object Model) approach to courseware design seems to be driven by a desire to increase access to education as well as use technology to enable a higher staff-student ratio than is currently possible. The LOM standard involves the use of standard metadata descriptions of content and adaptive content engines to deliver the…

The LOM Approach -- A CALL for Concern?

ERIC Educational Resources Information Center

Armitage, Nicholas; Bowerman, Chris

2005-01-01

The LOM (Learning Object Model) approach to courseware design seems to be driven by a desire to increase access to education as well as use technology to enable a higher staff-student ratio than is currently possible. The LOM standard involves the use of standard metadata descriptions of content and adaptive content engines to deliver the…

RELATE Competencies and Enablers Statements. Teacher Education Forum Series. Vol. 1, No. 5.

ERIC Educational Resources Information Center

Harste, Jerome C.; And Others

This report displays and briefly describes the set of professional competencies and other learning outcomes that comprise the objectives for elementary majors enrolled in the Indiana University competency-based teacher education program known as RELATE (Reading and Language Arts Teacher Education). This report is divided into 10 units and lists…

Radio/Television Repair. Trade and Industrial Education Course of Study.

ERIC Educational Resources Information Center

Beaumont, George J.; And Others

This guide, intended to be used in teaching and learning, should enable students to master basic skills, acquire knowledge, and develop favorable attitudes in the areas emphasized. Contents of the guide are organized as follows: (1) Introductory section giving the course philosophy, general course objectives, instructional plan, and bibliography,…

Developing Computer Programming Concepts and Skills via Technology-Enriched Language-Art Projects: A Case Study

ERIC Educational Resources Information Center

Lee, Young-Jin

2010-01-01

Teaching computer programming to young children has been considered difficult because of its abstract and complex nature. The objectives of this study are (1) to investigate whether an innovative educational technology tool called Scratch could enable young children to learn abstract knowledge of computer programming while creating multimedia…

The "Tweeting Book" and the Question of "Non-Human Data"

ERIC Educational Resources Information Center

Knox, Jeremy

2015-01-01

This short article describes an experimental radio-frequency identification (RFID) system designed to playfully explore the possibilities of object agency, in the form of "tweeting books". The use of web-enabled sensors is discussed in the context of the emerging field of Learning Analytics. The analysis of the "tweeting books"…

Diversity in School: A Brazilian Educational Policy against Homophobia

ERIC Educational Resources Information Center

Carrara, Sergio; Nascimento, Marcos; Duque, Aline; Tramontano, Lucas

2016-01-01

Diversity in School is a Brazilian initiative that seeks to increase understanding, recognition, respect, and value social and cultural differences through offering an e-learning course on gender, sexuality, and ethnic relations for teachers and school administrators in the public school system. The course and its objectives aim to enable staff…

Introducing and Developing Map Skills with Persons Having Mild or Moderate Learning Difficulties.

ERIC Educational Resources Information Center

Renfrew, Tom

1997-01-01

A British project found that appropriate training in map skills enabled children and adults with mild mental retardation to complete a white color-coded orienteering course with minimal assistance but that persons with moderate mental retardation required more assistance and instruction time to complete course objectives. Describes approaches to…

An Ethnographic Approach to Syllabus Design: A Case Study of the Indian Institute of Science, Bangalore.

ERIC Educational Resources Information Center

Ramani, Esther; And Others

1988-01-01

Argues for an ethnographic reorientation to needs analysis and syllabus design in English for specific purposes in advanced postgraduate centers of science and technology. The seven-stage framework (specify learners, analyze needs, specify enabling objectives, select materials, identify teaching/learning activities, evaluate, and revise) used to…

Common world model for unmanned systems

NASA Astrophysics Data System (ADS)

Dean, Robert Michael S.

2013-05-01

The Robotic Collaborative Technology Alliance (RCTA) seeks to provide adaptive robot capabilities which move beyond traditional metric algorithms to include cognitive capabilities. Key to this effort is the Common World Model, which moves beyond the state-of-the-art by representing the world using metric, semantic, and symbolic information. It joins these layers of information to define objects in the world. These objects may be reasoned upon jointly using traditional geometric, symbolic cognitive algorithms and new computational nodes formed by the combination of these disciplines. The Common World Model must understand how these objects relate to each other. Our world model includes the concept of Self-Information about the robot. By encoding current capability, component status, task execution state, and histories we track information which enables the robot to reason and adapt its performance using Meta-Cognition and Machine Learning principles. The world model includes models of how aspects of the environment behave, which enable prediction of future world states. To manage complexity, we adopted a phased implementation approach to the world model. We discuss the design of "Phase 1" of this world model, and interfaces by tracing perception data through the system from the source to the meta-cognitive layers provided by ACT-R and SS-RICS. We close with lessons learned from implementation and how the design relates to Open Architecture.

Making time for learning-oriented leadership in multidisciplinary hospital management groups.

PubMed

Singer, Sara J; Hayes, Jennifer E; Gray, Garry C; Kiang, Mathew V

2015-01-01

Although the clinical requirements of health care delivery imply the need for interdisciplinary management teams to work together to promote frontline learning, such interdisciplinary, learning-oriented leadership is atypical. We designed this study to identify behaviors enabling groups of diverse managers to perform as learning-oriented leadership teams on behalf of quality and safety. We randomly selected 12 of 24 intact groups of hospital managers from one hospital to participate in a Safety Leadership Team Training program. We collected primary data from March 2008 to February 2010 including pre- and post-staff surveys, multiple interviews, observations, and archival data from management groups. We examined the level and trend in frontline perceptions of managers' learning-oriented leadership following the intervention and ability of management groups to achieve objectives on targeted improvement projects. Among the 12 intervention groups, we identified higher- and lower-performing intervention groups and behaviors that enabled higher performers to work together more successfully. Management groups that achieved more of their performance goals and whose staff perceived more and greater improvement in their learning-oriented leadership after participation in Safety Leadership Team Training invested in structures that created learning capacity and conscientiously practiced prescribed learning-oriented management and problem-solving behaviors. They made the time to do these things because they envisioned the benefits of learning, valued the opportunity to learn, and maintained an environment of mutual respect and psychological safety within their group. Learning in management groups requires vision of what learning can accomplish; will to explore, practice, and build learning capacity; and mutual respect that sustains a learning environment.

Exploiting range imagery: techniques and applications

NASA Astrophysics Data System (ADS)

Armbruster, Walter

2009-07-01

Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems.

Neural principles of memory and a neural theory of analogical insight

NASA Astrophysics Data System (ADS)

Lawson, David I.; Lawson, Anton E.

1993-12-01

Grossberg's principles of neural modeling are reviewed and extended to provide a neural level theory to explain how analogies greatly increase the rate of learning and can, in fact, make learning and retention possible. In terms of memory, the key point is that the mind is able to recognize and recall when it is able to match sensory input from new objects, events, or situations with past memory records of similar objects, events, or situations. When a match occurs, an adaptive resonance is set up in which the synaptic strengths of neurons are increased; thus a long term record of the new input is formed in memory. Systems of neurons called outstars and instars are presumably the underlying units that enable this to occur. Analogies can greatly facilitate learning and retention because they activate the outstars (i.e., the cells that are sampling the to-be-learned pattern) and cause the neural activity to grow exponentially by forming feedback loops. This increased activity insures the boost in synaptic strengths of neurons, thus causing storage and retention in long-term memory (i.e., learning).

Data mining in bioinformatics using Weka.

PubMed

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

NASA Astrophysics Data System (ADS)

Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

2016-09-01

Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

Active learning in the lecture theatre using 3D printed objects.

PubMed

Smith, David P

2016-01-01

The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

Active learning in the lecture theatre using 3D printed objects

PubMed Central

Smith, David P.

2016-01-01

The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student. PMID:27366318

Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; De Colstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or nonimpervious.

Guided Online Group Discussion Enhances Student Critical Thinking Skills

ERIC Educational Resources Information Center

Gokhale, Anu; Machina, Kenton

2018-01-01

A teacher's objective is to provide students the cognitive strategies that enable them to think critically, make decisions, and solve problems. In order to guide student learning, teachers should be aware of the concepts that are prerequisite to the understanding of others and also of typical student misconceptions. The goal of this study was to…

Social Studies. Standards of Learning Objectives for Virginia Public Schools: Revised 1989.

ERIC Educational Resources Information Center

Virginia State Dept. of Education, Richmond.

The standards in this document resulted from a statewide effort to identify a scope and sequence of content, concepts, skills, and attitudes in social studies from kindergarten through grade twelve. The goals embodied in the standards include: (1) providing experiences that enable students to participate in society effectively and responsibly; (2)…

Fostering Students' Statistical Literacy through Significant Learning Experience

ERIC Educational Resources Information Center

Krishnan, Saras

2015-01-01

A major objective of statistics education is to develop students' statistical literacy that enables them to be educated users of data in context. Teaching statistics in today's educational settings is not an easy feat because teachers have a huge task in keeping up with the demands of the new generation of learners. The present day students have…

Use of Mobile Phones for Project Based Learning by Undergraduate Students of Nigerian Private Universities

ERIC Educational Resources Information Center

Utulu, Samuel C.; Alonge, Ayodele

2012-01-01

A university's objective is to educate its students using information and communication technologies (ICTs) and teaching techniques that would enable its graduates become flexible and life-long learners that can easily adapt to the changes eminent in the information society. Achieving this aim requires among other factors, the adoption of…

Using business intelligence to improve performance.

PubMed

Wadsworth, Tom; Graves, Brian; Glass, Steve; Harrison, A Marc; Donovan, Chris; Proctor, Andrew

2009-10-01

Cleveland Clinic's enterprise performance management program offers proof that comparisons of actual performance against strategic objectives can enable healthcare organization to achieve rapid organizational change. Here are four lessons Cleveland Clinic learned from this initiative: Align performance metrics with strategic initiatives. Structure dashboards for the CEO. Link performance to annual reviews. Customize dashboard views to the specific user.

Mobile Virtual Learning Object for the Assessment of Acute Pain as a Learning Tool to Assess Acute Pain in Nursing: An Analysis of the Mental Workload

PubMed Central

2015-01-01

Background The inclusion of new technologies in education has motivated the development of studies on mental workload. These technologies are now being used in the teaching and learning process. The analysis enables identification of factors intervening in this workload as well as planning of overload prevention for educational activities using these technologies. Objective To analyze the mental workload of an educational intervention with the Mobile Virtual Learning Object for the Assessment of Acute Pain in adults and newborns, according to the NASA Task Load Index criteria. Methods A methodological study with data collected from 5 nurses and 75 students, from November of 2013 to February of 2014. Results The highest students’ and specialists’ means were in the dimensions of “Mental demand” (57.20 ± 22.27; 51 ± 29.45) and “Performance” (58.47 ± 24.19; 73 ± 28.85). The specialists’ mental workload index was higher (50.20 ± 7.28) when compared with students’ (47.87 ± 16.85) on a scale from 0 to 100 (P=.557). Conclusions The instrument allowed for the assessment of mental workload after an online educational intervention with a mobile learning virtual object. An excessive overload was not identified among participants. Assessing mental workload from the use of educational technologies at the end of a task is a key to their applicability, with the aim of providing a more effective, stimulating, and long-lasting experience of the learning process. PMID:27731849

Top-down attention based on object representation and incremental memory for knowledge building and inference.

PubMed

Kim, Bumhwi; Ban, Sang-Woo; Lee, Minho

2013-10-01

Humans can efficiently perceive arbitrary visual objects based on an incremental learning mechanism with selective attention. This paper proposes a new task specific top-down attention model to locate a target object based on its form and color representation along with a bottom-up saliency based on relativity of primitive visual features and some memory modules. In the proposed model top-down bias signals corresponding to the target form and color features are generated, which draw the preferential attention to the desired object by the proposed selective attention model in concomitance with the bottom-up saliency process. The object form and color representation and memory modules have an incremental learning mechanism together with a proper object feature representation scheme. The proposed model includes a Growing Fuzzy Topology Adaptive Resonance Theory (GFTART) network which plays two important roles in object color and form biased attention; one is to incrementally learn and memorize color and form features of various objects, and the other is to generate a top-down bias signal to localize a target object by focusing on the candidate local areas. Moreover, the GFTART network can be utilized for knowledge inference which enables the perception of new unknown objects on the basis of the object form and color features stored in the memory during training. Experimental results show that the proposed model is successful in focusing on the specified target objects, in addition to the incremental representation and memorization of various objects in natural scenes. In addition, the proposed model properly infers new unknown objects based on the form and color features of previously trained objects. Copyright © 2013 Elsevier Ltd. All rights reserved.

Feature saliency and feedback information interactively impact visual category learning

PubMed Central

Hammer, Rubi; Sloutsky, Vladimir; Grill-Spector, Kalanit

2015-01-01

Visual category learning (VCL) involves detecting which features are most relevant for categorization. VCL relies on attentional learning, which enables effectively redirecting attention to object’s features most relevant for categorization, while ‘filtering out’ irrelevant features. When features relevant for categorization are not salient, VCL relies also on perceptual learning, which enables becoming more sensitive to subtle yet important differences between objects. Little is known about how attentional learning and perceptual learning interact when VCL relies on both processes at the same time. Here we tested this interaction. Participants performed VCL tasks in which they learned to categorize novel stimuli by detecting the feature dimension relevant for categorization. Tasks varied both in feature saliency (low-saliency tasks that required perceptual learning vs. high-saliency tasks), and in feedback information (tasks with mid-information, moderately ambiguous feedback that increased attentional load, vs. tasks with high-information non-ambiguous feedback). We found that mid-information and high-information feedback were similarly effective for VCL in high-saliency tasks. This suggests that an increased attentional load, associated with the processing of moderately ambiguous feedback, has little effect on VCL when features are salient. In low-saliency tasks, VCL relied on slower perceptual learning; but when the feedback was highly informative participants were able to ultimately attain the same performance as during the high-saliency VCL tasks. However, VCL was significantly compromised in the low-saliency mid-information feedback task. We suggest that such low-saliency mid-information learning scenarios are characterized by a ‘cognitive loop paradox’ where two interdependent learning processes have to take place simultaneously. PMID:25745404

Academic Staff Perspectives Towards Adoption of E-learning at Melaka Manipal Medical College: Has E-learning Redefined our Teaching Model?

PubMed

Bhardwaj, A; Nagandla, K; Swe, K Mm; Abas, A Bl

2015-01-01

E-learning is the use of Information and Communication Technology (ICT) to provide online education and learning. E- Learning has now been integrated into the traditional teaching as the concept of 'blended learning' that combines digital learning with the existing traditional teaching methods to address the various challenges in the field of medical education. Structured e-learning activities were started in Melaka Manipal Medical College in 2009 via e-learning platform (MOODLE-Modular Object-Oriented Dynamic Learning Environment). The objective of the present study is to investigate the faculty opinions toward the existing e-learning activities, and to analyse the extent of adopting and integration of e-learning into their traditional teaching methods. A cross sectional study was conducted among faculties of Medicine and Dentistry using pre-tested questionnaires. The data was analyzed by using the statistical package for social science, SPSS, version 16.0. The result of our survey indicates that majority of our faculty (65.4%) held positive opinion towards e-learning. Among the few, who demonstrated reservations, it is attributed to their average level of skills and aptitude in the use of computers that was statistically significant (p<0.05). Our study brings to light the need for formal training as perquisite to support e-learning that enables smooth transition of the faculty from their traditional teaching methods into blended approach. Our results are anticipated to strengthen the existing e-learning activities of our college and other universities and convincingly adopt e-learning as a viable teaching and learning strategy.

The inventory as a core element in the further development of the science curriculum in the Mannheim Reformed Curriculum of Medicine.

PubMed

Eckel, Julia; Schüttpelz-Brauns, Katrin; Miethke, Thomas; Rolletschek, Alexandra; Fritz, Harald M

2017-01-01

Introduction: The German Council of Science and Humanities as well as a number of medical professional associations support the strengthening of scientific competences by developing longitudinal curricula for teaching scientific competences in the undergraduate medical education. The National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) has also defined medical scientific skills as learning objectives in addition to the role of the scholar. The development of the Mannheim science curriculum started with a systematic inventory of the teaching of scientific competences in the Mannheim Reformed Curriculum of Medicine (MaReCuM). Methods: The inventory is based on the analysis of module profiles, teaching materials, surveys among experts, and verbatims from memory. Furthermore, science learning objectives were defined and prioritized, thus enabling the contents of the various courses to be assigned to the top three learning objectives. Results: The learning objectives systematic collection of information regarding the current state of research, critical assessment of scientific information and data sources, as well as presentation and discussion of the results of scientific studies are facilitated by various teaching courses from the first to the fifth year of undergraduate training. The review reveals a longitudinal science curriculum that has emerged implicitly. Future efforts must aim at eliminating redundancies and closing gaps; in addition, courses must be more closely aligned with each other, regarding both their contents and their timing, by means of a central coordination unit. Conclusion: The teaching of scientific thinking and working is a central component in the MaReCuM. The inventory and prioritization of science learning objectives form the basis for a structured ongoing development of the curriculum. An essential aspect here is the establishment of a central project team responsible for the planning, coordination, and review of these measures.

Automated analysis of short responses in an interactive synthetic tutoring system for introductory physics

NASA Astrophysics Data System (ADS)

Nakamura, Christopher M.; Murphy, Sytil K.; Christel, Michael G.; Stevens, Scott M.; Zollman, Dean A.

2016-06-01

Computer-automated assessment of students' text responses to short-answer questions represents an important enabling technology for online learning environments. We have investigated the use of machine learning to train computer models capable of automatically classifying short-answer responses and assessed the results. Our investigations are part of a project to develop and test an interactive learning environment designed to help students learn introductory physics concepts. The system is designed around an interactive video tutoring interface. We have analyzed 9 with about 150 responses or less. We observe for 4 of the 9 automated assessment with interrater agreement of 70% or better with the human rater. This level of agreement may represent a baseline for practical utility in instruction and indicates that the method warrants further investigation for use in this type of application. Our results also suggest strategies that may be useful for writing activities and questions that are more appropriate for automated assessment. These strategies include building activities that have relatively few conceptually distinct ways of perceiving the physical behavior of relatively few physical objects. Further success in this direction may allow us to promote interactivity and better provide feedback in online learning systems. These capabilities could enable our system to function more like a real tutor.

Parametric Crowd Generation Software for MS&T Simulations and Training

DTIC Science & Technology

2007-02-20

3 Technology Overview 5 Dynemotion System Components 5 Dynemotion System Architecture 6 Dynemotion-Enabled NPC Brain Cycles 9 Dynemotion API...Contents 10 Development Project Background Information 11 Potential Application and Impact for the DoD 13 Project Objectives, Scope...Methodology 13 Benefits of the Project 13 Project Innovation 14 *l_essons Learned and Open Questions 14 Research and Development Challenges 16

Error Detection and Self-Assessment as Mechanisms to Promote Self-Regulation of Learning among Secondary Education Students

ERIC Educational Resources Information Center

Zamora, Ángela; Suárez, José Manuel; Ardura, Diego

2018-01-01

The authors' objective was to study the role of error detection and retroactive self-regulation as determinants of performance in secondary education students. A total of 198 students participated in the quasiexperimental study, which involved a control group and two experimental groups. This enabled the authors to analyze the effects of both…

How Do They Research? An Ethnographic Study of Final Year Undergraduate Research Behavior in an Irish University

ERIC Educational Resources Information Center

Dunne, Siobhán

2016-01-01

The objectives of this study were to identify how, when, and where students research; the impact of learning environments on research productivity, and to recommend improved supports to facilitate research. An ethnographic approach that entailed following five students in the final six weeks of their program enabled deep level analysis. The study…

Exploring educational needs and design aspects of internet-enabled patient education for persons with diabetes: a qualitative interview study.

PubMed

Jafari, Javad; Karimi Moonaghi, Hosein; Zary, Nabil; Masiello, Italo

2016-10-31

The objective of this article is to explore the educational needs and design aspects of personalised internet-enabled education for patients with diabetes in Iran. Data were collected using semistructured interviews and then qualitatively analysed using inductive content analysis. 9 patients with type 2 diabetes were included. Inclusion criteria were access to and knowledge on how to use the internet. The selection ensured representation based on gender, age, occupation and educational background. The sample population was patients with diabetes who were admitted to an outpatient diabetes clinic in Mashhad, a large city of Iran with about 3 million inhabitants. 4 core categories emerged from the data: (1) seeking knowledge about diabetes, including specific knowledge acquisition, patient's interactions and learning requirements; (2) teaching and learning, including using different teaching methods and different ways to learn about the disease; (3) facilitators, including internet and mobile phone use to learn about the disease; and (4) barriers, including lack of internet access, uncertainty of access to the internet and lack of website in the local language and also perceived cultural barriers, such as patients' fears of the internet, lack of time and awareness. This study provides a better understanding of the patient's educational expectations and technical needs in relation to internet-enabled education. This knowledge will inform the development of functional mock-ups in the next research phase using a design-based research approach in order to design internet-enabled patient education for self-management of diabetes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Mobile Virtual Learning Object for the Assessment of Acute Pain as a Learning Tool to Assess Acute Pain in Nursing: An Analysis of the Mental Workload.

PubMed

Alvarez, Ana Graziela; Sasso, Grace; Iyengar, Sriram

2015-11-06

The inclusion of new technologies in education has motivated the development of studies on mental workload. These technologies are now being used in the teaching and learning process. The analysis enables identification of factors intervening in this workload as well as planning of overload prevention for educational activities using these technologies. To analyze the mental workload of an educational intervention with the Mobile Virtual Learning Object for the Assessment of Acute Pain in adults and newborns, according to the NASA Task Load Index criteria. A methodological study with data collected from 5 nurses and 75 students, from November of 2013 to February of 2014. The highest students' and specialists' means were in the dimensions of "Mental demand" (57.20 ± 22.27; 51 ± 29.45) and "Performance" (58.47 ± 24.19; 73 ± 28.85). The specialists' mental workload index was higher (50.20 ± 7.28) when compared with students' (47.87 ± 16.85) on a scale from 0 to 100 (P=.557). The instrument allowed for the assessment of mental workload after an online educational intervention with a mobile learning virtual object. An excessive overload was not identified among participants. Assessing mental workload from the use of educational technologies at the end of a task is a key to their applicability, with the aim of providing a more effective, stimulating, and long-lasting experience of the learning process.

Machine learning for a Toolkit for Image Mining

NASA Technical Reports Server (NTRS)

Delanoy, Richard L.

1995-01-01

A prototype user environment is described that enables a user with very limited computer skills to collaborate with a computer algorithm to develop search tools (agents) that can be used for image analysis, creating metadata for tagging images, searching for images in an image database on the basis of image content, or as a component of computer vision algorithms. Agents are learned in an ongoing, two-way dialogue between the user and the algorithm. The user points to mistakes made in classification. The algorithm, in response, attempts to discover which image attributes are discriminating between objects of interest and clutter. It then builds a candidate agent and applies it to an input image, producing an 'interest' image highlighting features that are consistent with the set of objects and clutter indicated by the user. The dialogue repeats until the user is satisfied. The prototype environment, called the Toolkit for Image Mining (TIM) is currently capable of learning spectral and textural patterns. Learning exhibits rapid convergence to reasonable levels of performance and, when thoroughly trained, Fo appears to be competitive in discrimination accuracy with other classification techniques.

Using reusable learning objects (RLOs) in wound care education: Undergraduate student nurse's evaluation of their learning gain.

PubMed

Redmond, Catherine; Davies, Carmel; Cornally, Deirdre; Adam, Ewa; Daly, Orla; Fegan, Marianne; O'Toole, Margaret

2018-01-01

Both nationally and internationally concerns have been expressed over the adequacy of preparation of undergraduate nurses for the clinical skill of wound care. This project describes the educational evaluation of a series of Reusable Learning Objects (RLOs) as a blended learning approach to facilitate undergraduate nursing students learning of wound care for competence development. Constructivism Learning Theory and Cognitive Theory of Multimedia Learning informed the design of the RLOs, promoting active learner approaches. Clinically based case studies and visual data from two large university teaching hospitals provided the authentic learning materials required. Interactive exercises and formative feedback were incorporated into the educational resource. Evaluation of student perceived learning gains in terms of knowledge, ability and attitudes were measured using a quantitative pre and posttest Wound Care Competency Outcomes Questionnaire. The RLO CETL Questionnaire was used to identify perceived learning enablers. Statistical and deductive thematic analyses inform the findings. Students (n=192) reported that their ability to meet the competency outcomes for wound care had increased significantly after engaging with the RLOs. Students rated the RLOs highly across all categories of perceived usefulness, impact, access and integration. These findings provide evidence that the use of RLOs for both knowledge-based and performance-based learning is effective. RLOs when designed using clinically real case scenarios reflect the true complexities of wound care and offer innovative interventions in nursing curricula. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Future of Web Maps in Next Generation Textbooks

NASA Astrophysics Data System (ADS)

DiBiase, D.; Prasad, S.

2014-12-01

The reformation of the "Object Formerly Known as Textbook" (coined by the Chronicle of Higher Education) toward a digital future is underway. Emerging nextgen texts look less like electronic books ("ebooks") and more like online courseware. In addition to text and illustrations, nextgen textbooks for STEM subjects are likely to combine quizzes, grade management tools, support for social learning, and interactive media including web maps. Web maps are interactive, multi-scale, online maps that enable teachers and learners to explore, interrogate, and mash up the wide variety of map layers available in the cloud. This presentation will show how web maps coupled with interactive quizzes enable students' purposeful explorations and interpretations of spatial patterns related to humankind's interactions with the earth. Attendees will also learn about Esri's offer to donate ArcGIS Online web mapping subscriptions to every U.S. school as part of the President Obama's ConnectED initiative.

Altruistic learning.

PubMed

Seymour, Ben; Yoshida, Wako; Dolan, Ray

2009-01-01

The origin of altruism remains one of the most enduring puzzles of human behaviour. Indeed, true altruism is often thought either not to exist, or to arise merely as a miscalculation of otherwise selfish behaviour. In this paper, we argue that altruism emerges directly from the way in which distinct human decision-making systems learn about rewards. Using insights provided by neurobiological accounts of human decision-making, we suggest that reinforcement learning in game-theoretic social interactions (habitisation over either individuals or games) and observational learning (either imitative of inference based) lead to altruistic behaviour. This arises not only as a result of computational efficiency in the face of processing complexity, but as a direct consequence of optimal inference in the face of uncertainty. Critically, we argue that the fact that evolutionary pressure acts not over the object of learning ('what' is learned), but over the learning systems themselves ('how' things are learned), enables the evolution of altruism despite the direct threat posed by free-riders.

Early object labels: the case for a developmental lexical principles framework.

PubMed

Golinkoff, R M; Mervis, C B; Hirsh-Pasek, K

1994-02-01

Universally, object names make up the largest proportion of any word type found in children's early lexicons. Here we present and critically evaluate a set of six lexical principles (some previously proposed and some new) for making object label learning a manageable task. Overall, the principles have the effect of reducing the amount of information that language-learning children must consider for what a new word might mean. These principles are constructed by children in a two-tiered developmental sequence, as a function of their sensitivity to linguistic input, contextual information, and social-interactional cues. Thus, the process of lexical acquisition changes as a result of the particular principles a given child has at his or her disposal. For children who have only the principles of the first tier (reference, extendibility, and object scope), word learning has a deliberate and laborious look. The principles of the second tier (categorical scope, novel name-nameless category' or N3C, and conventionality) enable the child to acquire many new labels rapidly. The present unified account is argued to have a number of advantages over treating such principles separately and non-developmentally. Further, the explicit recognition that the acquisition and operation of these principles is influenced by the child's interpretation of both linguistic and non-linguistic input is seen as an advance.

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

Eads, Damian Ryan; Rosten, Edward; Helmbold, David

The authors present BEAMER: a new spatially exploitative approach to learning object detectors which shows excellent results when applied to the task of detecting objects in greyscale aerial imagery in the presence of ambiguous and noisy data. There are four main contributions used to produce these results. First, they introduce a grammar-guided feature extraction system, enabling the exploration of a richer feature space while constraining the features to a useful subset. This is specified with a rule-based generative grammer crafted by a human expert. Second, they learn a classifier on this data using a newly proposed variant of AdaBoost whichmore » takes into account the spatially correlated nature of the data. Third, they perform another round of training to optimize the method of converting the pixel classifications generated by boosting into a high quality set of (x,y) locations. lastly, they carefully define three common problems in object detection and define two evaluation criteria that are tightly matched to these problems. Major strengths of this approach are: (1) a way of randomly searching a broad feature space, (2) its performance when evaluated on well-matched evaluation criteria, and (3) its use of the location prediction domain to learn object detectors as well as to generate detections that perform well on several tasks: object counting, tracking, and target detection. They demonstrate the efficacy of BEAMER with a comprehensive experimental evaluation on a challenging data set.« less

System light-loading technology for mHealth: Manifold-learning-based medical data cleansing and clinical trials in WE-CARE Project.

PubMed

Huang, Anpeng; Xu, Wenyao; Li, Zhinan; Xie, Linzhen; Sarrafzadeh, Majid; Li, Xiaoming; Cong, Jason

2014-09-01

Cardiovascular disease (CVD) is a major issue to public health. It contributes 41% to the Chinese death rate each year. This huge loss encouraged us to develop a Wearable Efficient teleCARdiology systEm (WE-CARE) for early warning and prevention of CVD risks in real time. WE-CARE is expected to work 24/7 online for mobile health (mHealth) applications. Unfortunately, this purpose is often disrupted in system experiments and clinical trials, even if related enabling technologies work properly. This phenomenon is rooted in the overload issue of complex Electrocardiogram (ECG) data in terms of system integration. In this study, our main objective is to get a system light-loading technology to enable mHealth with a benchmarked ECG anomaly recognition rate. To achieve this objective, we propose an approach to purify clinical features from ECG raw data based on manifold learning, called the Manifold-based ECG-feature Purification algorithm. Our clinical trials verify that our proposal can detect anomalies with a recognition rate of up to 94% which is highly valuable in daily public health-risk alert applications based on clinical criteria. Most importantly, the experiment results demonstrate that the WE-CARE system enabled by our proposal can enhance system reliability by at least two times and reduce false negative rates to 0.76%, and extend the battery life by 40.54%, in the system integration level.

A way forward for teaching and learning of Physiology: Students’ perception of the effectiveness of teaching methodologies

PubMed Central

Rehan, Rabiya; Ahmed, Khalid; Khan, Hira; Rehman, Rehana

2016-01-01

Objective: To compare the perception of medical students on the usefulness of the interactive lectures, case-based lectures, and structured interactive sessions (SIS) in teaching and learning of Physiology. Methods: A cross-sectional study was carried out from January to December 2012 at Bahria University Medical & Dental College, Karachi, which had qualitative and quantitative aspects, assessed by self- reported questionnaire and focused group discussion (FGD). The questionnaire was distributed to 100 medical students after completion of first year of teaching of MBBS Physiology. The data was analyzed using SPSS version 15. Differences were considered significant at p-values <0.05 after application of Friedman test. Responses of FGD were analyzed. Results: All the teaching methodologies helped in understanding of precise learning objectives. The comprehension of structure and functions with understanding of difficult concepts was made best possible by SIS (p=0.04, p<0.01). SIS enabled adult learning, self-directed learning, peer learning and critical reasoning more than the other teaching strategies (p< 0.01). Conclusion: SIS involved students who used reasoning skills and power of discussion in a group to comprehend difficult concepts for better understanding of Physiology as compared to interactive and case-based lectures. PMID:28083047

Commentary: Academic Enablers and School Learning.

ERIC Educational Resources Information Center

Keith, Timothy Z.

2002-01-01

This commentary presents academic enablers within the broader, overlapping context of school learning theory, including the theories of Carroll, Harnishfeger and Wiley, Walberg, and others. Multivariate models are needed to understand the influences of academic enabler and school learning variables on learning, as well as the influences of these…

Learning for VMM + WTA Embedded Classifiers

DTIC Science & Technology

2016-03-31

enabling correct classification of each novel acoustic signal (generator, idle car , and idle truck). The classification structure requires, after...measured on our SoC FPAA IC. The test input is composed of signals from urban environment for 3 objects (generator, idle car , and idle truck...classifier results from a rural truck data set, an urban generator set, and urban idle car dataset. Solid lines represent our extracted background

The Effect of 3D Virtual Learning Environment on Secondary School Third Grade Students' Attitudes toward Mathematics

ERIC Educational Resources Information Center

Simsek, Irfan

2016-01-01

With this research, in Second Life environment which is a three dimensional online virtual world, it is aimed to reveal the effects of student attitudes toward mathematics courses and design activities which will enable the third grade students of secondary school (primary education seventh grade) to see the 3D objects in mathematics courses in a…

Learning the Language of Healthcare Enabling Semantic Web Technology in CHCS

DTIC Science & Technology

2013-09-01

tuples”, (subject, predicate, object), to relate data and achieve semantic interoperability . Other similar technologies exist, but their... Semantic Healthcare repository [5]. Ultimately, both of our data approaches were successful. However, our current test system is based on the CPRS demo...to extract system dependencies and workflows; to extract semantically related patient data ; and to browse patient- centric views into the system . We

A Passive Learning Sensor Architecture for Multimodal Image Labeling: An Application for Social Robots.

PubMed

Gutiérrez, Marco A; Manso, Luis J; Pandya, Harit; Núñez, Pedro

2017-02-11

Object detection and classification have countless applications in human-robot interacting systems. It is a necessary skill for autonomous robots that perform tasks in household scenarios. Despite the great advances in deep learning and computer vision, social robots performing non-trivial tasks usually spend most of their time finding and modeling objects. Working in real scenarios means dealing with constant environment changes and relatively low-quality sensor data due to the distance at which objects are often found. Ambient intelligence systems equipped with different sensors can also benefit from the ability to find objects, enabling them to inform humans about their location. For these applications to succeed, systems need to detect the objects that may potentially contain other objects, working with relatively low-resolution sensor data. A passive learning architecture for sensors has been designed in order to take advantage of multimodal information, obtained using an RGB-D camera and trained semantic language models. The main contribution of the architecture lies in the improvement of the performance of the sensor under conditions of low resolution and high light variations using a combination of image labeling and word semantics. The tests performed on each of the stages of the architecture compare this solution with current research labeling techniques for the application of an autonomous social robot working in an apartment. The results obtained demonstrate that the proposed sensor architecture outperforms state-of-the-art approaches.

Leveraging Large-Scale Semantic Networks for Adaptive Robot Task Learning and Execution.

PubMed

Boteanu, Adrian; St Clair, Aaron; Mohseni-Kabir, Anahita; Saldanha, Carl; Chernova, Sonia

2016-12-01

This work seeks to leverage semantic networks containing millions of entries encoding assertions of commonsense knowledge to enable improvements in robot task execution and learning. The specific application we explore in this project is object substitution in the context of task adaptation. Humans easily adapt their plans to compensate for missing items in day-to-day tasks, substituting a wrap for bread when making a sandwich, or stirring pasta with a fork when out of spoons. Robot plan execution, however, is far less robust, with missing objects typically leading to failure if the robot is not aware of alternatives. In this article, we contribute a context-aware algorithm that leverages the linguistic information embedded in the task description to identify candidate substitution objects without reliance on explicit object affordance information. Specifically, we show that the task context provided by the task labels within the action structure of a task plan can be leveraged to disambiguate information within a noisy large-scale semantic network containing hundreds of potential object candidates to identify successful object substitutions with high accuracy. We present two extensive evaluations of our work on both abstract and real-world robot tasks, showing that the substitutions made by our system are valid, accepted by users, and lead to a statistically significant reduction in robot learning time. In addition, we report the outcomes of testing our approach with a large number of crowd workers interacting with a robot in real time.

Knowledge acquisition and learning process description in context of e-learning

NASA Astrophysics Data System (ADS)

Kiselev, B. G.; Yakutenko, V. A.; Yuriev, M. A.

2017-01-01

This paper investigates the problem of design of e-learning and MOOC systems. It describes instructional design-based approaches to e-learning systems design: IMS Learning Design, MISA and TELOS. To solve this problem we present Knowledge Field of Educational Environment with Competence boundary conditions - instructional engineering method for self-learning systems design. It is based on the simplified TELOS approach and enables a user to create their individual learning path by choosing prerequisite and target competencies. The paper provides the ontology model for the described instructional engineering method, real life use cases and the classification of the presented model. Ontology model consists of 13 classes and 15 properties. Some of them are inherited from Knowledge Field of Educational Environment and some are new and describe competence boundary conditions and knowledge validation objects. Ontology model uses logical constraints and is described using OWL 2 standard. To give TELOS users better understanding of our approach we list mapping between TELOS and KFEEC.

Real-Time Indoor Scene Description for the Visually Impaired Using Autoencoder Fusion Strategies with Visible Cameras.

PubMed

Malek, Salim; Melgani, Farid; Mekhalfi, Mohamed Lamine; Bazi, Yakoub

2017-11-16

This paper describes three coarse image description strategies, which are meant to promote a rough perception of surrounding objects for visually impaired individuals, with application to indoor spaces. The described algorithms operate on images (grabbed by the user, by means of a chest-mounted camera), and provide in output a list of objects that likely exist in his context across the indoor scene. In this regard, first, different colour, texture, and shape-based feature extractors are generated, followed by a feature learning step by means of AutoEncoder (AE) models. Second, the produced features are fused and fed into a multilabel classifier in order to list the potential objects. The conducted experiments point out that fusing a set of AE-learned features scores higher classification rates with respect to using the features individually. Furthermore, with respect to reference works, our method: (i) yields higher classification accuracies, and (ii) runs (at least four times) faster, which enables a potential full real-time application.

Simplify and Accelerate Earth Science Data Preparation to Systemize Machine Learning

NASA Astrophysics Data System (ADS)

Kuo, K. S.; Rilee, M. L.; Oloso, A.

2017-12-01

Data preparation is the most laborious and time-consuming part of machine learning. The effort required is usually more than linearly proportional to the varieties of data used. From a system science viewpoint, useful machine learning in Earth Science likely involves diverse datasets. Thus, simplifying data preparation to ease the systemization of machine learning in Earth Science is of immense value. The technologies we have developed and applied to an array database, SciDB, are explicitly designed for the purpose, including the innovative SpatioTemporal Adaptive-Resolution Encoding (STARE), a remapping tool suite, and an efficient implementation of connected component labeling (CCL). STARE serves as a universal Earth data representation that homogenizes data varieties and facilitates spatiotemporal data placement as well as alignment, to maximize query performance on massively parallel, distributed computing resources for a major class of analysis. Moreover, it converts spatiotemporal set operations into fast and efficient integer interval operations, supporting in turn moving-object analysis. Integrative analysis requires more than overlapping spatiotemporal sets. For example, meaningful comparison of temperature fields obtained with different means and resolutions requires their transformation to the same grid. Therefore, remapping has been implemented to enable integrative analysis. Finally, Earth Science investigations are generally studies of phenomena, e.g. tropical cyclone, atmospheric river, and blizzard, through their associated events, like hurricanes Katrina and Sandy. Unfortunately, except for a few high-impact phenomena, comprehensive episodic records are lacking. Consequently, we have implemented an efficient CCL tracking algorithm, enabling event-based investigations within climate data records beyond mere event presence. In summary, we have implemented the core unifying capabilities on a Big Data technology to enable systematic machine learning in Earth Science.

A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning.

PubMed

Windridge, David; Felsberg, Michael; Shaukat, Affan

2013-02-01

Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

Framing ICT-Enabled Innovation for Learning: The Case of One-to-One Learning Initiatives in Europe

ERIC Educational Resources Information Center

Bocconi, Stefania; Kampylis, Panagiotis; Punie, Yves

2013-01-01

This article discusses 1:1 learning initiatives in Europe in the context of a mapping framework of ICT-enabled innovation for learning. The aim of the framework, visualised as a spider's web, is two-fold: (i) to provide a further understanding of the nature of ICT-enabled innovation for learning; and (ii) to depict the impact of existing and…

Optimizing Virtual Network Functions Placement in Virtual Data Center Infrastructure Using Machine Learning

NASA Astrophysics Data System (ADS)

Bolodurina, I. P.; Parfenov, D. I.

2018-01-01

We have elaborated a neural network model of virtual network flow identification based on the statistical properties of flows circulating in the network of the data center and characteristics that describe the content of packets transmitted through network objects. This enabled us to establish the optimal set of attributes to identify virtual network functions. We have established an algorithm for optimizing the placement of virtual data functions using the data obtained in our research. Our approach uses a hybrid method of visualization using virtual machines and containers, which enables to reduce the infrastructure load and the response time in the network of the virtual data center. The algorithmic solution is based on neural networks, which enables to scale it at any number of the network function copies.

Learning in the workplace: the role of Nurse Managers.

PubMed

Yen, Margaret; Trede, Franziska; Patterson, Carmel

2016-06-01

Objective This research explores Nurse Managers' (NMs') influence on workplace learning. The facilitation of staff learning has implications for the role of NMs, who are responsible for the quality and safety of patient care. However, this aspect of their work is implicit and there is limited research in the area. Methods This paper discusses the findings from one hospital as part of a broader philosophical hermeneutic study conducted in two public hospitals over a 20-month timeframe. NMs participated in interviews, a period of observation, follow-up interviews and a focus group. Transcribed data was thematically analysed. Eraut's 'Two triangle theory of workplace learning' was used to interpret participants' accounts of how they facilitated workplace learning. Findings The analysis found that NMs worked to positively influence staff performance through learning in three domains: orientating new staff, assessing staff performance and managing underperformance. Conclusions This study purports that NMs influence workplace learning in ways that are seldom recognised. A more conscious understanding of the impact of their role can enable NMs to more purposefully influence workplace learning. Such understanding also has implications for the professional preparation of NMs for their role in the context of workplace learning, facilitating learning for change and enabling the advancement of quality and safety in healthcare. What is known about the topic? Studies exploring the influence of Nurse Managers in workplace learning have been limited to their role in the facilitation of formal learning. There is a paucity of research that examines their role in influencing informal learning. What does this paper add? The findings of this study draw on Eraut's 'Two triangle theory of workplace learning' to further define the interdependent relationship between management and educational practices. What are the implications for practitioners? NMs' awareness and deliberate use of their management role to enhance workplace learning will not only strengthen their role, but will also foster good learning environments and quality nursing services.

Glucose metabolism from mouth to muscle: a student experiment to teach glucose metabolism during exercise and rest.

PubMed

Engeroff, Tobias; Fleckenstein, Johannes; Banzer, Winfried

2017-03-01

We developed an experiment to help students understand basic regulation of postabsorptive and postprandial glucose metabolism and the availability of energy sources for physical activity in the fed and fasted state. Within a practical session, teams of two or three students (1 subject and 1 or 2 investigators) performed one of three different trials: 1) inactive, in which subjects ingested a glucose solution (75 g in 300 ml of water) and rested in the seated position until the end of the trial; 2) prior activity, in which the subject performed 15 min of walking before glucose ingestion and a subsequent resting phase; and 3) postactivity, in which the subject ingested glucose solution, walked (15 min), and rested afterwards. Glucose levels were drawn before trials (fasting value), immediately after glucose ingestion (0 min), and 5, 10, 15, 20, 25, 30, 40, 50, and 60 min thereafter. Students analyzed glucose values and worked on 12 tasks. Students evaluated the usefulness of the experiment; 54.2% of students found the experiment useful to enable them to gain a further understanding of the learning objectives and to clarify items, and 44.1% indicated that the experiment was necessary to enable them to understand the learning objectives. For 6.8% the experiment was not necessary but helpful to check what they had learned, and 3.4% found that the experiment was not necessary. The present article shows the great value of experiments within practical courses to help students gain knowledge of energy metabolism. Using an active learning strategy, students outworked complex physiological tasks and improved beneficial communication and interaction between students with different skill sets and problem-solving strategies. Copyright © 2017 the American Physiological Society.

A presentation system for just-in-time learning in radiology.

PubMed

Kahn, Charles E; Santos, Amadeu; Thao, Cheng; Rock, Jayson J; Nagy, Paul G; Ehlers, Kevin C

2007-03-01

There is growing interest in bringing medical educational materials to the point of care. We sought to develop a system for just-in-time learning in radiology. A database of 34 learning modules was derived from previously published journal articles. Learning objectives were specified for each module, and multiple-choice test items were created. A web-based system-called TEMPO-was developed to allow radiologists to select and view the learning modules. Web services were used to exchange clinical context information between TEMPO and the simulated radiology work station. Preliminary evaluation was conducted using the System Usability Scale (SUS) questionnaire. TEMPO identified learning modules that were relevant to the age, sex, imaging modality, and body part or organ system of the patient being viewed by the radiologist on the simulated clinical work station. Users expressed a high degree of satisfaction with the system's design and user interface. TEMPO enables just-in-time learning in radiology, and can be extended to create a fully functional learning management system for point-of-care learning in radiology.

Advanced miniature processing handware for ATR applications

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor); Daud, Taher (Inventor); Thakoor, Anikumar (Inventor)

2003-01-01

A Hybrid Optoelectronic Neural Object Recognition System (HONORS), is disclosed, comprising two major building blocks: (1) an advanced grayscale optical correlator (OC) and (2) a massively parallel three-dimensional neural-processor. The optical correlator, with its inherent advantages in parallel processing and shift invariance, is used for target of interest (TOI) detection and segmentation. The three-dimensional neural-processor, with its robust neural learning capability, is used for target classification and identification. The hybrid optoelectronic neural object recognition system, with its powerful combination of optical processing and neural networks, enables real-time, large frame, automatic target recognition (ATR).

Field Testing of Utility Robots for Lunar Surface Operations

NASA Technical Reports Server (NTRS)

Fong, Terrence; Bualat, Maria; Deans, Matt; Allan, Mark; Bouyssounouse, Xavier; Broxton, Michael; Edwards, Laurence; Lee, Pascal; Lee, Susan Y.; Lees, David;

NASA's Universe of Learning: Engaging Learners in Discovery

NASA Astrophysics Data System (ADS)

Cominsky, L.; Smith, D. A.; Lestition, K.; Greene, M.; Squires, G.

2016-12-01

NASA's Universe of Learning is one of 27 competitively awarded education programs selected by NASA's Science Mission Directorate (SMD) to enable scientists and engineers to more effectively engage with learners of all ages. The NASA's Universe of Learning program is created through a partnership between the Space Telescope Science Institute, Chandra X-ray Center, IPAC at Caltech, Jet Propulsion Laboratory Exoplanet Exploration Program, and Sonoma State University. The program will connect the scientists, engineers, science, technology and adventure of NASA Astrophysics with audience needs, proven infrastructure, and a network of over 500 partners to advance the objectives of SMD's newly restructured education program. The multi-institutional team will develop and deliver a unified, consolidated suite of education products, programs, and professional development offerings that spans the full spectrum of NASA Astrophysics, including the Exoplanet Exploration theme. Program elements include enabling educational use of Astrophysics mission data and offering participatory experiences; creating multimedia and immersive experiences; designing exhibits and community programs; providing professional development for pre-service educators, undergraduate instructors, and informal educators; and, producing resources for special needs and underserved/underrepresented audiences. This presentation will provide an overview of the program and process for mapping discoveries to products and programs for informal, lifelong, and self-directed learning environments.

Technology Enabled Learning. Symposium.

ERIC Educational Resources Information Center

2002

This document contains three papers on technology-enabled learning and human resource development. Among results found in "Current State of Technology-enabled Learning Programs in Select Federal Government Organizations: a Case Study of Ten Organizations" (Letitia A. Combs) are the following: the dominant delivery method is traditional…

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.

Enabling Software Acquisition Improvement: Government and Industry Software Development Team Acquisition Model

DTIC Science & Technology

2010-04-30

estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources , gathering and maintaining...previous and current complex SW development efforts, the program offices will have a source of objective lessons learned and metrics that can be applied...the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this

Clinical governance in Scotland: an educational model.

PubMed Central

Lough, Murray; Kelly, Diane; Taylor, Mike; Snadden, David; Patterson, Bill; McNamara, Iain; Murray, Stuart

2002-01-01

The concepts underpinning clinical governance are similar throughout the United Kingdom but models for its implementation will differ widely. This model aims to enable practices to identify areas for further learning and development against specific outcomes. Criteria sets and standards are suggested and a governance plan is used to allow practices to prioritise their objectives. Resourcing will always be a major issue and such a model should be fully evaluated. PMID:11942453

Clinical governance in Scotland: an educational model.

PubMed

Lough, Murray; Kelly, Diane; Taylor, Mike; Snadden, David; Patterson, Bill; McNamara, Iain; Murray, Stuart

2002-04-01

The concepts underpinning clinical governance are similar throughout the United Kingdom but models for its implementation will differ widely. This model aims to enable practices to identify areas for further learning and development against specific outcomes. Criteria sets and standards are suggested and a governance plan is used to allow practices to prioritise their objectives. Resourcing will always be a major issue and such a model should be fully evaluated.

The New South Wales Allied Health Workplace Learning Study: barriers and enablers to learning in the workplace.

PubMed

Lloyd, Bradley; Pfeiffer, Daniella; Dominish, Jacqueline; Heading, Gaynor; Schmidt, David; McCluskey, Annie

2014-03-25

Workplace learning refers to continuing professional development that is stimulated by and occurs through participation in workplace activities. Workplace learning is essential for staff development and high quality clinical care. The purpose of this study was to explore the barriers to and enablers of workplace learning for allied health professionals within NSW Health. A qualitative study was conducted with a purposively selected maximum variation sample (n =46) including 19 managers, 19 clinicians and eight educators from 10 allied health professions. Seven semi-structured interviews and nine focus groups were audio-recorded and transcribed. The 'framework approach' was used to guide the interviews and analysis. Textual data were coded and charted using an evolving thematic framework. Key enablers of workplace learning included having access to peers, expertise and 'learning networks', protected learning time, supportive management and positive staff attitudes. The absence of these key enablers including heavy workload and insufficient staffing were important barriers to workplace learning. Attention to these barriers and enablers may help organisations to more effectively optimise allied health workplace learning. Ultimately better workplace learning may lead to improved patient, staff and organisational outcomes.

The New South Wales Allied Health Workplace Learning Study: barriers and enablers to learning in the workplace

PubMed Central

2014-01-01

Background Workplace learning refers to continuing professional development that is stimulated by and occurs through participation in workplace activities. Workplace learning is essential for staff development and high quality clinical care. The purpose of this study was to explore the barriers to and enablers of workplace learning for allied health professionals within NSW Health. Methods A qualitative study was conducted with a purposively selected maximum variation sample (n = 46) including 19 managers, 19 clinicians and eight educators from 10 allied health professions. Seven semi-structured interviews and nine focus groups were audio-recorded and transcribed. The ‘framework approach’ was used to guide the interviews and analysis. Textual data were coded and charted using an evolving thematic framework. Results Key enablers of workplace learning included having access to peers, expertise and ‘learning networks’, protected learning time, supportive management and positive staff attitudes. The absence of these key enablers including heavy workload and insufficient staffing were important barriers to workplace learning. Conclusion Attention to these barriers and enablers may help organisations to more effectively optimise allied health workplace learning. Ultimately better workplace learning may lead to improved patient, staff and organisational outcomes. PMID:24661614

Experiential learning in nursing consultation education via clinical simulation with actors: action research.

PubMed

de Oliveira, Saionara Nunes; do Prado, Marta Lenise; Kempfer, Silvana Silveira; Martini, Jussara Gue; Caravaca-Morera, Jaime Alonso; Bernardi, Mariely Carmelina

2015-02-01

This was an action research study conducted during an undergraduate nursing course. The objective was to propose and implement experiential learning for nursing consultation education using clinical simulation with actors. The 4 steps of action research were followed: planning, action, observation and reflection. Three nursing undergraduate students participated in the study. Data were collected in May and July 2013 via participant comments and interviews and were analyzed in accordance with the operative proposal for qualitative data analysis. Planning included constructing and validating the clinical guides, selecting and training the actors, organizing and preparing the scenario and the issuing invitations to the participants. The action was carried out according to Kolb's (1984) 4 stages of learning cycles: Concrete Experience, Reflective Observation, Abstract Conceptualization and Active Experimentation. Clinical simulation involves different subjects' participation in all stages, and action research is a method that enables the clinical stimulation to be implemented. It must be guided by clear learning objectives and by a critical pedagogy that encourages critical thinking in students. Using actors and a real scenario facilitated psychological fidelity, and debriefing was the key moment of the reflective process that facilitated the integral training of students through experiential learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Anselmi, Fabio; Poggio, Tomaso

2015-01-01

Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. PMID:26496457

Managing clinical failure: a complex adaptive system perspective.

PubMed

Matthews, Jean I; Thomas, Paul T

2007-01-01

The purpose of this article is to explore the knowledge capture process at the clinical level. It aims to identify factors that enable or constrain learning. The study applies complex adaptive system thinking principles to reconcile learning within the NHS. The paper uses a qualitative exploratory study with an interpretative methodological stance set in a secondary care NHS Trust. Semi-structured interviews were conducted with healthcare practitioners and managers involved at both strategic and operational risk management processes. A network structure is revealed that exhibits the communication and interdependent working practices to support knowledge capture and adaptive learning. Collaborative multidisciplinary communities, whose values reflect local priorities and promote open dialogue and reflection, are featured. The main concern is that the characteristics of bureaucracy; rational-legal authority, a rule-based culture, hierarchical lines of communication and a centralised governance focus, are hindering clinical learning by generating barriers. Locally emergent collaborative processes are a key strategic resource to capture knowledge, potentially fostering an environment that could learn from failure and translate lessons between contexts. What must be addressed is that reporting mechanisms serve not only the governance objectives, but also supplement learning by highlighting the potential lessons in context. Managers must nurture a collaborative infrastructure using networks in a co-evolutionary manner. Their role is not to direct and design processes but to influence, support and create effective knowledge capture. Although the study only investigated one site the findings and conclusions may well translate to other trusts--such as the risk of not enabling a learning environment at clinical levels.

Design and Evaluation of a Cross-Cultural Training System

NASA Technical Reports Server (NTRS)

Santarelli, Thomas; Stagl, Kevin C.

2011-01-01

Cross-cultural competency, and the underlying communication and affective skills required to develop such expertise, is becoming increasingly important for a wide variety of domains. To address this need, we developed a blended learning platform which combines virtual role-play with tutorials, assessment and feedback. A Middle-Eastern Curriculum (MEC) exemplar for cross-cultural training U.S. military personnel was developed to guide the refinement of an existing game-based training platform. To complement this curriculum, we developed scenario authoring tools to enable end-users to define training objectives, link performance measures and feedback/remediation to these objectives, and deploy experiential scenarios within a game-based virtual environment (VE). Lessons learned from the design and development of this exemplar cross-cultural competency curriculum, as well as formative evaluation results, are discussed. Initial findings suggest that the underlying training technology promotes deep levels of semantic processing of the key information of relevant cultural and communication skills.

Access to oral health care services among adults with learning disabilities: a scoping review

PubMed Central

Naseem, Mustafa; Shah, Altaf H; Khiyani, Muhammad Faheem; Khurshid, Zohaib; Zafar, Muhammad Sohail; Gulzar, Shabnam; AlJameel, AlBandary H.; Khalil, Hesham S.

2016-01-01

Summary Background The prevalence of oral diseases including dental caries and periodontal conditions is remarkably higher in people with disabilities. The provision of accessible oral health services for people with learning disabilities may be challenging. Objectives The objectives of the review were to identify barriers in accessing oral health care that persists within society, enabling or disabling people with learning disabilities. Methods Using the Arksey O’Malley framework, a scoping review was conducted on PubMed/Medline, OVIDSP, and EMBASE. Studies were evaluated and short-listed based on the inclusion criteria, which consisted of: (1) study participants or population with learning disabilities, (2) aged 16 years or over, (3) reporting on access to oral health services, (4) published in the English language. Those that justified the inclusion criteria were carefully chosen after a blind peer-reviewed process when relevance and quality were debated. Results Nine studies were eventually included from searches. Tabulation of data was done under the heading of study type, outcomes, the year of publication and patient selection. The majority of studies provided a biomedical overview of access for adults with learning disabilities. Conclusions The concept of access for people with disability is still ill-defined and obscure. Access to oral health care and needs of people with learning disabilities are complex and multi-facet. PMID:28149451

Investigating the Educational Value of Social Learning Networks: A Quantitative Analysis

ERIC Educational Resources Information Center

Dafoulas, Georgios; Shokri, Azam

2016-01-01

Purpose: The emergence of Education 2.0 enabled technology-enhanced learning, necessitating new pedagogical approaches, while e-learning has evolved into an instrumental pedagogy of collaboration through affordances of social media. Social learning networks and ubiquitous learning enabled individual and group learning through social engagement and…

How Does Technology-Enabled Active Learning Affect Undergraduate Students' Understanding of Electromagnetism Concepts?

ERIC Educational Resources Information Center

Dori, Yehudit Judy; Belcher, John

2005-01-01

Educational technology supports meaningful learning and enables the presentation of spatial and dynamic images, which portray relationships among complex concepts. The Technology-Enabled Active Learning (TEAL) Project at the Massachusetts Institute of Technology (MIT) involves media-rich software for simulation and visualization in freshman…

A neural framework for organization and flexible utilization of episodic memory in cumulatively learning baby humanoids.

PubMed

Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro

2014-12-01

Cumulatively developing robots offer a unique opportunity to reenact the constant interplay between neural mechanisms related to learning, memory, prospection, and abstraction from the perspective of an integrated system that acts, learns, remembers, reasons, and makes mistakes. Situated within such interplay lie some of the computationally elusive and fundamental aspects of cognitive behavior: the ability to recall and flexibly exploit diverse experiences of one's past in the context of the present to realize goals, simulate the future, and keep learning further. This article is an adventurous exploration in this direction using a simple engaging scenario of how the humanoid iCub learns to construct the tallest possible stack given an arbitrary set of objects to play with. The learning takes place cumulatively, with the robot interacting with different objects (some previously experienced, some novel) in an open-ended fashion. Since the solution itself depends on what objects are available in the "now," multiple episodes of past experiences have to be remembered and creatively integrated in the context of the present to be successful. Starting from zero, where the robot knows nothing, we explore the computational basis of organization episodic memory in a cumulatively learning humanoid and address (1) how relevant past experiences can be reconstructed based on the present context, (2) how multiple stored episodic memories compete to survive in the neural space and not be forgotten, (3) how remembered past experiences can be combined with explorative actions to learn something new, and (4) how multiple remembered experiences can be recombined to generate novel behaviors (without exploration). Through the resulting behaviors of the robot as it builds, breaks, learns, and remembers, we emphasize that mechanisms of episodic memory are fundamental design features necessary to enable the survival of autonomous robots in a real world where neither everything can be known nor can everything be experienced.

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…

Expanded Concepts of the School Library Media Center; Narrative Evaluation Report on the Institute for Advanced Study for Librarians...University of Washington...July 6 to July 17, 1970.

ERIC Educational Resources Information Center

Washington Univ., Seattle. School of Librarianship.

The purpose of the institute was to update school librarians in elementary and secondary schools and enable them to gain competency in the new media. The objectives of the institute were to assist the school librarian in the selection, processing and utilization of nonbook media, to learn simple techniques in production of materials, and to…

The use of objective structured self-assessment and peer-feedback (OSSP) for learning communication skills: evaluation using a controlled trial.

PubMed

Perera, Jennifer; Mohamadou, Galy; Kaur, Satpal

2010-05-01

Feedback is essential to guide students towards expected performance goals. The usefulness of teacher feedback on improving communication skills (CS) has been well documented. It has been proposed that self-assessment and peer-feedback has an equally important role to play in enhancing learning. This is the focus of this study. Objectively structured self-assessment and peer feedback (OSSP) was incorporated into small group CS teaching sessions of a group of semester one medical students who were learning CS for the first time, to minimise the influence of previous educational interventions. A control group matched for academic performance, gender and age was used to enable parallel evaluation of the innovation. A reflective log containing closed and open ended questions was used for OSSP. Facilitators and simulated patients provided feedback to students in both groups during CS learning as per routine practice. Student perceptions on OSSP and acceptability as a learning method were explored using a questionnaire. CS were assessed in both groups using objective structured clinical examination (OSCE) as per routine practice and assessors were blinded as to which group the student belonged. Mean total score and scores for specific areas of interview skills were significantly higher in the experimental group. Analysis of the questionnaire data showed that students gained fresh insights into specific areas such as empathy, addressing patients' concerns and interview style during OSSP which clearly corroborated the specific differences in scores. The free text comments were highly encouraging as to acceptability of OSSP, in spite of 67% being never exposed to formal self- and peer-assessment during pre-university studies. OSSP promotes effective CS learning and learner acceptability is high.

National standards in pathology education: developing competencies for integrated medical school curricula.

PubMed

Sadofsky, Moshe; Knollmann-Ritschel, Barbara; Conran, Richard M; Prystowsky, Michael B

2014-03-01

Medical school education has evolved from department-specific memorization of facts to an integrated curriculum presenting knowledge in a contextual manner across traditional disciplines, integrating information, improving retention, and facilitating application to clinical practice. Integration occurs throughout medical school using live data-sharing technologies, thereby providing the student with a framework for lifelong active learning. Incorporation of educational teams during medical school prepares students for team-based patient care, which is also required for pay-for-performance models used in accountable care organizations. To develop learning objectives for teaching pathology to medical students. Given the rapid expansion of basic science knowledge of human development, normal function, and pathobiology, it is neither possible nor desirable for faculty to teach, and students to retain, this vast amount of information. Courses teaching the essentials in context and engaging students in the learning process enable them to become lifelong learners. An appreciation of pathobiology and the role of laboratory medicine underlies the modern practice of medicine. As such, all medical students need to acquire 3 basic competencies in pathology: an understanding of disease mechanisms, integration of mechanisms into organ system pathology, and application of pathobiology to diagnostic medicine. We propose the development of 3 specific competencies in pathology to be implemented nationwide, aimed at disease mechanisms/processes, organ system pathology, and application to diagnostic medicine. Each competency will include learning objectives and a means to assess acquisition, integration, and application of knowledge. The learning objectives are designed to be a living document managed (curated) by a group of pathologists representing Liaison Committee on Medical Education-accredited medical schools nationally. Development of a coherent set of learning objectives will assist medical students nationally to gain the basic competencies in pathology necessary for clinical practice. Having national standards for competencies preserves schools' independence in specific curriculum design while assuring all students meet the evolving needs of medical practice.

MFV-class: a multi-faceted visualization tool of object classes.

PubMed

Zhang, Zhi-meng; Pan, Yun-he; Zhuang, Yue-ting

2004-11-01

Classes are key software components in an object-oriented software system. In many industrial OO software systems, there are some classes that have complicated structure and relationships. So in the processes of software maintenance, testing, software reengineering, software reuse and software restructure, it is a challenge for software engineers to understand these classes thoroughly. This paper proposes a class comprehension model based on constructivist learning theory, and implements a software visualization tool (MFV-Class) to help in the comprehension of a class. The tool provides multiple views of class to uncover manifold facets of class contents. It enables visualizing three object-oriented metrics of classes to help users focus on the understanding process. A case study was conducted to evaluate our approach and the toolkit.

Multi-Objective Reinforcement Learning-based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy; Bilen, Sven; Reinhart, Richard; Mortensen, Dale

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

NASA Technical Reports Server (NTRS)

Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

2017-01-01

Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

Semantic Web, Reusable Learning Objects, Personal Learning Networks in Health: Key Pieces for Digital Health Literacy.

PubMed

Konstantinidis, Stathis Th; Wharrad, Heather; Windle, Richard; Bamidis, Panagiotis D

2017-01-01

The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person needs.

The Comparison of Students' Satisfaction between Ubiquitous and Web-Based Learning Environments

ERIC Educational Resources Information Center

Virtanen, Mari Aulikki; Kääriäinen, Maria; Liikanen, Eeva; Haavisto, Elina

2017-01-01

Higher education is moving towards digitalized learning. The rapid development of technological resources, devices and wireless networks enables more flexible opportunities to study and learn in innovative learning environments. New technologies enable combining of authentic and virtual learning spaces and digital resources as multifunctional…

An assessment of implementation of Community-Oriented Primary Care in Kenyan family medicine postgraduate medical education programmes

PubMed Central

Shabani, Jacob; Taché, Stephanie; Mohamoud, Gulnaz; Mahoney, Megan

2016-01-01

Background and objectives Family medicine postgraduate programmes in Kenya are examining the benefits of Community-Oriented Primary Care (COPC) curriculum, as a method to train residents in population-based approaches to health care delivery. Whilst COPC is an established part of family medicine training in the United States, little is known about its application in Kenya. We sought to conduct a qualitative study to explore the development and implementation of COPC curriculum in the first two family medicine postgraduate programmes in Kenya. Method Semi-structured interviews of COPC educators, practitioners, and academic stakeholders and focus groups of postgraduate students were conducted with COPC educators, practitioners and academic stakeholders in two family medicine postgraduate programmes in Kenya. Discussions were transcribed, inductively coded and thematically analysed. Results Two focus groups with eight family medicine postgraduate students and interviews with five faculty members at two universities were conducted. Two broad themes emerged from the analysis: expected learning outcomes and important community-based enablers. Three learning outcomes were (1) making a community diagnosis, (2) understanding social determinants of health and (3) training in participatory research. Three community-based enablers for sustainability of COPC were (1) partnerships with community health workers, (2) community empowerment and engagement and (3) institutional financial support. Conclusions Our findings illustrate the expected learning outcomes and important community-based enablers associated with the successful implementation of COPC projects in Kenya and will help to inform future curriculum development in Kenya. PMID:28155322

a Fully Automated Pipeline for Classification Tasks with AN Application to Remote Sensing

NASA Astrophysics Data System (ADS)

Suzuki, K.; Claesen, M.; Takeda, H.; De Moor, B.

2016-06-01

Nowadays deep learning has been intensively in spotlight owing to its great victories at major competitions, which undeservedly pushed `shallow' machine learning methods, relatively naive/handy algorithms commonly used by industrial engineers, to the background in spite of their facilities such as small requisite amount of time/dataset for training. We, with a practical point of view, utilized shallow learning algorithms to construct a learning pipeline such that operators can utilize machine learning without any special knowledge, expensive computation environment, and a large amount of labelled data. The proposed pipeline automates a whole classification process, namely feature-selection, weighting features and the selection of the most suitable classifier with optimized hyperparameters. The configuration facilitates particle swarm optimization, one of well-known metaheuristic algorithms for the sake of generally fast and fine optimization, which enables us not only to optimize (hyper)parameters but also to determine appropriate features/classifier to the problem, which has conventionally been a priori based on domain knowledge and remained untouched or dealt with naïve algorithms such as grid search. Through experiments with the MNIST and CIFAR-10 datasets, common datasets in computer vision field for character recognition and object recognition problems respectively, our automated learning approach provides high performance considering its simple setting (i.e. non-specialized setting depending on dataset), small amount of training data, and practical learning time. Moreover, compared to deep learning the performance stays robust without almost any modification even with a remote sensing object recognition problem, which in turn indicates that there is a high possibility that our approach contributes to general classification problems.

Clinical data miner: an electronic case report form system with integrated data preprocessing and machine-learning libraries supporting clinical diagnostic model research.

PubMed

Installé, Arnaud Jf; Van den Bosch, Thierry; De Moor, Bart; Timmerman, Dirk

2014-10-20

Using machine-learning techniques, clinical diagnostic model research extracts diagnostic models from patient data. Traditionally, patient data are often collected using electronic Case Report Form (eCRF) systems, while mathematical software is used for analyzing these data using machine-learning techniques. Due to the lack of integration between eCRF systems and mathematical software, extracting diagnostic models is a complex, error-prone process. Moreover, due to the complexity of this process, it is usually only performed once, after a predetermined number of data points have been collected, without insight into the predictive performance of the resulting models. The objective of the study of Clinical Data Miner (CDM) software framework is to offer an eCRF system with integrated data preprocessing and machine-learning libraries, improving efficiency of the clinical diagnostic model research workflow, and to enable optimization of patient inclusion numbers through study performance monitoring. The CDM software framework was developed using a test-driven development (TDD) approach, to ensure high software quality. Architecturally, CDM's design is split over a number of modules, to ensure future extendability. The TDD approach has enabled us to deliver high software quality. CDM's eCRF Web interface is in active use by the studies of the International Endometrial Tumor Analysis consortium, with over 4000 enrolled patients, and more studies planned. Additionally, a derived user interface has been used in six separate interrater agreement studies. CDM's integrated data preprocessing and machine-learning libraries simplify some otherwise manual and error-prone steps in the clinical diagnostic model research workflow. Furthermore, CDM's libraries provide study coordinators with a method to monitor a study's predictive performance as patient inclusions increase. To our knowledge, CDM is the only eCRF system integrating data preprocessing and machine-learning libraries. This integration improves the efficiency of the clinical diagnostic model research workflow. Moreover, by simplifying the generation of learning curves, CDM enables study coordinators to assess more accurately when data collection can be terminated, resulting in better models or lower patient recruitment costs.

Training a medical workforce to meet the needs of diverse minority communities.

PubMed

Sopoaga, Faafetai; Zaharic, Tony; Kokaua, Jesse; Covello, Sahra

2017-01-21

The growing demand for a competent health workforce to meet the needs of increasingly diverse societies has been widely acknowledged. One medical school in New Zealand explored the integration of the commonly used patient-centred model approach, with an intersectional framework in the development of a cultural competency training programme. In the Pacific Immersion Programme, medical students in their fourth year of training are given the opportunity to learn about different factors that influence the health and health care of a minority community through immersion in that community. The programme objectives include enabling students to learn through experience living within the local community context, and supporting them to re-evaluate their own personal beliefs, assumptions and/or prior prejudices. This study evaluates the usefulness of this programme in the training of medical students to work in diverse communities. Two analytical approaches were used for evaluation. Deductive and inductive analyses were conducted on 235 reflective essays completed by three cohorts of students from 2011 to 2013 to ascertain the value of the programme for student learning. In addition, one cohort was invited to complete a pre and post-programme questionnaire. Overall, the students found the programme to be a valued learning environment. They found living within a Pacific family environment to be an eye opening experience. It increased students comfort level in cross cultural engagement and emphasised the importance of patient's perspectives in health care provision. Students' self-reported knowledge about Pacific cultural values, protocols, traditional beliefs and the main health challenges increased significantly after the programme. They appreciated learning directly from community members, and through observations about how culture, beliefs and the socio-economic environment influence peoples' health and wellbeing. Medical schools are required to train a competent health workforce to meet the needs of diverse communities. The Pacific Immersion Programme provides a unique learning environment which can improve the training of doctors to work in diverse communities. The key to its success is enabling students to be engaged learners from "the inside" rather than an "outsider looking in". The Programme enables experiential learning in a sensitive and meaningful way and can be useful for training in other institutions.

Action Learning: Avoiding Conflict or Enabling Action

ERIC Educational Resources Information Center

Corley, Aileen; Thorne, Ann

2006-01-01

Action learning is based on the premise that action and learning are inextricably entwined and it is this potential, to enable action, which has contributed to the growth of action learning within education and management development programmes. However has this growth in action learning lead to an evolution or a dilution of Revan's classical…

Developing Guidelines for Evaluating the Adaptation of Accessible Web-Based Learning Materials

ERIC Educational Resources Information Center

Radovan, Marko; Perdih, Mojca

2016-01-01

E-learning is a rapidly developing form of education. One of the key characteristics of e-learning is flexibility, which enables easier access to knowledge for everyone. Information and communications technology (ICT), which is e-learning's main component, enables alternative means of accessing the web-based learning materials that comprise the…

Exploring Students' Progression in an Inquiry Science Curriculum Enabled by Mobile Learning

ERIC Educational Resources Information Center

Looi, Chee-Kit; Sun, Daner; Xie, Wenting

2015-01-01

The research literature reports on designs of ubiquitous and seamless learning environments enabled by the integration of mobile technology into learning. However, the lack of good pedagogical designs that provide for sustainability and the inadequate investigation of learning outcomes remain major gaps in the current studies on mobile learning.…

Educational gaming in the health sciences: systematic review.

PubMed

Blakely, Gillian; Skirton, Heather; Cooper, Simon; Allum, Peter; Nelmes, Pam

2009-02-01

This paper is a report of a review to investigate the use of games to support classroom learning in the health sciences. One aim of education in the health sciences is to enable learners to develop professional competence. Students have a range of learning styles and innovative teaching strategies assist in creating a dynamic learning environment. New attitudes towards experiential learning methods have contributed to the expansion of gaming as a strategy. A search for studies published between January 1980 and June 2008 was undertaken, using appropriate search terms. The databases searched were: British Education Index, British Nursing Index, The Cochrane Library, CINAHLPlus, Medline, PubMed, ERIC, PsychInfo and Australian Education Index. All publications and theses identified through the search were assessed for relevance. Sixteen papers reporting empirical studies or reviews that involved comparison of gaming with didactic methods were included. The limited research available indicates that, while both traditional didactic methods and gaming have been successful in increasing student knowledge, neither method is clearly more helpful to students. The use of games generally enhances student enjoyment and may improve long-term retention of information. While the use of games can be viewed as a viable teaching strategy, care should be exercised in the use of specific games that have not been assessed objectively. Further research on the use of gaming is needed to enable educators to gaming techniques appropriately for the benefit of students and, ultimately, patients.

A Cyber Enabled Collaborative Environment for Creating, Sharing and Using Data and Modeling Driven Curriculum Modules for Hydrology Education

NASA Astrophysics Data System (ADS)

Merwade, V.; Ruddell, B. L.; Fox, S.; Iverson, E. A. R.

2014-12-01

With the access to emerging datasets and computational tools, there is a need to bring these capabilities into hydrology classrooms. However, developing curriculum modules using data and models to augment classroom teaching is hindered by a steep technology learning curve, rapid technology turnover, and lack of an organized community cyberinfrastructure (CI) for the dissemination, publication, and sharing of the latest tools and curriculum material for hydrology and geoscience education. The objective of this project is to overcome some of these limitations by developing a cyber enabled collaborative environment for publishing, sharing and adoption of data and modeling driven curriculum modules in hydrology and geosciences classroom. The CI is based on Carleton College's Science Education Resource Center (SERC) Content Management System. Building on its existing community authoring capabilities the system is being extended to allow assembly of new teaching activities by drawing on a collection of interchangeable building blocks; each of which represents a step in the modeling process. Currently the system hosts more than 30 modules or steps, which can be combined to create multiple learning units. Two specific units: Unit Hydrograph and Rational Method, have been used in undergraduate hydrology class-rooms at Purdue University and Arizona State University. The structure of the CI and the lessons learned from its implementation, including preliminary results from student assessments of learning will be presented.

A Space-Based Near-Earth Object Survey Telescope in Support of Human Exploration, Solar System Science, and Planetary Defense

NASA Technical Reports Server (NTRS)

Abell, Paul A.

2011-01-01

Human exploration of near-Earth objects (NEOs) beginning in 2025 is one of the stated objectives of U.S. National Space Policy. Piloted missions to these bodies would further development of deep space mission systems and technologies, obtain better understanding of the origin and evolution of our Solar System, and support research for asteroid deflection and hazard mitigation strategies. As such, mission concepts have received much interest from the exploration, science, and planetary defense communities. One particular system that has been suggested by all three of these communities is a space-based NEO survey telescope. Such an asset is crucial for enabling affordable human missions to NEOs circa 2025 and learning about the primordial population of objects that could present a hazard to the Earth in the future.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

Using a computer simulation for teaching communication skills: A blinded multisite mixed methods randomized controlled trial

PubMed Central

Kron, Frederick W.; Fetters, Michael D.; Scerbo, Mark W.; White, Casey B.; Lypson, Monica L.; Padilla, Miguel A.; Gliva-McConvey, Gayle A.; Belfore, Lee A.; West, Temple; Wallace, Amelia M.; Guetterman, Timothy C.; Schleicher, Lauren S.; Kennedy, Rebecca A.; Mangrulkar, Rajesh S.; Cleary, James F.; Marsella, Stacy C.; Becker, Daniel M.

2016-01-01

Objectives To assess advanced communication skills among second-year medical students exposed either to a computer simulation (MPathic-VR) featuring virtual humans, or to a multimedia computer-based learning module, and to understand each group’s experiences and learning preferences. Methods A single-blinded, mixed methods, randomized, multisite trial compared MPathic-VR (N=210) to computer-based learning (N=211). Primary outcomes: communication scores during repeat interactions with MPathic-VR’s intercultural and interprofessional communication scenarios and scores on a subsequent advanced communication skills objective structured clinical examination (OSCE). Multivariate analysis of variance was used to compare outcomes. Secondary outcomes: student attitude surveys and qualitative assessments of their experiences with MPathic-VR or computer-based learning. Results MPathic-VR-trained students improved their intercultural and interprofessional communication performance between their first and second interactions with each scenario. They also achieved significantly higher composite scores on the OSCE than computer-based learning-trained students. Attitudes and experiences were more positive among students trained with MPathic-VR, who valued its providing immediate feedback, teaching nonverbal communication skills, and preparing them for emotion-charged patient encounters. Conclusions MPathic-VR was effective in training advanced communication skills and in enabling knowledge transfer into a more realistic clinical situation. Practice Implications MPathic-VR’s virtual human simulation offers an effective and engaging means of advanced communication training. PMID:27939846

Object-graphs for context-aware visual category discovery.

PubMed

Lee, Yong Jae; Grauman, Kristen

2012-02-01

How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

PubMed

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Video streaming into the mainstream.

PubMed

Garrison, W

2001-12-01

Changes in Internet technology are making possible the delivery of a richer mixture of media through data streaming. High-quality, dynamic content, such as video and audio, can be incorporated into Websites simply, flexibly and interactively. Technologies such as G3 mobile communication, ADSL, cable and satellites enable new ways of delivering medical services, information and learning. Systems such as Quicktime, Windows Media and Real Video provide reliable data streams as video-on-demand and users can tailor the experience to their own interests. The Learning Development Centre at the University of Portsmouth have used streaming technologies together with e-learning tools such as dynamic HTML, Flash, 3D objects and online assessment successfully to deliver on-line course content in economics and earth science. The Lifesign project--to develop, catalogue and stream health sciences media for teaching--is described and future medical applications are discussed.

Exogenous Attention Enables Perceptual Learning

PubMed Central

Szpiro, Sarit F. A.; Carrasco, Marisa

2015-01-01

Practice can improve visual perception, and these improvements are considered to be a form of brain plasticity. Training-induced learning is time-consuming and requires hundreds of trials across multiple days. The process of learning acquisition is understudied. Can learning acquisition be potentiated by manipulating visual attentional cues? We developed a protocol in which we used task-irrelevant cues for between-groups manipulation of attention during training. We found that training with exogenous attention can enable the acquisition of learning. Remarkably, this learning was maintained even when observers were subsequently tested under neutral conditions, which indicates that a change in perception was involved. Our study is the first to isolate the effects of exogenous attention and to demonstrate its efficacy to enable learning. We propose that exogenous attention boosts perceptual learning by enhancing stimulus encoding. PMID:26502745

ATLes: the strategic application of Web-based technology to address learning objectives and enhance classroom discussion in a veterinary pathology course.

PubMed

Hines, Stephen A; Collins, Peggy L; Quitadamo, Ian J; Brahler, C Jayne; Knudson, Cameron D; Crouch, Gregory J

2005-01-01

A case-based program called ATLes (Adaptive Teaching and Learning Environments) was designed for use in a systemic pathology course and implemented over a four-year period. Second-year veterinary students working in small collaborative learning groups used the program prior to their weekly pathology laboratory. The goals of ATLes were to better address specific learning objectives in the course (notably the appreciation of pathophysiology), to solve previously identified problems associated with information overload and information sorting that commonly occur as part of discovery-based processes, and to enhance classroom discussion. The program was also designed to model and allow students to practice the problem-oriented approach to clinical cases, thereby enabling them to study pathology in a relevant clinical context. Features included opportunities for students to obtain additional information on the case by requesting specific laboratory tests and/or diagnostic procedures. However, students were also required to justify their diagnostic plans and to provide mechanistic analyses. The use of ATLes met most of these objectives. Student acceptance was high, and students favorably reviewed the online ''Content Links'' that made useful information more readily accessible and level appropriate. Students came to the lab better prepared to engage in an in-depth and high-quality discussion and were better able to connect clinical problems to underlying changes in tissue (lesions). However, many students indicated that the required time on task prior to lab might have been excessive relative to what they thought they learned. The classroom discussion, although improved, was not elevated to the expected level-most likely reflecting other missing elements of the learning environment, including the existing student culture and the students' current discussion skills. This article briefly discusses the lessons learned from ATLes and how similar case-based exercises might be combined with other approaches to enhance and enliven classroom discussions in the veterinary curriculum.

Hard Times for HRD, Lean Times for Learning?: Workplace Participatory Practices as Enablers of Learning

ERIC Educational Resources Information Center

Warhurst, Russell

2013-01-01

Purpose: This article aims to show how in times of austerity when formal HRD activity is curtailed and yet the need for learning is greatest, non-formal learning methods such as workplace involvement and participation initiated by line managers can compensate by enabling the required learning and change. Design/methodology/approach: A qualitative…

Designing Technology-Enabled Instruction to Utilize Learning Analytics

ERIC Educational Resources Information Center

Davies, Randall; Nyland, Robert; Bodily, Robert; Chapman, John; Jones, Brian; Young, Jay

2017-01-01

A key notion conveyed by those who advocate for the use of data to enhance instruction is an awareness that learning analytics has the potential to improve instruction and learning but is not currently reaching that potential. Gibbons (2014) suggested that a lack of learning facilitated by current technology-enabled instructional systems may be…

Enabling the Development of Student Teacher Professional Identity through Vicarious Learning during an Educational Excursion

ERIC Educational Resources Information Center

Steenekamp, Karen; van der Merwe, Martyn; Mehmedova, Aygul Salieva

2018-01-01

This paper explores the views of student teachers who were provided vicarious learning opportunities during an educational excursion, and how the learning enabled them to develop their teacher professional identity. This qualitative research study, using a social-constructivist lens highlights how vicarious learning influenced student teachers'…

Design and Implementation of Technology Enabled Affective Learning Using Fusion of Bio-Physical and Facial Expression

ERIC Educational Resources Information Center

Ray, Arindam; Chakrabarti, Amlan

2016-01-01

Technology Enabled Learning is a cognitive, constructive, systematic, collaborative learning procedure, which transforms teaching-learning pedagogy where role of emotion is very often neglected. Emotion plays significant role in the cognitive process of human being, so the transformation is incomplete without capturing the learner's emotional…

Using Deep Learning Algorithm to Enhance Image-review Software for Surveillance Cameras

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

Cui, Yonggang; Thomas, Maikael A.

We propose the development of proven deep learning algorithms to flag objects and events of interest in Next Generation Surveillance System (NGSS) surveillance to make IAEA image review more efficient. Video surveillance is one of the core monitoring technologies used by the IAEA Department of Safeguards when implementing safeguards at nuclear facilities worldwide. The current image review software GARS has limited automated functions, such as scene-change detection, black image detection and missing scene analysis, but struggles with highly cluttered backgrounds. A cutting-edge algorithm to be developed in this project will enable efficient and effective searches in images and video streamsmore » by identifying and tracking safeguards relevant objects and detect anomalies in their vicinity. In this project, we will develop the algorithm, test it with the IAEA surveillance cameras and data sets collected at simulated nuclear facilities at BNL and SNL, and implement it in a software program for potential integration into the IAEA’s IRAP (Integrated Review and Analysis Program).« less

Scaling up spike-and-slab models for unsupervised feature learning.

PubMed

Goodfellow, Ian J; Courville, Aaron; Bengio, Yoshua

2013-08-01

We describe the use of two spike-and-slab models for modeling real-valued data, with an emphasis on their applications to object recognition. The first model, which we call spike-and-slab sparse coding (S3C), is a preexisting model for which we introduce a faster approximate inference algorithm. We introduce a deep variant of S3C, which we call the partially directed deep Boltzmann machine (PD-DBM) and extend our S3C inference algorithm for use on this model. We describe learning procedures for each. We demonstrate that our inference procedure for S3C enables scaling the model to unprecedented large problem sizes, and demonstrate that using S3C as a feature extractor results in very good object recognition performance, particularly when the number of labeled examples is low. We show that the PD-DBM generates better samples than its shallow counterpart, and that unlike DBMs or DBNs, the PD-DBM may be trained successfully without greedy layerwise training.

Improving CNN Performance Accuracies With Min-Max Objective.

PubMed

Shi, Weiwei; Gong, Yihong; Tao, Xiaoyu; Wang, Jinjun; Zheng, Nanning

2017-06-09

We propose a novel method for improving performance accuracies of convolutional neural network (CNN) without the need to increase the network complexity. We accomplish the goal by applying the proposed Min-Max objective to a layer below the output layer of a CNN model in the course of training. The Min-Max objective explicitly ensures that the feature maps learned by a CNN model have the minimum within-manifold distance for each object manifold and the maximum between-manifold distances among different object manifolds. The Min-Max objective is general and able to be applied to different CNNs with insignificant increases in computation cost. Moreover, an incremental minibatch training procedure is also proposed in conjunction with the Min-Max objective to enable the handling of large-scale training data. Comprehensive experimental evaluations on several benchmark data sets with both the image classification and face verification tasks reveal that employing the proposed Min-Max objective in the training process can remarkably improve performance accuracies of a CNN model in comparison with the same model trained without using this objective.

[Virtual reality simulation training in gynecology: review and perspectives].

PubMed

Ricard-Gauthier, Dominique; Popescu, Silvia; Benmohamed, Naida; Petignat, Patrick; Dubuisson, Jean

2016-10-26

Laparoscopic simulation has rapidly become an important tool for learning and acquiring technical skills in surgery. It is based on two different complementary pedagogic tools : the box model trainer and the virtual reality simulator. The virtual reality simulator has shown its efficiency by improving surgical skills, decreasing operating time, improving economy of movements and improving self-confidence. The main objective of this tool is the opportunity to easily organize a regular, structured and uniformed training program enabling an automated individualized feedback.

Can social semantic web techniques foster collaborative curriculum mapping in medicine?

PubMed

Spreckelsen, Cord; Finsterer, Sonja; Cremer, Jan; Schenkat, Hennig

2013-08-15

Curriculum mapping, which is aimed at the systematic realignment of the planned, taught, and learned curriculum, is considered a challenging and ongoing effort in medical education. Second-generation curriculum managing systems foster knowledge management processes including curriculum mapping in order to give comprehensive support to learners, teachers, and administrators. The large quantity of custom-built software in this field indicates a shortcoming of available IT tools and standards. The project reported here aims at the systematic adoption of techniques and standards of the Social Semantic Web to implement collaborative curriculum mapping for a complete medical model curriculum. A semantic MediaWiki (SMW)-based Web application has been introduced as a platform for the elicitation and revision process of the Aachen Catalogue of Learning Objectives (ACLO). The semantic wiki uses a domain model of the curricular context and offers structured (form-based) data entry, multiple views, structured querying, semantic indexing, and commenting for learning objectives ("LOs"). Semantic indexing of learning objectives relies on both a controlled vocabulary of international medical classifications (ICD, MeSH) and a folksonomy maintained by the users. An additional module supporting the global checking of consistency complements the semantic wiki. Statements of the Object Constraint Language define the consistency criteria. We evaluated the application by a scenario-based formative usability study, where the participants solved tasks in the (fictional) context of 7 typical situations and answered a questionnaire containing Likert-scaled items and free-text questions. At present, ACLO contains roughly 5350 operational (ie, specific and measurable) objectives acquired during the last 25 months. The wiki-based user interface uses 13 online forms for data entry and 4 online forms for flexible searches of LOs, and all the forms are accessible by standard Web browsers. The formative usability study yielded positive results (median rating of 2 ("good") in all 7 general usability items) and produced valuable qualitative feedback, especially concerning navigation and comprehensibility. Although not asked to, the participants (n=5) detected critical aspects of the curriculum (similar learning objectives addressed repeatedly and missing objectives), thus proving the system's ability to support curriculum revision. The SMW-based approach enabled an agile implementation of computer-supported knowledge management. The approach, based on standard Social Semantic Web formats and technology, represents a feasible and effectively applicable compromise between answering to the individual requirements of curriculum management at a particular medical school and using proprietary systems.

Flate-plate photovoltaic power systems handbook for Federal agencies

NASA Technical Reports Server (NTRS)

Cochrane, E. H.; Lawson, A. C.; Savage, C. H.

1984-01-01

The primary purpose is to provide a tool for personnel in Federal agencies to evaluate the viability of potential photovoltaic applications. A second objective is to provide descriptions of various photovoltaic systems installed by different Federal agencies under the Federal Photovoltaic Utilization Program so that other agencies may consider similar applications. A third objective is to share lessons learned to enable more effective procurement, design, installation, and operation of future photovoltaic systems. The intent is not to provide a complete handbook, but rather to provide a guide for Federal agency personnel with additional information incorporated by references. The steps to be followed in selecting, procuring, and installing a photovoltaic application are given.

Objective assessment of technique in laparoscopic colorectal surgery: what are the existing tools?

PubMed

Foster, J D; Francis, N K

2015-01-01

Assessment can improve the effectiveness of surgical training and enable valid judgments of competence. Laparoscopic colon resection surgery is now taught within surgical residency programs, and assessment tools are increasingly used to stimulate formative feedback and enhance learning. Formal assessment of technical performance in laparoscopic colon resection has been successfully applied at the specialist level in the English "LAPCO" National Training Program. Objective assessment tools need to be developed for training and assessment in laparoscopic rectal cancer resection surgery. Simulation may have a future role in assessment and accreditation in laparoscopic colorectal surgery; however, existing virtual reality models are not ready to be used for assessment of this advanced surgery.

Using complexity theory to develop a student-directed interprofessional learning activity for 1220 healthcare students.

PubMed

Jorm, Christine; Nisbet, Gillian; Roberts, Chris; Gordon, Christopher; Gentilcore, Stacey; Chen, Timothy F

2016-08-08

More and better interprofessional practice is predicated to be necessary to deliver good care to the patients of the future. However, universities struggle to create authentic learning activities that enable students to experience the dynamic interprofessional interactions common in healthcare and that can accommodate large interprofessional student cohorts. We investigated a large-scale mandatory interprofessional learning (IPL) activity for health professional students designed to promote social learning. A mixed methods research approach determined feasibility, acceptability and the extent to which student IPL outcomes were met. We developed an IPL activity founded in complexity theory to prepare students for future practice by engaging them in a self-directed (self-organised) learning activity with a diverse team, whose assessable products would be emergent creations. Complicated but authentic clinical cases (n = 12) were developed to challenge student teams (n = 5 or 6). Assessment consisted of a written management plan (academically marked) and a five-minute video (peer marked) designed to assess creative collaboration as well as provide evidence of integrated collective knowledge; the cohesive patient-centred management plan. All students (including the disciplines of diagnostic radiology, exercise physiology, medicine, nursing, occupational therapy, pharmacy, physiotherapy and speech pathology), completed all tasks successfully. Of the 26 % of students who completed the evaluation survey, 70 % agreed or strongly agreed that the IPL activity was worthwhile, and 87 % agreed or strongly agreed that their case study was relevant. Thematic analysis found overarching themes of engagement and collaboration-in-action suggesting that the IPL activity enabled students to achieve the intended learning objectives. Students recognised the contribution of others and described negotiation, collaboration and creation of new collective knowledge after working together on the complicated patient case studies. The novel video assessment was challenging to many students and contextual issues limited engagement for some disciplines. We demonstrated the feasibility and acceptability of a large scale IPL activity where design of cases, format and assessment tasks was founded in complexity theory. This theoretically based design enabled students to achieve complex IPL outcomes relevant to future practice. Future research could establish the psychometric properties of assessments of student performance in large-scale IPL events.

Using interactive problem-solving techniques to enhance control systems education for non English-speakers

NASA Astrophysics Data System (ADS)

Lamont, L. A.; Chaar, L.; Toms, C.

2010-03-01

Interactive learning is beneficial to students in that it allows the continual development and testing of many skills. An interactive approach enables students to improve their technical capabilities, as well as developing both verbal and written communicative ability. Problem solving and communication skills are vital for engineering students; in the workplace they will be required to communicate with people of varying technical abilities and from different linguistic and engineering backgrounds. In this paper, a case study is presented that discusses how the traditional method of teaching control systems can be improved. 'Control systems' is a complex engineering topic requiring students to process an extended amount of mathematical formulae. MATLAB software, which enables students to interactively compare a range of possible combinations and analyse the optimal solution, is used to this end. It was found that students became more enthusiastic and interested when given ownership of their learning objectives. As well as improving the students' technical knowledge, other important engineering skills are also improved by introducing an interactive method of teaching.

Exogenous Attention Enables Perceptual Learning.

PubMed

Szpiro, Sarit F A; Carrasco, Marisa

2015-12-01

Practice can improve visual perception, and these improvements are considered to be a form of brain plasticity. Training-induced learning is time-consuming and requires hundreds of trials across multiple days. The process of learning acquisition is understudied. Can learning acquisition be potentiated by manipulating visual attentional cues? We developed a protocol in which we used task-irrelevant cues for between-groups manipulation of attention during training. We found that training with exogenous attention can enable the acquisition of learning. Remarkably, this learning was maintained even when observers were subsequently tested under neutral conditions, which indicates that a change in perception was involved. Our study is the first to isolate the effects of exogenous attention and to demonstrate its efficacy to enable learning. We propose that exogenous attention boosts perceptual learning by enhancing stimulus encoding. © The Author(s) 2015.

Problem-based learning: an exploration of student opinions on its educational role in one UK pharmacy undergraduate curriculum.

PubMed

Wright, David; Wickham, Jane; Sach, Tracey

2014-06-01

Problem-based learning (PBL) was introduced into the first 3 years of the undergraduate degree course at the University of East Anglia (UEA) to both enhance the student learning experience and to enable it to meet external course accreditation criteria. Evidence to support both of these assertions is required. The objective was to determine student opinions on the value of PBL and the PBL learning process at one UK school of pharmacy. Utilising the professional accreditation criteria for UK schools of pharmacy a questionnaire was devised and piloted before being given to all UEA undergraduate pharmacy students for self-completion. The most appropriate method of dissemination was determined from a student-led focus group. A total of 201/329 (61.1%) students responded. The majority of students agreed that PBL improved their team working (83.1%), oral communication (89.1%) and problem-solving skills (61.7%). Additionally PBL improved students' ability to identify and address ethical dilemmas (74.5%) as well as enhancing their ability to manage their own learning (67.6%). Male students and those with a stated preference for team working were found to prefer PBL. Students generally believe that PBL develops a number of key skills and consequently inclusion of PBL alongside traditional teaching methods enables the school to meet a number of degree accreditation criteria. Male students, those who enjoyed team working and working with their current group were more positive about PBL. Further work is required to improve the experience for all students. © 2013 Royal Pharmaceutical Society.

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions.

PubMed

Loh, Brian C S; Then, Patrick H H

2017-01-01

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

PubMed Central

Then, Patrick H. H.

2017-01-01

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications. PMID:29184897

The Role of Learning Goals in Building a Knowledge Base for Elementary Mathematics Teacher Education

ERIC Educational Resources Information Center

Jansen, Amanda; Bartell, Tonya; Berk, Dawn

2009-01-01

In this article, we describe features of learning goals that enable indexing knowledge for teacher education. Learning goals are the key enabler for building a knowledge base for teacher education; they define what counts as essential knowledge for prospective teachers. We argue that 2 characteristics of learning goals support knowledge-building…

Development of a Web-Enabled Learning Platform for Geospatial Laboratories: Improving the Undergraduate Learning Experience

ERIC Educational Resources Information Center

Mui, Amy B.; Nelson, Sarah; Huang, Bruce; He, Yuhong; Wilson, Kathi

2015-01-01

This paper describes a web-enabled learning platform providing remote access to geospatial software that extends the learning experience outside of the laboratory setting. The platform was piloted in two undergraduate courses, and includes a software server, a data server, and remote student users. The platform was designed to improve the quality…

Using Email to Enable E[superscript 3] (Effective, Efficient, and Engaging) Learning

ERIC Educational Resources Information Center

Kim, ChanMin

2008-01-01

This article argues that technology that supports both noncognitive and cognitive aspects can make learning more effective, efficient, and engaging (e[superscript 3]-learning). The technology of interest in this article is email. The investigation focuses on characteristics of email that are likely to enable e[superscript 3]-learning. In addition,…

Statistical Relational Learning (SRL) as an Enabling Technology for Data Acquisition and Data Fusion in Video

DTIC Science & Technology

2013-05-02

REPORT Statistical Relational Learning ( SRL ) as an Enabling Technology for Data Acquisition and Data Fusion in Video 14. ABSTRACT 16. SECURITY...particular, it is important to reason about which portions of video require expensive analysis and storage. This project aims to make these...inferences using new and existing tools from Statistical Relational Learning ( SRL ). SRL is a recently emerging technology that enables the effective 1

Object Recognition using Feature- and Color-Based Methods

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu; Stubberud, Allen

2008-01-01

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Deep learning-based artificial vision for grasp classification in myoelectric hands

NASA Astrophysics Data System (ADS)

Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

2017-06-01

Objective. Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. Approach. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at {{5}\\circ} intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. Main results. The classification accuracy in the offline tests reached 85 % for the seen and 75 % for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of 84 % in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb UltraTM prosthetic hand and a motion controlTM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to 88 % . In addition, we show that with training, subjects’ performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. Significance. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Introducing Seismic Tomography with Computational Modeling

NASA Astrophysics Data System (ADS)

Neves, R.; Neves, M. L.; Teodoro, V.

2011-12-01

Learning seismic tomography principles and techniques involves advanced physical and computational knowledge. In depth learning of such computational skills is a difficult cognitive process that requires a strong background in physics, mathematics and computer programming. The corresponding learning environments and pedagogic methodologies should then involve sets of computational modelling activities with computer software systems which allow students the possibility to improve their mathematical or programming knowledge and simultaneously focus on the learning of seismic wave propagation and inverse theory. To reduce the level of cognitive opacity associated with mathematical or programming knowledge, several computer modelling systems have already been developed (Neves & Teodoro, 2010). Among such systems, Modellus is particularly well suited to achieve this goal because it is a domain general environment for explorative and expressive modelling with the following main advantages: 1) an easy and intuitive creation of mathematical models using just standard mathematical notation; 2) the simultaneous exploration of images, tables, graphs and object animations; 3) the attribution of mathematical properties expressed in the models to animated objects; and finally 4) the computation and display of mathematical quantities obtained from the analysis of images and graphs. Here we describe virtual simulations and educational exercises which enable students an easy grasp of the fundamental of seismic tomography. The simulations make the lecture more interactive and allow students the possibility to overcome their lack of advanced mathematical or programming knowledge and focus on the learning of seismological concepts and processes taking advantage of basic scientific computation methods and tools.

Web-based teaching video packages on anatomical education.

PubMed

Ozer, Mehmet Asim; Govsa, Figen; Bati, Ayse Hilal

2017-11-01

The aim of this study was to study the effect of web-based teaching video packages on medical students' satisfaction during gross anatomy education. The objective was to test the hypothesis that individual preference, which can be related to learning style, influences individual utilization of the video packages developed specifically for the undergraduate medical curriculum. Web-based teaching video packages consisting of Closed Circuit Audiovisual System and Distance Education of Anatomy were prepared. 54 informative application videos each lasting an average 12 min, competent with learning objectives have been prepared. 300 young adults of the medical school on applied anatomy education were evaluated in terms of their course content, exam performance and perceptions. A survey was conducted to determine the difference between the students who did not use teaching packages with those who used it during or after the lecture. A mean of 150 hits for each student per year was indicated. Academic performance of anatomy has been an increase of 10 points. Positive effects of the video packages on anatomy education have manifested on the survey conducted on students. The survey was compiled under twenty different items including effectiveness, providing education opportunity and affecting learning positively. Additionally, the difference was remarkable that the positive ideas of the second year students on learning were statistically significant from that of the third year students. Web-based video packages are helpful, definitive, easily accessible and affordable which enable students with different pace of learning to reach information simultaneously in equal conditions and increase the learning activity in crowded group lectures in cadaver labs. We conclude that personality/learning preferences of individual students influence their use of video packages in the medical curriculum.

Recommendations for the development of e-modules for the continuing professional development of European dentists.

PubMed

Kavadella, A; Kossioni, A E; Tsiklakis, K; Cowpe, J; Bullock, A; Barnes, E; Bailey, S; Thomas, H; Thomas, R; Karaharju-Suvanto, T; Suomalainen, K; Kersten, H; Povel, E; Giles, M; Walmsley, D; Soboleva, U; Liepa, A; Akota, I

2013-05-01

To provide evidence-based and peer-reviewed recommendations for the development of dental continuing professional development (CPD) learning e-modules. The present recommendations are consensus recommendations of the DentCPD project team and were informed by a literature research, consultations from e-learning and IT expert, discussions amongst the participants attending a special interest group during the 2012 ADEE meeting, and feedback from the evaluation procedures of the exemplar e-module (as described in a companion paper within this Supplement). The main focus of these recommendations is on the courses and modules organised and offered by dental schools. E-modules for dental CPD, as well as for other health professionals' continuing education, have been implemented and evaluated for a number of years. Research shows that the development of e-modules is a team process, undertaken by academics, subject experts, pedagogists, IT and web designers, learning technologists and librarians. The e-module must have clear learning objectives (outcomes), addressing the learners' individual needs, and must be visually attractive, relevant, interactive, promoting critical thinking and providing feedback. The text, graphics and animations must support the objectives and enable the learning process by creating an attractive, easy to navigate and interactive electronic environment. Technology is usually a concern for learners and tutors; therefore, it must be kept simple and interoperable within different systems and software. The pedagogical and technological proficiency of educators is of paramount importance, yet remains a challenge in many instances. The development of e-courses and modules for dental CPD is an endeavour undertaken by a group of professionals. It must be underpinned by sound pedagogical and e-learning principles and must incorporate elements for effective visual learning and visual design and a simple, consistent technology. © 2013 John Wiley & Sons A/S.

Deep learning-based artificial vision for grasp classification in myoelectric hands.

PubMed

Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

2017-06-01

Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at [Formula: see text] intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. The classification accuracy in the offline tests reached [Formula: see text] for the seen and [Formula: see text] for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of [Formula: see text] in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb Ultra TM prosthetic hand and a motion control TM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to [Formula: see text]. In addition, we show that with training, subjects' performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Supporting the "Collaborative" Part of Wiki-Mediated Collaborative Learning Activities

ERIC Educational Resources Information Center

Larusson, Johann Ari

2010-01-01

Prior research has highlighted the educational benefit of enabling students to participate in collaborative learning activities. Developing technology that extends the physical boundaries of the classroom and enables students to engage in meaningful collaborative learning activities outside class time can be of significant value. For any…

Can Social Semantic Web Techniques Foster Collaborative Curriculum Mapping In Medicine?

PubMed Central

Finsterer, Sonja; Cremer, Jan; Schenkat, Hennig

2013-01-01

Background Curriculum mapping, which is aimed at the systematic realignment of the planned, taught, and learned curriculum, is considered a challenging and ongoing effort in medical education. Second-generation curriculum managing systems foster knowledge management processes including curriculum mapping in order to give comprehensive support to learners, teachers, and administrators. The large quantity of custom-built software in this field indicates a shortcoming of available IT tools and standards. Objective The project reported here aims at the systematic adoption of techniques and standards of the Social Semantic Web to implement collaborative curriculum mapping for a complete medical model curriculum. Methods A semantic MediaWiki (SMW)-based Web application has been introduced as a platform for the elicitation and revision process of the Aachen Catalogue of Learning Objectives (ACLO). The semantic wiki uses a domain model of the curricular context and offers structured (form-based) data entry, multiple views, structured querying, semantic indexing, and commenting for learning objectives (“LOs”). Semantic indexing of learning objectives relies on both a controlled vocabulary of international medical classifications (ICD, MeSH) and a folksonomy maintained by the users. An additional module supporting the global checking of consistency complements the semantic wiki. Statements of the Object Constraint Language define the consistency criteria. We evaluated the application by a scenario-based formative usability study, where the participants solved tasks in the (fictional) context of 7 typical situations and answered a questionnaire containing Likert-scaled items and free-text questions. Results At present, ACLO contains roughly 5350 operational (ie, specific and measurable) objectives acquired during the last 25 months. The wiki-based user interface uses 13 online forms for data entry and 4 online forms for flexible searches of LOs, and all the forms are accessible by standard Web browsers. The formative usability study yielded positive results (median rating of 2 (“good”) in all 7 general usability items) and produced valuable qualitative feedback, especially concerning navigation and comprehensibility. Although not asked to, the participants (n=5) detected critical aspects of the curriculum (similar learning objectives addressed repeatedly and missing objectives), thus proving the system’s ability to support curriculum revision. Conclusions The SMW-based approach enabled an agile implementation of computer-supported knowledge management. The approach, based on standard Social Semantic Web formats and technology, represents a feasible and effectively applicable compromise between answering to the individual requirements of curriculum management at a particular medical school and using proprietary systems. PMID:23948519

Metaverse Utilization in the EFL Classroom - A Study. Second Life (Register Trademark) as Part of an Institution's Curriculum

NASA Technical Reports Server (NTRS)

Imaoka, Yukimi; Amaki, Yuki; Yagi, Kenji; Fuller, Chris; Madden, Anthony

2012-01-01

Starting on April 2010, the Kanda Institute of Foreign Languages integrated the Metaverse application known as Second Life into the core curriculum for 840 new enrollments. As of April 2011, we enrolled an additional 760 students. This course, the Hybrid English Learning Program, is commonly referred to by the acronym: HELP. By taking the advantages of learning in immersive 3D environments, we aim to meet two objectives, 1) namely to enable students to remember and properly use learned phrases and expressions, and 2) using Second Life(R) as a tool to enhance the meaning and practicality of what is being learned. ,Although there have been several online English learning programs or services here in Japan, this endeavor represents the first time Metaverse technology has been utilized as part of a core curriculum; a curriculum structured upon classroom learning and interaction within the Metaverse. This paper endeavors to explain the following: the planning and development of HELP, the class structure, and the results of a questionnaire which measured whether using such an approach would reduce student timidity and assist student to gain more confidence in speaking English in different social environments.

Towards Designing Cognitively-Enriched Project-Oriented Courses within a Blended Problem-Based Learning Context

ERIC Educational Resources Information Center

Tambouris, Efthimios; Zotou, Maria; Tarabanis, Konstantinos

2014-01-01

Traditional education seems to gradually and moderately make way for self-directed and student-centred learning strategies that will efficiently enable students to reach their full potentials and will sufficiently prepare them for their upcoming professional careers. Problem-Based Learning (PBL) is such a strategy, since it enables active…

Recasting Distance Learning with Network-Enabled Open Education: An Interview with Vijay Kumar

ERIC Educational Resources Information Center

Morrison, James L.; Kumar, Vijay

2008-01-01

In an interview with James Morrison, "Innovate's" editor-in-chief, Vijay Kumar describes how rethinking distance learning as network-enabled open education can catalyze a whole new set of learning opportunities. The growing open-education movement has made an increasing number and variety of resources freely available online, including everything…

Enabling Pedagogy and Andragogy for 21st-Century Sign Language Users and Learners

ERIC Educational Resources Information Center

Hermann-Shores, Patricia

2017-01-01

Enabling pedagogy and andragogy is discussed as a form of lifelong learning in which learners attain competences and skills as children (pedagogy) and as adults (andragogy) that enable them to engage in independent learning in the 21st century. Throughout the article the author avoids as much as possible the labels "deaf" and…

Enabling School Structures, Collegial Trust and Academic Emphasis: Antecedents of professional learning communities

ERIC Educational Resources Information Center

Gray, Julie; Kruse, Sharon; Tarter, C. John

2016-01-01

This study tested the role of enabling school structures, collegial trust and academic emphasis in the development of professional learning communities (PLCs) in a low-income school district. The empirical study was based upon the perceptions of teachers and principals as provided by survey responses (N = 67 schools). While enabling school…

Learning Object Repositories

ERIC Educational Resources Information Center

Lehman, Rosemary

2007-01-01

This chapter looks at the development and nature of learning objects, meta-tagging standards and taxonomies, learning object repositories, learning object repository characteristics, and types of learning object repositories, with type examples. (Contains 1 table.)

Heterogeneous distributed query processing: The DAVID system

NASA Technical Reports Server (NTRS)

Jacobs, Barry E.

1985-01-01

The objective of the Distributed Access View Integrated Database (DAVID) project is the development of an easy to use computer system with which NASA scientists, engineers and administrators can uniformly access distributed heterogeneous databases. Basically, DAVID will be a database management system that sits alongside already existing database and file management systems. Its function is to enable users to access the data in other languages and file systems without having to learn the data manipulation languages. Given here is an outline of a talk on the DAVID project and several charts.

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

PubMed

Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

2017-09-12

In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

Perspectives on object manipulation and action grammar for percussive actions in primates

PubMed Central

Hayashi, Misato

2015-01-01

The skill of object manipulation is a common feature of primates including humans, although there are species-typical patterns of manipulation. Object manipulation can be used as a comparative scale of cognitive development, focusing on its complexity. Nut cracking in chimpanzees has the highest hierarchical complexity of tool use reported in non-human primates. An analysis of the patterns of object manipulation in naive chimpanzees after nut-cracking demonstrations revealed the cause of difficulties in learning nut-cracking behaviour. Various types of behaviours exhibited within a nut-cracking context can be examined in terms of the application of problem-solving strategies, focusing on their basis in causal understanding or insightful intentionality. Captive chimpanzees also exhibit complex forms of combinatory manipulation, which is the precursor of tool use. A new notation system of object manipulation was invented to assess grammatical rules in manipulative actions. The notation system of action grammar enabled direct comparisons to be made between primates including humans in a variety of object-manipulation tasks, including percussive-tool use. PMID:26483528

Perspectives on object manipulation and action grammar for percussive actions in primates.

PubMed

Hayashi, Misato

2015-11-19

The skill of object manipulation is a common feature of primates including humans, although there are species-typical patterns of manipulation. Object manipulation can be used as a comparative scale of cognitive development, focusing on its complexity. Nut cracking in chimpanzees has the highest hierarchical complexity of tool use reported in non-human primates. An analysis of the patterns of object manipulation in naive chimpanzees after nut-cracking demonstrations revealed the cause of difficulties in learning nut-cracking behaviour. Various types of behaviours exhibited within a nut-cracking context can be examined in terms of the application of problem-solving strategies, focusing on their basis in causal understanding or insightful intentionality. Captive chimpanzees also exhibit complex forms of combinatory manipulation, which is the precursor of tool use. A new notation system of object manipulation was invented to assess grammatical rules in manipulative actions. The notation system of action grammar enabled direct comparisons to be made between primates including humans in a variety of object-manipulation tasks, including percussive-tool use. © 2015 The Author(s).

Navigating Bioethical Waters: Two Pilot Projects in Problem-Based Learning for Future Bioscience and Biotechnology Professionals.

PubMed

Berry, Roberta M; Levine, Aaron D; Kirkman, Robert; Blake, Laura Palucki; Drake, Matthew

2016-12-01

We believe that the professional responsibility of bioscience and biotechnology professionals includes a social responsibility to contribute to the resolution of ethically fraught policy problems generated by their work. It follows that educators have a professional responsibility to prepare future professionals to discharge this responsibility. This essay discusses two pilot projects in ethics pedagogy focused on particularly challenging policy problems, which we call "fractious problems". The projects aimed to advance future professionals' acquisition of "fractious problem navigational" skills, a set of skills designed to enable broad and deep understanding of fractious problems and the design of good policy resolutions for them. A secondary objective was to enhance future professionals' motivation to apply these skills to help their communities resolve these problems. The projects employed "problem based learning" courses to advance these learning objectives. A new assessment instrument, "Skills for Science/Engineering Ethics Test" (SkillSET), was designed and administered to measure the success of the courses in doing so. This essay first discusses the rationale for the pilot projects, and then describes the design of the pilot courses and presents the results of our assessment using SkillSET in the first pilot project and the revised SkillSET 2.0 in the second pilot project. The essay concludes with discussion of observations and results.

Mere exposure alters category learning of novel objects.

PubMed

Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J

2010-01-01

We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

Mere Exposure Alters Category Learning of Novel Objects

PubMed Central

Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.

2010-01-01

We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning. PMID:21833209

Effectiveness and Impact of Technology-Enabled Project-Based Learning with the Use of Process Prompts in Teacher Education

ERIC Educational Resources Information Center

Chen, Ching-Huei; Chan, Lim-Ha

2011-01-01

This study investigated the effectiveness and impacts of process prompts on students' learning and computer self-efficacy within the technology-enabled project-based learning (PBL) context in an undergraduate educational technology course. If the aim is to prepare prospective teachers to effectively, efficiently, and engagingly use technologies in…

A user-centered, object-oriented methodology for developing Health Information Systems: a Clinical Information System (CIS) example.

PubMed

Konstantinidis, Georgios; Anastassopoulos, George C; Karakos, Alexandros S; Anagnostou, Emmanouil; Danielides, Vasileios

2012-04-01

The aim of this study is to present our perspectives on healthcare analysis and design and the lessons learned from our experience with the development of a distributed, object-oriented Clinical Information System (CIS). In order to overcome known issues regarding development, implementation and finally acceptance of a CIS by the physicians we decided to develop a novel object-oriented methodology by integrating usability principles and techniques in a simplified version of a well established software engineering process (SEP), the Unified Process (UP). A multilayer architecture has been defined and implemented with the use of a vendor application framework. Our first experiences from a pilot implementation of our CIS are positive. This approach allowed us to gain a socio-technical understanding of the domain and enabled us to identify all the important factors that define both the structure and the behavior of a Health Information System.

Benchmarking health IT among OECD countries: better data for better policy

PubMed Central

Adler-Milstein, Julia; Ronchi, Elettra; Cohen, Genna R; Winn, Laura A Pannella; Jha, Ashish K

2014-01-01

Objective To develop benchmark measures of health information and communication technology (ICT) use to facilitate cross-country comparisons and learning. Materials and methods The effort is led by the Organisation for Economic Co-operation and Development (OECD). Approaches to definition and measurement within four ICT domains were compared across seven OECD countries in order to identify functionalities in each domain. These informed a set of functionality-based benchmark measures, which were refined in collaboration with representatives from more than 20 OECD and non-OECD countries. We report on progress to date and remaining work to enable countries to begin to collect benchmark data. Results The four benchmarking domains include provider-centric electronic record, patient-centric electronic record, health information exchange, and tele-health. There was broad agreement on functionalities in the provider-centric electronic record domain (eg, entry of core patient data, decision support), and less agreement in the other three domains in which country representatives worked to select benchmark functionalities. Discussion Many countries are working to implement ICTs to improve healthcare system performance. Although many countries are looking to others as potential models, the lack of consistent terminology and approach has made cross-national comparisons and learning difficult. Conclusions As countries develop and implement strategies to increase the use of ICTs to promote health goals, there is a historic opportunity to enable cross-country learning. To facilitate this learning and reduce the chances that individual countries flounder, a common understanding of health ICT adoption and use is needed. The OECD-led benchmarking process is a crucial step towards achieving this. PMID:23721983

Enhancing understanding and improving prediction of severe weather through spatiotemporal relational learning.

PubMed

McGovern, Amy; Gagne, David J; Williams, John K; Brown, Rodger A; Basara, Jeffrey B

Severe weather, including tornadoes, thunderstorms, wind, and hail annually cause significant loss of life and property. We are developing spatiotemporal machine learning techniques that will enable meteorologists to improve the prediction of these events by improving their understanding of the fundamental causes of the phenomena and by building skillful empirical predictive models. In this paper, we present significant enhancements of our Spatiotemporal Relational Probability Trees that enable autonomous discovery of spatiotemporal relationships as well as learning with arbitrary shapes. We focus our evaluation on two real-world case studies using our technique: predicting tornadoes in Oklahoma and predicting aircraft turbulence in the United States. We also discuss how to evaluate success for a machine learning algorithm in the severe weather domain, which will enable new methods such as ours to transfer from research to operations, provide a set of lessons learned for embedded machine learning applications, and discuss how to field our technique.

Competences for enhancing interprofessional collaboration in a paediatrics setting: Enabling and hindering factors.

PubMed

Solevåg, Anne Lee; Karlgren, Klas

2016-01-01

In 2011 an interprofessional educational programme called "Pediatric systematic assessment and communication for preventing emergencies" designed to increase clinical staff's competence in treating sick children was introduced in one paediatrics department in Norway. To elicit an in-depth understanding of the perceptions of clinical staff about the programme and enact adjustments according to identified enabling and hindering factors for learning, nurses and paediatricians were invited to participate in focus group interviews. The interviews were analysed by content analysis. Enabling factors for learning included improved interprofessional collaboration and positive feedback on performance. Hindering factors included perceptions that the programme was redundant and the fact that collaborating departments, such as the surgical departments, were not familiar with the programme. Peer learning, more interprofessional learning activities, and the fostering of a learning organization were suggestions for sustained learning. Based on the results of the study we have now included collaborating departments in the programme.

Workshop on active learning: two examples

NASA Astrophysics Data System (ADS)

Ben Lakhdar, Zohra; Lahmar, Souad; Lakshminarayanan, Vasudevan

2014-07-01

Optics is an enabling science that has far ranging importance in many diverse fields. However, many students do not find it to be of great interest. A solution to this problem is to train teachers in active learning methodologies so that the subject matter can be presented to generate student interest. We describe a workshop to present an example of an active learning process in Optics developed for training of teachers in developing countries (a UNESCO project) and will focus on 2 two different activities: 1. Interference and diffraction is considered by students as being very hard to understand and is taught in most developing countries as purely theoretical with almost no experiments. Simple experiments to enhance the conceptual understanding of these wave phenomena will be presented and 2. Image formation by the eye. Here we will discuss myopia, hyperopia and astigmatism as well as accommodation. In this module we will discuss image. The objective of the workshop will be to provide an experience of the use of the active learning method in optics including the use of experiments, mind's on and hands-on exercises, group and class discussions

An integrated system for interactive continuous learning of categorical knowledge

NASA Astrophysics Data System (ADS)

Skočaj, Danijel; Vrečko, Alen; Mahnič, Marko; Janíček, Miroslav; Kruijff, Geert-Jan M.; Hanheide, Marc; Hawes, Nick; Wyatt, Jeremy L.; Keller, Thomas; Zhou, Kai; Zillich, Michael; Kristan, Matej

2016-09-01

This article presents an integrated robot system capable of interactive learning in dialogue with a human. Such a system needs to have several competencies and must be able to process different types of representations. In this article, we describe a collection of mechanisms that enable integration of heterogeneous competencies in a principled way. Central to our design is the creation of beliefs from visual and linguistic information, and the use of these beliefs for planning system behaviour to satisfy internal drives. The system is able to detect gaps in its knowledge and to plan and execute actions that provide information needed to fill these gaps. We propose a hierarchy of mechanisms which are capable of engaging in different kinds of learning interactions, e.g. those initiated by a tutor or by the system itself. We present the theory these mechanisms are build upon and an instantiation of this theory in the form of an integrated robot system. We demonstrate the operation of the system in the case of learning conceptual models of objects and their visual properties.

Residential roof condition assessment system using deep learning

NASA Astrophysics Data System (ADS)

Wang, Fan; Kerekes, John P.; Xu, Zhuoyi; Wang, Yandong

2018-01-01

The emergence of high resolution (HR) and ultra high resolution (UHR) airborne remote sensing imagery is enabling humans to move beyond traditional land cover analysis applications to the detailed characterization of surface objects. A residential roof condition assessment method using techniques from deep learning is presented. The proposed method operates on individual roofs and divides the task into two stages: (1) roof segmentation, followed by (2) condition classification of the segmented roof regions. As the first step in this process, a self-tuning method is proposed to segment the images into small homogeneous areas. The segmentation is initialized with simple linear iterative clustering followed by deep learned feature extraction and region merging, with the optimal result selected by an unsupervised index, Q. After the segmentation, a pretrained residual network is fine-tuned on the augmented roof segments using a proposed k-pixel extension technique for classification. The effectiveness of the proposed algorithm was demonstrated on both HR and UHR imagery collected by EagleView over different study sites. The proposed algorithm has yielded promising results and has outperformed traditional machine learning methods using hand-crafted features.

Learning Semantics of Gestural Instructions for Human-Robot Collaboration

PubMed Central

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions. PMID:29615888

Learning Semantics of Gestural Instructions for Human-Robot Collaboration.

PubMed

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions.

The New School-Based Learning (SBL) to Work-Based Learning (WBL) Transition Module: A Practical Implementation in the Technical and Vocational Education (TVE) System in Bahrain

NASA Astrophysics Data System (ADS)

Alseddiqi, M.; Mishra, R.; Pislaru, C.

2012-05-01

This paper diagnoses the implementation of a new engineering course entitled 'school-based learning (SBL) to work-based learning (WBL) transition module' in the Bahrain Technical and Vocational Education (TVE) learning environment. The module was designed to incorporate an innovative education and training approach with a variety of learning activities that are included in various learning case studies. Each case study was based on with learning objectives coupled with desired learning outcomes. The TVE students should meet the desired outcomes after the completion of the learning activities and assessments. To help with the implementation phase of the new module, the authors developed guidelines for each case study. The guidelines incorporated learning activities to be delivered in an integrated learning environment. The skills to be transferred were related to cognitive, affective, and technical proficiencies. The guidelines included structured instructions to help students during the learning process. In addition, technology was introduced to improve learning effectiveness and flexibility. The guidelines include learning indicators for each learning activity and were based on their interrelation with competencies to be achieved with respect to modern industrial requirements. Each learning indicator was then correlated against the type of learning environment, teaching and learning styles, examples of mode of delivery, and assessment strategy. Also, the learning activities were supported by technological features such as discussion forums for social perception and engagement and immediate feedback exercises for self-motivation. Through the developed module, TVE teachers can effectively manage the teaching and learning process as well as the assessment strategy to satisfy students' individual requirements and enable them to meet workplace requirements.

Application of a model of instrumental conditioning to mobile robot control

NASA Astrophysics Data System (ADS)

Saksida, Lisa M.; Touretzky, D. S.

1997-09-01

Instrumental conditioning is a psychological process whereby an animal learns to associate its actions with their consequences. This type of learning is exploited in animal training techniques such as 'shaping by successive approximations,' which enables trainers to gradually adjust the animal's behavior by giving strategically timed reinforcements. While this is similar in principle to reinforcement learning, the real phenomenon includes many subtle effects not considered in the machine learning literature. In addition, a good deal of domain information is utilized by an animal learning a new task; it does not start from scratch every time it learns a new behavior. For these reasons, it is not surprising that mobile robot learning algorithms have yet to approach the sophistication and robustness of animal learning. A serious attempt to model instrumental learning could prove fruitful for improving machine learning techniques. In the present paper, we develop a computational theory of shaping at a level appropriate for controlling mobile robots. The theory is based on a series of mechanisms for 'behavior editing,' in which pre-existing behaviors, either innate or previously learned, can be dramatically changed in magnitude, shifted in direction, or otherwise manipulated so as to produce new behavioral routines. We have implemented our theory on Amelia, an RWI B21 mobile robot equipped with a gripper and color video camera. We provide results from training Amelia on several tasks, all of which were constructed as variations of one innate behavior, object-pursuit.

Automated expert modeling for automated student evaluation.

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

Abbott, Robert G.

The 8th International Conference on Intelligent Tutoring Systems provides a leading international forum for the dissemination of original results in the design, implementation, and evaluation of intelligent tutoring systems and related areas. The conference draws researchers from a broad spectrum of disciplines ranging from artificial intelligence and cognitive science to pedagogy and educational psychology. The conference explores intelligent tutoring systems increasing real world impact on an increasingly global scale. Improved authoring tools and learning object standards enable fielding systems and curricula in real world settings on an unprecedented scale. Researchers deploy ITS's in ever larger studies and increasingly use datamore » from real students, tasks, and settings to guide new research. With high volumes of student interaction data, data mining, and machine learning, tutoring systems can learn from experience and improve their teaching performance. The increasing number of realistic evaluation studies also broaden researchers knowledge about the educational contexts for which ITS's are best suited. At the same time, researchers explore how to expand and improve ITS/student communications, for example, how to achieve more flexible and responsive discourse with students, help students integrate Web resources into learning, use mobile technologies and games to enhance student motivation and learning, and address multicultural perspectives.« less

Stereotyping at the undergraduate level revealed during interprofessional learning between future doctors and biomedical scientists.

PubMed

Lewitt, Moira S; Ehrenborg, Ewa; Scheja, Max; Brauner, Annelie

2010-01-01

Interprofessional education (IPE) involving undergraduate health professionals is expected to promote collaboration in their later careers. The role of IPE between doctors and biomedical scientists has not been explored at the undergraduate level. Our aim was to introduce IPE sessions for medical and biomedical students in order to identify the benefits and barriers to these groups learning together. Medical and biomedical students together discussed laboratory results, relevant literature, and ideas for developing new diagnostic tools. The programme was evaluated with questionnaires and interviews. While there was general support for the idea of IPE, medical and biomedical students responded differently. Biomedical students were more critical, wanted more explicit learning objectives and felt that their professional role was often misunderstood. The medical students were more enthusiastic but regarded the way the biomedical students communicated concerns about their perceived role as a barrier to effective interprofessional learning. We conclude that stereotyping, which can impede effective collaborations between doctors and biomedical scientists, is already present at the undergraduate level and may be a barrier to IPE. Effective learning opportunities should be supported at the curriculum level and be designed to specifically enable a broad appreciation of each other's future professional roles.

Interoperability Gap Challenges for Learning Object Repositories & Learning Management Systems

ERIC Educational Resources Information Center

Mason, Robert T.

2011-01-01

An interoperability gap exists between Learning Management Systems (LMSs) and Learning Object Repositories (LORs). Learning Objects (LOs) and the associated Learning Object Metadata (LOM) that is stored within LORs adhere to a variety of LOM standards. A common LOM standard found in LORs is the Sharable Content Object Reference Model (SCORM)…

Use of camera drive in stereoscopic display of learning contents of introductory physics

NASA Astrophysics Data System (ADS)

Matsuura, Shu

2011-03-01

Simple 3D physics simulations with stereoscopic display were created for a part of introductory physics e-Learning. First, cameras to see the 3D world can be made controllable by the user. This enabled to observe the system and motions of objects from any position in the 3D world. Second, cameras were made attachable to one of the moving object in the simulation so as to observe the relative motion of other objects. By this option, it was found that users perceive the velocity and acceleration more sensibly on stereoscopic display than on non-stereoscopic 3D display. Simulations were made using Adobe Flash ActionScript, and Papervison 3D library was used to render the 3D models in the flash web pages. To display the stereogram, two viewports from virtual cameras were displayed in parallel in the same web page. For observation of stereogram, the images of two viewports were superimposed by using 3D stereogram projection box (T&TS CO., LTD.), and projected on an 80-inch screen. The virtual cameras were controlled by keyboard and also by Nintendo Wii remote controller buttons. In conclusion, stereoscopic display offers learners more opportunities to play with the simulated models, and to perceive the characteristics of motion better.

Teacher Educators as Learners: Enabling Learning while Developing Innovative Practice in ICT-Rich Education

ERIC Educational Resources Information Center

Reading, Chris; Doyle, Helen

2013-01-01

It's time for teachers to consider themselves as learners in ICT-rich learning environments and to become more aware of factors that enable their learning in such environments. The notion of teachers as learners in ICT-rich environments is not new but the focus is usually on school teachers and formal professional development, rather than teachers…

Applying Web-Enabled Problem-Based Learning and Self-Regulated Learning to Add Value to Computing Education in Taiwan's Vocational Schools

ERIC Educational Resources Information Center

Lee, Tsang-Hsiung; Shen, Pei-Di; Tsai, Chia-Wen

2008-01-01

This article describes the design and delivery of a compulsory course in packaged software at vocational schools in Taiwan. A course website was devised and deployed to supplement learning activities in the traditional classroom. A series of quasi-experiments was conducted with innovative instructional designs, that is, web-enabled problem-based…

Developing Long-Term Computing Skills among Low-Achieving Students via Web-Enabled Problem-Based Learning and Self-Regulated Learning

ERIC Educational Resources Information Center

Tsai, Chia-Wen; Lee, Tsang-Hsiung; Shen, Pei-Di

2013-01-01

Many private vocational schools in Taiwan have taken to enrolling students with lower levels of academic achievement. The authors re-designed a course and conducted a series of quasi-experiments to develop students' long-term computing skills, and examined the longitudinal effects of web-enabled, problem-based learning (PBL) and self-regulated…

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

PubMed Central

2016-01-01

Background As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs. Objective To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence. Methods A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method. Results The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models. Conclusions A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community. PMID:27986644

Evaluating the co-production of a near real time Earthquake Aftershock forecasting tool for humanitarian risk assessment and emergency planning

NASA Astrophysics Data System (ADS)

Quinn, Keira; Hope, Max; McCloskey, John; NicBhloscaidh, Mairead; Jimenez, Abigail; Dunlop, Paul

2015-04-01

Concern Worldwide and the University of Ulster Geophysics Research Group are engaged in a project to co-produce a suite of software and mapping tools to assess aftershock hazard in near real-time during the emergency response phase of earthquake disaster, and inform humanitarian emergency planning and response activities. This paper uses a social learning approach to evaluate this co-production process. Following Wenger (1999) we differentiate between the earthquake science and humanitarian communities of practice (CoP) along three dimensions: enterprise (the purpose of CoPs and the problems participants are working to address), repertoire (knowledge, skills, language), and identity (values and boundaries). We examine the effectiveness of learning between CoP, focusing on boundary work and objects, and various organisational structures and aspects of the wider political economy of learning that enable and hinder the co-production process. We conclude by identifying a number of ways to more effectively integrate earthquake science into humanitarian decision-making, policy development and programme design.

Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

PubMed

Choi, Ickwon; Chung, Amy W; Suscovich, Todd J; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J; Francis, Donald; Robb, Merlin L; Michael, Nelson L; Kim, Jerome H; Alter, Galit; Ackerman, Margaret E; Bailey-Kellogg, Chris

2015-04-01

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

Interviewing Neuroscientists for an Undergraduate Honors Project

PubMed Central

Montiel, Catalina; Meitzen, John

2017-01-01

Honors projects that supplement standard coursework are a widely used practice in undergraduate curricula. These projects can take many forms, ranging from laboratory research projects to performing service learning to literature analyses. Here we discuss an honors project focused on interviewing neuroscientists to learn about individual scientific practice and career paths, and synthesizing the resulting information into a personal reflection essay. We detail step-by-step instructions for performing this type of project, including how to develop interview questions, a sample project timeline, deliverables, learning objectives and outcomes, and address potential pitfalls. We provide sample interview questions, an interview solicitation email, and in the supplemental materials an example student reflection essay, assessment rubrics, and the transcription of a student-conducted interview of Drs. John Godwin and Santosh Mishra of North Carolina State University. This type of project is a promising method to enable student-researcher communication, and potentially useful to a broad spectrum of both honors and non-honors neuroscience coursework. PMID:29371847

Interviewing Neuroscientists for an Undergraduate Honors Project.

PubMed

Montiel, Catalina; Meitzen, John

2017-01-01

Honors projects that supplement standard coursework are a widely used practice in undergraduate curricula. These projects can take many forms, ranging from laboratory research projects to performing service learning to literature analyses. Here we discuss an honors project focused on interviewing neuroscientists to learn about individual scientific practice and career paths, and synthesizing the resulting information into a personal reflection essay. We detail step-by-step instructions for performing this type of project, including how to develop interview questions, a sample project timeline, deliverables, learning objectives and outcomes, and address potential pitfalls. We provide sample interview questions, an interview solicitation email, and in the supplemental materials an example student reflection essay, assessment rubrics, and the transcription of a student-conducted interview of Drs. John Godwin and Santosh Mishra of North Carolina State University. This type of project is a promising method to enable student-researcher communication, and potentially useful to a broad spectrum of both honors and non-honors neuroscience coursework.

Machine Learning Methods Enable Predictive Modeling of Antibody Feature:Function Relationships in RV144 Vaccinees

PubMed Central

Choi, Ickwon; Chung, Amy W.; Suscovich, Todd J.; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J.; Francis, Donald; Robb, Merlin L.; Michael, Nelson L.; Kim, Jerome H.; Alter, Galit; Ackerman, Margaret E.; Bailey-Kellogg, Chris

2015-01-01

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates. PMID:25874406

KDU E-Community Network.

ERIC Educational Resources Information Center

Jonhendro; Ching, Goh Bee; Wahab, Rohazna; Leng, Wang Meei; Aun, Jimmy Tan Lip; Yeoh, Eugene; Hock, Oon; Koo, W. K.

2001-01-01

Describes an education initiative developed by a company in Malaysia, the KDU, to implement a student-centered, teacher-facilitated, educational technology-enabled and knowledge-based learning environment. Explains the KDU e-Community Network that enables passive, interactive, collaborative, and constructivist learning for a variety of…

Implementation of the Xpert MTB/RIF assay for tuberculosis in Mongolia: a qualitative exploration of barriers and enablers

PubMed Central

Bekhbat, Solongo; Ganbaatar, Gantungalag; Dorjravdan, Munkhjargal; Pai, Madhukar; Dobler, Claudia C.

2017-01-01

Objective The aim of our study was to identify barriers and enablers to implementation of the Xpert MTB/RIF test within Mongolia’s National Tuberculosis Program. Methods Twenty-foursemi-structured interviews were conducted between June and September 2015 with laboratory staff and tuberculosis physicians in Mongolia’s capital Ulaanbaatar and regional towns where Xpert MTB/RIF testing had been implemented. Interviews were recorded, transcribed, translated and analysed thematically using NVIVO qualitative analysis software. Results Eight laboratory staff (five from the National Tuberculosis Reference Laboratory in Ulaanbaatar and three from provincial laboratories) and sixteen tuberculosis physicians (five from the Mongolian National Center for Communicable Diseases in Ulaanbaatar, four from district tuberculosis clinics in Ulaanbaatar and seven from provincial tuberculosis clinics) were interviewed. Major barriers to Xpert MTB/RIF implementation identified were: lack of awareness of program guidelines; inadequate staffing arrangements; problems with cartridge supply management; lack of local repair options for the Xpert machines; lack of regular formal training; paper based system; delayed treatment initiation due to consensus meeting and poor sample quality. Enablers to Xpert MTB/RIF implementation included availability of guidelines in the local language; provision of extra laboratory staff, shift working arrangements and additional modules; capacity for troubleshooting internally; access to experts; opportunities for peer learning; common understanding of diagnostic algorithms and decentralised testing. Conclusion Our study identified a number of barriers and enablers to implementation of Xpert MTB/RIF in the Mongolian National Tuberculosis Program. Lessons learned from this study can help to facilitate implementation of Xpert MTB/RIF in other Mongolian locations as well as other low-and middle-income countries. PMID:28717600

Building a balanced scorecard for a burn center.

PubMed

Wachtel, T L; Hartford, C E; Hughes, J A

1999-08-01

The Balanced Scorecard provides a model that can be adapted to the management of any burn center, burn service or burn program. This model enables an organization to translate its mission and vision into specific strategic objectives across the four perspective: (1) the financial perspective; (2) the customer service perspective; (3) the internal business perspective; and (4) the growth and learning perspective. Once the appropriate objectives are identified, the Balanced Scorecard guides the organization to develop reasonable performance measures and establishes targets, initiatives and alternatives to meet programmatic goals and pursue longer-term visionary improvements. We used the burn center at the University of Colorado Health Sciences Center to test whether the Balanced Scorecard methodology was appropriate for the core business plan of a healthcare strategic business unit (i.e. a burn center).

[Application of the balanced scorecard in nursing practice].

PubMed

Huang, Tsai-Yu; Chwo, Miao-Ju

2004-02-01

Kaplan and Norton's balanced scorecard (BSC) was developed in 1992. It was designed to be both a performance framework and a management methodology. The BSC enables an organization to convert its mission and vision into specific strategic objectives across four perspectives: (1) the financial perspective, (2) the customer perspective, (3) the internal business process perspective, and (4) the learning and growth perspective. Emphasis is focused on the balance of internal and external, outcome and future, and subjective and objective measures. Currently, some health care organizations have implemented the concept of the BSC as a performance measurement tool and are convinced that the BSC can be of great value to an organization. This paper provides development of the BSC and its application in the health care system and nursing practice.

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.

An interplay of fusiform gyrus and hippocampus enables prototype- and exemplar-based category learning.

PubMed

Lech, Robert K; Güntürkün, Onur; Suchan, Boris

2016-09-15

The aim of the present study was to examine the contributions of different brain structures to prototype- and exemplar-based category learning using functional magnetic resonance imaging (fMRI). Twenty-eight subjects performed a categorization task in which they had to assign prototypes and exceptions to two different families. This test procedure usually produces different learning curves for prototype and exception stimuli. Our behavioral data replicated these previous findings by showing an initially superior performance for prototypes and typical stimuli and a switch from a prototype-based to an exemplar-based categorization for exceptions in the later learning phases. Since performance varied, we divided participants into learners and non-learners. Analysis of the functional imaging data revealed that the interaction of group (learners vs. non-learners) and block (Block 5 vs. Block 1) yielded an activation of the left fusiform gyrus for the processing of prototypes, and an activation of the right hippocampus for exceptions after learning the categories. Thus, successful prototype- and exemplar-based category learning is associated with activations of complementary neural substrates that constitute object-based processes of the ventral visual stream and their interaction with unique-cue representations, possibly based on sparse coding within the hippocampus. Copyright © 2016 Elsevier B.V. All rights reserved.

Access to oral health care services among adults with learning disabilities: a scoping review.

PubMed

Naseem, Mustafa; Shah, Altaf H; Khiyani, Muhammad Faheem; Khurshid, Zohaib; Zafar, Muhammad Sohail; Gulzar, Shabnam; AlJameel, AlBandary H; Khalil, Hesham S

2016-01-01

The prevalence of oral diseases including dental caries and periodontal conditions is remarkably higher in people with disabilities. The provision of accessible oral health services for people with learning disabilities may be challenging. The objectives of the review were to identify barriers in accessing oral health care that persists within society, enabling or disabling people with learning disabilities. Using the Arksey O'Malley framework, a scoping review was conducted on PubMed/Medline, OVIDSP, and EMBASE. Studies were evaluated and short-listed based on the inclusion criteria, which consisted of: (1) study participants or population with learning disabilities, (2) aged 16 years or over, (3) reporting on access to oral health services, (4) published in the English language. Those that justified the inclusion criteria were carefully chosen after a blind peer-reviewed process when relevance and quality were debated. Nine studies were eventually included from searches. Tabulation of data was done under the heading of study type, outcomes, the year of publication and patient selection. The majority of studies provided a biomedical overview of access for adults with learning disabilities. The concept of access for people with disability is still ill-defined and obscure. Access to oral health care and needs of people with learning disabilities are complex and multi-facet.

A Study of Factors Affecting the Adoption of E-Learning Systems Enabled with Cultural Contextual Features by Instructions in Jamaican Tertiary Institutions

ERIC Educational Resources Information Center

Rhoden, Niccardo S.

2014-01-01

Understanding factors affecting the acceptance of E-Learning Systems Enabled with Cultural Contextual Features by lnstructors in Jamaican Tertiary Institutions is an important topic that's relevant to not only educational institutions, but developers of software for on line learning. The use of the unified theory of acceptance and use of…

Intelligent Discovery for Learning Objects Using Semantic Web Technologies

ERIC Educational Resources Information Center

Hsu, I-Ching

2012-01-01

The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…

Algorithms for Learning Preferences for Sets of Objects

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; desJardins, Marie; Eaton, Eric

2010-01-01

A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical concepts to estimate quantitative measures of the user s preferences from training examples (preferred subsets) specified by the user. Once preferences have been learned, the system uses those preferences to select preferred subsets from new sets. The method was found to be viable when tested in computational experiments on menus, music playlists, and rover images. Contemplated future development efforts include further tests on more diverse sets and development of a sub-method for (a) estimating the parameter that represents the relative importance of diversity versus depth, and (b) incorporating background knowledge about the nature of quality functions, which are special functions that specify depth preferences for features.

SU-D-201-05: On the Automatic Recognition of Patient Safety Hazards in a Radiotherapy Setup Using a Novel 3D Camera System and a Deep Learning Framework

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

Santhanam, A; Min, Y; Beron, P

Purpose: Patient safety hazards such as a wrong patient/site getting treated can lead to catastrophic results. The purpose of this project is to automatically detect potential patient safety hazards during the radiotherapy setup and alert the therapist before the treatment is initiated. Methods: We employed a set of co-located and co-registered 3D cameras placed inside the treatment room. Each camera provided a point-cloud of fraxels (fragment pixels with 3D depth information). Each of the cameras were calibrated using a custom-built calibration target to provide 3D information with less than 2 mm error in the 500 mm neighborhood around the isocenter.more » To identify potential patient safety hazards, the treatment room components and the patient’s body needed to be identified and tracked in real-time. For feature recognition purposes, we used a graph-cut based feature recognition with principal component analysis (PCA) based feature-to-object correlation to segment the objects in real-time. Changes in the object’s position were tracked using the CamShift algorithm. The 3D object information was then stored for each classified object (e.g. gantry, couch). A deep learning framework was then used to analyze all the classified objects in both 2D and 3D and was then used to fine-tune a convolutional network for object recognition. The number of network layers were optimized to identify the tracked objects with >95% accuracy. Results: Our systematic analyses showed that, the system was effectively able to recognize wrong patient setups and wrong patient accessories. The combined usage of 2D camera information (color + depth) enabled a topology-preserving approach to verify patient safety hazards in an automatic manner and even in scenarios where the depth information is partially available. Conclusion: By utilizing the 3D cameras inside the treatment room and a deep learning based image classification, potential patient safety hazards can be effectively avoided.« less

Discussion of the enabling environments for decentralised water systems.

PubMed

Moglia, M; Alexander, K S; Sharma, A

2011-01-01

Decentralised water supply systems are becoming increasingly affordable and commonplace in Australia and have the potential to alleviate urban water shortages and reduce pollution into natural receiving marine and freshwater streams. Learning processes are necessary to support the efficient implementation of decentralised systems. These processes reveal the complex socio-technical and institutional factors to be considered when developing an enabling environment supporting decentralised water and wastewater servicing solutions. Critical to the technological transition towards established decentralised systems is the ability to create strategic and adaptive capacity to promote learning and dialogue. Learning processes require institutional mechanisms to ensure the lessons are incorporated into the formulation of policy and regulation, through constructive involvement of key government institutions. Engagement of stakeholders is essential to the enabling environment. Collaborative learning environments using systems analysis with communities (social learning) and adaptive management techniques are useful in refining and applying scientists' and managers' knowledge (knowledge management).

Appreciative Inquiry for quality improvement in primary care practices.

PubMed

Ruhe, Mary C; Bobiak, Sarah N; Litaker, David; Carter, Caroline A; Wu, Laura; Schroeder, Casey; Zyzanski, Stephen J; Weyer, Sharon M; Werner, James J; Fry, Ronald E; Stange, Kurt C

2011-01-01

To test the effect of an Appreciative Inquiry (AI) quality improvement strategy on clinical quality management and practice development outcomes. Appreciative inquiry enables the discovery of shared motivations, envisioning a transformed future, and learning around the implementation of a change process. Thirty diverse primary care practices were randomly assigned to receive an AI-based intervention focused on a practice-chosen topic and on improving preventive service delivery (PSD) rates. Medical-record review assessed change in PSD rates. Ethnographic field notes and observational checklist analysis used editing and immersion/crystallization methods to identify factors affecting intervention implementation and practice development outcomes. The PSD rates did not change. Field note analysis suggested that the intervention elicited core motivations, facilitated development of a shared vision, defined change objectives, and fostered respectful interactions. Practices most likely to implement the intervention or develop new practice capacities exhibited 1 or more of the following: support from key leader(s), a sense of urgency for change, a mission focused on serving patients, health care system and practice flexibility, and a history of constructive practice change. An AI approach and enabling practice conditions can lead to intervention implementation and practice development by connecting individual and practice strengths and motivations to the change objective.

Appreciative Inquiry for Quality Improvement in Primary Care Practices

PubMed Central

Ruhe, Mary C.; Bobiak, Sarah N.; Litaker, David; Carter, Caroline A.; Wu, Laura; Schroeder, Casey; Zyzanski, Stephen; Weyer, Sharon M.; Werner, James J.; Fry, Ronald E.; Stange, Kurt C.

2014-01-01

Purpose To test the effect of an Appreciative Inquiry (AI) quality improvement strategy, on clinical quality management and practice development outcomes. AI enables discovery of shared motivations, envisioning a transformed future, and learning around implementation of a change process. Methods Thirty diverse primary care practices were randomly assigned to receive an AI-based intervention focused on a practice-chosen topic and on improving preventive service delivery (PSD) rates. Medical record review assessed change in PSD rates. Ethnographic fieldnotes and observational checklist analysis used editing and immersion/crystallization methods to identify factors affecting intervention implementation and practice development outcomes. Results PSD rates did not change. Field note analysis suggested that the intervention elicited core motivations, facilitated development of a shared vision, defined change objectives and fostered respectful interactions. Practices most likely to implement the intervention or develop new practice capacities exhibited one or more of the following: support from key leader(s), a sense of urgency for change, a mission focused on serving patients, health care system and practice flexibility, and a history of constructive practice change. Conclusions An AI approach and enabling practice conditions can lead to intervention implementation and practice development by connecting individual and practice strengths and motivations to the change objective. PMID:21192206

Visualizer: 3D Gridded Data Visualization Software for Geoscience Education and Research

NASA Astrophysics Data System (ADS)

Harwood, C.; Billen, M. I.; Kreylos, O.; Jadamec, M.; Sumner, D. Y.; Kellogg, L. H.; Hamann, B.

2008-12-01

In both research and education learning is an interactive and iterative process of exploring and analyzing data or model results. However, visualization software often presents challenges on the path to learning because it assumes the user already knows the locations and types of features of interest, instead of enabling flexible and intuitive examination of results. We present examples of research and teaching using the software, Visualizer, specifically designed to create an effective and intuitive environment for interactive, scientific analysis of 3D gridded data. Visualizer runs in a range of 3D virtual reality environments (e.g., GeoWall, ImmersaDesk, or CAVE), but also provides a similar level of real-time interactivity on a desktop computer. When using Visualizer in a 3D-enabled environment, the software allows the user to interact with the data images as real objects, grabbing, rotating or walking around the data to gain insight and perspective. On the desktop, simple features, such as a set of cross-bars marking the plane of the screen, provide extra 3D spatial cues that allow the user to more quickly understand geometric relationships within the data. This platform portability allows the user to more easily integrate research results into classroom demonstrations and exercises, while the interactivity provides an engaging environment for self-directed and inquiry-based learning by students. Visualizer software is freely available for download (www.keckcaves.org) and runs on Mac OSX and Linux platforms.

Assessing Learning, Quality and Engagement in Learning Objects: The Learning Object Evaluation Scale for Students (LOES-S)

ERIC Educational Resources Information Center

Kay, Robin H.; Knaack, Liesel

2009-01-01

Learning objects are interactive web-based tools that support the learning of specific concepts by enhancing, amplifying, and/or guiding the cognitive processes of learners. Research on the impact, effectiveness, and usefulness of learning objects is limited, partially because comprehensive, theoretically based, reliable, and valid evaluation…

Liberating Learning Object Design from the Learning Style of Student Instructional Designers

ERIC Educational Resources Information Center

Akpinar, Yavuz

2007-01-01

Learning objects are a new form of learning resource, and the design of these digital environments has many facets. To investigate senior instructional design students' use of reflection tools in designing learning objects, a series of studies was conducted using the Reflective Action Instructional Design and Learning Object Review Instrument…

Learning Objects and Gerontology

ERIC Educational Resources Information Center

Weinreich, Donna M.; Tompkins, Catherine J.

2006-01-01

Virtual AGE (vAGE) is an asynchronous educational environment that utilizes learning objects focused on gerontology and a learning anytime/anywhere philosophy. This paper discusses the benefits of asynchronous instruction and the process of creating learning objects. Learning objects are "small, reusable chunks of instructional media" Wiley…

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

Surgical education and training in an outer metropolitan hospital: a qualitative study of surgical trainers and trainees.

PubMed

Nestel, Debra; Harlim, Jennifer; Bryant, Melanie; Rampersad, Rajay; Hunter-Smith, David; Spychal, Bob

2017-08-01

The landscape of surgical training is changing. The anticipated increase in the numbers of surgical trainees and the shift to competency-based surgical training places pressures on an already stretched health service. With these pressures in mind, we explored trainers' and trainees' experiences of surgical training in a less traditional rotation, an outer metropolitan hospital. We considered practice-based learning theories to make meaning of surgical training in this setting, in particular Actor-network theory. We adopted a qualitative approach and purposively sampled surgical trainers and trainees to participate in individual interviews and focus groups respectively. Transcripts were made and thematically analysed. Institutional human research ethics approval was obtained. Four surgical trainers and fourteen trainees participated. Almost without exception, participants' report training needs to be well met. Emergent inter-related themes were: learning as social activity; learning and programmatic factors; learning and physical infrastructure; and, learning and organizational structure. This outer metropolitan hospital is suited to the provision of surgical training with the current rotational system for trainees. The setting offers experiences that enable consolidation of learning providing a rich and varied overall surgical training program. Although relational elements of learning were paramount they occurred within a complex environment. Actor-network theory was used to give meaning to emergent themes acknowledging that actors (both people and objects) and their interactions combine to influence training quality, shifting the focus of responsibility for learning away from individuals to the complex interactions in which they work and learn.

Health disorders related to learning the welding trade: assessment of approaches to risk communication 1

PubMed Central

Bonow, Clarice Alves; Cezar-Vaz, Marta Regina; da Silva, Lauro Roberto Witt; Rocha, Laurelize Pereira; Turik, Claudia

2014-01-01

Objective to assess the identification of health disorders as self-reported by apprentices of welding and to analyze the strength of the relationship between age and time of experience with self-reported health disorders before and after a socio-environmental nursing intervention. Method this quasi-experimental, non-randomized, before-and-after study was conducted with 86 welding apprentices from a private entity. Results the results show a significant difference for the pre- and post-test means and an increase in the post-test mean score for the cardiovascular, respiratory and cutaneous systems. There was also a negative correlation between the apprentices' ages and the identification of health disorders. Conclusion the socio-environmental nursing intervention enabled obtaining information on health disorders related to welding. In turn, such information enabled the apprentices to assess information and self-report health disorders. PMID:24553702

[A cooperation learning program to improve health promotion approach].

PubMed

Dollet, Agnès

2014-10-01

Cooperation in the health and social welfare sectors enables the users to be taken care of, as a part of a health promotion approach. The aim of L'IRFSS Auvergne is to promote cooperation between future nurses and social workers within its training sessions. Based on that work, the objective was to implement a framework integrated to both the nursing and social work curriculum, enabling the students to develop team working skills on the field. A survey of nurses and social workers leads to the creation of a pedagogical tool adapted to issues encountered on the field. « the cooperation toolbox kit »In addition to this project, the study raised the question of the role of health promotion in the social work curriculum, the organization of the lifelong training department in a given area, and the role of coordination in the training of managerial staff.

Generalization in Adaptation to Stable and Unstable Dynamics

PubMed Central

Kadiallah, Abdelhamid; Franklin, David W.; Burdet, Etienne

2012-01-01

Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. PMID:23056191

Towards an understanding of the attributes of simulation that enable learning in undergraduate nurse education: A grounded theory study.

PubMed

Bland, Andrew J; Tobbell, Jane

2016-09-01

Simulation has become an established feature of nurse education yet little is understood about the mechanisms that lead to learning. To explore the attributes of simulation-based education that enable student learning in undergraduate nurse education. Final year students drawn from one UK University (n=46) participated in a grounded theory study. First, nonparticipant observation and video recording of student activity was undertaken. Following initial analysis, recordings and observations were deconstructed during focus group interviews that enabled both the researcher and participants to unpack meaning. Lastly emergent findings were verified with final year students drawn from a second UK University (n=6). A staged approach to learning emerged from engagement in simulation. This began with initial hesitation as students moved through nonlinear stages to making connections and thinking like a nurse. Core findings suggest that simulation enables curiosity and intellect (main concern) through doing (core category) and interaction with others identified as social collaboration (category). This study offers a theoretical basis for understanding simulation-based education and integration of strategies that maximise the potential for learning. Additionally it offers direction for further research, particularly with regards to how the application of theory to practice is accelerated through learning by doing and working collaboratively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Human-robot skills transfer interfaces for a flexible surgical robot.

PubMed

Calinon, Sylvain; Bruno, Danilo; Malekzadeh, Milad S; Nanayakkara, Thrishantha; Caldwell, Darwin G

2014-09-01

In minimally invasive surgery, tools go through narrow openings and manipulate soft organs to perform surgical tasks. There are limitations in current robot-assisted surgical systems due to the rigidity of robot tools. The aim of the STIFF-FLOP European project is to develop a soft robotic arm to perform surgical tasks. The flexibility of the robot allows the surgeon to move within organs to reach remote areas inside the body and perform challenging procedures in laparoscopy. This article addresses the problem of designing learning interfaces enabling the transfer of skills from human demonstration. Robot programming by demonstration encompasses a wide range of learning strategies, from simple mimicking of the demonstrator's actions to the higher level imitation of the underlying intent extracted from the demonstrations. By focusing on this last form, we study the problem of extracting an objective function explaining the demonstrations from an over-specified set of candidate reward functions, and using this information for self-refinement of the skill. In contrast to inverse reinforcement learning strategies that attempt to explain the observations with reward functions defined for the entire task (or a set of pre-defined reward profiles active for different parts of the task), the proposed approach is based on context-dependent reward-weighted learning, where the robot can learn the relevance of candidate objective functions with respect to the current phase of the task or encountered situation. The robot then exploits this information for skills refinement in the policy parameters space. The proposed approach is tested in simulation with a cutting task performed by the STIFF-FLOP flexible robot, using kinesthetic demonstrations from a Barrett WAM manipulator. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Issues in the Adoption of Broadband-Enabled Learning

ERIC Educational Resources Information Center

Murphy, Elizabeth

2005-01-01

This paper presents one case of broadband-enabled learning (BEL) involving geo-culturally and organisationally diverse collaboration using music as the vehicle. Findings from five evaluations over a 15-month period were considered in relation to issues of relative advantage, compatibility, complexity, trialability, and observability. Advantages…

MEDICOL: online learning in medicine and dentistry.

PubMed

Broudo, Marc; Walsh, Charlene

2002-09-01

MEDICOL (Medicine and Dentistry Integrated Curriculum Online) provides a variety of Web-based resources that act as important adjuncts to all the teaching components of the medical and dental undergraduate curriculum. It uses WebCT, a course-management system, to provide the following educational functions: (1) track students' progress and present course information such as time-tables, learning objectives, handout materials, images, references, course assignments, and evaluations; (2) promote student-to-student and student-to-instructor interactions (through e-mail and bulletin boards); and (3) deliver self-directed learning components, including weekly self-assessment quizzes that provide immediate feedback and multimedia learning modules (clinical skills, radiology, evidence-based medicine, etc.). The University of British Columbia Faculties of Medicine and Dentistry feature a problem-based learning (PBL) curriculum in which students access many of the same tools they will utilize in their professional practice. In the PBL curriculum, students must access the relevant clinical data and educational resources. A MEDICOL site has also been developed for medical students to use during their rural family practice, a four- to six-week experience in the summer after their second year. This site has been designed to be a supplemental learning environment for not only these students, but also for their physician preceptors. It is intended to foster communication among participants, bring new resources to the rural setting, and allow preceptors to develop their Internet skills with the help of students who are already familiar with the electronic environment. The MEDICOL sites enable the exchange of information about the learning issues between, as well as within, tutorial groups. MEDICOL also provides students with faculty-reviewed resources that are listed online; multimedia presentations; and access to histology, radiology, and pathology images through an online image database. Each week, students have access to a new interactive and automatically graded self-assessment quiz for individual study. These quizzes test learning objectives from tutorial, lecture, and lab material for each week of the curriculum and are modeled after summative examinations held twice each year. Question authors provide immediately accessible quality feedback to students. A comprehensive quiz databank of approximately 1,500 questions has been attained. WebCT enables MEDICOL to deliver anonymous, online program-evaluation questionnaires during clinical clerkships (resulting in a 99% response rate after a few e-mail reminders), with easy and timely data collection and reporting methods. Summative assessments have also been delivered through MEDICOL. Use statistics indicate that over 90% of students regularly use the MEDICOL sites and have found them helpful. University of British Columbia medical school enrollment will increase because of collaborations with campuses and medical centers across the province. MEDICOL will likely play an increased role in distance learning by continuing to deliver the resources already described, as well as facilitating synchronous communications (e.g., PBL chat rooms) and teaching (e.g., video-streamed lectures) to students located across the province.

An Investigation on the Correlation of Learner Styles and Learning Objects Characteristics in a Proposed Learning Objects Management Model (LOMM)

ERIC Educational Resources Information Center

Wanapu, Supachanun; Fung, Chun Che; Kerdprasop, Nittaya; Chamnongsri, Nisachol; Niwattanakul, Suphakit

2016-01-01

The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system.…

Integrating Touch-Enabled and Mobile Devices into Contemporary Mathematics Education

ERIC Educational Resources Information Center

Meletiou-Mavrotheris, Maria, Ed.; Mavrou, Katerina, Ed.; Paparistodemou, Efi, Ed.

2015-01-01

Despite increased interest in mobile devices as learning tools, the amount of available primary research studies on their integration into mathematics teaching and learning is still relatively small due to the novelty of these technologies. "Integrating Touch-Enabled and Mobile Devices into Contemporary Mathematics Education" presents…

Student Agency for Powerful Learning

ERIC Educational Resources Information Center

Wiliams, Philip

2017-01-01

School libraries play a powerful role in enabling, informing, and sustaining student agency, and nothing engages and motivates students more deeply than enabling them to become the active agents in the process of learning. Students with agency are powerful learners who are prepared to engage with the world with sustained, courageous curiosity.…

Organizational and Relational Factors in Professional Learning Communities

ERIC Educational Resources Information Center

Gray, Julie; Mitchell, Roxanne; Tarter, C. John

2014-01-01

The roles of organizational and relational factors in regard to professional learning communities (PLCs) have been investigated by many, yet none have considered enabling school structures, trust, and collective efficacy as variables. We take a deeper look at the formal or organizational aspects of the school represented by enabling school…

The Role of Virtual Learning Environment in Improving Information and Communication Technology Adoption in Teaching Exploring How Virtual Learning Environments Improve University Teacher's Attitudes about the Use of Information and Communication Technology

ERIC Educational Resources Information Center

Ageel, Mohammed

2012-01-01

The adoption of ICT-enabled teaching in contemporary schools has largely lagged behind despite its obvious and many benefits, mainly because teachers still hold ignorant, misinformed and highly negative attitudes towards ICT-enabled teaching. This article aimed at investigating the effect of Virtual Learning Environments (VLE) on university…

Unsupervised domain adaptation for early detection of drought stress in hyperspectral images

NASA Astrophysics Data System (ADS)

Schmitter, P.; Steinrücken, J.; Römer, C.; Ballvora, A.; Léon, J.; Rascher, U.; Plümer, L.

2017-09-01

Hyperspectral images can be used to uncover physiological processes in plants if interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) and Random Forests have been applied to estimate development of biomass and detect and predict plant diseases and drought stress. One basic requirement of machine learning implies, that training and testing is done in the same domain and the same distribution. Different genotypes, environmental conditions, illumination and sensors violate this requirement in most practical circumstances. Here, we present an approach, which enables the detection of physiological processes by transferring the prior knowledge within an existing model into a related target domain, where no label information is available. We propose a two-step transformation of the target features, which enables a direct application of an existing model. The transformation is evaluated by an objective function including additional prior knowledge about classification and physiological processes in plants. We have applied the approach to three sets of hyperspectral images, which were acquired with different plant species in different environments observed with different sensors. It is shown, that a classification model, derived on one of the sets, delivers satisfying classification results on the transformed features of the other data sets. Furthermore, in all cases early non-invasive detection of drought stress was possible.

Process evaluation of the Enabling Mothers toPrevent Pediatric Obesity Through Web-Based Learning and Reciprocal Determinism (EMPOWER) randomized control trial.

PubMed

Knowlden, Adam P; Sharma, Manoj

2014-09-01

Family-and-home-based interventions are an important vehicle for preventing childhood obesity. Systematic process evaluations have not been routinely conducted in assessment of these interventions. The purpose of this study was to plan and conduct a process evaluation of the Enabling Mothers to Prevent Pediatric Obesity Through Web-Based Learning and Reciprocal Determinism (EMPOWER) randomized control trial. The trial was composed of two web-based, mother-centered interventions for prevention of obesity in children between 4 and 6 years of age. Process evaluation used the components of program fidelity, dose delivered, dose received, context, reach, and recruitment. Categorical process evaluation data (program fidelity, dose delivered, dose exposure, and context) were assessed using Program Implementation Index (PII) values. Continuous process evaluation variables (dose satisfaction and recruitment) were assessed using ANOVA tests to evaluate mean differences between groups (experimental and control) and sessions (sessions 1 through 5). Process evaluation results found that both groups (experimental and control) were equivalent, and interventions were administered as planned. Analysis of web-based intervention process objectives requires tailoring of process evaluation models for online delivery. Dissemination of process evaluation results can advance best practices for implementing effective online health promotion programs. © 2014 Society for Public Health Education.

A quantitative theory of the functions of the hippocampal CA3 network in memory

PubMed Central

Rolls, Edmund T.

2013-01-01

A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory. PMID:23805074

Virtual Workshop Environment (VWE): A Taxonomy and Service Oriented Architecture (SOA) Framework for Modularized Virtual Learning Environments (VLE)--Applying the Learning Object Concept to the VLE

ERIC Educational Resources Information Center

Paulsson, Fredrik; Naeve, Ambjorn

2006-01-01

Based on existing Learning Object taxonomies, this article suggests an alternative Learning Object taxonomy, combined with a general Service Oriented Architecture (SOA) framework, aiming to transfer the modularized concept of Learning Objects to modularized Virtual Learning Environments. The taxonomy and SOA-framework exposes a need for a clearer…

Smart Learning: Are We Ready for It?

ERIC Educational Resources Information Center

Poulova, Petra; Klimova, Blanka

2015-01-01

Nowadays learning, particularly the university learning, is supported with modern information and communication technologies. These technologies also enable electronic learning, known as eLearning, which is now firmly established at almost all institutions of higher learning in developed and developing countries. Moreover, at present eLearning is…

Dopamine release from the locus coeruleus to the dorsal hippocampus promotes spatial learning and memory

PubMed Central

Kempadoo, Kimberly A.; Mosharov, Eugene V.; Choi, Se Joon; Sulzer, David; Kandel, Eric R.

2016-01-01

Dopamine neurotransmission in the dorsal hippocampus is critical for a range of functions from spatial learning and synaptic plasticity to the deficits underlying psychiatric disorders such as attention-deficit hyperactivity disorder. The ventral tegmental area (VTA) is the presumed source of dopamine in the dorsal hippocampus. However, there is a surprising scarcity of VTA dopamine axons in the dorsal hippocampus despite the dense network of dopamine receptors. We have explored this apparent paradox using optogenetic, biochemical, and behavioral approaches and found that dopaminergic axons and subsequent dopamine release in the dorsal hippocampus originate from neurons of the locus coeruleus (LC). Photostimulation of LC axons produced an increase in dopamine release in the dorsal hippocampus as revealed by high-performance liquid chromatography. Furthermore, optogenetically induced release of dopamine from the LC into the dorsal hippocampus enhanced selective attention and spatial object recognition via the dopamine D1/D5 receptor. These results suggest that spatial learning and memory are energized by the release of dopamine in the dorsal hippocampus from noradrenergic neurons of the LC. The present findings are critical for identifying the neural circuits that enable proper attention selection and successful learning and memory. PMID:27930324

Dopamine release from the locus coeruleus to the dorsal hippocampus promotes spatial learning and memory.

PubMed

Kempadoo, Kimberly A; Mosharov, Eugene V; Choi, Se Joon; Sulzer, David; Kandel, Eric R

2016-12-20

Dopamine neurotransmission in the dorsal hippocampus is critical for a range of functions from spatial learning and synaptic plasticity to the deficits underlying psychiatric disorders such as attention-deficit hyperactivity disorder. The ventral tegmental area (VTA) is the presumed source of dopamine in the dorsal hippocampus. However, there is a surprising scarcity of VTA dopamine axons in the dorsal hippocampus despite the dense network of dopamine receptors. We have explored this apparent paradox using optogenetic, biochemical, and behavioral approaches and found that dopaminergic axons and subsequent dopamine release in the dorsal hippocampus originate from neurons of the locus coeruleus (LC). Photostimulation of LC axons produced an increase in dopamine release in the dorsal hippocampus as revealed by high-performance liquid chromatography. Furthermore, optogenetically induced release of dopamine from the LC into the dorsal hippocampus enhanced selective attention and spatial object recognition via the dopamine D1/D5 receptor. These results suggest that spatial learning and memory are energized by the release of dopamine in the dorsal hippocampus from noradrenergic neurons of the LC. The present findings are critical for identifying the neural circuits that enable proper attention selection and successful learning and memory.

Helping Hands: Using Augmented Reality to Provide Remote Guidance to Health Professionals.

PubMed

Mather, Carey; Barnett, Tony; Broucek, Vlasti; Saunders, Annette; Grattidge, Darren; Huang, Weidong

2017-01-01

Access to expert practitioners or geographic distance can compound the capacity for appropriate supervision of health professionals in the workplace. Guidance and support of clinicians and students to undertake new or infrequent procedures can be resource intensive. The Helping Hands remote augmented reality system is an innovation to support the development of, and oversee the acquisition of procedural skills through remote learning and teaching supervision while in clinical practice. Helping Hands is a wearable, portable, hands-free, low cost system comprised of two networked laptops, a head-mounted display worn by the recipient and a display screen used remotely by the instructor. Hand hygiene was used as the test procedure as it is a foundation skill learned by all health profession students. The technology supports unmediated remote gesture guidance by augmenting the object with the Helping Hands of a health professional. A laboratory-based study and field trial tested usability and feasibility of the remote guidance system. The study found the Helping Hands system did not compromise learning outcomes. This innovation has the potential to transform remote learning and teaching supervision by enabling health professionals and students opportunities to develop and improve their procedural performance at the workplace.

How we launched a developmental student-as-teacher (SAT) program for all medical students.

PubMed

Blanco, Maria A; Maderer, Ann; Oriel, Amanda; Epstein, Scott K

2014-05-01

Teaching is a necessary skill for medical trainees and physicians. We designed and launched a developmental Student-as-Teacher program for all students, beginning with the class of 2016. A task force of faculty and students designed the program. The goal is to enable all students to acquire basic principles of teaching and learning at different stages in their four-year medical school career. Upon completion, students will achieve twenty-eight learning objectives grouped within four competency domains: (1) Adult and Practice-Based Learning; (2) Learning Environment; (3) Instructional Design and Performance; and, (4) Learner's Assessment and Evaluation. The program combines online learning modules and a field teaching experience. The entire class of 2016 (N = 200) completed the first online module. Students found the module effective, and 70% reported an increase in their level of knowledge. Although most students are expected to complete their field teaching experience in fourth year, twelve students completed their field experience in first year. Reported strengths of these experiences include reinforcement of their medical knowledge and improvement of their adult teaching skills. The program was successfully launched, and students are already experiencing the benefits of training in basic teaching skills in the first year of the program.

An Energy-Efficient and Scalable Deep Learning/Inference Processor With Tetra-Parallel MIMD Architecture for Big Data Applications.

PubMed

Park, Seong-Wook; Park, Junyoung; Bong, Kyeongryeol; Shin, Dongjoo; Lee, Jinmook; Choi, Sungpill; Yoo, Hoi-Jun

2015-12-01

Deep Learning algorithm is widely used for various pattern recognition applications such as text recognition, object recognition and action recognition because of its best-in-class recognition accuracy compared to hand-crafted algorithm and shallow learning based algorithms. Long learning time caused by its complex structure, however, limits its usage only in high-cost servers or many-core GPU platforms so far. On the other hand, the demand on customized pattern recognition within personal devices will grow gradually as more deep learning applications will be developed. This paper presents a SoC implementation to enable deep learning applications to run with low cost platforms such as mobile or portable devices. Different from conventional works which have adopted massively-parallel architecture, this work adopts task-flexible architecture and exploits multiple parallelism to cover complex functions of convolutional deep belief network which is one of popular deep learning/inference algorithms. In this paper, we implement the most energy-efficient deep learning and inference processor for wearable system. The implemented 2.5 mm × 4.0 mm deep learning/inference processor is fabricated using 65 nm 8-metal CMOS technology for a battery-powered platform with real-time deep inference and deep learning operation. It consumes 185 mW average power, and 213.1 mW peak power at 200 MHz operating frequency and 1.2 V supply voltage. It achieves 411.3 GOPS peak performance and 1.93 TOPS/W energy efficiency, which is 2.07× higher than the state-of-the-art.

Using literature to help physician-learners understand and manage "difficult" patients.

PubMed

Shapiro, J; Lie, D

2000-07-01

Despite significant clinical and research efforts aimed at recognizing and managing "difficult" patients, such patients remain a frustrating experience for many clinicians. This is especially true for primary care residents, who are required to see a significant volume of patients with diverse and complex problems, but who may not have adequate training and life experience to enable them to deal with problematic doctor-patient situations. Literature--short stories, poems, and patient narratives--is a little-explored educational tool to help residents in understanding and working with difficult patients. In this report, the authors examine the mechanics of using literature to teach about difficult patients, including structuring the learning environment, establishing learning objectives, identifying teaching resources and appropriate pedagogic methods, and incorporating creative writing assignments. They also present an illustrative progression of a typical literature-based teaching session about a difficult patient.

Metric Learning to Enhance Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Thompson, David R.; Castano, Rebecca; Bue, Brian; Gilmore, Martha S.

2013-01-01

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

Plasticity in neuromagnetic cortical responses suggests enhanced auditory object representation

PubMed Central

2013-01-01

Background Auditory perceptual learning persistently modifies neural networks in the central nervous system. Central auditory processing comprises a hierarchy of sound analysis and integration, which transforms an acoustical signal into a meaningful object for perception. Based on latencies and source locations of auditory evoked responses, we investigated which stage of central processing undergoes neuroplastic changes when gaining auditory experience during passive listening and active perceptual training. Young healthy volunteers participated in a five-day training program to identify two pre-voiced versions of the stop-consonant syllable ‘ba’, which is an unusual speech sound to English listeners. Magnetoencephalographic (MEG) brain responses were recorded during two pre-training and one post-training sessions. Underlying cortical sources were localized, and the temporal dynamics of auditory evoked responses were analyzed. Results After both passive listening and active training, the amplitude of the P2m wave with latency of 200 ms increased considerably. By this latency, the integration of stimulus features into an auditory object for further conscious perception is considered to be complete. Therefore the P2m changes were discussed in the light of auditory object representation. Moreover, P2m sources were localized in anterior auditory association cortex, which is part of the antero-ventral pathway for object identification. The amplitude of the earlier N1m wave, which is related to processing of sensory information, did not change over the time course of the study. Conclusion The P2m amplitude increase and its persistence over time constitute a neuroplastic change. The P2m gain likely reflects enhanced object representation after stimulus experience and training, which enables listeners to improve their ability for scrutinizing fine differences in pre-voicing time. Different trajectories of brain and behaviour changes suggest that the preceding effect of a P2m increase relates to brain processes, which are necessary precursors of perceptual learning. Cautious discussion is required when interpreting the finding of a P2 amplitude increase between recordings before and after training and learning. PMID:24314010

Development of a National Consensus for Tactical Emergency Medical Support (TEMS) Training Programs--Operators and Medical Providers.

PubMed

Schwartz, Richard; Lerner, Brooke; Llwewllyn, Craig; Pennardt, Andre; Wedmore, Ian; Callaway, David; Wightman, John; Casillas, Raymond; Eastman, Alex; Gerold, Kevin; Giebner, Stephen; Davidson, Robert; Kamin, Richard; Piazza, Gina; Bollard, Glenn; Carmona, Phillip; Sonstrom, Ben; Seifarth, William; Nicely, Barbara; Croushorn, John; Carmona, Richard

2014-01-01

Tactical teams are at high risk of sustaining injuries. Caring for these casualties in the field involves unique requirements beyond what is provided by traditional civilian emergency medical services (EMS) systems. Despite this need, the training objectives and competencies are not uniformly agreed to or taught. An expert panel was convened that included members from the Departments of Defense, Homeland Security, Justice, and Health and Human Services, as well as federal, state, and local law-enforcement officers who were recruited through requests to stakeholder agencies and open invitations to individuals involved in Tactical Emergency Medical Services (TEMS) or its oversight. Two face-to-face meetings took place. Using a modified Delphi technique, previously published TEMS competencies were reviewed and updated. The original 17 competency domains were modified and the most significant changes were the addition of Tactical Emergency Casualty Care (TECC), Tactical Familiarization, Legal Aspects of TEMS, and Mass Casualty Triage to the competency domains. Additionally, enabling and terminal learning objectives were developed for each competency domain. This project has developed a minimum set of medical competencies and learning objectives for both tactical medical providers and operators. This work should serve as a platform for ensuring minimum knowledge among providers, which will serve enhance team interoperability and improve the health and safety of tactical teams and the public. 2014.

Shared Canadian Curriculum in Family Medicine (SHARC-FM): Creating a national consensus on relevant and practical training for medical students.

PubMed

Keegan, David A; Scott, Ian; Sylvester, Michael; Tan, Amy; Horrey, Kathleen; Weston, W Wayne

2017-04-01

In 2006, leaders of undergraduate family medicine education programs faced a series of increasing curriculum mandates in the context of limited time and financial resources. Additionally, it became apparent that a hidden curriculum against family medicine as a career choice was active in medical schools. The Shared Canadian Curriculum in Family Medicine was developed by the Canadian Undergraduate Family Medicine Education Directors and supported by the College of Family Physicians of Canada as a national collaborative project to support medical student training in family medicine clerkship. Its key objective is to enable education leaders to meet their educational mandates, while at the same time countering the hidden curriculum and providing a route to scholarship. The Shared Canadian Curriculum in Family Medicine is an open-access, shared, national curriculum ( www.sharcfm.ca ). It contains 23 core clinical topics (determined through a modified Delphi process) with demonstrable objectives for each. It also includes low- and medium-fidelity virtual patient cases, point-of-care learning resources (clinical cards), and assessment tools, all aligned with the core topics. French translation of the resources is ongoing. The core topics, objectives, and educational resources have been adopted by medical schools across Canada, according to their needs. The lessons learned from mounting this multi-institutional collaborative project will help others develop their own collaborative curricula. Copyright© the College of Family Physicians of Canada.

Implementing simulated learning modules to improve students’ pharmacy practice skills and professionalism

PubMed Central

Fejzic, Jasmina; Barker, Michelle

2015-01-01

Background: Effective communication enables healthcare professionals and students to practise their disciplines in a professional and competent manner. Simulated-based education (SBE) has been increasingly used to improve students’ communication and practice skills in Health Education. Objective: Simulated learning modules (SLMs) were developed using practice-based scenarios grounded in effective communication competencies. The effect of the SLMs on Pharmacy students’ (i) Practice skills and (ii) Professionalism were evaluated. Methods: SLMs integrating EXCELL competencies were applied in the classroom to study their effect on a number of learning outcomes. EXcellence in Cultural Experiential Learning and Leadership (EXCELL) Program is a schematic, evidence-based professional development resource centred around developing participants’ self-efficacy and generic communication competencies. Students (N=95) completed three hours of preliminary lectures and eight hours of SLM workshops including six scenarios focused on Pharmacy Practice and Experiential Placements. Each SLM included briefing, role-plays with actors, facilitation, and debriefing on EXCELL social interaction maps (SIMs). Evaluations comprised quantitative and qualitative survey responsed by students before and post-workshops, and post-placements, and teachers’ reflections. Surveys examine specific learning outcomes by using pharmacy professionalism and pharmacy practice effectiveness scales. Responses were measured prior to the commencement of SLMs, after completion of the two workshops and after students completed their block placement. Self-report measures enabled students to self-assess whether any improvements occurred. Results: Student responses were overwhelmingly positive and indicated significant improvements in their Pharmacy practice and professionalism skills, and commitment to professional ethics. Qualitative feedback strongly supported students’ improved communication skills and confidence. Teacher reflections observed ecological validity of SLMs as a method to enhance professionalism and communication skills, and suggested ways to improve this teaching modality. Conclusion: Inclusion of SLMs centred on practice and professionalism was evaluated as an effective, teaching strategy by students and staff. The integration of SIMs in SLMs has potential for wider application in clinical teaching. PMID:26445619

Concurrent extensions to the FORTRAN language for parallel programming of computational fluid dynamics algorithms

NASA Technical Reports Server (NTRS)

Weeks, Cindy Lou

1986-01-01

Experiments were conducted at NASA Ames Research Center to define multi-tasking software requirements for multiple-instruction, multiple-data stream (MIMD) computer architectures. The focus was on specifying solutions for algorithms in the field of computational fluid dynamics (CFD). The program objectives were to allow researchers to produce usable parallel application software as soon as possible after acquiring MIMD computer equipment, to provide researchers with an easy-to-learn and easy-to-use parallel software language which could be implemented on several different MIMD machines, and to enable researchers to list preferred design specifications for future MIMD computer architectures. Analysis of CFD algorithms indicated that extensions of an existing programming language, adaptable to new computer architectures, provided the best solution to meeting program objectives. The CoFORTRAN Language was written in response to these objectives and to provide researchers a means to experiment with parallel software solutions to CFD algorithms on machines with parallel architectures.

Understanding Learner Acceptance of Learning Objects: The Roles of Learning Object Characteristics and Individual Differences

ERIC Educational Resources Information Center

Lau, Siong-Hoe; Woods, Peter C.

2009-01-01

Many organisations and institutions have integrated learning objects into their e-learning systems to make the instructional resources more efficient. Like any other information systems, this trend has made user acceptance of learning objects an increasingly critical issue as a high level of learner satisfaction and acceptance reflects that the…

Developing a "toolkit" to measure implementation of concurrent palliative care in rural community cancer centers.

PubMed

Zubkoff, Lisa; Dionne-Odom, J Nicholas; Pisu, Maria; Babu, Dilip; Akyar, Imatullah; Smith, Tasha; Mancarella, Gisella A; Gansauer, Lucy; Sullivan, Margaret Murray; Swetz, Keith M; Azuero, Andres; Bakitas, Marie A

2018-02-01

Despite national guidelines recommending early concurrent palliative care for individuals newly diagnosed with metastatic cancer, few community cancer centers, especially those in underserved rural areas do so. We are implementing an early concurrent palliative care model, ENABLE (Educate, Nurture, Advise, Before Life Ends) in four, rural-serving community cancer centers. Our objective was to develop a "toolkit" to assist community cancer centers that wish to integrate early palliative care for patients with newly diagnosed advanced cancer and their family caregivers. Guided by the RE-AIM (Reach, Effectiveness-Adoption, Implementation, Maintenance) framework, we undertook an instrument-development process based on the literature, expert and site stakeholder review and feedback, and pilot testing during site visits. We developed four instruments to measure ENABLE implementation: (1) the ENABLE RE-AIM Self-Assessment Tool to assess reach, adoption, implementation, and maintenance; (2) the ENABLE General Organizational Index to assess institutional implementation; (3) an Implementation Costs Tool; and (4) an Oncology Clinicians' Perceptions of Early Concurrent Oncology Palliative Care survey. We developed four measures to determine early palliative care implementation. These measures have been pilot-tested, and will be integrated into a comprehensive "toolkit" to assist community cancer centers to measure implementation outcomes. We describe the lessons learned and recommend strategies for promoting long-term program sustainability.

Learned filters for object detection in multi-object visual tracking

NASA Astrophysics Data System (ADS)

Stamatescu, Victor; Wong, Sebastien; McDonnell, Mark D.; Kearney, David

2016-05-01

We investigate the application of learned convolutional filters in multi-object visual tracking. The filters were learned in both a supervised and unsupervised manner from image data using artificial neural networks. This work follows recent results in the field of machine learning that demonstrate the use learned filters for enhanced object detection and classification. Here we employ a track-before-detect approach to multi-object tracking, where tracking guides the detection process. The object detection provides a probabilistic input image calculated by selecting from features obtained using banks of generative or discriminative learned filters. We present a systematic evaluation of these convolutional filters using a real-world data set that examines their performance as generic object detectors.

Smart Learning Adoption in Employees and HRD Managers

ERIC Educational Resources Information Center

Lee, Junghwan; Zo, Hangjung; Lee, Hwansoo

2014-01-01

The innovation of online technologies and the rapid diffusion of smart devices are changing workplace learning environment. Smart learning, as emerging learning paradigm, enables employees' learning to take place anywhere and anytime. Workplace learning studies, however, have focused on traditional e-learning environment, and they have failed…

EarthCollab, building geoscience-centric implementations of the VIVO semantic software suite

NASA Astrophysics Data System (ADS)

Rowan, L. R.; Gross, M. B.; Mayernik, M. S.; Daniels, M. D.; Krafft, D. B.; Kahn, H. J.; Allison, J.; Snyder, C. B.; Johns, E. M.; Stott, D.

2017-12-01

EarthCollab, an EarthCube Building Block project, is extending an existing open-source semantic web application, VIVO, to enable the exchange of information about scientific researchers and resources across institutions. EarthCollab is a collaboration between UNAVCO, a geodetic facility and consortium that supports diverse research projects informed by geodesy, The Bering Sea Project, an interdisciplinary field program whose data archive is hosted by NCAR's Earth Observing Laboratory, and Cornell University. VIVO has been implemented by more than 100 universities and research institutions to highlight research and institutional achievements. This presentation will discuss benefits and drawbacks of working with and extending open source software. Some extensions include plotting georeferenced objects on a map, a mobile-friendly theme, integration of faceting via Elasticsearch, extending the VIVO ontology to capture geoscience-centric objects and relationships, and the ability to cross-link between VIVO instances. Most implementations of VIVO gather information about a single organization. The EarthCollab project created VIVO extensions to enable cross-linking of VIVO instances to reduce the amount of duplicate information about the same people and scientific resources and to enable dynamic linking of related information across VIVO installations. As the list of customizations grows, so does the effort required to maintain compatibility between the EarthCollab forks and the main VIVO code. For example, dozens of libraries and dependencies were updated prior to the VIVO v1.10 release, which introduced conflicts in the EarthCollab cross-linking code. The cross-linking code has been developed to enable sharing of data across different versions of VIVO, however, using a JSON output schema standardized across versions. We will outline lessons learned in working with VIVO and its open source dependencies, which include Jena, Solr, Freemarker, and jQuery and discuss future work by EarthCollab, which includes refining the cross-linking VIVO capabilities by continued integration of persistent and unique identifiers to enable automated lookup and matching across institutional VIVOs.

PixelLearn

NASA Technical Reports Server (NTRS)

Mazzoni, Dominic; Wagstaff, Kiri; Bornstein, Benjamin; Tang, Nghia; Roden, Joseph

2006-01-01

PixelLearn is an integrated user-interface computer program for classifying pixels in scientific images. Heretofore, training a machine-learning algorithm to classify pixels in images has been tedious and difficult. PixelLearn provides a graphical user interface that makes it faster and more intuitive, leading to more interactive exploration of image data sets. PixelLearn also provides image-enhancement controls to make it easier to see subtle details in images. PixelLearn opens images or sets of images in a variety of common scientific file formats and enables the user to interact with several supervised or unsupervised machine-learning pixel-classifying algorithms while the user continues to browse through the images. The machinelearning algorithms in PixelLearn use advanced clustering and classification methods that enable accuracy much higher than is achievable by most other software previously available for this purpose. PixelLearn is written in portable C++ and runs natively on computers running Linux, Windows, or Mac OS X.

Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

PubMed Central

Tian, Moqian; Grill-Spector, Kalanit

2015-01-01

Recognizing objects is difficult because it requires both linking views of an object that can be different and distinguishing objects with similar appearance. Interestingly, people can learn to recognize objects across views in an unsupervised way, without feedback, just from the natural viewing statistics. However, there is intense debate regarding what information during unsupervised learning is used to link among object views. Specifically, researchers argue whether temporal proximity, motion, or spatiotemporal continuity among object views during unsupervised learning is beneficial. Here, we untangled the role of each of these factors in unsupervised learning of novel three-dimensional (3-D) objects. We found that after unsupervised training with 24 object views spanning a 180° view space, participants showed significant improvement in their ability to recognize 3-D objects across rotation. Surprisingly, there was no advantage to unsupervised learning with spatiotemporal continuity or motion information than training with temporal proximity. However, we discovered that when participants were trained with just a third of the views spanning the same view space, unsupervised learning via spatiotemporal continuity yielded significantly better recognition performance on novel views than learning via temporal proximity. These results suggest that while it is possible to obtain view-invariant recognition just from observing many views of an object presented in temporal proximity, spatiotemporal information enhances performance by producing representations with broader view tuning than learning via temporal association. Our findings have important implications for theories of object recognition and for the development of computational algorithms that learn from examples. PMID:26024454

Overview of NASA's Universe of Learning: An Integrated Astrophysics STEM Learning and Literacy Program

NASA Astrophysics Data System (ADS)

Smith, Denise; Lestition, Kathleen; Squires, Gordon; Biferno, Anya A.; Cominsky, Lynn; Manning, Colleen; NASA's Universe of Learning Team

2018-01-01

NASA's Universe of Learning creates and delivers science-driven, audience-driven resources and experiences designed to engage and immerse learners of all ages and backgrounds in exploring the universe for themselves. The project is the result of a unique partnership between the Space Telescope Science Institute, Caltech/IPAC, Jet Propulsion Laboratory, Smithsonian Astrophysical Observatory, and Sonoma State University, and is one of 27 competitively-selected cooperative agreements within the NASA Science Mission Directorate STEM Activation program. The NASA's Universe of Learning team draws upon cutting-edge science and works closely with Subject Matter Experts (scientists and engineers) from across the NASA Astrophysics Physics of the Cosmos, Cosmic Origins, and Exoplanet Exploration themes. Together we develop and disseminate data tools and participatory experiences, multimedia and immersive experiences, exhibits and community programs, and professional learning experiences that meet the needs of our audiences, with attention to underserved and underrepresented populations. In doing so, scientists and educators from the partner institutions work together as a collaborative, integrated Astrophysics team to support NASA objectives to enable STEM education, increase scientific literacy, advance national education goals, and leverage efforts through partnerships. Robust program evaluation is central to our efforts, and utilizes portfolio analysis, process studies, and studies of reach and impact. This presentation will provide an overview of NASA's Universe of Learning, our direct connection to NASA Astrophysics, and our collaborative work with the NASA Astrophysics science community.

Incremental Support Vector Machine Framework for Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Awad, Mariette; Jiang, Xianhua; Motai, Yuichi

2006-12-01

Motivated by the emerging requirements of surveillance networks, we present in this paper an incremental multiclassification support vector machine (SVM) technique as a new framework for action classification based on real-time multivideo collected by homogeneous sites. The technique is based on an adaptation of least square SVM (LS-SVM) formulation but extends beyond the static image-based learning of current SVM methodologies. In applying the technique, an initial supervised offline learning phase is followed by a visual behavior data acquisition and an online learning phase during which the cluster head performs an ensemble of model aggregations based on the sensor nodes inputs. The cluster head then selectively switches on designated sensor nodes for future incremental learning. Combining sensor data offers an improvement over single camera sensing especially when the latter has an occluded view of the target object. The optimization involved alleviates the burdens of power consumption and communication bandwidth requirements. The resulting misclassification error rate, the iterative error reduction rate of the proposed incremental learning, and the decision fusion technique prove its validity when applied to visual sensor networks. Furthermore, the enabled online learning allows an adaptive domain knowledge insertion and offers the advantage of reducing both the model training time and the information storage requirements of the overall system which makes it even more attractive for distributed sensor networks communication.

"I'm the New Girl": The Meanings Positions Hold for Students

ERIC Educational Resources Information Center

Lassonde, Cynthia A.

2005-01-01

This study offers ways to understand how a fifth-grade student and her teacher co-constructed academic and social positions within classroom writing practices and how these positions constrained and enabled literacy learning. Positioning is viewed as central rather than optional to learning. Classroom writing practices enabled the case-study…

Understanding Knowledge-Sharing Breakdowns: A Meeting of the Quantitative and Qualitative Minds

ERIC Educational Resources Information Center

Soller, Amy

2004-01-01

The rapid advance of distance learning and networking technology has enabled universities and corporations to reach out and educate students across time and space barriers. Although this technology enables structured collaborative learning activities, online groups often do not enjoy the same benefits as face-to-face learners, and their…

Supporting Pre-Service Teachers' Technology-Enabled Learning Design Thinking through Whole of Programme Transformation

ERIC Educational Resources Information Center

Bower, Matt; Highfield, Kate; Furney, Pam; Mowbray, Lee

2013-01-01

This paper explains a development and evaluation project aimed at transforming two pre-service teacher education programmes at Macquarie University to more effectively cultivate students' technology-enabled learning design thinking. The process of transformation was based upon an explicit and sustained focus on developing university academics'…

Assessment of Project-Based Learning in a MECHATRONICS Context

ERIC Educational Resources Information Center

Doppelt, Yaron

2005-01-01

Project-based learning (PBL) that has authenticity in the pupils' world enables the teaching of science and technology to pupils from a variety of backgrounds. PBL has the potential to enable pupils to research, plan, design, and reflect on the creation of technological projects (Doppelt, 2000). Engineering education, which is common in Israel,…

A Service Oriented Architecture to Integrate Mobile Assessment in Learning Management Systems

ERIC Educational Resources Information Center

Riad, A. M.; El-Ghareeb, H. A.

2008-01-01

Mobile Learning (M-Learning) is an approach to E-Learning that utilizes mobile devices. Learning Management System (LMS) should enable M-Learning. Unfortunately, M-Learning is not the same at each educational institution. Assessment is one of the learning activities that can be achieved electronically and via mobile device. Mobile assessment…

Towards a unified theory of neocortex: laminar cortical circuits for vision and cognition.

PubMed

Grossberg, Stephen

2007-01-01

A key goal of computational neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how laminar neocortical circuits give rise to biological intelligence. These circuits embody two new and revolutionary computational paradigms: Complementary Computing and Laminar Computing. Circuit properties include a novel synthesis of feedforward and feedback processing, of digital and analog processing, and of preattentive and attentive processing. This synthesis clarifies the appeal of Bayesian approaches but has a far greater predictive range that naturally extends to self-organizing processes. Examples from vision and cognition are summarized. A LAMINART architecture unifies properties of visual development, learning, perceptual grouping, attention, and 3D vision. A key modeling theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. It is noted how higher-order attentional constraints can influence multiple cortical regions, and how spatial and object attention work together to learn view-invariant object categories. In particular, a form-fitting spatial attentional shroud can allow an emerging view-invariant object category to remain active while multiple view categories are associated with it during sequences of saccadic eye movements. Finally, the chapter summarizes recent work on the LIST PARSE model of cognitive information processing by the laminar circuits of prefrontal cortex. LIST PARSE models the short-term storage of event sequences in working memory, their unitization through learning into sequence, or list, chunks, and their read-out in planned sequential performance that is under volitional control. LIST PARSE provides a laminar embodiment of Item and Order working memories, also called Competitive Queuing models, that have been supported by both psychophysical and neurobiological data. These examples show how variations of a common laminar cortical design can embody properties of visual and cognitive intelligence that seem, at least on the surface, to be mechanistically unrelated.

An evaluation of the role of the clinical education facilitator.

PubMed

McCormack, Brendan; Slater, Paul

2006-02-01

The objective of the study was to identify whether clinical education facilitators made a difference to the learning experiences of nurses in a large teaching hospital. Strategies for enabling continuous professional development are well established in health care organizations as key components of approaches to lifelong learning. The benefits of continuous professional development include the maintenance of high standards of care, the improvement and development of services, ensuring the competency of all nursing staff and guaranteeing the accountability of nurses for their actions. The role of clinical education facilitator is relatively new and little evaluation of this role has been undertaken. This study highlights important issues to be considered in developing a 'learning culture' in a hospital organization, through the adoption of such roles as clinical education facilitators. Whilst the roles have had an important function in the active coordination of learning activities in the hospital, there is little evidence of the role directly impacting on the learning culture of clinical settings. Learning mechanisms have been identified. The results of this evaluation can be subjected to further testing through ongoing evaluation of the outcomes arising from the learning mechanisms in place. Given the emphasis on work-based learning and continuing professional development in health care, then this ongoing evaluation can yield important information about future directions for nurse education. The study highlights the importance of supported learning in the workplace. However, more importantly, it identifies the need for a culture of professional practice to be developed in order to sustain learning in practice. Classroom-based learning alone, cannot create a culture of development in nursing and there is thus a need for models of work-based learning to be integrated into practice environments.

Practice Makes Learning.

ERIC Educational Resources Information Center

Neill, Judy

This paper focuses on how people learn to help educators design curriculum that will enable students to successfully complete a distance learning class. Up-front organization, clear communication about performance expectations, outcome driven assessment, and imaginative learning strategies are critical to successful distance learning.…

Participatory Multimedia Learning: Engaging Learners

ERIC Educational Resources Information Center

Kiili, Kristian

2005-01-01

The purpose of this paper is to present a participatory multimedia learning model for use in designing multimedia learning environments that support an active learning process, creative participation, and learner engagement. Participatory multimedia learning can be defined as learning with systems that enable learners to produce part of the…

The influence of personality on neural mechanisms of observational fear and reward learning

PubMed Central

Hooker, Christine I.; Verosky, Sara C.; Miyakawa, Asako; Knight, Robert T.; D’Esposito, Mark

2012-01-01

Fear and reward learning can occur through direct experience or observation. Both channels can enhance survival or create maladaptive behavior. We used fMRI to isolate neural mechanisms of observational fear and reward learning and investigate whether neural response varied according to individual differences in neuroticism and extraversion. Participants learned object-emotion associations by observing a woman respond with fearful (or neutral) and happy (or neutral) facial expressions to novel objects. The amygdala-hippocampal complex was active when learning the object-fear association, and the hippocampus was active when learning the object-happy association. After learning, objects were presented alone; amygdala activity was greater for the fear (vs. neutral) and happy (vs. neutral) associated object. Importantly, greater amygdala-hippocampal activity during fear (vs. neutral) learning predicted better recognition of learned objects on a subsequent memory test. Furthermore, personality modulated neural mechanisms of learning. Neuroticism positively correlated with neural activity in the amygdala and hippocampus during fear (vs. neutral) learning. Low extraversion/high introversion was related to faster behavioral predictions of the fearful and neutral expressions during fear learning. In addition, low extraversion/high introversion was related to greater amygdala activity during happy (vs. neutral) learning, happy (vs. neutral) object recognition, and faster reaction times for predicting happy and neutral expressions during reward learning. These findings suggest that neuroticism is associated with an increased sensitivity in the neural mechanism for fear learning which leads to enhanced encoding of fear associations, and that low extraversion/high introversion is related to enhanced conditionability for both fear and reward learning. PMID:18573512

View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds.

PubMed

Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio

2009-02-01

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.

Student generated learning objectives: extent of congruence with faculty set objectives and factors influencing their generation.

PubMed

Abdul Ghaffar Al-Shaibani, Tarik A; Sachs-Robertson, Annette; Al Shazali, Hafiz O; Sequeira, Reginald P; Hamdy, Hosam; Al-Roomi, Khaldoon

2003-07-01

A problem-based learning strategy is used for curriculum planning and implementation at the Arabian Gulf University, Bahrain. Problems are constructed in a way that faculty-set objectives are expected to be identified by students during tutorials. Students in small groups, along with a tutor functioning as a facilitator, identify learning issues and define their learning objectives. We compared objectives identified by student groups with faculty-set objectives to determine extent of congruence, and identified factors that influenced students' ability at identifying faculty-set objectives. Male and female students were segregated and randomly grouped. A faculty tutor was allocated for each group. This study was based on 13 problems given to entry-level medical students. Pooled objectives of these problems were classified into four categories: structural, functional, clinical and psychosocial. Univariate analysis of variance was used for comparison, and a p > 0.05 was considered significant. The mean of overall objectives generated by the students was 54.2%, for each problem. Students identified psychosocial learning objectives more readily than structural ones. Female students identified more psychosocial objectives, whereas male students identified more of structural objectives. Tutor characteristics such as medical/non-medical background, and the years of teaching were correlated with categories of learning issues identified. Students identify part of the faculty-set learning objectives during tutorials with a faculty tutor acting as a facilitator. Students' gender influences types of learning issues identified. Content expertise of tutors does not influence identification of learning needs by students.

Automated volumetric lung segmentation of thoracic CT images using fully convolutional neural network

NASA Astrophysics Data System (ADS)

Negahdar, Mohammadreza; Beymer, David; Syeda-Mahmood, Tanveer

2018-02-01

Deep Learning models such as Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in 2D medical image analysis. In clinical practice; however, most analyzed and acquired medical data are formed of 3D volumes. In this paper, we present a fast and efficient 3D lung segmentation method based on V-net: a purely volumetric fully CNN. Our model is trained on chest CT images through volume to volume learning, which palliates overfitting problem on limited number of annotated training data. Adopting a pre-processing step and training an objective function based on Dice coefficient addresses the imbalance between the number of lung voxels against that of background. We have leveraged Vnet model by using batch normalization for training which enables us to use higher learning rate and accelerates the training of the model. To address the inadequacy of training data and obtain better robustness, we augment the data applying random linear and non-linear transformations. Experimental results on two challenging medical image data show that our proposed method achieved competitive result with a much faster speed.

Evaluation of the quality of the teaching-learning process in undergraduate courses in Nursing 1

PubMed Central

González-Chordá, Víctor Manuel; Maciá-Soler, María Loreto

2015-01-01

Abstract Objective: to identify aspects of improvement of the quality of the teaching-learning process through the analysis of tools that evaluated the acquisition of skills by undergraduate students of Nursing. Method: prospective longitudinal study conducted in a population of 60 secondyear Nursing students based on registration data, from which quality indicators that evaluate the acquisition of skills were obtained, with descriptive and inferential analysis. Results: nine items were identified and nine learning activities included in the assessment tools that did not reach the established quality indicators (p<0.05). There are statistically significant differences depending on the hospital and clinical practices unit (p<0.05). Conclusion: the analysis of the evaluation tools used in the article "Nursing Care in Welfare Processes" of the analyzed university undergraduate course enabled the detection of the areas for improvement in the teachinglearning process. The challenge of education in nursing is to reach the best clinical research and educational results, in order to provide improvements to the quality of education and health care. PMID:26444173

Not just another multi-professional course! Part 1. Rationale for a transformative curriculum.

PubMed

Duncan, Madeleine; Alperstein, Melanie; Mayers, Pat; Olckers, Lorna; Gibbs, Trevor

2006-02-01

Undergraduate inter- and multi-professional education has traditionally aimed to develop health professionals who are able to collaborate effectively in comprehensive healthcare delivery. The respective professions learn from and about each other through comparisons of roles, responsibilities, powers, duties and perspectives in order to promote integrated service. Described here is the educational rationale of a multi-professional course with a difference; one that injects value to undergraduate health professional education through the development of critical cross-field knowledge, skills and attitudes that unite rather than differentiate professions. The aim of this course, offered at the Faculty of Health Sciences, University of Cape Town, is to lay an integrated, pan-professional foundation for the advancement of collective commitment to and understanding of national health and social development objectives such as primary health care, human rights and professionalism. Pan-professional refers to curriculum content that is core and of critical relevance to all participating professions. What is learned, how it is learned, how learning is facilitated and how it is applied, has been co-constructed by a multi-professional design team representing a range of health professions (audiology, medicine, occupational therapy, nursing, physiotherapy and speech therapy) and academic disciplines (anthropology, sociology, psychology, history, African studies and social development, information technology and language literacy). Education specialists facilitate the ongoing design process ensuring that the structure and content of the curriculum complies with contemporary adult learning principles and national higher education imperatives. Designing the original curriculum required the deconstruction of intra-professional and disciplinary canons of knowledge and ways of 'doing things' in order to identify and develop shared interpretations of critical epistemology and axiology for health professional practice in the South African context. This enabled the alignment of the learning objectives, at first year level, of all the represented professions. The educational rationale guiding the curriculum design process is discussed in Part 1 of two articles. Part 2 describes the 'nuts and bolts' or practicalities of the curriculum design process.

Dynamic Learning Objects to Teach Java Programming Language

ERIC Educational Resources Information Center

Narasimhamurthy, Uma; Al Shawkani, Khuloud

2010-01-01

This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…

A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs

ERIC Educational Resources Information Center

Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry

2004-01-01

This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

Blended learning for reinforcing dental pharmacology in the clinical years: A qualitative analysis

PubMed Central

Eachempati, Prashanti; Kiran Kumar, K. S.; Sumanth, K. N.

2016-01-01

Objectives: Blended learning has become the method of choice in educational institutions because of its systematic integration of traditional classroom teaching and online components. This study aims to analyze student’s reflection regarding blended learning in dental pharmacology. Subjects and Methods: A cross-sectional study was conducted in Faculty of Dentistry, Melaka-Manipal Medical College among 3rd and 4th year BDS students. A total of 145 dental students, who consented, participate in the study. Students were divided into 14 groups. Nine online sessions followed by nine face-to-face discussions were held. Each session addressed topics related to oral lesions and orofacial pain with pharmacological applications. After each week, students were asked to reflect on blended learning. On completion of 9 weeks, reflections were collected and analyzed. Statistical Analysis: Qualitative analysis was done using thematic analysis model suggested by Braun and Clarke. Results: The four main themes were identified, namely, merits of blended learning, skill in writing prescription for oral diseases, dosages of drugs, and identification of strengths and weakness. In general, the participants had a positive feedback regarding blended learning. Students felt more confident in drug selection and prescription writing. They could recollect the doses better after the online and face-to-face sessions. Most interestingly, the students reflected that they are able to identify their strength and weakness after the blended learning sessions. Conclusions: Blended learning module was successfully implemented for reinforcing dental pharmacology. The results obtained in this study enable us to plan future comparative studies to know the effectiveness of blended learning in dental pharmacology. PMID:28031603

Object Oriented Learning Objects

ERIC Educational Resources Information Center

Morris, Ed

2005-01-01

We apply the object oriented software engineering (OOSE) design methodology for software objects (SOs) to learning objects (LOs). OOSE extends and refines design principles for authoring dynamic reusable LOs. Our learning object class (LOC) is a template from which individualised LOs can be dynamically created for, or by, students. The properties…

Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

ERIC Educational Resources Information Center

Niemann, Katja; Wolpers, Martin

2015-01-01

In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

[Competence Based Catalogue of Learning Objectives for Rehabilitation, Physical Medicine, Naturopathic Treatment - Revised Version - Joint Recommendations of the German Society of Rehabilitation Science and the German Society of Physical Medicine and Rehabilitation].

PubMed

Mau, Wilfried; Liebl, Max Emanuel; Deck, Ruth; Lange, Uwe; Smolenski, Ulrich Christian; Walter, Susanne; Gutenbrunner, Christoph

2017-12-01

Since the first publication of learning objectives for the interdisciplinary subject "Rehabilitation, Physical Medicine, Naturopathic Treatment" in undergraduate medical education in 2004 a revision is reasonable due to heterogenous teaching programmes in the faculties and the introduction of the National Competence Based Catalogue of Learning Objectives in Medicine as well as the "Masterplan Medical Education 2020". Therefore the German Society of Rehabilitation Science and the German Society of Physical Medicine and Rehabilitation started a structured consensus process using the DELPHI-method to reduce the learning objectives and arrange them more clearly. Objectives of particular significance are emphasised. All learning objectives are assigned to the cognitive and methodological level 1 or to the action level 2. The learning objectives refer to the less detailed National Competence Based Catalogue of Learning Objectives in Medicine. The revised learning objectives will contribute to further progress in competence based and more homogenous medical teaching in core objectives of Rehabilitation, Physical Medicine, and Naturopathic Treatment in the faculties. © Georg Thieme Verlag KG Stuttgart · New York.

Group Modeling in Social Learning Environments

ERIC Educational Resources Information Center

Stankov, Slavomir; Glavinic, Vlado; Krpan, Divna

2012-01-01

Students' collaboration while learning could provide better learning environments. Collaboration assumes social interactions which occur in student groups. Social theories emphasize positive influence of such interactions on learning. In order to create an appropriate learning environment that enables social interactions, it is important to…

E-Learning in Malaysia: Moving forward in Open Distance Learning

ERIC Educational Resources Information Center

Abas, Zoraini Wati

2009-01-01

Many higher education institutions have embarked on e-learning as a means to support their learning and teaching activities. In distance learning institutions, e-learning has enabled them to reach out to students dispersed over a wide geographical area, locally and internationally. In some countries, e-learning has also given students the…

Learning in a u-Museum: Developing a Context-Aware Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Chen, Chia-Chen; Huang, Tien-Chi

2012-01-01

Context-awareness techniques can support learners in learning without time or location constraints by using mobile devices and associated learning activities in a real learning environment. Enrichment of context-aware technologies has enabled students to learn in an environment that integrates learning resources from both the real world and the…

Personal Learning Environments: A Solution for Self-Directed Learners

ERIC Educational Resources Information Center

Haworth, Ryan

2016-01-01

In this paper I discuss "personal learning environments" and their diverse benefits, uses, and implications for life-long learning. Personal Learning Environments (PLEs) are Web 2.0 and social media technologies that enable individual learners the ability to manage their own learning. Self-directed learning is explored as a foundation…

Mobile Learning in the Theater Arts Classroom

ERIC Educational Resources Information Center

Li, Zihao

2017-01-01

Mobile learning (m-learning) challenges the traditional definition of teaching and learning. M-learning concept is gaining popularity because it enables learning across multiple contexts and disciplines by using portable mobile devices. In recent years, it has attracted increasing attention at the tertiary level as some institutions adopt Bring…

Learning Environments Designed According to Learning Styles and Its Effects on Mathematics Achievement

ERIC Educational Resources Information Center

Özerem, Aysen; Akkoyunlu, Buket

2015-01-01

Problem Statement: While designing a learning environment it is vital to think about learner characteristics (learning styles, approaches, motivation, interests… etc.) in order to promote effective learning. The learning environment and learning process should be designed not to enable students to learn in the same manner and at the same level,…

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

Yuan, Jiangye

Up-to-date maps of installed solar photovoltaic panels are a critical input for policy and financial assessment of solar distributed generation. However, such maps for large areas are not available. With high coverage and low cost, aerial images enable large-scale mapping, bit it is highly difficult to automatically identify solar panels from images, which are small objects with varying appearances dispersed in complex scenes. We introduce a new approach based on deep convolutional networks, which effectively learns to delineate solar panels in aerial scenes. The approach has successfully mapped solar panels in imagery covering 200 square kilometers in two cities, usingmore » only 12 square kilometers of training data that are manually labeled.« less

Revised Bloom's taxonomy and integral calculus: unpacking the knowledge dimension

NASA Astrophysics Data System (ADS)

Radmehr, Farzad; Drake, Michael

2017-11-01

In this paper, the knowledge dimension for Revised Bloom's taxonomy (RBT) is unpacked for integral calculus. As part of this work, the 11 subtypes of the knowledge dimension are introduced, and through document analysis of chapter 4 of the RBT handbook, these subtypes are defined. Then, by consulting materials frequently used for teaching integral calculus, each subtype is exemplified. The developed dimension may enable or enhance opportunities for dialogue between lecturers, teachers, and researchers about how to develop and align educational objectives, teaching activities, and assessments in integral calculus, or how metacognition and metacognitive knowledge could be used to support teaching and learning.

Extended Relation Metadata for SCORM-Based Learning Content Management Systems

ERIC Educational Resources Information Center

Lu, Eric Jui-Lin; Horng, Gwoboa; Yu, Chia-Ssu; Chou, Ling-Ying

2010-01-01

To increase the interoperability and reusability of learning objects, Advanced Distributed Learning Initiative developed a model called Content Aggregation Model (CAM) to describe learning objects and express relationships between learning objects. However, the suggested relations defined in the CAM can only describe structure-oriented…

Implementing Computer Algebra Enabled Questions for the Assessment and Learning of Mathematics

ERIC Educational Resources Information Center

Sangwin, Christopher J.; Naismith, Laura

2008-01-01

We present principles for the design of an online system to support computer algebra enabled questions for use within the teaching and learning of mathematics in higher education. The introduction of a computer algebra system (CAS) into a computer aided assessment (CAA) system affords sophisticated response processing of student provided answers.…

The Flipped Classroom, Disruptive Pedagogies, Enabling Technologies and Wicked Problems: Responding to "The Bomb in the Basement"

ERIC Educational Resources Information Center

Hutchings, Maggie; Quinney, Anne

2015-01-01

The adoption of enabling technologies by universities provides unprecedented opportunities for flipping the classroom to achieve student-centred learning. While higher education policies focus on placing students at the heart of the education process, the propensity for student identities to shift from partners in learning to consumers of…

Using Learning Analytics to Assess Student Engagement and Academic Outcomes in Open Access Enabling Programmes

ERIC Educational Resources Information Center

Atherton, Mirella; Shah, Mahsood; Vazquez, Jenny; Griffiths, Zoe; Jackson, Brian; Burgess, Catherine

2017-01-01

Curriculum design, teaching methods, assessments and range of academic support need to be inclusive in Open Access Enabling courses. The findings of this study confirm a correlation between student access to online learning materials and a positive impact on grades in science courses. More specifically, students who frequently use the online…

Age-related impairments in active learning and strategic visual exploration.

PubMed

Brandstatt, Kelly L; Voss, Joel L

2014-01-01

Old age could impair memory by disrupting learning strategies used by younger individuals. We tested this possibility by manipulating the ability to use visual-exploration strategies during learning. Subjects controlled visual exploration during active learning, thus permitting the use of strategies, whereas strategies were limited during passive learning via predetermined exploration patterns. Performance on tests of object recognition and object-location recall was matched for younger and older subjects for objects studied passively, when learning strategies were restricted. Active learning improved object recognition similarly for younger and older subjects. However, active learning improved object-location recall for younger subjects, but not older subjects. Exploration patterns were used to identify a learning strategy involving repeat viewing. Older subjects used this strategy less frequently and it provided less memory benefit compared to younger subjects. In previous experiments, we linked hippocampal-prefrontal co-activation to improvements in object-location recall from active learning and to the exploration strategy. Collectively, these findings suggest that age-related memory problems result partly from impaired strategies during learning, potentially due to reduced hippocampal-prefrontal co-engagement.

Perceptual Learning and Attention: Reduction of Object Attention Limitations with Practice

PubMed Central

Dosher, Barbara Anne; Han, Songmei; Lu, Zhong-Lin

2012-01-01

Perceptual learning has widely been claimed to be attention driven; attention assists in choosing the relevant sensory information and attention may be necessary in many cases for learning. In this paper, we focus on the interaction of perceptual learning and attention – that perceptual learning can reduce or eliminate the limitations of attention, or, correspondingly, that perceptual learning depends on the attention condition. Object attention is a robust limit on performance. Two attributes of a single attended object may be reported without loss, while the same two attributes of different objects can exhibit a substantial dual-report deficit due to the sharing of attention between objects. The current experiments document that this fundamental dual-object report deficit can be reduced, or eliminated, through perceptual learning that is partially specific to retinal location. This suggests that alternative routes established by practice may reduce the competition between objects for processing resources. PMID:19796653

Common world model for unmanned systems: Phase 2

NASA Astrophysics Data System (ADS)

Dean, Robert M. S.; Oh, Jean; Vinokurov, Jerry

2014-06-01

The Robotics Collaborative Technology Alliance (RCTA) seeks to provide adaptive robot capabilities which move beyond traditional metric algorithms to include cognitive capabilities. Key to this effort is the Common World Model, which moves beyond the state-of-the-art by representing the world using semantic and symbolic as well as metric information. It joins these layers of information to define objects in the world. These objects may be reasoned upon jointly using traditional geometric, symbolic cognitive algorithms and new computational nodes formed by the combination of these disciplines to address Symbol Grounding and Uncertainty. The Common World Model must understand how these objects relate to each other. It includes the concept of Self-Information about the robot. By encoding current capability, component status, task execution state, and their histories we track information which enables the robot to reason and adapt its performance using Meta-Cognition and Machine Learning principles. The world model also includes models of how entities in the environment behave which enable prediction of future world states. To manage complexity, we have adopted a phased implementation approach. Phase 1, published in these proceedings in 2013 [1], presented the approach for linking metric with symbolic information and interfaces for traditional planners and cognitive reasoning. Here we discuss the design of "Phase 2" of this world model, which extends the Phase 1 design API, data structures, and reviews the use of the Common World Model as part of a semantic navigation use case.

Interactive web-based learning modules prior to general medicine advanced pharmacy practice experiences.

PubMed

Isaacs, Alex N; Walton, Alison M; Nisly, Sarah A

2015-04-25

To implement and evaluate interactive web-based learning modules prior to advanced pharmacy practice experiences (APPEs) on inpatient general medicine. Three clinical web-based learning modules were developed for use prior to APPEs in 4 health care systems. The aim of the interactive modules was to strengthen baseline clinical knowledge before the APPE to enable the application of learned material through the delivery of patient care. For the primary endpoint, postassessment scores increased overall and for each individual module compared to preassessment scores. Postassessment scores were similar among the health care systems. The survey demonstrated positive student perceptions of this learning experience. Prior to inpatient general medicine APPEs, web-based learning enabled the standardization and assessment of baseline student knowledge across 4 health care systems.

Taking Aim at the Cognitive Side of Learning in Sensorimotor Adaptation Tasks.

PubMed

McDougle, Samuel D; Ivry, Richard B; Taylor, Jordan A

2016-07-01

Sensorimotor adaptation tasks have been used to characterize processes responsible for calibrating the mapping between desired outcomes and motor commands. Research has focused on how this form of error-based learning takes place in an implicit and automatic manner. However, recent work has revealed the operation of multiple learning processes, even in this simple form of learning. This review focuses on the contribution of cognitive strategies and heuristics to sensorimotor learning, and how these processes enable humans to rapidly explore and evaluate novel solutions to enable flexible, goal-oriented behavior. This new work points to limitations in current computational models, and how these must be updated to describe the conjoint impact of multiple processes in sensorimotor learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning while Babbling: Prelinguistic Object-Directed Vocalizations Indicate a Readiness to Learn

ERIC Educational Resources Information Center

Goldstein, Michael H.; Schwade, Jennifer; Briesch, Jacquelyn; Syal, Supriya

2010-01-01

Two studies illustrate the functional significance of a new category of prelinguistic vocalizing--object-directed vocalizations (ODVs)--and show that these sounds are connected to learning about words and objects. Experiment 1 tested 12-month-old infants' perceptual learning of objects that elicited ODVs. Fourteen infants' vocalizations were…

Assessment of the core learning objectives curriculum for the urology clerkship.

PubMed

Rapp, David E; Gong, Edward M; Reynolds, W Stuart; Lucioni, Alvaro; Zagaja, Gregory P

2007-11-01

The traditional approach to the surgical clerkship has limitations, including variability of clinical exposure. To optimize student education we developed and introduced the core learning objectives curriculum, which is designed to allow students freedom to direct their learning and focus on core concepts. We performed a prospective, randomized, controlled study to compare the efficacy of core learning objectives vs traditional curricula through objective and subjective measures. Medical students were randomly assigned to the core learning objectives or traditional curricula during the 2-week urology clerkship. Faculty was blinded to student assignment. Upon rotation completion all students were given a 20-question multiple choice examination covering basic urology concepts. In addition, students completed a questionnaire addressing subjective clerkship satisfaction, comprising 15 questions. Between June 2005 and January 2007, 10 core learning objectives students and 10 traditional students completed the urology clerkship. The average +/- SEM multiple choice examination score was 12.1 +/- 0.87 and 9.8 +/- 0.59 for students assigned to the core learning objectives and traditional curricula, respectively (p <0.05). Subjective scores were higher in the core learning objectives cohort, although this result did not attain statistical significance (124.9 +/- 3.72 vs 114.3 +/- 4.96, p = 0.1). Core learning objectives students reported higher satisfaction in all 15 assessed subjective end points. Our experience suggests that the core learning objectives model may be an effective educational tool to help students achieve a broad and directed exposure to the core urological concepts.

Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

PubMed Central

Bowen, Chris; Ye, Gu; Alterovitz, Ron

2015-01-01

In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints. Note to Practitioners Motivated by the desire to enable robots to autonomously operate in cluttered home and workplace environments, this paper presents an approach for intuitively training a robot in a manner that enables it to repeat the task in novel scenarios and in the presence of unforeseen obstacles in the environment. Based on user-provided demonstrations of the task, our method learns features of the task that are consistent across the demonstrations and that we expect should be repeated by the robot when performing the task. We next present an efficient algorithm for planning robot motions to perform the task based on the learned features while avoiding obstacles. We demonstrate the effectiveness of our motion planner for scenarios requiring transferring a powder and pushing a button in environments with obstacles, and we plan to extend our results to more complex tasks in the future. PMID:26279642

The contribution of a MOOC to community discussions around death and dying.

PubMed

Tieman, Jennifer; Miller-Lewis, Lauren; Rawlings, Deb; Parker, Deborah; Sanderson, Christine

2018-02-20

Advances in medicine have helped many to live longer lives and to be able to meet health challenges. However death rates are anticipated to increase given the ageing population and chronic disease progression. Being able to talk about death is seen to be important in normalising death as part of life and supporting preparedness for death. Massive Open Online Courses (MOOCs) provide opportunities for the community to engage in collaborative learning. A 5 week MOOC was developed covering four main topics (language and humour, representations of death, medicalisation of dying, and digital dying) aiming: To enable participants to openly and supportively discuss and learn about issues around living, death and dying, To explore the normally unheard opinions and views of Australians around death and dying, and To determine what effect online learning and discussions offered through the MOOC had on participants' feelings and attitudes towards death and dying. Data was captured on engagement rates in the various MOOC activities. Death Attitudes were measured by five items representing the MOOC's learning objectives and completed at enrolment and conclusion. MOOC Satisfaction was measured with six items at the end of the MOOC. Descriptive statistics were produced for each variable and Chi-Square Tests of Independence assessed the extent of the relationship between categorical variables. Socio-demographic variables were examined as predictors of the outcome variables of MOOC engagement, MOOC satisfaction, and death attitudes. Ethical approval was received from Flinders University Social and Behavioural Research Ethics Committee (Project No. 7247). One thousand one hundred fifty six people enrolled in the Dying2Learn MOOC with 895 participating in some way. Enrolees were primarily female (92.1%). Age ranged from 16 to 84 (mean = 49.5, SD = 12.3). MOOC satisfaction scores were high. Responses to the experience of participating in the MOOC were very positive, with mean scores ranging from 4.3 to 4.6 (aligning with agreement and strong agreement to statements on the value of participating). Death Attitudes were positive at commencement but increased significantly following participation. The Dying2Learn MOOC provided an environment that enabled open and supportive discussion around death and dying and influenced attitudinal change.

Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator

NASA Technical Reports Server (NTRS)

Allen, B. Danette; Cross, Charles D.; Motter, Mark A.; Neilan, James H.; Qualls, Garry D.; Rothhaar, Paul M.; Tran, Loc; Trujillo, Anna C.; Crisp, Vicki K.

2015-01-01

NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.

Pre-service Elementary School Teachers' Ability to Account for the Operation of Simple Physical Systems Using the Energy Conservation Law

NASA Astrophysics Data System (ADS)

Papadouris, Nicos; Hadjigeorgiou, Angela; Constantinou, Constantinos P.

2014-12-01

Energy is recognized as a core idea in science and, hence, a significant learning objective of science education. The effective promotion of this learning objective posits that teachers themselves possess sound conceptual understanding. This is needed for enabling them to organize effective learning environments for their students. In this study, we report on the results of an empirical investigation of teachers' understanding of energy. In particular, the focus is placed on pre-service teachers' ability to employ energy as a framework for analyzing the operation of physical systems. We have collected data from 198 pre-service teachers through three open-ended tasks that involved the application of the energy conservation principle to simple physical systems. The results corroborate the claim made in the literature that teachers typically do not possess functional, coherent understanding of this principle. Most importantly, the data serve to identify and document specific difficulties that hamper attempts to use energy for the analysis of the operation of physical systems. The difficulties we were able to document lend support to the idea that it is important to introduce the idea of energy degradation alongside the conservation of energy principle. The findings of this study have implications for the design of preparation programs for teachers, about energy. The findings also provide insights into the limitations of conventional teaching of energy, to which the participants had been exposed as students, in fostering coherent understanding of energy conservation.

A Data Mining Approach to Improve Re-Accessibility and Delivery of Learning Knowledge Objects

ERIC Educational Resources Information Center

Sabitha, Sai; Mehrotra, Deepti; Bansal, Abhay

2014-01-01

Today Learning Management Systems (LMS) have become an integral part of learning mechanism of both learning institutes and industry. A Learning Object (LO) can be one of the atomic components of LMS. A large amount of research is conducted into identifying benchmarks for creating Learning Objects. Some of the major concerns associated with LO are…

Collaborative Clustering for Sensor Networks

NASA Technical Reports Server (NTRS)

Wagstaff. Loro :/; Green Jillian; Lane, Terran

2011-01-01

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

WE-DE-207A-02: Advances in Cone Beam CT Anatomical and Functional Imaging in Angio-Suite to Enable One-Stop-Shop Stroke Imaging Workflow

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

Chen, G.

1. Parallels in the evolution of x-ray angiographic systems and devices used for minimally invasive endovascular therapy Charles Strother - DSA, invented by Dr. Charles Mistretta at UW-Madison, was the technology which enabled the development of minimally invasive endovascular procedures. As DSA became widely available and the potential benefits for accessing the cerebral vasculature from an endovascular approach began to be apparent, industry began efforts to develop tools for use in these procedures. Along with development of catheters, embolic materials, pushable coils and the GDC coils there was simultaneous development and improvement of 2D DSA image quality and the introductionmore » of 3D DSA. Together, these advances resulted in an enormous expansion in the scope and numbers of minimally invasive endovascular procedures. The introduction of flat detectors for c-arm angiographic systems in 2002 provided the possibility of the angiographic suite becoming not just a location for vascular imaging where physiological assessments might also be performed. Over the last decade algorithmic and hardware advances have been sufficient to now realize this potential in clinical practice. The selection of patients for endovascular treatments is enhanced by this dual capability. Along with these advances has been a steady reduction in the radiation exposure required so that today, vascular and soft tissue images may be obtained with equal or in many cases less radiation exposure than is the case for comparable images obtained with multi-detector CT. Learning Objectives: To understand the full capabilities of today’s angiographic suite To understand how c-arm cone beam CT soft tissue imaging can be used for assessments of devices, blood flow and perfusion. Advances in real-time x-ray neuro-endovascular image guidance Stephen Rudin - Reacting to the demands on real-time image guidance for ever finer neurovascular interventions, great improvements in imaging chains are being pursued. For the highest spatial and temporal resolution, x-ray guidance with fluoroscopy and angiography although dominant are still being vastly improved. New detectors such as the Micro-Angiographic Fluoroscope (MAF) and x-ray source designs that enable higher outputs while maintaining small focal spots will be highlighted along with new methods for minimizing the radiation dose to patients. Additionally, new platforms for training and device testing that include patient-specific 3D printed vascular phantoms and new metrics such as generalized relative object detectability for objectively inter-comparing systems will be discussed. This will improve the opportunity for better evaluation of these technological advances which should contribute to the safety and efficacy of image guided minimally invasive neuro-endovascular procedures. Learning Objectives: To understand the operation of new x-ray imaging chain components such as detectors and sources To be informed about the latest testing methods, with 3D printed vascular phantoms, and new evaluation metrics for advanced imaging in x-ray image guided neurovascular interventions Advances in cone beam CT anatomical and functional imaging in angio-suite to enable one-stop-shop stroke imaging workflow Guang-Hong Chen - The introduction of flat-panel detector based cone-beam CT in clinical angiographic imaging systems enabled treating physicians to obtain three-dimensional anatomic roadmaps for bony structure, soft brain tissue, and vasculatures for treatment planning and efficacy checking after the procedures. However, much improvement is needed to reduce image artifacts, reduce radiation dose, and add potential functional imaging capability to provide four-dimensional dynamic information of vasculature and brain perfusion. In this presentation, some of the new techniques developed to address radiation dose issues, image artifact reduction and brain perfusion using C-arm cone-beam CT imaging system will be introduced for the audience. Learning Objectives: To understand the clinical need of one-stop-shop stroke imaging workflow To understand to technical challenges in cone beam CT perfusion To understand the potential technical solutions to enable one-stop-shop imaging workflow Recent advances in devices used in neuro--interventions Mattew Gounis - Over the past two decades, there has been explosive development of medical devices that have revolutionized the endovascular treatment of cerebrovascular diseases. There is now Level 1, Class A evidence that intra-arterial, mechanical thrombectomy in acute ischemic stroke is superior to medical management; and similarly that minimally invasive, endovascular repair of ruptured brain aneurysms is superior to surgical treatment. Stent-retrievers are now standard of care for emergent large vessel occlusions causing a stroke, with a number of patients need to treat for good clinical outcomes as low as 4. Recent technologies such as flow diverters and disrupters, intracranial self-expanding stents, flexible large bore catheters that can reach vessels beyond the circle of Willis, stent-retrievers, and super-compliant balloons are the result of successful miniaturization of design features and novel manufacturing technologies capable of building these devices. This is a rapidly evolving field, and the device technology enabling such advancements will be reviewed. Importantly, image-guidance technology has not kept pace in neurointervention and the ability to adequately characterize these devices in vivo remains a significant opportunity. Learning Objectives: A survey of devices used in neurointerventions, their materials and essential design characteristics Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; G. Chen, Funding received from NIH; funding received from DOD; funding received from GE Healthcare; funding received from Siemens AX.; M. Gounis, consultant for Codman Neurovascular and Stryker Neurovascular; Holds stock in InNeuroCo Inc, research grants: NIH, Medtronic Neurovascular, Microvention/Terumo, Cerevasc LLC, Gentuity, Codman Neurovascular, Philips Healthcare, Stryker Neurovascular, Tay Sachs Foundation, and InNeuroCo Inc.; S. Rudin, Supported in part by NIH Grant R01EB002873 and the Toshiba Medical System Corp.« less

Learned Non-Rigid Object Motion is a View-Invariant Cue to Recognizing Novel Objects

PubMed Central

Chuang, Lewis L.; Vuong, Quoc C.; Bülthoff, Heinrich H.

2012-01-01

There is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested the recognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel viewpoints. Recognition performance was affected by viewpoint changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all viewpoint changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint. PMID:22661939

Reimagining Human Research Protections for 21st Century Science

PubMed Central

Bietz, Matthew; Bae, Deborah; Bigby, Barbara; Devereaux, Mary; Fowler, James; Waldo, Ann; Weibel, Nadir; Patrick, Kevin; Klemmer, Scott; Melichar, Lori

2016-01-01

Background Evolving research practices and new forms of research enabled by technological advances require a redesigned research oversight system that respects and protects human research participants. Objective Our objective was to generate creative ideas for redesigning our current human research oversight system. Methods A total of 11 researchers and institutional review board (IRB) professionals participated in a January 2015 design thinking workshop to develop ideas for redesigning the IRB system. Results Ideas in 5 major domains were generated. The areas of focus were (1) improving the consent form and process, (2) empowering researchers to protect their participants, (3) creating a system to learn from mistakes, (4) improving IRB efficiency, and (5) facilitating review of research that leverages technological advances. Conclusions We describe the impetus for and results of a design thinking workshop to reimagine a human research protections system that is responsive to 21st century science. PMID:28007687

Diamond Eye: a distributed architecture for image data mining

NASA Astrophysics Data System (ADS)

Burl, Michael C.; Fowlkes, Charless; Roden, Joe; Stechert, Andre; Mukhtar, Saleem

1999-02-01

Diamond Eye is a distributed software architecture, which enables users (scientists) to analyze large image collections by interacting with one or more custom data mining servers via a Java applet interface. Each server is coupled with an object-oriented database and a computational engine, such as a network of high-performance workstations. The database provides persistent storage and supports querying of the 'mined' information. The computational engine provides parallel execution of expensive image processing, object recognition, and query-by-content operations. Key benefits of the Diamond Eye architecture are: (1) the design promotes trial evaluation of advanced data mining and machine learning techniques by potential new users (all that is required is to point a web browser to the appropriate URL), (2) software infrastructure that is common across a range of science mining applications is factored out and reused, and (3) the system facilitates closer collaborations between algorithm developers and domain experts.

Efficient Exact Inference With Loss Augmented Objective in Structured Learning.

PubMed

Bauer, Alexander; Nakajima, Shinichi; Muller, Klaus-Robert

2016-08-19

Structural support vector machine (SVM) is an elegant approach for building complex and accurate models with structured outputs. However, its applicability relies on the availability of efficient inference algorithms--the state-of-the-art training algorithms repeatedly perform inference to compute a subgradient or to find the most violating configuration. In this paper, we propose an exact inference algorithm for maximizing nondecomposable objectives due to special type of a high-order potential having a decomposable internal structure. As an important application, our method covers the loss augmented inference, which enables the slack and margin scaling formulations of structural SVM with a variety of dissimilarity measures, e.g., Hamming loss, precision and recall, Fβ-loss, intersection over union, and many other functions that can be efficiently computed from the contingency table. We demonstrate the advantages of our approach in natural language parsing and sequence segmentation applications.

Changes to Students' Learning Processes Following Instruction on the Topic

ERIC Educational Resources Information Center

Clump, Michael A.

2005-01-01

Previous research indicates that students' learning styles, as assessed by the Inventory of Learning Processes (ILP; Schmeck, Ribich, & Ramanaiah, 1977), change during college. Additionally, prior research indicates that teaching students about their learning styles enables them to change those learning styles. The current study investigated…

Behavioral methods for the study of the Ras-ERK pathway in memory formation and consolidation: passive avoidance and novel object recognition tests.

PubMed

d'Isa, Raffaele; Brambilla, Riccardo; Fasano, Stefania

2014-01-01

Memory is a high-level brain function that enables organisms to adapt their behavioral responses to the environment, hence increasing their probability of survival. The Ras-ERK pathway is a key molecular intracellular signalling cascade for memory consolidation. In this chapter we will describe two main one-trial behavioral tests commonly used in the field of memory research in order to assess the role of Ras-ERK signalling in long-term memory: passive avoidance and object recognition. Passive avoidance (PA) is a fear-motivated instrumental learning task, designed by Jarvik and Essman in 1960, in which animals learn to refrain from emitting a behavioral response that has previously been associated with a punishment. We will describe here the detailed protocol and show some examples of how PA can reveal impairments or enhancements in memory consolidation following loss or gain of function genetic manipulations of the Ras-ERK pathway. The phenotypes of global mutants as Ras-GRF1 KO, GENA53, and ERK1 KO mice, as well as of conditional region-specific mutants (striatal K-CREB mice), will be illustrated as examples. Novel object recognition (NOR), developed by Ennaceur and Delacour in 1988, is instead a more recent and highly ecological test, which relies on the natural tendency of rodents to spontaneously approach and explore novel objects, representing hence a useful non-stressful tool for the study of memory in animals without the employment of punishments or starvation/water restriction regimens. Careful indications will be given on how to select the positions for the novel object, in order to counterbalance for individual side preferences among mice during the training. Finally, the methods for calculating two learning indexes will be described. In addition to the classical discrimination index (DI) that measures the ability of an animal to discriminate between two different objects which are presented at the same time, we will describe the formula of a new index that we present here for the first time, the recognition index (RI), which quantifies the ability of an animal to recognize a same object at different time points and that, by taking into account the basal individual preferences displayed during the training, can give a more accurate measure of an animal's actual recognition memory.

Hippocampus-dependent place learning enables spatial flexibility in C57BL6/N mice

PubMed Central

Kleinknecht, Karl R.; Bedenk, Benedikt T.; Kaltwasser, Sebastian F.; Grünecker, Barbara; Yen, Yi-Chun; Czisch, Michael; Wotjak, Carsten T.

2012-01-01

Spatial navigation is a fundamental capability necessary in everyday life to locate food, social partners, and shelter. It results from two very different strategies: (1) place learning which enables for flexible way finding and (2) response learning that leads to a more rigid “route following.” Despite the importance of knockout techniques that are only available in mice, little is known about mice' flexibility in spatial navigation tasks. Here we demonstrate for C57BL6/N mice in a water-cross maze (WCM) that only place learning enables spatial flexibility and relearning of a platform position, whereas response learning does not. This capability depends on an intact hippocampal formation, since hippocampus lesions by ibotenic acid (IA) disrupted relearning. In vivo manganese-enhanced magnetic resonance imaging revealed a volume loss of ≥60% of the hippocampus as a critical threshold for relearning impairments. In particular the changes in the left ventral hippocampus were indicative of relearning deficits. In summary, our findings establish the importance of hippocampus-dependent place learning for spatial flexibility and provide a first systematic analysis on spatial flexibility in mice. PMID:23293591

Teacher Trainees as Learning Object Designers: Problems and Issues in Learning Object Development Process

ERIC Educational Resources Information Center

Guler, Cetin; Altun, Arif

2010-01-01

Learning objects (LOs) can be defined as resources that are reusable, digital with the aim of fulfilling learning objectives (or expectations). Educators, both at the individual and institutional levels, are cautioned about the fact that LOs are to be processed through a proper development process. Who should be involved in the LO development…

Patterns of Learning Object Reuse in the Connexions Repository

ERIC Educational Resources Information Center

Duncan, S. M.

2009-01-01

Since the term "learning object" was first published, there has been either an explicit or implicit expectation of reuse. There has also been a lot of speculation about why learning objects are, or are not, reused. This study quantitatively examined the actual amount and type of learning object use, to include reuse, modification, and translation,…

Using Instructional Pervasive Game for School Children's Cultural Learning

ERIC Educational Resources Information Center

Chen, Cheng-Ping; Shih, Ju-Ling; Ma, Yi-Chun

2014-01-01

In the past ten years, mobile learning (m-learning) has created a new learning environment that enables learners, through active learning aids. Instructional pervasive gaming (IPG) seems to be an innovative way introduced to enhance m-learning. This study employed a theoretical IPG model to construct a cultural-based pervasive game. Individual and…

Using Wikis as a Support and Assessment Tool in Collaborative Digital Game-Based Learning Environments

ERIC Educational Resources Information Center

Samur, Yavuz

2011-01-01

In computer-supported collaborative learning (CSCL) environments, there are many researches done on collaborative learning activities; however, in game-based learning environments, more research and literature on collaborative learning activities are required. Actually, both game-based learning environments and wikis enable us to use new chances…

Applying Learning Analytics for the Early Prediction of Students' Academic Performance in Blended Learning

ERIC Educational Resources Information Center

Lu, Owen H. T.; Huang, Anna Y. Q.; Huang, Jeff C. H.; Lin, Albert J. Q.; Ogata, Hiroaki; Yang, Stephen J. H.

2018-01-01

Blended learning combines online digital resources with traditional classroom activities and enables students to attain higher learning performance through well-defined interactive strategies involving online and traditional learning activities. Learning analytics is a conceptual framework and is a part of our Precision education used to analyze…

Writing objectives and evaluating learning in the affective domain.

PubMed

Maier-Lorentz, M M

1999-01-01

Staff educators recognize the importance of affective competency for effective nursing practice. Inservice programs must include affective learning with objectives stated in measurable terms. Staff educators often express frustration in developing affective objectives and evaluating the learning outcome because attitudes and feelings are usually inferred from observations. This article presents affective learning objectives for a gerontological nursing inservice program and a rating scale that measures attitudes to evaluate the learning outcome.

Learning to learn causal models.

PubMed

Kemp, Charles; Goodman, Noah D; Tenenbaum, Joshua B

2010-09-01

Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. Copyright © 2010 Cognitive Science Society, Inc.

Remembering Math: The Design of Digital Learning Objects to Spark Professional Learning

ERIC Educational Resources Information Center

Halverson, Richard; Wolfenstein, Moses; Williams, Caroline C.; Rockman, Charles

2009-01-01

This article describes how the design of digital learning objects can spark professional learning. The challenge was to build learning objects that would help experienced special education teachers, who had been teaching in math classes, to demonstrate their proficiency in middle and secondary school mathematics on the PRAXIS examination. While…

Collaborative Production of Learning Objects on French Literary Works Using the LOC Software

ERIC Educational Resources Information Center

Penman, Christine

2015-01-01

This case study situates the collaborative design of learning objects (interactive online learning material) using the LOC (Learning Object Creator) software in the context of language activities external to the core learning activities of language students at a UK university. It describes the creative and pedagogical processes leading to the…

Learning Objects and Virtual Learning Environments Technical Evaluation Criteria

ERIC Educational Resources Information Center

Kurilovas, Eugenijus; Dagiene, Valentina

2009-01-01

The main scientific problems investigated in this article deal with technical evaluation of quality attributes of the main components of e-Learning systems (referred here as DLEs--Digital Libraries of Educational Resources and Services), i.e., Learning Objects (LOs) and Virtual Learning Environments (VLEs). The main research object of the work is…

A Case Study: Developing Learning Objects with an Explicit Learning Design

ERIC Educational Resources Information Center

Watson, Julie

2010-01-01

In learning object design an emphasis on visual attractiveness and high technological impact has seemed to persist while content frequently reflects a lack of clear pedagogical basis for the application of learning objects for online learning. Most apparent is the absence of supportive scaffolding for the student user; interactivity built on an…

Learning anatomy via mobile augmented reality: Effects on achievement and cognitive load.

PubMed

Küçük, Sevda; Kapakin, Samet; Göktaş, Yüksel

2016-10-01

Augmented reality (AR), a new generation of technology, has attracted the attention of educators in recent years. In this study, a MagicBook was developed for a neuroanatomy topic by using mobile augmented reality (mAR) technology. This technology integrates virtual learning objects into the real world and allow users to interact with the environment using mobile devices. The purpose of this study was to determine the effects of learning anatomy via mAR on medical students' academic achievement and cognitive load. The mixed method was applied in the study. The random sample consisted of 70 second-year undergraduate medical students: 34 in an experimental group and 36 in a control group. Academic achievement test and cognitive load scale were used as data collection tool. A one-way MANOVA test was used for analysis. The experimental group, which used mAR applications, reported higher achievement and lower cognitive load. The use of mAR applications in anatomy education contributed to the formation of an effective and productive learning environment. Student cognitive load decreased as abstract information became concrete in printed books via multimedia materials in mAR applications. Additionally, students were able to access the materials in the MagicBook anytime and anywhere they wanted. The mobile learning approach helped students learn better by exerting less cognitive effort. Moreover, the sensory experience and real time interaction with environment may provide learning satisfaction and enable students to structure their knowledge to complete the learning tasks. Anat Sci Educ 9: 411-421. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

Creative Writing and Promoting Understanding in Science: Alternative Ways to Interest Students in Writing about Science

ERIC Educational Resources Information Center

Akcay, Hakan; Hand, Brian; Norton-Meier, Lori

2010-01-01

Science writing opportunities are used as a resource to enable students to understand science concepts. This study represents three different writing-to-learn tasks that enable students to learn science and to demonstrate their developing understanding about the human body system. The teacher and students engaged in a variety of science enquiries…

Implementation of formal learning objectives during a physical medicine and rehabilitation sports medicine rotation.

PubMed

Smith, Jay; Laskowski, Edward R; Newcomer-Aney, Karen L; Thompson, Jeffrey M; Schaefer, Michael P; Morfe, Erasmus G

2005-04-01

To develop and implement formal learning objectives during a physical medicine and rehabilitation sports medicine rotation and characterize resident experiences with the objectives over a 16-mo period. Prospective, including learning objective development, implementation, and postrotation survey. A total of 69 learning objectives were developed by physical medicine and rehabilitation staff physician consensus, including 39 core objectives. Eighteen residents completed 4-wk sports medicine rotations from January 2003 through April 2004. Residents completed an average of 31 total objectives (45%; range, 3-52), of which 24 (62%; range, 3-35) were core. Residents completed the highest percentage of knee (60%), shoulder (57%), and ankle-foot (57%) objectives and reported that objectives related to these areas were most effective to facilitate learning. In general, residents reported that objective content was good and that the objectives delineated important concepts to learn during the rotation. Seventeen of 18 residents indicated that the objectives should be permanently implemented into the sports rotation and that similar objectives should be developed for other rotations. Based on our experience and the recommendations of residents, the average resident should be able to complete approximately 30 objectives during a typical 4-wk rotation. Successful implementation of specific, consensus-derived learning objectives is possible within the context of a busy clinical practice. Our initial physician staff and resident experience with the objectives suggests that this model may be useful as a supplementary educational tool in physical medicine and rehabilitation residency programs.

Health-Enabling and Ambient Assistive Technologies: Past, Present, Future

PubMed Central

2016-01-01

Summary Background During the last decades, health-enabling and ambient assistive technologies became of considerable relevance for new informatics-based forms of diagnosis, prevention, and therapy. Objectives To describe the state of the art of health-enabling and ambient assistive technologies in 1992 and today, and its evolution over the last 25 years as well as to project where the field is expected to be in the next 25 years. In the context of this review, we define health-enabling and ambient assistive technologies as ambiently used sensor-based information and communication technologies, aiming at contributing to a person’s health and health care as well as to her or his quality of life. Methods Systematic review of all original articles with research focus in all volumes of the IMIA Yearbook of Medical Informatics. Surveying authors independently on key projects and visions as well as on their lessons learned in the context of health-enabling and ambient assistive technologies and summarizing their answers. Surveying authors independently on their expectations for the future and summarizing their answers. Results IMIA Yearbook papers containing statements on health-enabling and ambient assistive technologies appear first in 2002. These papers form a minor part of published research articles in medical informatics. However, during recent years the number of articles published has increased significantly. Key projects were identified. There was a clear progress on the use of technologies. However proof of diagnostic relevance and therapeutic efficacy remains still limited. Reforming health care processes and focussing more on patient needs are required. Conclusions Health-enabling and ambient assistive technologies remain an important field for future health care and for interdisciplinary research. More and more publications assume that a person‘s home and their interaction therein, are becoming important components in health care provision, assessment, and management. PMID:27362588

General practitioners learning qualitative research: A case study of postgraduate education.

PubMed

Hepworth, Julie; Kay, Margaret

2015-10-01

Qualitative research is increasingly being recognised as a vital aspect of primary healthcare research. Teaching and learning how to conduct qualitative research is especially important for general practitioners and other clinicians in the professional educational setting. This article examines a case study of postgraduate professional education in qualitative research for clinicians, for the purpose of enabling a robust discussion around teaching and learning in medicine and the health sciences. A series of three workshops was delivered for primary healthcare academics. The workshops were evaluated using a quantitative survey and qualitative free-text responses to enable descriptive analyses. Participants found qualitative philosophy and theory the most difficult areas to engage with, and learning qualitative coding and analysis was considered the easiest to learn. Key elements for successful teaching were identified, including the use of adult learning principles, the value of an experienced facilitator and an awareness of the impact of clinical subcultures on learning.

Evidence-based decision-making as a practice-based learning skill: a pilot study.

PubMed

Falzer, Paul R; Garman, D Melissa

2012-03-01

As physicians are being trained to adapt their practices to the needs and experience of patients, initiatives to standardize care have been gaining momentum. The resulting conflict can be addressed through a practice-based learning and improvement (PBL) program that develops competency in using treatment guidelines as decision aids and incorporating patient-specific information into treatment recommendations. This article describes and tests a program that is consistent with the ACGME's multilevel competency-based approach, targets students at four levels of training, and features progressive learning objectives and assessments. The program was pilot-tested with 22 paid volunteer psychiatric residents and fellows. They were introduced to a schizophrenia treatment guideline and reviewed six case vignettes of varying complexity. PBL assessments were based on how treatment recommendations were influenced by clinical and patient-specific factors. The task permitted separate assessments of learning objectives all four training levels. Among the key findings at each level, most participants found the treatment guideline helpful in making treatment decisions. Recommendations were influenced by guideline-based assessment criteria and other clinical features. They were also influenced by patients' perceptions of their illness, patient-based progress assessments, and complications such as stressors and coping patterns. Recommendations were strongly influenced by incongruence between clinical facts and patient experience. Practical understanding of how patient experience joins with clinical knowledge can enhance the use of treatment guidelines as decision tools and enable clinicians to appreciate more fully how and why patients' perceptions of their illness should influence treatment recommendations. This PBL program can assist training facilities in preparing students to cope with contradictory demands to both standardize and adapt their practice. The program can be modified to accommodate various disorders and a range of clinical factors and patient-specific complications.

Towards Web 3.0: taxonomies and ontologies for medical education -- a systematic review.

PubMed

Blaum, Wolf E; Jarczweski, Anne; Balzer, Felix; Stötzner, Philip; Ahlers, Olaf

2013-01-01

Both for curricular development and mapping, as well as for orientation within the mounting supply of learning resources in medical education, the Semantic Web ("Web 3.0") poses a low-threshold, effective tool that enables identification of content related items across system boundaries. Replacement of the currently required manual with an automatically generated link, which is based on content and semantics, requires the use of a suitably structured vocabulary for a machine-readable description of object content. Aim of this study is to compile the existing taxonomies and ontologies used for the annotation of medical content and learning resources, to compare those using selected criteria, and to verify their suitability in the context described above. Based on a systematic literature search, existing taxonomies and ontologies for the description of medical learning resources were identified. Through web searches and/or direct contact with the respective editors, each of the structured vocabularies thus identified were examined in regards to topic, structure, language, scope, maintenance, and technology of the taxonomy/ontology. In addition, suitability for use in the Semantic Web was verified. Among 20 identified publications, 14 structured vocabularies were identified, which differed rather strongly in regards to language, scope, currency, and maintenance. None of the identified vocabularies fulfilled the necessary criteria for content description of medical curricula and learning resources in the German-speaking world. While moving towards Web 3.0, a significant problem lies in the selection and use of an appropriate German vocabulary for the machine-readable description of object content. Possible solutions include development, translation and/or combination of existing vocabularies, possibly including partial translations of English vocabularies.

Social E-Learning in Topolor: A Case Study

ERIC Educational Resources Information Center

Shi, Lei; Al Qudah, Dana; Cristea, Alexandra I.

2013-01-01

Social e-learning is a process through which learners achieve their learning goals via social interactions with each other by sharing knowledge, skills, abilities and educational materials. Adaptive e-learning enables adaptation and personalization of the learning process, based on learner needs, knowledge, preferences and other characteristics.…

Exploring Mobile Learning in the Third Space

ERIC Educational Resources Information Center

Schuck, Sandy; Kearney, Matthew; Burden, Kevin

2017-01-01

Mobile learning is enabling educators and students to learn in ways not previously possible. The ways that portable, multi-functional mobile devices can untether the learner from formal institutional learning give scope for learning to be conceptualised in an expanded variety of places, times and ways. In this conceptual article the authors…

Cultural Narratives: Developing a Three-Dimensional Learning Community through Braided Understanding

ERIC Educational Resources Information Center

Heck, Marsha L.

2004-01-01

Paula Underwood's "Learning Stories" braid together body, mind, and spirit to enable understanding that does not easily unravel. They tell of relationships among individual and community learning that parallel other ancient and contemporary ideas about learning in caring communities. Underwood's tradition considers learning sacred; everyone's…

Learning during Tourism: The Experience of Learning from the Tourist's Perspective

ERIC Educational Resources Information Center

Van Winkle, Christine M.; Lagay, Katya

2012-01-01

The purpose of the research described in the paper was to explore the learning experience that occurs during leisure tourism from the tourist's perspective. Learning throughout the lifespan occurs in diverse contexts and travel presents a unique learning environment enabling both unplanned and planned opportunities. The Husserlian phenomenology…

Practical Applications and Experiences in K-20 Blended Learning Environments

ERIC Educational Resources Information Center

Kyei-Blankson, Lydia, Ed.; Ntuli, Esther, Ed.

2014-01-01

Learning environments continue to change considerably and is no longer confined to the face-to-face classroom setting. As learning options have evolved, educators must adopt a variety of pedagogical strategies and innovative technologies to enable learning. "Practical Applications and Experiences in K-20 Blended Learning Environments"…

An Investigation into Digital Media: Characteristics of Learning Objects Which K-12 Teachers Determine Meet Their Instructional Needs

ERIC Educational Resources Information Center

Guthrie, Patricia Ann

2010-01-01

In recent years, learning objects have emerged as an instructional tool for teachers. Digital libraries and collections provide teachers with free or fee-base access to a variety of learning objects from photos and famous speeches to Flash animations and interactive Java Applets. Learning objects offer opportunities for students to interact with…

Inquiry-Based Learning Using Everyday Objects: Hands-On Instructional Strategies That Promote Active Learning in Grades 3-8.

ERIC Educational Resources Information Center

Alvarado, Amy Edmonds; Herr, Patricia R.

This book explores the concept of using everyday objects as a process initiated both by students and teachers, encouraging growth in student observation, inquisitiveness, and reflection in learning. After "Introduction: Welcome to Inquiry-Based Learning using Everyday Objects (Object-Based Inquiry), there are nine chapters in two parts. Part 1,…

Application of machine learning methods in bioinformatics

NASA Astrophysics Data System (ADS)

Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

2018-05-01

Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

PubMed Central

Jones, Michael N.

2017-01-01

A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity. PMID:29059185

Competition between multiple words for a referent in cross-situational word learning

PubMed Central

Benitez, Viridiana L.; Yurovsky, Daniel; Smith, Linda B.

2016-01-01

Three experiments investigated competition between word-object pairings in a cross-situational word-learning paradigm. Adults were presented with One-Word pairings, where a single word labeled a single object, and Two-Word pairings, where two words labeled a single object. In addition to measuring learning of these two pairing types, we measured competition between words that refer to the same object. When the word-object co-occurrences were presented intermixed in training (Experiment 1), we found evidence for direct competition between words that label the same referent. Separating the two words for an object in time eliminated any evidence for this competition (Experiment 2). Experiment 3 demonstrated that adding a linguistic cue to the second label for a referent led to different competition effects between adults who self-reported different language learning histories, suggesting both distinctiveness and language learning history affect competition. Finally, in all experiments, competition effects were unrelated to participants’ explicit judgments of learning, suggesting that competition reflects the operating characteristics of implicit learning processes. Together, these results demonstrate that the role of competition between overlapping associations in statistical word-referent learning depends on time, the distinctiveness of word-object pairings, and language learning history. PMID:27087742

The Analysis of the Relationship between Primary Learning Styles and Learning Objects in an Online Environment

ERIC Educational Resources Information Center

Özdemir, Muzaffer

2016-01-01

This study investigates the relationships between the primary learning styles of students and different learning objects presented simultaneously in an online learning environment in the context of the usage levels of these objects. A total of 103 sophomores from a Turkish State University participated in the study. Felder-Solomon Index of…

Building Interoperable Learning Objects Using Reduced Learning Object Metadata

ERIC Educational Resources Information Center

Saleh, Mostafa S.

2005-01-01

The new e-learning generation depends on Semantic Web technology to produce learning objects. As the production of these components is very costly, they should be produced and registered once, and reused and adapted in the same context or in other contexts as often as possible. To produce those components, developers should use learning standards…

Applied Welding Technology Curriculum Guide.

ERIC Educational Resources Information Center

Idaho State Dept. of Education, Boise. Div. of Vocational Education.

This Idaho state curriculum guide provides lists of tasks, performance objectives, and enabling objectives for instruction in welding. Following an introduction and a list of tasks, the bulk of the document consists of 10 modules, each of which is a list of tasks and the performance objectives and enabling objectives that pertain to each task. The…

Developing Recreation Skills in Persons with Learning Disabilities.

ERIC Educational Resources Information Center

Peniston, Lorraine C.

This book provides specific suggestions for ways to make accommodations and modify leisure activities to enable and encourage the participation of individuals with learning disabilities. The following chapters include: (1) "An Introduction"; (2) "Learning Disabilities," which describes types of learning disabilities, guidelines…

Protocol for Short- and Longer-term Spatial Learning and Memory in Mice

PubMed Central

Willis, Emily F.; Bartlett, Perry F.; Vukovic, Jana

2017-01-01

Studies on the role of the hippocampus in higher cognitive functions such as spatial learning and memory in rodents are reliant upon robust and objective behavioral tests. This protocol describes one such test—the active place avoidance (APA) task. This behavioral task involves the mouse continuously integrating visual cues to orientate itself within a rotating arena in order to actively avoid a shock zone, the location of which remains constant relative to the room. This protocol details the step-by-step procedures for a novel paradigm of the hippocampal-dependent APA task, measuring acquisition of spatial learning during a single 20-min trial (i.e., short-term memory), with spatial memory encoding and retrieval (i.e., long-term memory) assessed by trials conducted over consecutive days. Using the APA task, cognitive flexibility can be assessed using the reversal learning paradigm, as this increases the cognitive load required for efficient performance in the task. In addition to a detailed experimental protocol, this paper also describes the range of its possible applications, the expected key results, as well as the analytical methods to assess the data, and the pitfalls/troubleshooting measures. The protocol described herein is highly robust and produces replicable results, thus presenting an important paradigm that enables the assessment of subtle short-term changes in spatial learning and memory, such as those observed for many experimental interventions. PMID:29089878

Activating Student to Learn Chemistry using Chemmy Card 6-1 Game as an Instructional Medium in IUPAC Nomenclature of Inorganic Compounds

NASA Astrophysics Data System (ADS)

Lutfi, A.; Hidayah, R.

2018-01-01

The aim of this study is to know the effect of Internet-assisted Chemmy Card 6-1 game as an instructional medium in IUPAC Nomenclature of Inorganic Compounds material for X grade of senior high school on students’ activity, learning motivation, and learning outcome. The study was conducted at SMA Negeri Sidoarjo, Indonesia, in two different classes. The instruction was done based on the lesson plan made. The observation on students’ activity was conducted during the instruction with the game while test and questionnaire were given after the instruction. The result showed positive activities, which students listened to the teacher’s explanation, actively delivered questions, and enabled to solve problems in naming compounds. It was also effective to avoid the drowsiness. The result of students’ motivation of X MIPA 6 was 74.78% (good) while X MIPA 7 was 83.80% (very good). The pretest results of two classes showed that no students mastered but 100% students mastered and the increase of N-gain scores in two classes was categorized as high, ≥0,7, after the instruction. The result of this study showed that the use of Internet-assisted Chemmy Card 6-1 game in IUPAC nomenclature of inorganic compounds for X grade of senior high school could be pleasant for students to learn and effective in achieving the learning objective.

Using a computer simulation for teaching communication skills: A blinded multisite mixed methods randomized controlled trial.

PubMed

Kron, Frederick W; Fetters, Michael D; Scerbo, Mark W; White, Casey B; Lypson, Monica L; Padilla, Miguel A; Gliva-McConvey, Gayle A; Belfore, Lee A; West, Temple; Wallace, Amelia M; Guetterman, Timothy C; Schleicher, Lauren S; Kennedy, Rebecca A; Mangrulkar, Rajesh S; Cleary, James F; Marsella, Stacy C; Becker, Daniel M

2017-04-01

To assess advanced communication skills among second-year medical students exposed either to a computer simulation (MPathic-VR) featuring virtual humans, or to a multimedia computer-based learning module, and to understand each group's experiences and learning preferences. A single-blinded, mixed methods, randomized, multisite trial compared MPathic-VR (N=210) to computer-based learning (N=211). Primary outcomes: communication scores during repeat interactions with MPathic-VR's intercultural and interprofessional communication scenarios and scores on a subsequent advanced communication skills objective structured clinical examination (OSCE). Multivariate analysis of variance was used to compare outcomes. student attitude surveys and qualitative assessments of their experiences with MPathic-VR or computer-based learning. MPathic-VR-trained students improved their intercultural and interprofessional communication performance between their first and second interactions with each scenario. They also achieved significantly higher composite scores on the OSCE than computer-based learning-trained students. Attitudes and experiences were more positive among students trained with MPathic-VR, who valued its providing immediate feedback, teaching nonverbal communication skills, and preparing them for emotion-charged patient encounters. MPathic-VR was effective in training advanced communication skills and in enabling knowledge transfer into a more realistic clinical situation. MPathic-VR's virtual human simulation offers an effective and engaging means of advanced communication training. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Use of Wireless Laptop Computers for Computer-Assisted Learning in Pharmacokinetics

PubMed Central

Munar, Myrna Y.; Singh, Harleen; Belle, Donna; Brackett, Carolyn C.; Earle, Sandra B.

2006-01-01

Objective To implement computer-assisted learning workshops into pharmacokinetics courses in a doctor of pharmacy (PharmD) program. Design Workshops were designed for students to utilize computer software programs on laptop computers to build pharmacokinetic models to predict drug concentrations resulting from various dosage regimens. In addition, students were able to visualize through graphing programs how altering different parameters changed drug concentration-time curves. Surveys were conducted to measure students’ attitudes toward computer technology before and after implementation. Finally, traditional examinations were used to evaluate student learning. Assessment Doctor of pharmacy students responded favorably to the use of wireless laptop computers in problem-based pharmacokinetic workshops. Eighty-eight percent (n = 61/69) and 82% (n = 55/67) of PharmD students completed surveys before and after computer implementation, respectively. Prior to implementation, 95% of students agreed that computers would enhance learning in pharmacokinetics. After implementation, 98% of students strongly agreed (p < 0.05) that computers enhanced learning. Examination results were significantly higher after computer implementation (89% with computers vs. 84% without computers; p = 0.01). Conclusion Implementation of wireless laptop computers in a pharmacokinetic course enabled students to construct their own pharmacokinetic models that could respond to changing parameters. Students had greater comprehension and were better able to interpret results and provide appropriate recommendations. Computer-assisted pharmacokinetic techniques can be powerful tools when making decisions about drug therapy. PMID:17136147

Implementing Infrastructures for Managing Learning Objects

ERIC Educational Resources Information Center

Klemke, Roland; Ternier, Stefaan; Kalz, Marco; Specht, Marcus

2010-01-01

Making learning objects available is critical to reuse learning resources. Making content transparently available and providing added value to different stakeholders is among the goals of the European Commission's eContentplus programme. This paper analyses standards and protocols relevant for making learning objects accessible in distributed data…

Credit assignment between body and object probed by an object transportation task.

PubMed

Kong, Gaiqing; Zhou, Zhihao; Wang, Qining; Kording, Konrad; Wei, Kunlin

2017-10-17

It has been proposed that learning from movement errors involves a credit assignment problem: did I misestimate properties of the object or those of my body? For example, an overestimate of arm strength and an underestimate of the weight of a coffee cup can both lead to coffee spills. Though previous studies have found signs of simultaneous learning of the object and of the body during object manipulation, there is little behavioral evidence about their quantitative relation. Here we employed a novel weight-transportation task, in which participants lift the first cup filled with liquid while assessing their learning from errors. Specifically, we examined their transfer of learning when switching to a contralateral hand, the second identical cup, or switching both hands and cups. By comparing these transfer behaviors, we found that 25% of the learning was attributed to the object (simply because of the use of the same cup) and 58% of the learning was attributed to the body (simply because of the use of the same hand). The nervous system thus seems to partition the learning of object manipulation between the object and the body.

How does tele-learning compare with other forms of education delivery? A systematic review of tele-learning educational outcomes for health professionals.

PubMed

Tomlinson, Jo; Shaw, Tim; Munro, Ana; Johnson, Ros; Madden, D Lynne; Phillips, Rosemary; McGregor, Deborah

2013-11-01

Telecommuniciation technologies, including audio and videoconferencing facilities, afford geographically dispersed health professionals the opportunity to connect and collaborate with others. Recognised for enabling tele-consultations and tele-collaborations between teams of health care professionals and their patients, these technologies are also well suited to the delivery of distance learning programs, known as tele-learning. To determine whether tele-learning delivery methods achieve equivalent learning outcomes when compared with traditional face-to-face education delivery methods. A systematic literature review was commissioned by the NSW Ministry of Health to identify results relevant to programs applying tele-learning delivery methods in the provision of education to health professionals. The review found few studies that rigorously compared tele-learning with traditional formats. There was some evidence, however, to support the premise that tele-learning models achieve comparable learning outcomes and that participants are generally satisfied with and accepting of this delivery method. The review illustrated that tele-learning technologies not only enable distance learning opportunities, but achieve comparable learning outcomes to traditional face-to-face models. More rigorous evidence is required to strengthen these findings and should be the focus of future tele-learning research.

Effects of Integrating an Active Learning-Promoting Mechanism into Location-Based Real-World Learning Environments on Students' Learning Performances and Behaviors

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chang, Shao-Chen; Chen, Pei-Ying; Chen, Xiang-Ya

2018-01-01

Engaging students in real-world learning contexts has been identified by educators as being an important way of helping them learn to apply what they have learned from textbooks to practical problems. The advancements in mobile and image-processing technologies have enabled students to access learning resources and receive learning guidance in…

The Effects of Students' Learning Anxiety and Motivation on the Learning Achievement in the Activity Theory Based Gamified Learning Environment

ERIC Educational Resources Information Center

Su, Chung-Ho

2017-01-01

The advancement of mobile game-based learning has encouraged many related studies, which has enabled students to learn more and faster. To enhance the clinical path of cardiac catheterization learning, this paper has developed a mobile 3D-CCGBLS (3D Cardiac Catheterization Game-Based Learning System) with a learning assessment for cardiac…

Predictable Locations Aid Early Object Name Learning

PubMed Central

Benitez, Viridiana L.; Smith, Linda B.

2012-01-01

Expectancy-based localized attention has been shown to promote the formation and retrieval of multisensory memories in adults. Three experiments show that these processes also characterize attention and learning in 16- to 18- month old infants and, moreover, that these processes may play a critical role in supporting early object name learning. The three experiments show that infants learn names for objects when those objects have predictable rather than varied locations, that infants who anticipate the location of named objects better learn those object names, and that infants integrate experiences that are separated in time but share a common location. Taken together, these results suggest that localized attention, cued attention, and spatial indexing are an inter-related set of processes in young children that aid in the early building of coherent object representations. The relevance of the experimental results and spatial attention for everyday word learning are discussed. PMID:22989872

Preceptors’ Self-Assessment of Their Ability to Perform the Learning Objectives of an Experiential Program

PubMed Central

2012-01-01

Objective. To evaluate preceptors’ perception of their ability to perform the Structured Practical Experiences in Pharmacy (SPEP) learning objectives through a self-assessment activity. Methods. A self-assessment instrument consisting of 28 learning objectives associated with clinic, community, and hospital pharmacy practice experiences were developed. Preceptors rated their performance ability for each of the learning objectives using a 3-point Likert scale. Results. Of the 116 preceptors, 89 (77%) completed the self-assessment survey instrument. The overall preceptor responses to the items on performance of the 28 SPEP learning objectives ranged from good to excellent. Years of experience, practice experience setting, and involvement as a SPEP or SPEP and PharmD preceptor had no influence on their self-reported capabilities. Conclusion. Most preceptors rated their ability to perform the learning objectives for the structured practical experiences in pharmacy as high. Competency areas requiring further preceptor development were identified. PMID:23193333

Translational Rodent Paradigms to Investigate Neuromechanisms Underlying Behaviors Relevant to Amotivation and Altered Reward Processing in Schizophrenia

PubMed Central

Young, Jared W.; Markou, Athina

2015-01-01

Amotivation and reward-processing deficits have long been described in patients with schizophrenia and considered large contributors to patients’ inability to integrate well in society. No effective treatments exist for these symptoms, partly because the neuromechanisms mediating such symptoms are poorly understood. Here, we propose a translational neuroscientific approach that can be used to assess reward/motivational deficits related to the negative symptoms of schizophrenia using behavioral paradigms that can also be conducted in experimental animals. By designing and using objective laboratory behavioral tools that are parallel in their parameters in rodents and humans, the neuromechanisms underlying behaviors with relevance to these symptoms of schizophrenia can be investigated. We describe tasks that measure the motivation of rodents to expend physical and cognitive effort to gain rewards, as well as probabilistic learning tasks that assess both reward learning and feedback-based decision making. The latter tasks are relevant because of demonstrated links of performance deficits correlating with negative symptoms in patients with schizophrenia. These tasks utilize operant techniques in order to investigate neural circuits targeting a specific domain across species. These tasks therefore enable the development of insights into altered mechanisms leading to negative symptom-relevant behaviors in patients with schizophrenia. Such findings will then enable the development of targeted treatments for these altered neuromechanisms and behaviors seen in schizophrenia. PMID:26194891

Supporting Teachers in Identifying Students' Learning Styles in Learning Management Systems: An Automatic Student Modelling Approach

ERIC Educational Resources Information Center

Graf, Sabine; Kinshuk; Liu, Tzu-Chien

2009-01-01

In learning management systems (LMSs), teachers have more difficulties to notice and know how individual students behave and learn in a course, compared to face-to-face education. Enabling teachers to know their students' learning styles and making students aware of their own learning styles increases teachers' and students' understanding about…

Unconscious Familiarity-based Color-Form Binding: Evidence from Visual Extinction.

PubMed

Rappaport, Sarah J; Riddoch, M Jane; Chechlacz, Magda; Humphreys, Glyn W

2016-03-01

There is good evidence that early visual processing involves the coding of different features in independent brain regions. A major question, then, is how we see the world in an integrated manner, in which the different features are "bound" together. A standard account of this has been that feature binding depends on attention to the stimulus, which enables only the relevant features to be linked together [Treisman, A., & Gelade, G. A feature-integration theory of attention. Cognitive Psychology, 12, 97-136, 1980]. Here we test this influential idea by examining whether, in patients showing visual extinction, the processing of otherwise unconscious (extinguished) stimuli is modulated by presenting objects in their correct (familiar) color. Correctly colored objects showed reduced extinction when they had a learned color, and this color matched across the ipsi- and contralesional items (red strawberry + red tomato). In contrast, there was no reduction in extinction under the same conditions when the stimuli were colored incorrectly (blue strawberry + blue tomato; Experiment 1). The result was not due to the speeded identification of a correctly colored ipsilesional item, as there was no benefit from having correctly colored objects in different colors (red strawberry + yellow lemon; Experiment 2). There was also no benefit to extinction from presenting the correct colors in the background of each item (Experiment 3). The data suggest that learned color-form binding can reduce extinction even when color is irrelevant for the task. The result is consistent with preattentive binding of color and shape for familiar stimuli.

A Common Core for Active Conceptual Modeling for Learning from Surprises

NASA Astrophysics Data System (ADS)

Liddle, Stephen W.; Embley, David W.

The new field of active conceptual modeling for learning from surprises (ACM-L) may be helpful in preserving life, protecting property, and improving quality of life. The conceptual modeling community has developed sound theory and practices for conceptual modeling that, if properly applied, could help analysts model and predict more accurately. In particular, we need to associate more semantics with links, and we need fully reified high-level objects and relationships that have a clear, formal underlying semantics that follows a natural, ontological approach. We also need to capture more dynamic aspects in our conceptual models to more accurately model complex, dynamic systems. These concepts already exist, and the theory is well developed; what remains is to link them with the ideas needed to predict system evolution, thus enabling risk assessment and response planning. No single researcher or research group will be able to achieve this ambitious vision alone. As a starting point, we recommend that the nascent ACM-L community agree on a common core model that supports all aspects—static and dynamic—needed for active conceptual modeling in support of learning from surprises. A common core will more likely gain the traction needed to sustain the extended ACM-L research effort that will yield the advertised benefits of learning from surprises.

Problem based learning in midwifery - the teachers perspective.

PubMed

Rowan, Catherine J; McCourt, Christine; Bick, Debra; Beake, Sarah

2007-02-01

Problem- or evidence-based learning (PBL or EBL) has become more widely used in the education of health professionals. Although there has been research exploring its effectiveness and the student's perspective, there has been little research exploring the perceptions of the teacher. The objective of this study was to investigate the experiences of teachers facilitating a problem based learning curriculum in midwifery. The study took place at Thames Valley University, which has implemented this approach across the entire curriculum. Semi-structured interviews were undertaken following random selection from two groups of teachers; those more experienced as teachers and those who had entered teaching more recently. Aspects of the teacher's role identified included questioning students to draw out their knowledge and understanding and to help students challenge each other, discuss and evaluate their learning. Strategies used varied depending on the stage of the programme. Difficulties encountered were mostly in relation to facilitating groups of differing backgrounds and ability and seeking to enable the students to work well together. Key challenges for teachers were in relation to developing facilitation skills, balancing input or guidance with facilitating independent learning. Problem based learning was perceived to be beneficial in helping students relate theory to practice and in encouraging an active and enquiring approach to evidence, but teachers raised important questions about its practice. Tensions were identified between the constructivist theories on which the model of PBL rests and the formal requirements of an externally regulated professional curriculum.

Participative Knowledge Production of Learning Objects for E-Books.

ERIC Educational Resources Information Center

Dodero, Juan Manuel; Aedo, Ignacio; Diaz, Paloma

2002-01-01

Defines a learning object as any digital resource that can be reused to support learning and thus considers electronic books as learning objects. Highlights include knowledge management; participative knowledge production, i.e. authoring electronic books by a distributed group of authors; participative knowledge production architecture; and…

Using Active Learning for Speeding up Calibration in Simulation Models.

PubMed

Cevik, Mucahit; Ergun, Mehmet Ali; Stout, Natasha K; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2016-07-01

Most cancer simulation models include unobservable parameters that determine disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality, and their values are typically estimated via a lengthy calibration procedure, which involves evaluating a large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We developed an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs and therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using the previously developed University of Wisconsin breast cancer simulation model (UWBCS). In a recent study, calibration of the UWBCS required the evaluation of 378 000 input parameter combinations to build a race-specific model, and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378 000 combinations. Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. © The Author(s) 2015.

Using Active Learning for Speeding up Calibration in Simulation Models

PubMed Central

Cevik, Mucahit; Ali Ergun, Mehmet; Stout, Natasha K.; Trentham-Dietz, Amy; Craven, Mark; Alagoz, Oguzhan

2015-01-01

Background Most cancer simulation models include unobservable parameters that determine the disease onset and tumor growth. These parameters play an important role in matching key outcomes such as cancer incidence and mortality and their values are typically estimated via lengthy calibration procedure, which involves evaluating large number of combinations of parameter values via simulation. The objective of this study is to demonstrate how machine learning approaches can be used to accelerate the calibration process by reducing the number of parameter combinations that are actually evaluated. Methods Active learning is a popular machine learning method that enables a learning algorithm such as artificial neural networks to interactively choose which parameter combinations to evaluate. We develop an active learning algorithm to expedite the calibration process. Our algorithm determines the parameter combinations that are more likely to produce desired outputs, therefore reduces the number of simulation runs performed during calibration. We demonstrate our method using previously developed University of Wisconsin Breast Cancer Simulation Model (UWBCS). Results In a recent study, calibration of the UWBCS required the evaluation of 378,000 input parameter combinations to build a race-specific model and only 69 of these combinations produced results that closely matched observed data. By using the active learning algorithm in conjunction with standard calibration methods, we identify all 69 parameter combinations by evaluating only 5620 of the 378,000 combinations. Conclusion Machine learning methods hold potential in guiding model developers in the selection of more promising parameter combinations and hence speeding up the calibration process. Applying our machine learning algorithm to one model shows that evaluating only 1.49% of all parameter combinations would be sufficient for the calibration. PMID:26471190

Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern

ERIC Educational Resources Information Center

Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai

2007-01-01

With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future,…

Learning Object Retrieval and Aggregation Based on Learning Styles

ERIC Educational Resources Information Center

Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

2017-01-01

The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

Learning from Collaborative New Product Development Projects

ERIC Educational Resources Information Center

Kleinsmann, Maaike; Valkenburg, Rianne

2005-01-01

Purpose--In an empirical study learning opportunities were identified. Learning opportunities are enablers or disablers for the achievement of shared understanding. Design/methodology/approach--Actors were interviewed about their communication process. The learning history method was used to analyze and structure the data. From the learning…

An Online Debate Series for First-Year Pharmacy Students

PubMed Central

Crawford, Stephanie Y.

2007-01-01

Objectives This article describes an online debate series that was developed as a new component to an introductory core course for first-professional year pharmacy students. Objectives were to facilitate the group process, introduce controversial issues related to the US healthcare system, improve critical thinking and communication skills, enable students' ability to analyze and evaluate evidence, help develop skills in formulating written arguments, and encourage tolerance of diverse points of view. Design One hundred sixty-two students were assigned to 40 teams (half assigned to argue as “Pros” and half as “Cons”) and paired into 20 debating groups. The paired teams posted 3 arguments in an online forum alternatively over a 12-week period. The winning teams were determined by a panel of 3 judges. Assessment Feedback from the judges was posted online and summarized in an in-class discussion. Thematic analysis of qualitative data from students and faculty members demonstrated the effectiveness of the online debate component in helping students work together in a group, learn alternative sides of complex issues, and write persuasive arguments. Conclusion This novel online-debate forum was a feasible teaching and learning strategy, which helped pharmacy students improve their communication skills and critical thinking, expanded their scope of knowledge, and provided a platform for group process. PMID:17429512

Aesthetic concepts, perceptual learning, and linguistic enculturation: considerations from Wittgenstein, language, and music.

PubMed

Croom, Adam M

2012-03-01

Aesthetic non-cognitivists deny that aesthetic statements express genuinely aesthetic beliefs and instead hold that they work primarily to express something non-cognitive, such as attitudes of approval or disapproval, or desire. Non-cognitivists deny that aesthetic statements express aesthetic beliefs because they deny that there are aesthetic features in the world for aesthetic beliefs to represent. Their assumption, shared by scientists and theorists of mind alike, was that language-users possess cognitive mechanisms with which to objectively grasp abstract rules fixed independently of human responses, and that cognizers are thereby capable of grasping rules for the correct application of aesthetic concepts without relying on evaluation or enculturation. However, in this article I use Wittgenstein's rule-following considerations to argue that psychological theories grounded upon this so-called objective model of rule-following fail to adequately account for concept acquisition and mastery. I argue that this is because linguistic enculturation, and the perceptual learning that's often involved, influences and enables the mastery of aesthetic concepts. I argue that part of what's involved in speaking aesthetically is to belong to a cultural practice of making sense of things aesthetically, and that it's within a socio-linguistic community, and that community's practices, that such aesthetic sense can be made intelligible.

E-learning policies, practices and challenges in two Norwegian organizations.

PubMed

Welle-Strand, Anne; Thune, Taran

2003-05-01

This article reports a pilot study on the uses of technology to enable learning within a formal educational setting in a higher education institution and within a corporation. These two Norwegian cases were selected due to their commitment to technology-enabled learning, as expressed in policy and strategy documents. The aim was to investigate the commitment and actual use of information and communications technology (ICT) for learning as well as what key actors think are the major challenges for successful large scale implementation of ICT for learning. The findings indicate that there is insufficient follow-up on e-learning policies and that there is a general lack of strategic direction and leadership in this area. The key challenges respondents highlight relate to the need for a systematic and pedagogical approach to e-learning in which three equally important considerations must be balanced: organization, pedagogy and technology. Key perspectives of a coherent pedagogical and organizational framework for planning e-learning are discussed.

An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

ERIC Educational Resources Information Center

Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

2013-01-01

Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…

Integrate WeChat with Moodle to Provide a Mobile Learning Environment for Students

ERIC Educational Resources Information Center

Li, Zhigao; Fan, Yibo; Jiao, Jianli

2016-01-01

In the information age, learning has become ubiquitous, and mobile learning enabled by mobile technologies is expected to play a significant role in various educational settings. Currently, there exist some limitations on mobile learning from the perspective of technology. The implementation of mobile learning usually depends on the development of…

A Method of Cross-Level Frequent Pattern Mining for Web-Based Instruction

ERIC Educational Resources Information Center

Huang, Yueh-Min; Chen, Juei-Nan; Cheng, Shu-Chen

2007-01-01

Due to the rise of e-Learning, more and more useful learning materials are open to public access. Therefore, an appropriate learning suggestion mechanism is an important tool to enable learners to work more efficiently. A smoother learning process increases the learning effect, avoiding unnecessarily difficult concepts and disorientation during…

A Simultaneous Mobile E-Learning Environment and Application

ERIC Educational Resources Information Center

Karal, Hasan; Bahcekapili, Ekrem; Yildiz, Adil

2010-01-01

The purpose of the present study was to design a mobile learning environment that enables the use of a teleconference application used in simultaneous e-learning with mobile devices and to evaluate this mobile learning environment based on students' views. With the mobile learning environment developed in the study, the students are able to follow…

Combining an Exciting Classroom Learning Environment with an Effective Computerized Learning Management System

ERIC Educational Resources Information Center

Hallam, Teresa A.; Hallam, Stephen F.

2009-01-01

Imagine a computerized learning management system that enables teachers to deliver pertinent learning materials to students. Lectures are prerecorded and made available to download from the learning management system. If all their lectures were prerecorded, what would teachers do in the classroom? Classroom time could be used to coordinate…

Learning Objects--Instructional Metadata and Sequencing.

ERIC Educational Resources Information Center

Redeker, Giselher

The main focus of current discussions within the standardization process of learning technology is on economical opportunities and technical aspects of learning objects. There has been little discussion about the instructional or didactical issues. The purpose of this paper is to conceptualize a taxonomy of learning objects for the facilitation of…

The International Learning Object Metadata Survey

ERIC Educational Resources Information Center

Friesen, Norm

2004-01-01

A wide range of projects and organizations is currently making digital learning resources (learning objects) available to instructors, students, and designers via systematic, standards-based infrastructures. One standard that is central to many of these efforts and infrastructures is known as Learning Object Metadata (IEEE 1484.12.1-2002, or LOM).…

Teaching undergraduate students in rural general practice: an evaluation of a new rural campus in England.

PubMed

Bartlett, Maggie; Pritchard, Katie; Lewis, Leo; Hays, Richard B; Mckinley, Robert K

2016-01-01

One approach to facilitating student interactions with patient pathways at Keele University School of Medicine, England, is the placement of medical students for 25% of their clinical placement time in general practices. The largest component is a 15-week 'student attachment' in primary care during the final year, which required the development of a new network of teaching practices in a rural district of England about 90 km (60 mi) from the main campus in North Staffordshire. The new accommodation and education hub was established in 2011-2012 to enable students to become immersed in those communities and learn about medical practice within a rural and remote context. Objectives were to evaluate the rural teaching from the perspectives of four groups: patients, general practice tutors, community hospital staff and students. Learning outcomes (as measured by objective structured clinical examinations) of students learning in rural practices in the final year were compared with those in other practices. Data were gathered from a variety of sources. Students' scores in cohort-wide clinical assessment were compared with those in other locations. Semi-structured interviews were conducted with general practice tutors and community hospital staff. Serial focus groups explored the perceptions of the students, and questionnaires were used to gather the views of patients. Patients reported positive experiences of students in their consultations, with 97% expressing willingness to see students. The majority of patients considered that teaching in general practice was a good thing. They also expressed altruistic ideas about facilitating learning. The tutors were enthusiastic and perceived that teaching had positive impacts on their practices despite negative effects on their workload. The community hospital staff welcomed students and expressed altruistic ideas about helping them learn. There was no significant difference between the rurally placed students' objective structured clinical examination performance and that of their peers in other locations. Some students had difficulty with the isolation from peers and academic activities, and travel was a problem despite their accommodation close to the practices. Students valued the learning opportunities offered by the rural practice placements. The general practice tutors, patients and community hospital staff found teaching to be a positive experience overall and perceived a value to the health system and broader community in students learning locally for substantial periods of time. The evaluation has identified some student concerns about transport times and costs, social isolation, and access to resources and administrative tasks, and these are being addressed.

Effect of tDCS on task relevant and irrelevant perceptual learning of complex objects.

PubMed

Van Meel, Chayenne; Daniels, Nicky; de Beeck, Hans Op; Baeck, Annelies

2016-01-01

During perceptual learning the visual representations in the brain are altered, but these changes' causal role has not yet been fully characterized. We used transcranial direct current stimulation (tDCS) to investigate the role of higher visual regions in lateral occipital cortex (LO) in perceptual learning with complex objects. We also investigated whether object learning is dependent on the relevance of the objects for the learning task. Participants were trained in two tasks: object recognition using a backward masking paradigm and an orientation judgment task. During both tasks, an object with a red line on top of it were presented in each trial. The crucial difference between both tasks was the relevance of the object: the object was relevant for the object recognition task, but not for the orientation judgment task. During training, half of the participants received anodal tDCS stimulation targeted at the lateral occipital cortex (LO). Afterwards, participants were tested on how well they recognized the trained objects, the irrelevant objects presented during the orientation judgment task and a set of completely new objects. Participants stimulated with tDCS during training showed larger improvements of performance compared to participants in the sham condition. No learning effect was found for the objects presented during the orientation judgment task. To conclude, this study suggests a causal role of LO in relevant object learning, but given the rather low spatial resolution of tDCS, more research on the specificity of this effect is needed. Further, mere exposure is not sufficient to train object recognition in our paradigm.

Exploring emerging learning needs: a UK-wide consultation on environmental sustainability learning objectives for medical education.

PubMed

Walpole, Sarah C; Mortimer, Frances; Inman, Alice; Braithwaite, Isobel; Thompson, Trevor

2015-12-24

This study aimed to engage wide-ranging stakeholders and develop consensus learning objectives for undergraduate and postgraduate medical education. A UK-wide consultation garnered opinions of healthcare students, healthcare educators and other key stakeholders about environmental sustainability in medical education. The policy Delphi approach informed this study. Draft learning objectives were revised iteratively during three rounds of consultation: online questionnaire or telephone interview, face-to-face seminar and email consultation. Twelve draft learning objectives were developed based on review of relevant literature. In round one, 64 participants' median ratings of the learning objectives were 3.5 for relevance and 3.0 for feasibility on a Likert scale of one to four. Revisions were proposed, e.g. to highlight relevance to public health and professionalism. Thirty three participants attended round two. Conflicting opinions were explored. Added content areas included health benefits of sustainable behaviours. To enhance usability, restructuring provided three overarching learning objectives, each with subsidiary points. All participants from rounds one and two were contacted in round three, and no further edits were required. This is the first attempt to define consensus learning objectives for medical students about environmental sustainability. Allowing a wide range of stakeholders to comment on multiple iterations of the document stimulated their engagement with the issues raised and ownership of the resulting learning objectives.

Enhance Low-Achieving Students' Learning Involvement in Taiwan's Higher Education: An Approach via E-Learning with Problem-Based Learning and Self-Regulated Learning

ERIC Educational Resources Information Center

Lee, Tsang-Hsiung; Shen, Pei-Di; Tsai, Chia-Wen

2010-01-01

This study explored the effects of web-enabled pedagogies on students' involvement in learning. A series of quasi-experiments were conducted to investigate whether students' involvement increases over time if intervened, respectively, by problem-based learning (PBL), self-regulated learning (SRL), and their combinations. Two classes of 102…

Building Trust and Shared Knowledge in Communities of E-Learning Practice: Collaborative Leadership in the JISC eLISA and CAMEL Lifelong Learning Projects

ERIC Educational Resources Information Center

Jameson, Jill; Ferrell, Gill; Kelly, Jacquie; Walker, Simon; Ryan, Malcolm

2006-01-01

Trust and collective learning are useful features that are enabled by effective collaborative leadership of e-learning projects across higher and further education (HE/FE) institutions promoting lifelong learning. These features contribute effectively to the development of design for learning in communities of e-learning practice. For this,…

Web-based faculty development: e-learning for clinical teachers in the London Deanery.

PubMed

McKimm, Judy; Swanwick, Tim

2010-03-01

the London Deanery has provided a web-based resource for supporting the educational development needs of clinical teachers since 2002. This forms part of a range of resources supporting the professional development of clinical teachers and postgraduate supervisors. Following a review in 2007, the deanery commissioned a series of new e-learning modules designed as an introduction to clinical teaching. the deanery's faculty development initiatives are one response to requirements of the Postgraduate Medical Education and Training Board (PMETB), other policy drivers, workforce demands and service changes. Increasingly, doctors are required to provide an educational portfolio of evidence, and satisfy the teaching and training component of Good Medical Practice in revalidation or recertification. 'E-learning for clinical teachers' comprises 16 short, open-access, free-standing modules. The modules are built around a unifying structure, and cover core topics in clinical teaching: feedback; supervision; workplace-based learning; assessment; diversity and equal opportunities; career development; appraisal; lecturing; small group teaching; interprofessional education; and setting learning objectives. The modules can be used as a complementary resource to award-bearing programmes. On completion of a module, a certificate can be printed out for the teacher's portfolio. reflective practice and engagement with an individual's teaching practice is encouraged through self-assessment and a reflective log. The open-access, web-based format enables engagement with the material to suit a doctor's working and learning patterns, and is a valuable adjunct to other forms of learning. The site has been accessed by over 64000 health professionals (including students, trainees, qualified professionals, supervisors and staff developers) from 155 countries. Blackwell Publishing Ltd 2010.

Patients with heart failure as co-designers of an educational website: implications for medical education

PubMed Central

Svanholm, Jette R.; Schjødt, Inge; Mølgaard Jensen, Karsten; Silén, Charlotte; Karlgren, Klas

2017-01-01

Objectives To identify the learning needs of patients with heart failure between outpatients follow-up visits from their perspective and to ascertain what they emphasize as being important in the design of an educational website for them. Methods We conducted a two-step qualitative study at Aarhus University Hospital, Denmark. Twenty patients with heart failure participated either in focus group interviews, diary writing, or video-recorded design sessions. Data on learning needs were collected in step 1 and analyses, therefore, helped develop the preliminary prototypes of a website. In step 2, patients worked on the prototypes in video-recorded design sessions, employing a think-aloud method. The interviews were transcribed and a content analysis was performed on the text and video data. Results Patients’ learning needs were multifaceted, driven by anxiety, arising from, and often influenced by, such daily situations and contexts as the medical condition, medication, challenges in daily life, and where to get support and how to manage their self-care. They emphasized different ways of adapting the design to the patient group to enable interaction with peers and professionals and specific interface issues. Conclusions This study provided insights into the different learning needs of patients with heart failure, how managing daily situations is the starting point for these needs and how emotions play a part in patients’ learning. Moreover, it showed how patient co-designers proved to be useful for understanding how to design a website that supports patients’ learning: insights, which may become important in designing online learning tools for patients. PMID:28237976

Competencies to enable learning-focused clinical supervision: a thematic analysis of the literature.

PubMed

Pront, Leeanne; Gillham, David; Schuwirth, Lambert W T

2016-04-01

Clinical supervision is essential for development of health professional students and widely recognised as a significant factor influencing student learning. Although considered important, delivery is often founded on personal experience or a series of predetermined steps that offer standardised behavioural approaches. Such a view may limit the capacity to promote individualised student learning in complex clinical environments. The objective of this review was to develop a comprehensive understanding of what is considered 'good' clinical supervision, within health student education. The literature provides many perspectives, so collation and interpretation were needed to aid development and understanding for all clinicians required to perform clinical supervision within their daily practice. A comprehensive thematic literature review was carried out, which included a variety of health disciplines and geographical environments. Literature addressing 'good' clinical supervision consists primarily of descriptive qualitative research comprising mostly small studies that repeated descriptions of student and supervisor opinions of 'good' supervision. Synthesis and thematic analysis of the literature resulted in four 'competency' domains perceived to inform delivery of learning-focused or 'good' clinical supervision. Domains understood to promote student learning are co-dependent and include 'to partner', 'to nurture', 'to engage' and 'to facilitate meaning'. Clinical supervision is a complex phenomenon and establishing a comprehensive understanding across health disciplines can influence the future health workforce. The learning-focused clinical supervision domains presented here provide an alternative perspective of clinical supervision of health students. This paper is the first step in establishing a more comprehensive understanding of learning-focused clinical supervision, which may lead to development of competencies for clinical supervision. © 2016 John Wiley & Sons Ltd.

Powered mobility intervention: understanding the position of tool use learning as part of implementing the ALP tool.

PubMed

Nilsson, Lisbeth; Durkin, Josephine

2017-10-01

To explore the knowledge necessary for adoption and implementation of the Assessment of Learning Powered mobility use (ALP) tool in different practice settings for both adults and children. To consult with a diverse population of professionals working with adults and children, in different countries and various settings; who were learning about or using the ALP tool, as part of exploring and implementing research findings. Classical grounded theory with a rigorous comparative analysis of data from informants together with reflections on our own rich experiences of powered mobility practice and comparisons with the literature. A core category learning tool use and a new theory of cognizing tool use, with its interdependent properties: motivation, confidence, permissiveness, attentiveness and co-construction has emerged which explains in greater depth what enables the application of the ALP tool. The scientific knowledge base on tool use learning and the new theory conveys the information necessary for practitioner's cognizing how to apply the learning approach of the ALP tool in order to enable tool use learning through powered mobility practice as a therapeutic intervention in its own right. This opens up the possibility for more children and adults to have access to learning through powered mobility practice. Implications for rehabilitation Tool use learning through powered mobility practice is a therapeutic intervention in its own right. Powered mobility practice can be used as a rehabilitation tool with individuals who may not need to become powered wheelchair users. Motivation, confidence, permissiveness, attentiveness and co-construction are key properties for enabling the application of the learning approach of the ALP tool. Labelling and the use of language, together with honing observational skills through viewing video footage, are key to developing successful learning partnerships.

[Digital learning object for diagnostic reasoning in nursing applied to the integumentary system].

PubMed

da Costa, Cecília Passos Vaz; Luz, Maria Helena Barros Araújo

2015-12-01

To describe the creation of a digital learning object for diagnostic reasoning in nursing applied to the integumentary system at a public university of Piaui. A methodological study applied to technological production based on the pedagogical framework of problem-based learning. The methodology for creating the learning object observed the stages of analysis, design, development, implementation and evaluation recommended for contextualized instructional design. The revised taxonomy of Bloom was used to list the educational goals. The four modules of the developed learning object were inserted into the educational platform Moodle. The theoretical assumptions allowed the design of an important online resource that promotes effective learning in the scope of nursing education. This study should add value to nursing teaching practices through the use of digital learning objects for teaching diagnostic reasoning applied to skin and skin appendages.

The Role of e-Portfolios in Supporting Productive Learning

ERIC Educational Resources Information Center

Yang, Min; Tai, Mui; Lim, Cher Ping

2016-01-01

e-Portfolios are a form of authentic assessment with formative functions that include showcasing and sharing learning artifacts, documenting reflective learning processes, connecting learning across various stages and enabling frequent feedback for improvements. This paper examines how e-portfolios take up these formative roles to support…

Virtual Representations in 3D Learning Environments

ERIC Educational Resources Information Center

Shonfeld, Miri; Kritz, Miki

2013-01-01

This research explores the extent to which virtual worlds can serve as online collaborative learning environments for students by increasing social presence and engagement. 3D environments enable learning, which simulates face-to-face encounters while retaining the advantages of online learning. Students in Education departments created avatars…

The Role of Technology in Supporting Learning Communities.

ERIC Educational Resources Information Center

Riel, Margaret; Fulton, Kathleen

2001-01-01

In a learning community, students learn to cooperate and make teams work. Past technologies (print, photography, film, and computers) have enabled idea sharing, but are one-way communication modes. Broader learning communities have been made possible through electronic field trips, online mentoring, science investigations, and humanities…

Case-Based Reasoning in Mixed Paradigm Settings and with Learning

DTIC Science & Technology

1994-04-30

Learning Prototypical Cases OFF-BROADWAY, MCI and RMHC -* are three CBR-ML systems that learn case prototypes. We feel that methods that enable the...at Irvine Machine Learning Repository, including heart disease and breast cancer databases. OFF-BROADWAY, MCI and RMHC -* made the following notable

iVFTs - immersive virtual field trips for interactive learning about Earth's environment.

NASA Astrophysics Data System (ADS)

Bruce, G.; Anbar, A. D.; Semken, S. C.; Summons, R. E.; Oliver, C.; Buxner, S.

2014-12-01

Innovations in immersive interactive technologies are changing the way students explore Earth and its environment. State-of-the-art hardware has given developers the tools needed to capture high-resolution spherical content, 360° panoramic video, giga-pixel imagery, and unique viewpoints via unmanned aerial vehicles as they explore remote and physically challenging regions of our planet. Advanced software enables integration of these data into seamless, dynamic, immersive, interactive, content-rich, and learner-driven virtual field explorations, experienced online via HTML5. These surpass conventional online exercises that use 2-D static imagery and enable the student to engage in these virtual environments that are more like games than like lectures. Grounded in the active learning of exploration, inquiry, and application of knowledge as it is acquired, users interact non-linearly in conjunction with an intelligent tutoring system (ITS). The integration of this system allows the educational experience to be adapted to each individual student as they interact within the program. Such explorations, which we term "immersive virtual field trips" (iVFTs), are being integrated into cyber-learning allowing science teachers to take students to scientifically significant but inaccessible environments. Our team and collaborators are producing a diverse suite of freely accessible, iVFTs to teach key concepts in geology, astrobiology, ecology, and anthropology. Topics include Early Life, Biodiversity, Impact craters, Photosynthesis, Geologic Time, Stratigraphy, Tectonics, Volcanism, Surface Processes, The Rise of Oxygen, Origin of Water, Early Civilizations, Early Multicellular Organisms, and Bioarcheology. These diverse topics allow students to experience field sites all over the world, including, Grand Canyon (USA), Flinders Ranges (Australia), Shark Bay (Australia), Rainforests (Panama), Teotihuacan (Mexico), Upheaval Dome (USA), Pilbara (Australia), Mid-Atlantic Ridge (Iceland), and Mauna Kea (Hawaii). iVFTs are being beta-tested and used at ASU in several large-enrollment courses to assess its usability and effectiveness in meeting specific learning objectives. We invite geoscience educators to partake of this resource and find new applications to their own teaching.

Developing Learning Objectives for Accounting Ethics Using Bloom's Taxonomy

ERIC Educational Resources Information Center

Kidwell, Linda A.; Fisher, Dann G.; Braun, Robert L.; Swanson, Diane L.

2013-01-01

The purpose of our article is to offer a set of core knowledge learning objectives for accounting ethics education. Using Bloom's taxonomy of educational objectives, we develop learning objectives in six content areas: codes of ethical conduct, corporate governance, the accounting profession, moral development, classical ethics theories, and…

Design, Development, and Validation of Learning Objects

ERIC Educational Resources Information Center

Nugent, Gwen; Soh, Leen-Kiat; Samal, Ashok

2006-01-01

A learning object is a small, stand-alone, mediated content resource that can be reused in multiple instructional contexts. In this article, we describe our approach to design, develop, and validate Shareable Content Object Reference Model (SCORM) compliant learning objects for undergraduate computer science education. We discuss the advantages of…

Q-Learning-Based Adjustable Fixed-Phase Quantum Grover Search Algorithm

NASA Astrophysics Data System (ADS)

Guo, Ying; Shi, Wensha; Wang, Yijun; Hu, Jiankun

2017-02-01

We demonstrate that the rotation phase can be suitably chosen to increase the efficiency of the phase-based quantum search algorithm, leading to a dynamic balance between iterations and success probabilities of the fixed-phase quantum Grover search algorithm with Q-learning for a given number of solutions. In this search algorithm, the proposed Q-learning algorithm, which is a model-free reinforcement learning strategy in essence, is used for performing a matching algorithm based on the fraction of marked items λ and the rotation phase α. After establishing the policy function α = π(λ), we complete the fixed-phase Grover algorithm, where the phase parameter is selected via the learned policy. Simulation results show that the Q-learning-based Grover search algorithm (QLGA) enables fewer iterations and gives birth to higher success probabilities. Compared with the conventional Grover algorithms, it avoids the optimal local situations, thereby enabling success probabilities to approach one.

Influence of an Integrated Learning Diagnosis and Formative Assessment-Based Personalized Web Learning Approach on Students' Learning Performances and Perceptions

ERIC Educational Resources Information Center

Wongwatkit, Charoenchai; Srisawasdi, Niwat; Hwang, Gwo-Jen; Panjaburee, Patcharin

2017-01-01

The advancement of computer and communication technologies has enabled students to learn across various real-world contexts with supports from the learning system. In the meantime, researchers have emphasized the necessity of providing personalized learning guidance or support by considering individual students' status and needs in order to…

Has Web 2.0 Revitalized Informal Learning? The Relationship between Web 2.0 and Informal Learning

ERIC Educational Resources Information Center

Song, D.; Lee, J.

2014-01-01

Learning is becoming increasingly self-directed and often occurs away from schools and other formal educational settings. The development of a myriad of new technologies for learning has enabled people to learn anywhere and anytime. Web 2.0 technology allows researchers to shed a new light on the importance and prevalence of informal learning.…

How learning might strengthen existing visual object representations in human object-selective cortex.

PubMed

Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

Computer-based teaching module design: principles derived from learning theories.

PubMed

Lau, K H Vincent

2014-03-01

The computer-based teaching module (CBTM), which has recently gained prominence in medical education, is a teaching format in which a multimedia program serves as a single source for knowledge acquisition rather than playing an adjunctive role as it does in computer-assisted learning (CAL). Despite empirical validation in the past decade, there is limited research into the optimisation of CBTM design. This review aims to summarise research in classic and modern multimedia-specific learning theories applied to computer learning, and to collapse the findings into a set of design principles to guide the development of CBTMs. Scopus was searched for: (i) studies of classic cognitivism, constructivism and behaviourism theories (search terms: 'cognitive theory' OR 'constructivism theory' OR 'behaviourism theory' AND 'e-learning' OR 'web-based learning') and their sub-theories applied to computer learning, and (ii) recent studies of modern learning theories applied to computer learning (search terms: 'learning theory' AND 'e-learning' OR 'web-based learning') for articles published between 1990 and 2012. The first search identified 29 studies, dominated in topic by the cognitive load, elaboration and scaffolding theories. The second search identified 139 studies, with diverse topics in connectivism, discovery and technical scaffolding. Based on their relative representation in the literature, the applications of these theories were collapsed into a list of CBTM design principles. Ten principles were identified and categorised into three levels of design: the global level (managing objectives, framing, minimising technical load); the rhetoric level (optimising modality, making modality explicit, scaffolding, elaboration, spaced repeating), and the detail level (managing text, managing devices). This review examined the literature in the application of learning theories to CAL to develop a set of principles that guide CBTM design. Further research will enable educators to take advantage of this unique teaching format as it gains increasing importance in medical education. © 2014 John Wiley & Sons Ltd.

Challenges faced by parents of children with learning disabilities in Opuwo, Namibia

PubMed Central

Taderera, Clever

2017-01-01

Background Parenting children with learning disabilities requires a high level of knowledge and access to resources, information and services. In developing countries, however, these resources and services are not always available. Parents in Namibia, a developing country, therefore face challenges addressing children’s learning and other developmental disabilities, including challenges related to preventative and supportive interventions. Objective This research focuses on challenges faced by parents as they parent children with learning disabilities in Opuwo, Namibia. Method In-depth interviews were conducted with eight parents regarding the challenges they face in parenting their children with learning disabilities. Thematic analysis enabled the researchers to identify, analyse and report on themes that emerged from the qualitative interview data. Results Analysis of the interviews indicated that some participants had only a vague understanding of learning disabilities, as they did not have access to essential knowledge about this phenomenon. They also lacked an awareness of the availability of programmes, services and policies meant to benefit their children with learning disabilities. Participants voiced that they, their children with learning disabilities and community members have stereotypes and prejudices regarding learning disabilities. In this study, most of the children with learning disabilities were raised by single, unemployed parents who seemed to have access to less support from external sources than married couples parenting children with learning disabilities. These single parents are usually not married and because of lack of financial support from the other parent, the majority of them indicated that they struggle to meet the financial and material needs of their children. Conclusion The researchers concluded that the participants in this study experience a range of challenges in parenting their children with learning disabilities. The main challenges emanate from financial instability, as well as lack of knowledge regarding services and programmes for children with learning disabilities. This lack of knowledge on the part of participants could indicate poor policy education by policy implementers at grass-roots level. PMID:28951851

Remote supervision of medical training via videoconference in northern Australia: a qualitative study of the perspectives of supervisors and trainees

PubMed Central

Ray, Robin; Sabesan, Sabe

2015-01-01

Objectives Telemedicine has revolutionised the ability to provide care to patients, relieve professional isolation and provide guidance and supervision to junior medical officers in rural areas. This study evaluated the Townsville teleoncology supervision model for the training of junior medical officers in rural areas of North Queensland, Australia. Specifically, the perspectives of junior and senior medical officers were explored to identify recommendations for future implementation. Design A qualitative approach incorporating observation and semistructured interviews was used to collect data. Interviews were uploaded into NVivo 10 data management software. Template analysis enabled themes to be tested and developed through consensus between researchers. Setting One tertiary level and four secondary level healthcare centres in rural and regional Queensland, Australia. Participants 10 junior medical officers (Interns, Registrars) and 10 senior medical officers (Senior Medical Officers, Consultants) who participated in the Townsville teleoncology model of remote supervision via videoconference (TTMRS) were included in the study. Primary and Secondary outcome measures Perspectives on the telemedicine experience, technology, engagement, professional support, satisfaction and limitations were examined. Perspectives on topics raised by participants were also examined as the interviews progressed. Results Four major themes with several subthemes emerged from the data: learning environment, beginning the learning relationship, stimulus for learning and practicalities of remote supervision via videoconference. While some themes were consistent with the current literature, new themes like increased professional edge, recognising non-verbal cues and physical examination challenges were identified. Conclusions Remote supervision via videoconference provides readily available guidance to trainees supporting their delivery of appropriate care to patients. However, resources required for upskilling, training in the use of supervision via videoconference, administration issues and nursing support, as well as physical barriers to examinations, must be addressed to enable more efficient implementation. PMID:25795687

Residential immersive life skills programs for youth with disabilities: service providers' perceptions of change processes.

PubMed

King, Gillian; McPherson, Amy; Kingsnorth, Shauna; Stewart, Debra; Glencross-Eimantas, Tanya; Jones-Galley, Kimberlea; Morrison, Andrea; Isihi, Ana Maria; Gorter, Jan Willem

2015-05-01

Residential immersive life skills (RILS) programs are designed to equip youth with physical disabilities with the foundational life skills required to assume adult roles. The objective was to determine RILS service providers' perceptions of the active ingredients of the intervention change process. Thirty-seven service providers from various disciplines completed measures to assess expertise status and participated in qualitative interviews. Qualitative themes were derived, and similarities and differences in themes were identified for blinded groups of novices, intermediates, and experts. The three main themes, reflecting change processes, were: (a) creating a supportive program atmosphere with multiple opportunities for learning, (b) using strategies to support, encourage, and engage youth, and (c) intentionally fostering youth experiences of skill development, social interaction, and pride in accomplishment. In contrast to the novices, experts displayed a more holistic perspective and paid attention to higher-order issues such as providing opportunities and enabling youth. The findings indicate how RILS service providers work to create a program atmosphere and employ strategies to intentionally foster particular youth experiences. The findings explicate service providers' theories of practice, the intentional design of RILS program environments to bring about client change, and the value of service provider expertise. Implications for Rehabilitation Service providers of youth independence-oriented life skills programs can intentionally create a learning-oriented and supportive program atmosphere by using non-directive, coaching/guiding, and engagement strategies Youth experiences of skill development, shared experience with others, and pride in accomplishment can be cultivated by providing a range of learning opportunities, including choice making, problem-solving, and skill mastery Compared to more novice service providers, experts discussed managing the program conditions and context, creating opportunities for choice and new experiences, and adopting a facilitating and enabling role (coaching and capitalizing on teachable moments).

DAVE: A plug and play model for distributed multimedia application development

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

Mines, R.F.; Friesen, J.A.; Yang, C.L.

1994-07-01

This paper presents a model being used for the development of distributed multimedia applications. The Distributed Audio Video Environment (DAVE) was designed to support the development of a wide range of distributed applications. The implementation of this model is described. DAVE is unique in that it combines a simple ``plug and play`` programming interface, supports both centralized and fully distributed applications, provides device and media extensibility, promotes object reuseability, and supports interoperability and network independence. This model enables application developers to easily develop distributed multimedia applications and create reusable multimedia toolkits. DAVE was designed for developing applications such as videomore » conferencing, media archival, remote process control, and distance learning.« less

End-to-end deep neural network for optical inversion in quantitative photoacoustic imaging.

PubMed

Cai, Chuangjian; Deng, Kexin; Ma, Cheng; Luo, Jianwen

2018-06-15

An end-to-end deep neural network, ResU-net, is developed for quantitative photoacoustic imaging. A residual learning framework is used to facilitate optimization and to gain better accuracy from considerably increased network depth. The contracting and expanding paths enable ResU-net to extract comprehensive context information from multispectral initial pressure images and, subsequently, to infer a quantitative image of chromophore concentration or oxygen saturation (sO 2 ). According to our numerical experiments, the estimations of sO 2 and indocyanine green concentration are accurate and robust against variations in both optical property and object geometry. An extremely short reconstruction time of 22 ms is achieved.

Transportable Applications Environment Plus, Version 5.1

NASA Technical Reports Server (NTRS)

1994-01-01

Transportable Applications Environment Plus (TAE+) computer program providing integrated, portable programming environment for developing and running application programs based on interactive windows, text, and graphical objects. Enables both programmers and nonprogrammers to construct own custom application interfaces easily and to move interfaces and application programs to different computers. Used to define corporate user interface, with noticeable improvements in application developer's and end user's learning curves. Main components are; WorkBench, What You See Is What You Get (WYSIWYG) software tool for design and layout of user interface; and WPT (Window Programming Tools) Package, set of callable subroutines controlling user interface of application program. WorkBench and WPT's written in C++, and remaining code written in C.

Lessons Learned in Science Operations for Planetary Surface Exploration

NASA Technical Reports Server (NTRS)

Young, K. E.; Graff, T. G.; Reagan, M.; Coan, D.; Evans, C. A.; Bleacher, J. E.; Glotch, T. D.

2017-01-01

The six Apollo lunar surface missions represent the only occasions where we have conducted scientific operations on another planetary surface. While these six missions were successful in bringing back valuable geologic samples, technology advances in the subsequent forty years have enabled much higher resolution scientific activity in situ. Regardless of where astronauts next visit (whether it be back to the Moon or to Mars or a Near Earth Object), the science operations procedures completed during this mission will need to be refined and updated to reflect these advances. We have undertaken a series of operational tests in relevant field environments to understand how best to develop the new generation of science operations procedures for planetary surface exploration.

Learning Objects as Tools for Teaching Information Literacy Online: A Survey of Librarian Usage

ERIC Educational Resources Information Center

Mestre, Lori S.; Baures, Lisa; Niedbala, Mona; Bishop, Corinne; Cantrell, Sarah; Perez, Alice; Silfen, Kate

2011-01-01

Based on information gathered from two discussion sessions moderated by members of the Education and Behavioral Sciences Section's Online Learning Research Committee a survey was conducted to identify how librarians use course/learning management systems and learning objects to deliver instruction. Objectives of the study were to identify the…

Learning from Objects: A Future for 21st Century Urban Arts Education

ERIC Educational Resources Information Center

Lasky, Dorothea

2009-01-01

In this technological age, where mind and body are increasingly disconnected in the classroom, object-based learning--along with strong museum-school partnerships--provide many benefits for student learning. In this article, the author first outlines some of the special mind-body connections that object-based learning in museums affords learners…

Learning Grasp Context Distinctions that Generalize

NASA Technical Reports Server (NTRS)

Platt, Robert; Grupen, Roderic A.; Fagg, Andrew H.

2006-01-01

Control-based approaches to grasp synthesis create grasping behavior by sequencing and combining control primitives. In the absence of any other structure, these approaches must evaluate a large number of feasible control sequences as a function of object shape, object pose, and task. This work explores a new approach to grasp synthesis that limits consideration to variations on a generalized localize-reach-grasp control policy. A new learning algorithm, known as schema structured learning, is used to learn which instantiations of the generalized policy are most likely to lead to a successful grasp in different problem contexts. Two experiments are described where Dexter, a bimanual upper torso, learns to select an appropriate grasp strategy as a function of object eccentricity and orientation. In addition, it is shown that grasp skills learned in this way can generalize to new objects. Results are presented showing that after learning how to grasp a small, representative set of objects, the robot's performance quantitatively improves for similar objects that it has not experienced before.

Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

PubMed

Trelease, Robert B; Nieder, Gary L

2013-01-01

Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. © 2012 American Association of Anatomists.

Let’s Get Healthy! Health Awareness Through Public Participation in an Education and Research Exhibit

PubMed Central

Marriott, Lisa K.; Cameron, William E.; Purnell, Jonathan Q.; Cetola, Stephano; Ito, Matthew K.; Williams, Craig D.; Newcomb, Kenneth C.; Randall, Joan A.; Messenger, Wyatt B.; Lipus, Adam C.; Shannon, Jackilen

2013-01-01

Background Health information technology (HIT) offers a resource for public empowerment through tailored information. Objective Use interactive community health events to improve awareness of chronic disease risk factors while collecting data to improve health. Methods Let’s Get Healthy! is an education and research program in which participants visit interactive research stations to learn about their own health (diet, body composition, blood chemistry). HIT enables computerized data collection that presents participants with immediate results and tailored educational feedback. An anonymous wristband number links collected data in a population database. Results and Lessons Learned Communities tailor events to meet community health needs with volunteers trained to conduct research. Participants experience being a research participant and contribute to an anonymous population database for both traditional research purposes and open-source community use. Conclusions By integrating HIT with community involvement, health fairs become an interactive method for engaging communities in research and raising health awareness. PMID:22982846

Development of an Antimicrobial Stewardship-based Infectious Diseases Elective that Incorporates Human Patient Simulation Technology

PubMed Central

Meyer, Susan M.

2014-01-01

Objective. To design an elective for pharmacy students that facilitates antimicrobial stewardship awareness, knowledge, and skill development by solving clinical cases, using human patient simulation technology. Design. The elective was designed for PharmD students to describe principles and functions of stewardship programs, select, evaluate, refine, or redesign patient-specific plans for infectious diseases in the context of antimicrobial stewardship, and propose criteria and stewardship management strategies for an antimicrobial class at a health care institution. Teaching methods included active learning and lectures. Cases of bacterial endocarditis and cryptococcal meningitis were developed that incorporated human patient simulation technology. Assessment. Forty-five pharmacy students completed an antimicrobial stewardship elective between 2010 and 2013. Outcomes were assessed using student perceptions of and performance on rubric-graded assignments. Conclusion. A PharmD elective using active learning, including novel cases conducted with human patient simulation technology, enabled outcomes consistent with those desired of pharmacists assisting in antimicrobial stewardship programs. PMID:25386016

Atelier paludisme: an international malaria training course held in Madagascar.

PubMed

Domarle, Olivier; Randrianarivelojosia, Milijaona; Duchemin, Jean-Bernard; Robert, Vincent; Ariey, Frédéric

2008-05-09

The Atelier Paludisme (Malaria Workshop) is an international training course organized by the Institut Pasteur de Madagascar, which has been held annually for the past five years. The course was designed for both young and experienced researchers, as well as for healthcare professionals, mostly from malaria-endemic countries. Its objective is to provide participants with a broad knowledge of all features of malaria, to improve their skills in project management, to break geographical isolation by using the Internet as a source of documentary information. This six-week course makes use of concepts of andragogy and problem-based learning, i.e. a relationship between participants and tutors, which promotes a process of exchange rather than the simple transmission of knowledge, where participants have to search actively for information. This approach to training, combined with the wide background and experience of those involved, creates positive dynamics and enables participants to acquire new skills, develop their critical and analytical abilities. This paper describes the course and the lessons learned from its evaluation.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

PubMed

Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

2015-01-01

An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations

NASA Astrophysics Data System (ADS)

Bilionis, I.; Koutsourelakis, P. S.

2012-05-01

The present paper proposes an adaptive biasing potential technique for the computation of free energy landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy function, under the same objective of minimizing the Kullback-Leibler divergence between appropriately selected densities. It offers rigorous convergence diagnostics even though history dependent, non-Markovian dynamics are employed. It makes use of a greedy optimization scheme in order to obtain sparse representations of the free energy function which can be particularly useful in multidimensional cases. It employs embarrassingly parallelizable sampling schemes that are based on adaptive Sequential Monte Carlo and can be readily coupled with legacy molecular dynamics simulators. The sequential nature of the learning and sampling scheme enables the efficient calculation of free energy functions parametrized by the temperature. The characteristics and capabilities of the proposed method are demonstrated in three numerical examples.

Neural Network Training by Integration of Adjoint Systems of Equations Forward in Time

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)

1999-01-01

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically. it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved. but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. Tbc trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

Neural network training by integration of adjoint systems of equations forward in time

NASA Technical Reports Server (NTRS)

Toomarian, Nikzad (Inventor); Barhen, Jacob (Inventor)

1992-01-01

A method and apparatus for supervised neural learning of time dependent trajectories exploits the concepts of adjoint operators to enable computation of the gradient of an objective functional with respect to the various parameters of the network architecture in a highly efficient manner. Specifically, it combines the advantage of dramatic reductions in computational complexity inherent in adjoint methods with the ability to solve two adjoint systems of equations together forward in time. Not only is a large amount of computation and storage saved, but the handling of real-time applications becomes also possible. The invention has been applied it to two examples of representative complexity which have recently been analyzed in the open literature and demonstrated that a circular trajectory can be learned in approximately 200 iterations compared to the 12000 reported in the literature. A figure eight trajectory was achieved in under 500 iterations compared to 20000 previously required. The trajectories computed using our new method are much closer to the target trajectories than was reported in previous studies.

The company objects keep: Linking referents together during cross-situational word learning.

PubMed

Zettersten, Martin; Wojcik, Erica; Benitez, Viridiana L; Saffran, Jenny

2018-04-01

Learning the meanings of words involves not only linking individual words to referents but also building a network of connections among entities in the world, concepts, and words. Previous studies reveal that infants and adults track the statistical co-occurrence of labels and objects across multiple ambiguous training instances to learn words. However, it is less clear whether, given distributional or attentional cues, learners also encode associations amongst the novel objects. We investigated the consequences of two types of cues that highlighted object-object links in a cross-situational word learning task: distributional structure - how frequently the referents of novel words occurred together - and visual context - whether the referents were seen on matching backgrounds. Across three experiments, we found that in addition to learning novel words, adults formed connections between frequently co-occurring objects. These findings indicate that learners exploit statistical regularities to form multiple types of associations during word learning.

Generating Contextual Descriptions of Virtual Reality (VR) Spaces

NASA Astrophysics Data System (ADS)

Olson, D. M.; Zaman, C. H.; Sutherland, A.

2017-12-01

Virtual reality holds great potential for science communication, education, and research. However, interfaces for manipulating data and environments in virtual worlds are limited and idiosyncratic. Furthermore, speech and vision are the primary modalities by which humans collect information about the world, but the linking of visual and natural language domains is a relatively new pursuit in computer vision. Machine learning techniques have been shown to be effective at image and speech classification, as well as at describing images with language (Karpathy 2016), but have not yet been used to describe potential actions. We propose a technique for creating a library of possible context-specific actions associated with 3D objects in immersive virtual worlds based on a novel dataset generated natively in virtual reality containing speech, image, gaze, and acceleration data. We will discuss the design and execution of a user study in virtual reality that enabled the collection and the development of this dataset. We will also discuss the development of a hybrid machine learning algorithm linking vision data with environmental affordances in natural language. Our findings demonstrate that it is possible to develop a model which can generate interpretable verbal descriptions of possible actions associated with recognized 3D objects within immersive VR environments. This suggests promising applications for more intuitive user interfaces through voice interaction within 3D environments. It also demonstrates the potential to apply vast bodies of embodied and semantic knowledge to enrich user interaction within VR environments. This technology would allow for applications such as expert knowledge annotation of 3D environments, complex verbal data querying and object manipulation in virtual spaces, and computer-generated, dynamic 3D object affordances and functionality during simulations.

Mathematics and Experiential Learning--Are They Compatible?

ERIC Educational Resources Information Center

Davidovitch, Nitza; Yavich, Roman; Keller, Nelly

2014-01-01

In the process of experiential learning, students acquire skills and values as the consequence of a direct experience. Experiential learning draws on senses, emotions, and cognition and appeals to learners' entire being. Such learning, by nature, enables the development of a variety of capabilities, such as planning, teamwork, coping with…

Toward an Alternative Learning Environment Interface for Learning Management Systems

ERIC Educational Resources Information Center

Abdous, M'hammed

2013-01-01

An effective learning environment interface (LEI) is a means to enable students to focus on learning and to understand content, while establishing connections and relationships among course activities. Using this fundamental premise, we propose a flexible, user-centered, and seamless LEI which is intended to remediate the fragmented interface…

Transparency in Teaching: Faculty Share Data and Improve Students' Learning

ERIC Educational Resources Information Center

Winkelmes, Mary-Ann

2013-01-01

The Illinois Initiative on Transparency in Learning and Teaching is a grassroots assessment project designed to promote students' conscious understanding of how they learn and to enable faculty to gather, share, and promptly benefit from data about students' learning by coordinating their efforts across disciplines, institutions, and countries.…

The Effect of Professor's Attractiveness on Distance Learning Students

ERIC Educational Resources Information Center

Liu, Jeanny; Tomasi, Stella D.

2015-01-01

Technology enabled learning is becoming more popular and pervasive in education. While the effectiveness of distance learning versus traditional classroom education is strongly debated, human factors such as students' perception of their professors can influence their desire to learn. This research examines the perceptual effect of attractive…

Linking Learning Styles and Learning on Mobile Facebook

ERIC Educational Resources Information Center

Chen, Yu-ching

2015-01-01

With continued development of related technologies, Web 2.0 has become an important site of learning innovation. In particular, social networking sites such as Facebook, which have become popular, have the potential to function as an educational tool enabling peer feedback, interaction, and learning in a social context. Preparing appropriate…

Green School--A Service Learning Instrument to Enhance School Society Relation

ERIC Educational Resources Information Center

Madhusoodanan, Harikrishnan; Vitus, Geetha Janet

2014-01-01

A Green school is energy efficient, higher performing school that can be environmentally beneficial. Importance of Green school lies in the environmental friendliness value it upholds. Service learning has emanated out of philosophies of progressiveness and pragmatism. Service learning enables students to grow and learn through active…

An Investigation between Multiple Intelligences and Learning Styles

ERIC Educational Resources Information Center

Sener, Sabriye; Çokçaliskan, Ayten

2018-01-01

Exploring learning style and multiple intelligence type of learners can enable the students to identify their strengths and weaknesses and learn from them. It is also very important for teachers to understand their learners' learning styles and multiple intelligences since they can carefully identify their goals and design activities that can…

A Collaborative Model for Ubiquitous Learning Environments

ERIC Educational Resources Information Center

Barbosa, Jorge; Barbosa, Debora; Rabello, Solon

2016-01-01

Use of mobile devices and widespread adoption of wireless networks have enabled the emergence of Ubiquitous Computing. Application of this technology to improving education strategies gave rise to Ubiquitous e-Learning, also known as Ubiquitous Learning. There are several approaches to organizing ubiquitous learning environments, but most of them…

An Integrated Scale for Measuring an Organizational Learning System

ERIC Educational Resources Information Center

Jyothibabu, C.; Farooq, Ayesha; Pradhan, Bibhuti Bhusan

2010-01-01

Purpose: The purpose of this paper is to develop an integrated measurement scale for an organizational learning system by capturing the learning enablers, learning results and performance outcome in an organization. Design/methodology/approach: A new measurement scale was developed by integrating and modifying two existing scales, identified…

Teaching and Learning National Transformation Programme

ERIC Educational Resources Information Center

Browne, Liz

2006-01-01

This article reports on a research project undertaken on behalf of the Standards Unit to research the impact of the Teaching and Learning National Transformation Programme for the Learning and Skills sector. The transformational programme is best described as having three enablers, namely teaching and learning resources to support practitioners,…

Learning Strategy Training in English Teaching

ERIC Educational Resources Information Center

Arulselvi, M. Evangelin

2016-01-01

The fundamental task of schools is to endow students with strategies, which enable them to elaborate, transform, contrast and critically rebuild knowledge, that develops strategic knowledge. Learning strategy is the specific action to make the students better in learning a second language. Learning Strategy Training is based on problems the…

Connected and Ubiquitous: A Discussion of Two Theories That Impact Future Learning Applications

ERIC Educational Resources Information Center

Bair, Richard A.; Stafford, Timothy

2016-01-01

Mobile media break down traditional barriers that have defined learning in schools because they enable constant, personalized access to media. This information-rich environment could dramatically expand learning opportunities. This article identifies and discusses two instructional design theories for mobile learning including the major…

Engaging Professional Learning in Online Environments

ERIC Educational Resources Information Center

Bell, Amani; Morris, Gayle

2009-01-01

Much of what is regarded as effective professional learning is that which is situated, incorporates a social dimension and enables practitioners to converge in and around authentic practice. This article describes an inter-university online learning resource for tutors which is underpinned by a practice based approach to professional learning. The…

Exploring Moodle Functionality for Managing Open Distance Learning E-Assessments

ERIC Educational Resources Information Center

Koneru, Indira

2017-01-01

Current and emerging technologies enable Open Distance Learning (ODL) institutions integrate e-Learning in innovative ways and add value to the existing teaching-learning and assessment processes. ODL e-Assessment systems have evolved from Computer Assisted/Aided Assessment (CAA) systems through intelligent assessment and feedback systems.…

Users' Behavior towards Ubiquitous M-Learning

ERIC Educational Resources Information Center

Suki, Norazah Mohd; Suki, Norbayah Mohd

2011-01-01

Mobile technologies have enabled a new way of communicating, for whom mobile communications are part of normal daily interaction. This paper explores the proposed and verified Technology Acceptance Model (TAM) that can be employed to explain the acceptance of Mobile Learning (M-learning), an activity in which users access learning material with…

Collaborative E-Learning Using Semantic Course Blog

ERIC Educational Resources Information Center

Lu, Lai-Chen; Yeh, Ching-Long

2008-01-01

Collaborative e-learning delivers many enhancements to e-learning technology; it enables students to collaborate with each other and improves their learning efficiency. Semantic blog combines semantic Web and blog technology that users can import, export, view, navigate, and query the blog. We developed a semantic course blog for collaborative…

Effects of DDL Technology on Genre Learning

ERIC Educational Resources Information Center

Cotos, Elena; Link, Stephanie; Huffman, Sarah

2017-01-01

To better understand the promising effects of data-driven learning (DDL) on language learning processes and outcomes, this study explored DDL learning events enabled by the Research Writing Tutor (RWT), a web-based platform containing an English language corpus annotated to enhance rhetorical input, a concordancer that was searchable for…

Classifying K-12 Blended Learning

ERIC Educational Resources Information Center

Staker, Heather; Horn, Michael B.

2012-01-01

The growth of online learning in the K-12 sector is occurring both remotely through virtual schools and on campuses through blended learning. In emerging fields, definitions are important because they create a shared language that enables people to talk about the new phenomena. The blended-learning taxonomy and definitions presented in this paper…

Reclaiming Power and Identity: Marginalized Students' Experiences of Service-Learning

ERIC Educational Resources Information Center

Winans-Solis, Jaime

2014-01-01

This qualitative case study investigates how service-learning may enable self-direction and the development of a critical consciousness for marginalized high school students by exploring the dynamics of service-learning through a theoretical framework of critical theory. Service-learning is theorized to counter the oppressive nature of schooling…

The extinction context enables extinction performance after a change in context

PubMed Central

Nelson, James Byron; Gregory, Pamela; Sanjuan, Maria del Carmen

2012-01-01

One experiment with human participants determined the extent to which recovery of extinguished responding with a context switch was due to a failure to retrieve contextually-controlled learning, or some other process such as participants learning that context changes signal reversals in the meaning of stimulus – outcome relationships. In a video game, participants learned to suppress mouse clicking in the presence of a stimulus that predicted an attack. Then, that stimulus underwent extinction in a different context (environment within the game). Following extinction, suppression was recovered and then extinguished again during testing in the conditioning context. In a final test, participants that were tested in the context where extinction first took place showed less of a recovery than those tested in a neutral context, but they showed a recovery of suppression nevertheless. A change in context tended to cause a change in the meaning of the stimulus, leading to recovery in both the neutral and extinction contexts. The extinction context attenuated that recovery, perhaps by enabling retrieval of the learning that took place in extinction. Recovery outside an extinction context is due to a failure of the context to enable the learning acquired during extinction, but only in part. PMID:22521549