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Sample records for semantic concept learning

  1. A robotic framework for semantic concept learning.

    SciTech Connect

    Squire, Kevin M.; Levinson, Stephen E.; Xavier, Patrick Gordon

    2004-09-01

    This report describes work carried out under a Sandia National Laboratories Excellence in Engineering Fellowship in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. Our research group (at UIUC) is developing a intelligent robot, and attempting to teach it language. While there are many aspects of this research, for the purposes of this report the most important are the following ideas. Language is primarily based on semantics, not syntax. To truly learn meaning, the language engine must be part of an embodied intelligent system, one capable of using associative learning to form concepts from the perception of experiences in the world, and further capable of manipulating those concepts symbolically. In the work described here, we explore the use of hidden Markov models (HMMs) in this capacity. HMMs are capable of automatically learning and extracting the underlying structure of continuous-valued inputs and representing that structure in the states of the model. These states can then be treated as symbolic representations of the inputs. We describe a composite model consisting of a cascade of HMMs that can be embedded in a small mobile robot and used to learn correlations among sensory inputs to create symbolic concepts. These symbols can then be manipulated linguistically and used for decision making. This is the project final report for the University Collaboration LDRD project, 'A Robotic Framework for Semantic Concept Learning'.

  2. The Semantic Learning Organization

    ERIC Educational Resources Information Center

    Sicilia, Miguel-Angel; Lytras, Miltiadis D.

    2005-01-01

    Purpose: The aim of this paper is introducing the concept of a "semantic learning organization" (SLO) as an extension of the concept of "learning organization" in the technological domain. Design/methodology/approach: The paper takes existing definitions and conceptualizations of both learning organizations and Semantic Web technology to develop…

  3. Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments

    PubMed Central

    Pereira, Francisco; Botvinick, Matthew; Detre, Greg

    2012-01-01

    In this paper we show that a corpus of a few thousand Wikipedia articles about concrete or visualizable concepts can be used to produce a low-dimensional semantic feature representation of those concepts. The purpose of such a representation is to serve as a model of the mental context of a subject during functional magnetic resonance imaging (fMRI) experiments. A recent study [19] showed that it was possible to predict fMRI data acquired while subjects thought about a concrete concept, given a representation of those concepts in terms of semantic features obtained with human supervision. We use topic models on our corpus to learn semantic features from text in an unsupervised manner, and show that those features can outperform those in [19] in demanding 12-way and 60-way classification tasks. We also show that these features can be used to uncover similarity relations in brain activation for different concepts which parallel those relations in behavioral data from human subjects. PMID:23243317

  4. Learning Semantic Query Suggestions

    NASA Astrophysics Data System (ADS)

    Meij, Edgar; Bron, Marc; Hollink, Laura; Huurnink, Bouke; de Rijke, Maarten

    An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive queries that are able to return more useful search results than the original query and most popular search engines provide facilities that let users complete, specify, or reformulate their queries. We study the problem of semantic query suggestion, a special type of query transformation based on identifying semantic concepts contained in user queries. We use a feature-based approach in conjunction with supervised machine learning, augmenting term-based features with search history-based and concept-specific features. We apply our method to the task of linking queries from real-world query logs (the transaction logs of the Netherlands Institute for Sound and Vision) to the DBpedia knowledge base. We evaluate the utility of different machine learning algorithms, features, and feature types in identifying semantic concepts using a manually developed test bed and show significant improvements over an already high baseline. The resources developed for this paper, i.e., queries, human assessments, and extracted features, are available for download.

  5. Semantic Categories and Context in L2 Vocabulary Learning

    ERIC Educational Resources Information Center

    Bolger, Patrick; Zapata, Gabriela

    2011-01-01

    This article extends recent findings that presenting semantically related vocabulary simultaneously inhibits learning. It does so by adding story contexts. Participants learned 32 new labels for known concepts from four different semantic categories in stories that were either semantically related (one category per story) or semantically unrelated…

  6. Enhancing clinical concept extraction with distributional semantics

    PubMed Central

    Cohen, Trevor; Wu, Stephen; Gonzalez, Graciela

    2011-01-01

    Extracting concepts (such as drugs, symptoms, and diagnoses) from clinical narratives constitutes a basic enabling technology to unlock the knowledge within and support more advanced reasoning applications such as diagnosis explanation, disease progression modeling, and intelligent analysis of the effectiveness of treatment. The recent release of annotated training sets of de-identified clinical narratives has contributed to the development and refinement of concept extraction methods. However, as the annotation process is labor-intensive, training data are necessarily limited in the concepts and concept patterns covered, which impacts the performance of supervised machine learning applications trained with these data. This paper proposes an approach to minimize this limitation by combining supervised machine learning with empirical learning of semantic relatedness from the distribution of the relevant words in additional unannotated text. The approach uses a sequential discriminative classifier (Conditional Random Fields) to extract the mentions of medical problems, treatments and tests from clinical narratives. It takes advantage of all Medline abstracts indexed as being of the publication type “clinical trials” to estimate the relatedness between words in the i2b2/VA training and testing corpora. In addition to the traditional features such as dictionary matching, pattern matching and part-of-speech tags, we also used as a feature words that appear in similar contexts to the word in question (that is, words that have a similar vector representation measured with the commonly used cosine metric, where vector representations are derived using methods of distributional semantics). To the best of our knowledge, this is the first effort exploring the use of distributional semantics, the semantics derived empirically from unannotated text often using vector space models, for a sequence classification task such as concept extraction. Therefore, we first

  7. E-Learning for Depth in the Semantic Web

    ERIC Educational Resources Information Center

    Shafrir, Uri; Etkind, Masha

    2006-01-01

    In this paper, we describe concept parsing algorithms, a novel semantic analysis methodology at the core of a new pedagogy that focuses learners attention on deep comprehension of the conceptual content of learned material. Two new e-learning tools are described in some detail: interactive concept discovery learning and meaning equivalence…

  8. Shared Features Dominate Semantic Richness Effects for Concrete Concepts

    ERIC Educational Resources Information Center

    Grondin, Ray; Lupker, Stephen J.; McRae, Ken

    2009-01-01

    When asked to list semantic features for concrete concepts, participants list many features for some concepts and few for others. Concepts with many semantic features are processed faster in lexical and semantic decision tasks [Pexman, P. M., Lupker, S. J., & Hino, Y. (2002). "The impact of feedback semantics in visual word recognition:…

  9. Implicit Learning of Semantic Preferences of Verbs

    ERIC Educational Resources Information Center

    Paciorek, Albertyna; Williams, John N.

    2015-01-01

    Previous studies of semantic implicit learning in language have only examined learning grammatical form-meaning connections in which learning could have been supported by prior linguistic knowledge. In this study we target the domain of verb meaning, specifically semantic preferences regarding novel verbs (e.g., the preference for a novel verb to…

  10. LEARNING SEMANTICS-ENHANCED LANGUAGE MODELS APPLIED TO UNSUEPRVISED WSD

    SciTech Connect

    VERSPOOR, KARIN; LIN, SHOU-DE

    2007-01-29

    An N-gram language model aims at capturing statistical syntactic word order information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can be learned without annotated training examples. Finally, we report on a case study showing how the semantics-enhanced language model can be applied to unsupervised word sense disambiguation with promising results.

  11. Representations for Semantic Learning Webs: Semantic Web Technology in Learning Support

    ERIC Educational Resources Information Center

    Dzbor, M.; Stutt, A.; Motta, E.; Collins, T.

    2007-01-01

    Recent work on applying semantic technologies to learning has concentrated on providing novel means of accessing and making use of learning objects. However, this is unnecessarily limiting: semantic technologies will make it possible to develop a range of educational Semantic Web services, such as interpretation, structure-visualization, support…

  12. Modeling Spatial Dependencies and Semantic Concepts in Data Mining

    SciTech Connect

    Vatsavai, Raju

    2012-01-01

    Data mining is the process of discovering new patterns and relationships in large datasets. However, several studies have shown that general data mining techniques often fail to extract meaningful patterns and relationships from the spatial data owing to the violation of fundamental geospatial principles. In this tutorial, we introduce basic principles behind explicit modeling of spatial and semantic concepts in data mining. In particular, we focus on modeling these concepts in the widely used classification, clustering, and prediction algorithms. Classification is the process of learning a structure or model (from user given inputs) and applying the known model to the new data. Clustering is the process of discovering groups and structures in the data that are ``similar,'' without applying any known structures in the data. Prediction is the process of finding a function that models (explains) the data with least error. One common assumption among all these methods is that the data is independent and identically distributed. Such assumptions do not hold well in spatial data, where spatial dependency and spatial heterogeneity are a norm. In addition, spatial semantics are often ignored by the data mining algorithms. In this tutorial we cover recent advances in explicitly modeling of spatial dependencies and semantic concepts in data mining.

  13. Learning the Semantics of Structured Data Sources

    ERIC Educational Resources Information Center

    Taheriyan, Mohsen

    2015-01-01

    Information sources such as relational databases, spreadsheets, XML, JSON, and Web APIs contain a tremendous amount of structured data, however, they rarely provide a semantic model to describe their contents. Semantic models of data sources capture the intended meaning of data sources by mapping them to the concepts and relationships defined by a…

  14. Semantic Learning Modifies Perceptual Face Processing

    ERIC Educational Resources Information Center

    Heisz, Jennifer J.; Shedden, Judith M.

    2009-01-01

    Face processing changes when a face is learned with personally relevant information. In a five-day learning paradigm, faces were presented with rich semantic stories that conveyed personal information about the faces. Event-related potentials were recorded before and after learning during a passive viewing task. When faces were novel, we observed…

  15. Semantic Generalization in Implicit Language Learning

    ERIC Educational Resources Information Center

    Paciorek, Albertyna; Williams, John N.

    2015-01-01

    Despite many years of investigation into implicit learning in nonlinguistic domains, the potential for implicit learning to deliver the kinds of generalizations that underlie natural language competence remains unclear. In a series of experiments, we investigated implicit learning of the semantic preferences of novel verbs, specifically, whether…

  16. Learning semantic and visual similarity for endomicroscopy video retrieval.

    PubMed

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

    2012-06-01

    Content-based image retrieval (CBIR) is a valuable computer vision technique which is increasingly being applied in the medical community for diagnosis support. However, traditional CBIR systems only deliver visual outputs, i.e., images having a similar appearance to the query, which is not directly interpretable by the physicians. Our objective is to provide a system for endomicroscopy video retrieval which delivers both visual and semantic outputs that are consistent with each other. In a previous study, we developed an adapted bag-of-visual-words method for endomicroscopy retrieval, called "Dense-Sift," that computes a visual signature for each video. In this paper, we present a novel approach to complement visual similarity learning with semantic knowledge extraction, in the field of in vivo endomicroscopy. We first leverage a semantic ground truth based on eight binary concepts, in order to transform these visual signatures into semantic signatures that reflect how much the presence of each semantic concept is expressed by the visual words describing the videos. Using cross-validation, we demonstrate that, in terms of semantic detection, our intuitive Fisher-based method transforming visual-word histograms into semantic estimations outperforms support vector machine (SVM) methods with statistical significance. In a second step, we propose to improve retrieval relevance by learning an adjusted similarity distance from a perceived similarity ground truth. As a result, our distance learning method allows to statistically improve the correlation with the perceived similarity. We also demonstrate that, in terms of perceived similarity, the recall performance of the semantic signatures is close to that of visual signatures and significantly better than those of several state-of-the-art CBIR methods. The semantic signatures are thus able to communicate high-level medical knowledge while being consistent with the low-level visual signatures and much shorter than them

  17. Semantic E-Learning: Synthesising Fantasies

    ERIC Educational Resources Information Center

    Lytras, Miltiadis; Naeve, Ambjorn

    2006-01-01

    When the subject of scientific analysis is learning, the research needs to be anchored in various nonmonolithic pillars. Several disciplines require a common ground of convergence. An objective observer of the domain can easily conclude that semantic e-learning brings together the three different worlds of learners, pedagogues and technologists.…

  18. How Do Korsakoff Patients Learn New Concepts?

    ERIC Educational Resources Information Center

    Pitel, Anne Lise; Beaunieux, Helene; Guillery-Girard, Berengere; Witkowski, Thomas; de la Sayette, Vincent; Viader, Fausto; Desgranges, Beatrice; Eustache, Francis

    2009-01-01

    The goal of the present investigation was to assess semantic learning in Korsakoff patients (KS), compared with uncomplicated alcoholics (AL) and control subjects (CS), taking the nature of the information to-be-learned and the episodic memory profiles of the three groups into account. Ten new complex concepts, each illustrated by a photo and…

  19. 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…

  20. An Intelligent Semantic E-Learning Framework Using Context-Aware Semantic Web Technologies

    ERIC Educational Resources Information Center

    Huang, Weihong; Webster, David; Wood, Dawn; Ishaya, Tanko

    2006-01-01

    Recent developments of e-learning specifications such as Learning Object Metadata (LOM), Sharable Content Object Reference Model (SCORM), Learning Design and other pedagogy research in semantic e-learning have shown a trend of applying innovative computational techniques, especially Semantic Web technologies, to promote existing content-focused…

  1. A Bayesian generative model for learning semantic hierarchies

    PubMed Central

    Mittelman, Roni; Sun, Min; Kuipers, Benjamin; Savarese, Silvio

    2014-01-01

    Building fine-grained visual recognition systems that are capable of recognizing tens of thousands of categories, has received much attention in recent years. The well known semantic hierarchical structure of categories and concepts, has been shown to provide a key prior which allows for optimal predictions. The hierarchical organization of various domains and concepts has been subject to extensive research, and led to the development of the WordNet domains hierarchy (Fellbaum, 1998), which was also used to organize the images in the ImageNet (Deng et al., 2009) dataset, in which the category count approaches the human capacity. Still, for the human visual system, the form of the hierarchy must be discovered with minimal use of supervision or innate knowledge. In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. Our model is motivated by the super-subordinate organization of domain labels and concepts that characterizes WordNet, and accounts for several important challenges: maintaining context information when progressing deeper into the hierarchy, learning a coherent semantic concept for each node, and modeling uncertainty in the perception process. PMID:24904452

  2. Learning contextualized semantics from co-occurring terms via a Siamese architecture.

    PubMed

    Sandouk, Ubai; Chen, Ke

    2016-04-01

    One of the biggest challenges in Multimedia information retrieval and understanding is to bridge the semantic gap by properly modeling concept semantics in context. The presence of out of vocabulary (OOV) concepts exacerbates this difficulty. To address the semantic gap issues, we formulate a problem on learning contextualized semantics from descriptive terms and propose a novel Siamese architecture to model the contextualized semantics from descriptive terms. By means of pattern aggregation and probabilistic topic models, our Siamese architecture captures contextualized semantics from the co-occurring descriptive terms via unsupervised learning, which leads to a concept embedding space of the terms in context. Furthermore, the co-occurring OOV concepts can be easily represented in the learnt concept embedding space. The main properties of the concept embedding space are demonstrated via visualization. Using various settings in semantic priming, we have carried out a thorough evaluation by comparing our approach to a number of state-of-the-art methods on six annotation corpora in different domains, i.e., MagTag5K, CAL500 and Million Song Dataset in the music domain as well as Corel5K, LabelMe and SUNDatabase in the image domain. Experimental results on semantic priming suggest that our approach outperforms those state-of-the-art methods considerably in various aspects. PMID:26874967

  3. Shared Features Dominate Semantic Richness Effects for Concrete Concepts

    PubMed Central

    Grondin, Ray; Lupker, Stephen J.; McRae, Ken

    2009-01-01

    When asked to list semantic features for concrete concepts, participants list many features for some concepts and few for others. Concepts with many semantic features are processed faster in lexical and semantic decision tasks (Pexman, Holyk, & Monfils, 2003; Pexman, Lupker, & Hino, 2002). Using both lexical and concreteness decision tasks, we provided further insight into these number-of-features (NoF) effects. We began by replicating the effect using a larger and better controlled set of items. We then investigated the relationship between NoF and feature distinctiveness and found that features shared by numerous concrete concepts such as facilitate decisions to a greater extent than do distinctive features such as . Finally, we showed that NoF effects are carried by shared visual form and surface, encyclopedic, tactile, and taste knowledge. We propose a decision-making account of these results, rather than one based on the computation of word meaning. PMID:20046224

  4. Semantic generalization in implicit language learning.

    PubMed

    Paciorek, Albertyna; Williams, John N

    2015-07-01

    Despite many years of investigation into implicit learning in nonlinguistic domains, the potential for implicit learning to deliver the kinds of generalizations that underlie natural language competence remains unclear. In a series of experiments, we investigated implicit learning of the semantic preferences of novel verbs, specifically, whether they collocate with abstract or concrete nouns. After reading sentences containing the verbs, participants were required to judge the familiarity of pairs of novel verbs and nouns and to indicate their confidence or the basis of their judgment (i.e., guess, intuition, memory). Although all of the words had occurred in the texts, none of the critical items had actually occurred together. However, endorsement rates were significantly higher for pairs that respected the semantic preference rules than those that did not. Through analysis of subjective measures and verbal report, we argue that, for the majority of participants, this effect was based on unconscious knowledge. We argue that implicit learning of the kind of generalizations underlying semantic preferences is possible even after limited exposure. PMID:25581225

  5. Semantic Mappings and Locality of Nursing Diagnostic Concepts in UMLS

    PubMed Central

    Kim, Tae Youn; Coenen, Amy; Hardiker, Nicholas

    2011-01-01

    One solution for enhancing the interoperability between nursing information systems, given the availability of multiple nursing terminologies, is to cross-map existing nursing concepts. The Unified Medical Language System (UMLS) developed and distributed by the National Library of Medicine (NLM) is a knowledge resource containing cross-mappings of various terminologies in a unified framework. While the knowledge resource has been available for the last two decades, little research on the representation of nursing terminologies in UMLS has been conducted. As a first step, UMLS semantic mappings and concept locality were examined for nursing diagnostic concepts or problems selected from three terminologies (i.e., CCC, ICNP, and NANDA-I) along with corresponding SNOMED CT concepts. The evaluation of UMLS semantic mappings was conducted by measuring the proportion of concordance between UMLS and human expert mappings. The semantic locality of nursing diagnostic concepts was assessed by examining the associations of select concepts and the placement of the nursing concepts on the Semantic Network and Group. The study found that the UMLS mappings of CCC and NANDA-I concepts to SNOMED CT were highly concordant to expert mappings. The level of concordance in mappings of ICNP to SNOMED CT, CCC and NANDA-I within UMLS was relatively low, indicating the need for further research and development. Likewise, the semantic locality of ICNP concepts could be further improved. Various stakeholders need to collaborate to enhance the NLM knowledge resource and the interoperability of nursing data within the discipline as well as across health-related disciplines. PMID:21951759

  6. Measure Transformer Semantics for Bayesian Machine Learning

    NASA Astrophysics Data System (ADS)

    Borgström, Johannes; Gordon, Andrew D.; Greenberg, Michael; Margetson, James; van Gael, Jurgen

    The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (that is, a prior distribution) and a set of observations of variables. There is a trend in machine learning towards expressing Bayesian models as probabilistic programs. As a foundation for this kind of programming, we propose a core functional calculus with primitives for sampling prior distributions and observing variables. We define combinators for measure transformers, based on theorems in measure theory, and use these to give a rigorous semantics to our core calculus. The original features of our semantics include its support for discrete, continuous, and hybrid measures, and, in particular, for observations of zero-probability events. We compile our core language to a small imperative language that has a straightforward semantics via factor graphs, data structures that enable many efficient inference algorithms. We use an existing inference engine for efficient approximate inference of posterior marginal distributions, treating thousands of observations per second for large instances of realistic models.

  7. Case-Based Learning, Pedagogical Innovation, and Semantic Web Technologies

    ERIC Educational Resources Information Center

    Martinez-Garcia, A.; Morris, S.; Tscholl, M.; Tracy, F.; Carmichael, P.

    2012-01-01

    This paper explores the potential of Semantic Web technologies to support teaching and learning in a variety of higher education settings in which some form of case-based learning is the pedagogy of choice. It draws on the empirical work of a major three year research and development project in the United Kingdom: "Ensemble: Semantic Technologies…

  8. Learning semantic histopathological representation for basal cell carcinoma classification

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

    2013-03-01

    Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

  9. Improved verbal learning in the semantic variant of primary progressive aphasia when using semantic cues.

    PubMed

    Milano, Nicholas J; Williamson, John B; Heilman, Kenneth M

    2015-01-01

    The semantic variant of primary progressive aphasia (PPA-S) is characterized by impairments in confrontation naming and single word comprehension. Although episodic memory may be relatively spared, there can be impairment in verbal learning tasks. We report a patient with PPA-S and impaired verbal learning who was tested to learn if when provided with semantic categories, her learning would improve. A 70-year-old right-handed woman with a 2-year history of progressive difficulties with word finding, naming, and memory was tested for language and memory deficits using the Hopkins Verbal Learning Test-Revised (HVLT-R). She was then retested with the HVLT-R after being provided with the three semantic categories to which these words belonged. Confrontation naming was impaired on the Boston Naming Test. Sentence repetition was normal. Comprehension testing with word picture matching and sentence comprehension was normal. On a test of semantic associations, Pyramids and Palm Trees, she was impaired. She was also impaired on tests of verbal learning (HVLT-R) (total: 13) but not recall. When a different version of the HVLT-R was given with the semantic categories of the words given beforehand, her scores improved (total: 26). This patient with PPA-S had an impairment of verbal learning, but not delayed recall. When given a semantic category cue beforehand, her verbal learning performance improved. This observation suggests that this patient did not spontaneously use semantic encoding. Using a semantic cueing strategy may help other patients with PPA-S improve their capacity for verbal learning. PMID:24611440

  10. E-Learning System Overview Based on Semantic Web

    ERIC Educational Resources Information Center

    Alsultanny, Yas A.

    2006-01-01

    The challenge of the semantic web is the provision of distributed information with well-defined meaning, understandable for different parties. e-Learning is efficient task relevant and just-in-time learning grown from the learning requirements of the new dynamically changing, distributed business world. In this paper we design an e-Learning system…

  11. Learning Statistical Concepts

    ERIC Educational Resources Information Center

    Akram, Muhammad; Siddiqui, Asim Jamal; Yasmeen, Farah

    2004-01-01

    In order to learn the concept of statistical techniques one needs to run real experiments that generate reliable data. In practice, the data from some well-defined process or system is very costly and time consuming. It is difficult to run real experiments during the teaching period in the university. To overcome these difficulties, statisticians…

  12. Concept-Based Learning

    ERIC Educational Resources Information Center

    Schill, Bethany; Howell, Linda

    2011-01-01

    A major part of developing concept-based instruction is the use of an overarching idea to provide a conceptual lens through which students view the content of a particular subject. By using a conceptual lens to focus learning, students think at a much deeper level about the content and its facts (Erickson 2007). Therefore, the authors collaborated…

  13. Learning from Animated Concept Maps with Concurrent Audio Narration

    ERIC Educational Resources Information Center

    Nesbit, John C.; Adesope, Olusola O.

    2011-01-01

    An animated concept map is a presentation of a network diagram in which nodes and links are sequentially added or modified. An experiment compared learning from animated concept maps and text by randomly assigning 133 undergraduates to study 1 of 4 narrated animations presenting semantically equivalent information accompanied by identical audio…

  14. Competencies in Organizational E-Learning: Concepts and Tools

    ERIC Educational Resources Information Center

    Sicilia, Miguel-Angel, Ed.

    2007-01-01

    "Competencies in Organizational E-Learning: Concepts and Tools" provides a comprehensive view of the way competencies can be used to drive organizational e-learning, including the main conceptual elements, competency gap analysis, advanced related computing topics, the application of semantic Web technologies, and the integration of competencies…

  15. RuleML-Based Learning Object Interoperability on the Semantic Web

    ERIC Educational Resources Information Center

    Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

    2008-01-01

    Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

  16. Semantic Network Analysis of Earth ScienceTextbooks Focus on Learning Objectives in Korea

    NASA Astrophysics Data System (ADS)

    Chung, Duk Ho

    2014-05-01

    The purpose of this study was to investigate how congruently the learning objectives of Earth Science textbooks match the 2009 revised Earth Science curriculum in Korea. For this purpose, we classified the learning objectives of curriculum and textbooks were into three factors including ability, cross-cutting concepts, and behavioral verbs. The text data were analyzed using the semantic network analysis method. The results are as follows. The learning objectives of textbooks with regard to ability factors mainly emphasized the cognitive and affective domain. In addition, the ability of inquiry performance was emphasized in the learning objective of the curriculum. The textbooks used various sub-frame of cross-cutting concepts in comparison with the curriculum. Both textbooks and curriculum used the term 'comprehension' the most as behavioral verbs. However, most behavioral verbs just remained at the level of cognitive system. Keywords: curriculum, textbook, learning objectives, semantic network analysis

  17. Social Concepts and Judgments: A Semantic Differential Analysis of the Concepts Feminist, Man, and Woman

    ERIC Educational Resources Information Center

    Pierce, W. David; Sydie, R. A.; Stratkotter, Rainer

    2003-01-01

    Male and female participants (N = 274) made judgments about the social concepts of "feminist," "man," and "woman" on 63 semantic differential items. Factor analysis identified three basic dimensions termed evaluative, potency, and activity as well as two secondary factors called expressiveness and sexuality. Results for the evaluative dimension…

  18. Semantic Priming for Coordinate Distant Concepts in Alzheimer's Disease Patients

    ERIC Educational Resources Information Center

    Perri, R.; Zannino, G. D.; Caltagirone, C.; Carlesimo, G. A.

    2011-01-01

    Semantic priming paradigms have been used to investigate semantic knowledge in patients with Alzheimer's disease (AD). While priming effects produced by prime-target pairs with associative relatedness reflect processes at both lexical and semantic levels, priming effects produced by words that are semantically related but not associated should…

  19. Semi-Supervised Learning to Identify UMLS Semantic Relations

    PubMed Central

    Luo, Yuan; Uzuner, Ozlem

    2014-01-01

    The UMLS Semantic Network is constructed by experts and requires periodic expert review to update. We propose and implement a semi-supervised approach for automatically identifying UMLS semantic relations from narrative text in PubMed. Our method analyzes biomedical narrative text to collect semantic entity pairs, and extracts multiple semantic, syntactic and orthographic features for the collected pairs. We experiment with seeded k-means clustering with various distance metrics. We create and annotate a ground truth corpus according to the top two levels of the UMLS semantic relation hierarchy. We evaluate our system on this corpus and characterize the learning curves of different clustering configuration. Using KL divergence consistently performs the best on the held-out test data. With full seeding, we obtain macro-averaged F-measures above 70% for clustering the top level UMLS relations (2-way), and above 50% for clustering the second level relations (7-way). PMID:25954580

  20. Supervised learning of semantic classes for image annotation and retrieval.

    PubMed

    Carneiro, Gustavo; Chan, Antoni B; Moreno, Pedro J; Vasconcelos, Nuno

    2007-03-01

    A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as the group of database images labeled with a common semantic label. It is shown that, by establishing this one-to-one correspondence between semantic labels and semantic classes, a minimum probability of error annotation and retrieval are feasible with algorithms that are 1) conceptually simple, 2) computationally efficient, and 3) do not require prior semantic segmentation of training images. In particular, images are represented as bags of localized feature vectors, a mixture density estimated for each image, and the mixtures associated with all images annotated with a common semantic label pooled into a density estimate for the corresponding semantic class. This pooling is justified by a multiple instance learning argument and performed efficiently with a hierarchical extension of expectation-maximization. The benefits of the supervised formulation over the more complex, and currently popular, joint modeling of semantic label and visual feature distributions are illustrated through theoretical arguments and extensive experiments. The supervised formulation is shown to achieve higher accuracy than various previously published methods at a fraction of their computational cost. Finally, the proposed method is shown to be fairly robust to parameter tuning. PMID:17224611

  1. Learning document semantic representation with hybrid deep belief network.

    PubMed

    Yan, Yan; Yin, Xu-Cheng; Li, Sujian; Yang, Mingyuan; Hao, Hong-Wei

    2015-01-01

    High-level abstraction, for example, semantic representation, is vital for document classification and retrieval. However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural language processing. In this paper, we propose a new Hybrid Deep Belief Network (HDBN) which uses Deep Boltzmann Machine (DBM) on the lower layers together with Deep Belief Network (DBN) on the upper layers. The advantage of DBM is that it employs undirected connection when training weight parameters which can be used to sample the states of nodes on each layer more successfully and it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance. PMID:25878657

  2. Learning Document Semantic Representation with Hybrid Deep Belief Network

    PubMed Central

    Yan, Yan; Yin, Xu-Cheng; Li, Sujian; Yang, Mingyuan; Hao, Hong-Wei

    2015-01-01

    High-level abstraction, for example, semantic representation, is vital for document classification and retrieval. However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural language processing. In this paper, we propose a new Hybrid Deep Belief Network (HDBN) which uses Deep Boltzmann Machine (DBM) on the lower layers together with Deep Belief Network (DBN) on the upper layers. The advantage of DBM is that it employs undirected connection when training weight parameters which can be used to sample the states of nodes on each layer more successfully and it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance. PMID:25878657

  3. Concept Representation Reflects Multimodal Abstraction: A Framework for Embodied Semantics.

    PubMed

    Fernandino, Leonardo; Binder, Jeffrey R; Desai, Rutvik H; Pendl, Suzanne L; Humphries, Colin J; Gross, William L; Conant, Lisa L; Seidenberg, Mark S

    2016-05-01

    Recent research indicates that sensory and motor cortical areas play a significant role in the neural representation of concepts. However, little is known about the overall architecture of this representational system, including the role played by higher level areas that integrate different types of sensory and motor information. The present study addressed this issue by investigating the simultaneous contributions of multiple sensory-motor modalities to semantic word processing. With a multivariate fMRI design, we examined activation associated with 5 sensory-motor attributes--color, shape, visual motion, sound, and manipulation--for 900 words. Regions responsive to each attribute were identified using independent ratings of the attributes' relevance to the meaning of each word. The results indicate that these aspects of conceptual knowledge are encoded in multimodal and higher level unimodal areas involved in processing the corresponding types of information during perception and action, in agreement with embodied theories of semantics. They also reveal a hierarchical system of abstracted sensory-motor representations incorporating a major division between object interaction and object perception processes. PMID:25750259

  4. Verbal Memory and Semantic Organization of Children with Learning Disabilities

    ERIC Educational Resources Information Center

    Polychroni, Fotini; Economou, Alexandra; Printezi, Anna; Koutlidi, Ifigeneia

    2011-01-01

    The present study examined the verbal learning performance and the semantic organization used by Greek reading-disabled readers as compared to a control group using a list-learning task. The sample consisted of 45 elementary school children with reading difficulties and 45 comparison children matched for age and gender. Tests of reading ability,…

  5. Concept Learning through Image Processing.

    ERIC Educational Resources Information Center

    Cifuentes, Lauren; Yi-Chuan, Jane Hsieh

    This study explored computer-based image processing as a study strategy for middle school students' science concept learning. Specifically, the research examined the effects of computer graphics generation on science concept learning and the impact of using computer graphics to show interrelationships among concepts during study time. The 87…

  6. Orthographic Learning in Learning to Spell: The Roles of Semantics and Type of Practice

    ERIC Educational Resources Information Center

    Ouellette, Gene

    2010-01-01

    This study investigated the relevance of type of practice and presence of semantic representation for orthographic learning in learning to spell. A total of 36 students in Grade 2 (mean age = 7 years 10 months) were exposed to 10 novel nonwords, 5 of which were paired with semantic information. Half of the participants practiced reading these new…

  7. How Visual and Semantic Information Influence Learning in Familiar Contexts

    ERIC Educational Resources Information Center

    Goujon, Annabelle; Brockmole, James R.; Ehinger, Krista A.

    2012-01-01

    Previous research using the contextual cuing paradigm has revealed both quantitative and qualitative differences in learning depending on whether repeated contexts are defined by letter arrays or real-world scenes. To clarify the relative contributions of visual features and semantic information likely to account for such differences, the typical…

  8. Semantic Services in e-Learning: An Argumentation Case Study

    ERIC Educational Resources Information Center

    Moreale, Emanuela; Vargas-Vera, Maria

    2004-01-01

    This paper outlines an e-Learning services architecture offering semantic-based services to students and tutors, in particular ways to browse and obtain information through web services. Services could include registration, authentication, tutoring systems, smart question answering for students' queries, automated marking systems and a student…

  9. Does Learning to Count Involve a Semantic Induction?

    ERIC Educational Resources Information Center

    Davidson, Kathryn; Eng, Kortney; Barner, David

    2012-01-01

    We tested the hypothesis that, when children learn to correctly count sets, they make a semantic induction about the meanings of their number words. We tested the logical understanding of number words in 84 children that were classified as "cardinal-principle knowers" by the criteria set forth by Wynn (1992). Results show that these children often…

  10. Integrating Experiential and Distributional Data to Learn Semantic Representations

    ERIC Educational Resources Information Center

    Andrews, Mark; Vigliocco, Gabriella; Vinson, David

    2009-01-01

    The authors identify 2 major types of statistical data from which semantic representations can be learned. These are denoted as "experiential data" and "distributional data". Experiential data are derived by way of experience with the physical world and comprise the sensory-motor data obtained through sense receptors. Distributional data, by…

  11. Semantic Processing of Living and Nonliving Concepts across the Cerebral Hemispheres

    ERIC Educational Resources Information Center

    Pilgrim, L.K.; Moss, H.E.; Tyler, L.K.

    2005-01-01

    Studies of patients with category-specific semantic deficits suggest that the right and left cerebral hemispheres may be differently involved in the processing of living and nonliving domains concepts. In this study, we investigate whether there are hemisphere differences in the semantic processing of these domains in healthy volunteers. Based on…

  12. Semantic Concept Co-Occurrence Patterns for Image Annotation and Retrieval.

    PubMed

    Feng, Linan; Bhanu, Bir

    2016-04-01

    Describing visual image contents by semantic concepts is an effective and straightforward way to facilitate various high level applications. Inferring semantic concepts from low-level pictorial feature analysis is challenging due to the semantic gap problem, while manually labeling concepts is unwise because of a large number of images in both online and offline collections. In this paper, we present a novel approach to automatically generate intermediate image descriptors by exploiting concept co-occurrence patterns in the pre-labeled training set that renders it possible to depict complex scene images semantically. Our work is motivated by the fact that multiple concepts that frequently co-occur across images form patterns which could provide contextual cues for individual concept inference. We discover the co-occurrence patterns as hierarchical communities by graph modularity maximization in a network with nodes and edges representing concepts and co-occurrence relationships separately. A random walk process working on the inferred concept probabilities with the discovered co-occurrence patterns is applied to acquire the refined concept signature representation. Through experiments in automatic image annotation and semantic image retrieval on several challenging datasets, we demonstrate the effectiveness of the proposed concept co-occurrence patterns as well as the concept signature representation in comparison with state-of-the-art approaches. PMID:26959678

  13. Semantic Maps Capturing Organization Knowledge in e-Learning

    NASA Astrophysics Data System (ADS)

    Mavridis, Androklis; Koumpis, Adamantios; Demetriadis, Stavros N.

    e-learning, shows much promise in accessibility and opportunity to learn, due to its asynchronous nature and its ability to transmit knowledge fast and effectively. However without a universal standard for online learning and teaching, many systems are proclaimed as “e-learning-compliant”, offering nothing more than automated services for delivering courses online, providing no additional enhancement to reusability and learner personalization. Hence, the focus is not on providing reusable and learner-centered content, but on developing the technology aspects of e-learning. This current trend has made it crucial to find a more refined definition of what constitutes knowledge in the e-learning context. We propose an e-learning system architecture that makes use of a knowledge model to facilitate continuous dialogue and inquiry-based knowledge learning, by exploiting the full benefits of the semantic web as a medium capable for supplying the web with formalized knowledge.

  14. A Learning Content Authoring Approach Based on Semantic Technologies and Social Networking: An Empirical Study

    ERIC Educational Resources Information Center

    Nesic, Sasa; Gasevic, Dragan; Jazayeri, Mehdi; Landoni, Monica

    2011-01-01

    Semantic web technologies have been applied to many aspects of learning content authoring including semantic annotation, semantic search, dynamic assembly, and personalization of learning content. At the same time, social networking services have started to play an important role in the authoring process by supporting authors' collaborative…

  15. A Method for Overcoming the Problem of Concept-Scale Interaction in Semantic Differential Research

    ERIC Educational Resources Information Center

    Bynner, John; Romney, David

    1972-01-01

    Data collected in a study of hospital staff attitudes to drug addicts and other types of patients are used to illustrate the problem of concept-scale interaction in semantic differential research. (Authors)

  16. 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…

  17. Concept Model on Topological Learning

    NASA Astrophysics Data System (ADS)

    Ae, Tadashi; Kioi, Kazumasa

    2010-11-01

    We discuss a new model for concept based on topological learning, where the learning process on the neural network is represented by mathematical topology. The topological learning of neural networks is summarized by a quotient of input space and the hierarchical step induces a tree where each node corresponds to a quotient. In general, the concept acquisition is a difficult problem, but the emotion for a subject is represented by providing the questions to a person. Therefore, a kind of concept is captured by such data and the answer sheet can be mapped into a topology consisting of trees. In this paper, we will discuss a way of mapping the emotional concept to a topological learning model.

  18. Learning Our Concepts

    ERIC Educational Resources Information Center

    Laverty, Megan J.

    2009-01-01

    Richard Stanley Peters appreciates the centrality of concepts for everyday life, however, he fails to recognize their pedagogical dimension. He distinguishes concepts employed at the first-order (our ordinary language-use) from second-order conceptual clarification (conducted exclusively by academically trained philosophers). This distinction…

  19. The Concept of Developmental Learning.

    ERIC Educational Resources Information Center

    Fowler, William

    Cognitive developmental learning is a concept expressing the hypothesis that learning has a continuing, cumulative, and transformational function in the development of intelligence. Two important questions are, "How much do we know about methods?" and "What classes of knowledge and abilities should we develop?" An analysis of past investigations,…

  20. Learning Aids Crystallize Complex Concepts.

    ERIC Educational Resources Information Center

    Selman, Victor; Selman, Jerry

    1999-01-01

    Presents a learning system paradigm which uses a multiplicity of toys and simulated models to reinforce concepts in business management and production. Describes concrete learning tools and experiences for each component of a proposed instructional paradigm: measurement, efficacy, data development, imagery and integration, computerization,…

  1. Enabling Creative Learning Design through Semantic Technologies

    ERIC Educational Resources Information Center

    Charlton, Patricia; Magoulas, George; Laurillard, Diana

    2012-01-01

    The paper advocates an approach to learning design that considers it as creating digital artefacts that can be extended, modified and used for different purposes. This is realised through an "act becoming artefact" cycle, where users' actions in the authors' software environment, named Learning Designer, are automatically interpreted on the basis…

  2. Learning to use scientific concepts

    NASA Astrophysics Data System (ADS)

    Wells, Gordon

    2008-07-01

    In responding to the research on conceptual change, this article attempts to make two points. First, scientific concepts are not possessed by individuals; rather, they are part of a culture's resources, which individuals learn to use for their own or for group purposes. Second, particular concepts are most effectively mastered when the learner is deeply engaged in solving a problem for which they function as effective semiotic tools in achieving a solution. On these grounds, it is argued that the mastering of scientific concepts is best achieved through learning to use them in motivated inquiry.

  3. Semantic pragmatic disorder with application of selected pragmatic concepts.

    PubMed

    Coulter, L

    1998-01-01

    Children with semantic pragmatic disorder have been described as having difficulties in conversational interaction. The content of their conversations has been described as 'odd', 'loose', tangential', 'irrelevant' and 'inappropriate' (Stubbs 1986). A diagnosis of semantic pragmatic disorder is currently made based on whether or not a child displays certain surface characteristics. The present study attempts to apply precision to the intuitive terms which have been used to describe these children's conversations. To this end conversation samples from three children identified by speech and language therapists as fitting the clinical diagnosis of semantic pragmatic disorder were analysed. Aspects of pragmatic theory which best explained the strengths and weaknesses which emerged in the conversations are discussed. Therefore this represents an essentially data driven study. PMID:10343733

  4. Episodic Representations Support Early Semantic Learning: Evidence from Midazolam Induced Amnesia

    ERIC Educational Resources Information Center

    Merritt, Paul; Hirshman, Elliot; Zamani, Shane; Hsu, John; Berrigan, Michael

    2006-01-01

    Current controversy exists regarding the role of episodic representations in the formation of long-term semantic memories. Using the drug "midazolam" to induce temporary amnesia we tested participants' memories for newly learned facts in a semantic cue condition or an episodic and semantic cue condition. Following midazolam administration, memory…

  5. Transforming Selected Concepts into Dimensions in Latent Semantic Analysis

    ERIC Educational Resources Information Center

    Olmos, Ricardo; Jorge-Botana, Guillermo; León, José Antonio; Escudero, Inmaculada

    2014-01-01

    This study presents a new approach for transforming the latent representation derived from a Latent Semantic Analysis (LSA) space into one where dimensions have nonlatent meanings. These meanings are based on lexical descriptors, which are selected by the LSA user. The authors present three analyses that provide examples of the utility of this…

  6. Semantic Similarity Computation and Concept Mapping in Earth and Environmental Science

    NASA Astrophysics Data System (ADS)

    Zheng, J.; Ma, X.; Fox, P. A.

    2013-12-01

    Ontologies have been widely adopted and used by Earth and Environmental Science community to capture and represent knowledge in the domain. One of the major problem that prevent us to combine and reuse these ontologies to solve more interesting problems is semantic heterogeneity problem, for example, same vocabularies from different ontologies may refer to different concept; or different terms from different ontologies may have same meaning. In this proposed work, we will address the problem by (1) developing a semantic similarity computation model to compute similarity among the concepts in Earth and Environmental Science; (2) based on the computation model, we will implement concept mapping tool that creates alignment for concepts that are semantically the same; (3) we will demonstrate the effectiveness of the tool using GCMD and CLEAN vocabularies and other earth science related ontologies.

  7. Semantic Annotation of Ubiquitous Learning Environments

    ERIC Educational Resources Information Center

    Weal, M. J.; Michaelides, D. T.; Page, K.; De Roure, D. C.; Monger, E.; Gobbi, M.

    2012-01-01

    Skills-based learning environments are used to promote the acquisition of practical skills as well as decision making, communication, and problem solving. It is important to provide feedback to the students from these sessions and observations of their actions may inform the assessment process and help researchers to better understand the learning…

  8. Aging and semantic cueing during learning and retention of verbal episodic information.

    PubMed

    Woo, Ellen; Schmitter-Edgecombe, Maureen

    2009-01-01

    The purpose of this study was to determine the effectiveness of semantic cues provided at encoding and during retention for older adults' memory. For the California Verbal Learning Test-II, participants received semantic or nonsemantic cues that were varied across groups at encoding and during the retention interval. Provision of a semantic cue at encoding led to greater semantic clustering at learning, but not increased recall performance. Providing a semantic cue during the retention interval led to better delayed free recall and greater semantic clustering. No group differences in recall or semantic clustering were found at delayed cued recall. The current findings suggest that semantic cues can be beneficial for recalling unstructured information when administered during the retention interval. PMID:18923945

  9. Designing Collaborative E-Learning Environments Based upon Semantic Wiki: From Design Models to Application Scenarios

    ERIC Educational Resources Information Center

    Li, Yanyan; Dong, Mingkai; Huang, Ronghuai

    2011-01-01

    The knowledge society requires life-long learning and flexible learning environment that enables fast, just-in-time and relevant learning, aiding the development of communities of knowledge, linking learners and practitioners with experts. Based upon semantic wiki, a combination of wiki and Semantic Web technology, this paper designs and develops…

  10. Concept Map Engineering: Methods and Tools Based on the Semantic Relation Approach

    ERIC Educational Resources Information Center

    Kim, Minkyu

    2013-01-01

    The purpose of this study is to develop a better understanding of technologies that use natural language as the basis for concept map construction. In particular, this study focuses on the semantic relation (SR) approach to drawing rich and authentic concept maps that reflect students' internal representations of a problem situation. The…

  11. Knowledge represented using RDF semantic network in the concept of semantic web

    NASA Astrophysics Data System (ADS)

    Lukasova, A.; Vajgl, M.; Zacek, M.

    2016-06-01

    The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDF to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.

  12. Dynamics of activation of semantically similar concepts during spoken word recognition

    PubMed Central

    Mirman, Daniel; Magnuson, James S.

    2010-01-01

    Semantic similarity effects provide critical insight into the organization of semantic knowledge and the nature of semantic processing. In the present study, we examined the dynamics of semantic similarity effects by using the visual world eyetracking paradigm. Four objects were shown on a computer monitor, and participants were instructed to click on a named object, during which time their gaze position was recorded. The likelihood of fixating competitor objects was predicted by the degree of semantic similarity to the target concept. We found reliable, graded competition that depended on degree of target–competitor similarity, even for distantly related items for which priming has not been found in previous priming studies. Time course measures revealed a consistently earlier fixation peak for near semantic neighbors relative to targets. Computational investigations with an attractor dynamical model, a spreading activation model, and a decision model revealed that a combination of excitatory and inhibitory mechanisms is required to obtain such peak timing, providing new constraints on models of semantic processing. PMID:19744941

  13. Semantic Size of Abstract Concepts: It Gets Emotional When You Can’t See It

    PubMed Central

    Yao, Bo; Vasiljevic, Milica; Weick, Mario; Sereno, Margaret E.; O’Donnell, Patrick J.; Sereno, Sara C.

    2013-01-01

    Size is an important visuo-spatial characteristic of the physical world. In language processing, previous research has demonstrated a processing advantage for words denoting semantically “big” (e.g., jungle) versus “small” (e.g., needle) concrete objects. We investigated whether semantic size plays a role in the recognition of words expressing abstract concepts (e.g., truth). Semantically “big” and “small” concrete and abstract words were presented in a lexical decision task. Responses to “big” words, regardless of their concreteness, were faster than those to “small” words. Critically, we explored the relationship between semantic size and affective characteristics of words as well as their influence on lexical access. Although a word’s semantic size was correlated with its emotional arousal, the temporal locus of arousal effects may depend on the level of concreteness. That is, arousal seemed to have an earlier (lexical) effect on abstract words, but a later (post-lexical) effect on concrete words. Our findings provide novel insights into the semantic representations of size in abstract concepts and highlight that affective attributes of words may not always index lexical access. PMID:24086421

  14. Harmonisation of the Educational Concept "Learning Outcome" in the Lithuanian Language

    ERIC Educational Resources Information Center

    Pukelis, Kestutis; Smetona, Antanas

    2011-01-01

    In this article, an example of translation of the English term "learning outcome" into the Lithuanian system of educational terms is used to discuss semantic peculiarities of translating professional terms. Consistency of a concept signifier and content of a concept, as well as their tune with already existing systems of educational terms are…

  15. Implicit Word Learning Benefits from Semantic Richness: Electrophysiological and Behavioral Evidence

    ERIC Educational Resources Information Center

    Rabovsky, Milena; Sommer, Werner; Abdel Rahman, Rasha

    2012-01-01

    Words differ considerably in the amount of associated semantic information. Despite the crucial role of meaning in language, it is still unclear whether and how this variability modulates language learning. Here, we provide initial evidence demonstrating that implicit learning in repetition priming is influenced by the amount of semantic features…

  16. A Research on E - learning Resources Construction Based on Semantic Web

    NASA Astrophysics Data System (ADS)

    Rui, Liu; Maode, Deng

    Traditional e-learning platforms have the flaws that it's usually difficult to query or positioning, and realize the cross platform sharing and interoperability. In the paper, the semantic web and metadata standard is discussed, and a kind of e - learning system framework based on semantic web is put forward to try to solve the flaws of traditional elearning platforms.

  17. Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective

    ERIC Educational Resources Information Center

    Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.

    2005-01-01

    In the context of Knowledge Society, the convergence of knowledge and learning management is a critical milestone. "Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective" provides state-of-the art knowledge through a balanced theoretical and technological discussion. The semantic web perspective…

  18. Hypermedia-Assisted Instruction and Second Language Learning: A Semantic-Network-Based Approach.

    ERIC Educational Resources Information Center

    Liu, Min

    This literature review examines a hypermedia learning environment from a semantic network basis and the application of such an environment to second language learning. (A semantic network is defined as a conceptual representation of knowledge in human memory). The discussion is organized under the following headings and subheadings: (1) Advantages…

  19. Semantic annotation for concept-based cross-language medical information retrieval.

    PubMed

    Volk, Martin; Ripplinger, Bärbel; Vintar, Spela; Buitelaar, Paul; Raileanu, Diana; Sacaleanu, Bogdan

    2002-12-01

    We present a framework for concept-based cross-language information retrieval in the medical domain, which is under development in the MUCHMORE project. Our approach is based on using the Unified Medical Language System (UMLS) as the primary source of semantic data. Documents and queries are annotated with multiple layers of linguistic information. Linguistic processing includes part-of-speech tagging, morphological analysis, phrase recognition and the identification of medical terms and semantic relations between them. The paper describes experiments in monolingual and cross-language document retrieval, performed on a corpus of medical abstracts. Results show that linguistic processing, especially lemmatization and compound analysis for German, is a crucial step in achieving a good baseline performance. On the other hand, they show that semantic information, specifically the combined use of concepts and relations, increases the performance in monolingual and cross-language retrieval. PMID:12460635

  20. How visual and semantic information influence learning in familiar contexts.

    PubMed

    Goujon, Annabelle; Brockmole, James R; Ehinger, Krista A

    2012-10-01

    Previous research using the contextual cuing paradigm has revealed both quantitative and qualitative differences in learning depending on whether repeated contexts are defined by letter arrays or real-world scenes. To clarify the relative contributions of visual features and semantic information likely to account for such differences, the typical contextual cuing procedure was adapted to use meaningless but nevertheless visually complex images. The data in reaction time and in eye movements show that, like scenes, such repeated contexts can trigger large, stable, and explicit cuing effects, and that those effects result from facilitated attentional guidance. Like simpler stimulus arrays, however, those effects were impaired by a sudden change of a repeating image's color scheme at the end of the learning phase (Experiment 1), or when the repeated images were presented in a different and unique color scheme across each presentation (Experiment 2). In both cases, search was driven by explicit memory. Collectively, these results suggest that semantic information is not required for conscious awareness of context-target covariation, but it plays a primary role in overcoming variability in specific features within familiar displays. PMID:22612057

  1. Relational, Structural, and Semantic Analysis of Graphical Representations and Concept Maps

    ERIC Educational Resources Information Center

    Ifenthaler, Dirk

    2010-01-01

    The demand for good instructional environments presupposes valid and reliable analytical instruments for educational research. This paper introduces the "SMD Technology" (Surface, Matching, Deep Structure), which measures relational, structural, and semantic levels of graphical representations and concept maps. The reliability and validity of the…

  2. An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

    ERIC Educational Resources Information Center

    Gao, Wenlong

    2012-01-01

    The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

  3. Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

    NASA Astrophysics Data System (ADS)

    Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

    2014-05-01

    We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the

  4. ASSOCIATIVE CONCEPT LEARNING IN ANIMALS

    PubMed Central

    Zentall, Thomas R.; Wasserman, Edward A.; Urcuioli, Peter J.

    2014-01-01

    Nonhuman animals show evidence for three types of concept learning: perceptual or similarity-based in which objects/stimuli are categorized based on physical similarity; relational in which one object/stimulus is categorized relative to another (e.g., same/different); and associative in which arbitrary stimuli become interchangeable with one another by virtue of a common association with another stimulus, outcome, or response. In this article, we focus on various methods for establishing associative concepts in nonhuman animals and evaluate data documenting the development of associative classes of stimuli. We also examine the nature of the common within-class representation of samples that have been associated with the same reinforced comparison response (i.e., many-to-one matching) by describing manipulations for distinguishing possible representations. Associative concepts provide one foundation for human language such that spoken and written words and the objects they represent become members of a class of interchangeable stimuli. The mechanisms of associative concept learning and the behavioral flexibility it allows, however, are also evident in the adaptive behaviors of animals lacking language. PMID:24170540

  5. SOLE: Applying Semantics and Social Web to Support Technology Enhanced Learning in Software Engineering

    NASA Astrophysics Data System (ADS)

    Colomo-Palacios, Ricardo; Jiménez-López, Diego; García-Crespo, Ángel; Blanco-Iglesias, Borja

    eLearning educative processes are a challenge for educative institutions and education professionals. In an environment in which learning resources are being produced, catalogued and stored using innovative ways, SOLE provides a platform in which exam questions can be produced supported by Web 2.0 tools, catalogued and labeled via semantic web and stored and distributed using eLearning standards. This paper presents, SOLE, a social network of exam questions sharing particularized for Software Engineering domain, based on semantics and built using semantic web and eLearning standards, such as IMS Question and Test Interoperability specification 2.1.

  6. Teachers' Conceptions of Student Learning and Own Learning

    ERIC Educational Resources Information Center

    Bolhuis, Sanneke; Voeten, Marinus J. M.

    2004-01-01

    New learning theory, underpinning the idea of teaching for self-directed learning, provides new conceptions of learning: the self-regulation of learning, the construct-character of knowledge, the social nature of learning and a dynamic model of intelligence. What conceptions teachers hold may be related to their tolerance of uncertainty. We…

  7. Simulating Expert Clinical Comprehension: Adapting Latent Semantic Analysis to Accurately Extract Clinical Concepts from Psychiatric Narrative

    PubMed Central

    Cohen, Trevor; Blatter, Brett; Patel, Vimla

    2008-01-01

    Cognitive studies reveal that less-than-expert clinicians are less able to recognize meaningful patterns of data in clinical narratives. Accordingly, psychiatric residents early in training fail to attend to information that is relevant to diagnosis and the assessment of dangerousness. This manuscript presents cognitively motivated methodology for the simulation of expert ability to organize relevant findings supporting intermediate diagnostic hypotheses. Latent Semantic Analysis is used to generate a semantic space from which meaningful associations between psychiatric terms are derived. Diagnostically meaningful clusters are modeled as geometric structures within this space and compared to elements of psychiatric narrative text using semantic distance measures. A learning algorithm is defined that alters components of these geometric structures in response to labeled training data. Extraction and classification of relevant text segments is evaluated against expert annotation, with system-rater agreement approximating rater-rater agreement. A range of biomedical informatics applications for these methods are suggested. PMID:18455483

  8. A semantic image retrieval approach between visual features and medical concepts

    NASA Astrophysics Data System (ADS)

    Li, Jin; Liang, Hong; Yang, Guangda; Feng, Yaoyu; Lv, Meichao

    2009-07-01

    In the medical domain, digital images are produced in ever-increasing quantities, which offer great opportunities for diagnostics, therapy and training. So how to manage these data and utilize them effectively and efficiently possess significant technical challenges. Thus, the technique of Content-based Medical Image Retrieval (CBMIR) emerges as the times require. However, current CBMIR is not sufficient to capture the semantic content of images. Accordingly, in this paper, an innovative approach for medical image knowledge representation and retrieval is proposed by focusing on the mapping modeling between visual feature and semantic concept. Firstly, the low-level fusion visual features are extracted based on statistical features. Secondly, a set of disjoint semantic tokens with appearance in medical images is selected to define a Visual and Medical Vocabulary. Thirdly, to narrow down the semantic gap and increase the retrieval efficiency, we investigate support vector machine (SVM) to associate low-level visual image features with their highlevel semantic. Experiments are conducted with a medical image DB consisting of 300 diverse medical images obtained from the Hei Longjiang Province Hospital. And the comparison of the retrieval results shows that the approach proposed in this paper is effective.

  9. Concepts as Semantic Pointers: A Framework and Computational Model

    ERIC Educational Resources Information Center

    Blouw, Peter; Solodkin, Eugene; Thagard, Paul; Eliasmith, Chris

    2016-01-01

    The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts…

  10. From Distributional Semantics to Conceptual Spaces: A Novel Computational Method for Concept Creation

    NASA Astrophysics Data System (ADS)

    McGregor, Stephen; Agres, Kat; Purver, Matthew; Wiggins, Geraint A.

    2015-12-01

    We investigate the relationship between lexical spaces and contextually-defined conceptual spaces, offering applications to creative concept discovery. We define a computational method for discovering members of concepts based on semantic spaces: starting with a standard distributional model derived from corpus co-occurrence statistics, we dynamically select characteristic dimensions associated with seed terms, and thus a subspace of terms defining the related concept. This approach performs as well as, and in some cases better than, leading distributional semantic models on a WordNet-based concept discovery task, while also providing a model of concepts as convex regions within a space with interpretable dimensions. In particular, it performs well on more specific, contextualized concepts; to investigate this we therefore move beyond WordNet to a set of human empirical studies, in which we compare output against human responses on a membership task for novel concepts. Finally, a separate panel of judges rate both model output and human responses, showing similar ratings in many cases, and some commonalities and divergences which reveal interesting issues for computational concept discovery.

  11. The Role of Self-Teaching in Learning Orthographic and Semantic Aspects of New Words

    ERIC Educational Resources Information Center

    Ricketts, Jessie; Bishop, Dorothy V. M.; Pimperton, Hannah; Nation, Kate

    2011-01-01

    This study explores how children learn the meaning (semantics) and spelling patterns (orthography) of novel words encountered in story context. English-speaking children (N = 88) aged 7 to 8 years read 8 stories and each story contained 1 novel word repeated 4 times. Semantic cues were provided by the story context such that children could infer…

  12. Autobiographically significant concepts: more episodic than semantic in nature? An electrophysiological investigation of overlapping types of memory.

    PubMed

    Renoult, Louis; Davidson, Patrick S R; Schmitz, Erika; Park, Lillian; Campbell, Kenneth; Moscovitch, Morris; Levine, Brian

    2015-01-01

    A common assertion is that semantic memory emerges from episodic memory, shedding the distinctive contexts associated with episodes over time and/or repeated instances. Some semantic concepts, however, may retain their episodic origins or acquire episodic information during life experiences. The current study examined this hypothesis by investigating the ERP correlates of autobiographically significant (AS) concepts, that is, semantic concepts that are associated with vivid episodic memories. We inferred the contribution of semantic and episodic memory to AS concepts using the amplitudes of the N400 and late positive component, respectively. We compared famous names that easily brought to mind episodic memories (high AS names) against equally famous names that did not bring such recollections to mind (low AS names) on a semantic task (fame judgment) and an episodic task (recognition memory). Compared with low AS names, high AS names were associated with increased amplitude of the late positive component in both tasks. Moreover, in the recognition task, this effect of AS was highly correlated with recognition confidence. In contrast, the N400 component did not differentiate the high versus low AS names but, instead, was related to the amount of general knowledge participants had regarding each name. These results suggest that semantic concepts high in AS, such as famous names, have an episodic component and are associated with similar brain processes to those that are engaged by episodic memory. Studying AS concepts may provide unique insights into how episodic and semantic memory interact. PMID:25061931

  13. A Study of the Semantic Differential Based on Motivational Concepts as a Technique for Predicting Student Achievement.

    ERIC Educational Resources Information Center

    Sizemore, Oral Glen

    The purpose of this study was to develop a semantic differential scale based on achievement motivation concepts by which grade point averages could be predicted. A scale was constructed and administered to 944 freshmen at Northeastern State College in Fall 1967. Two approaches were used. One was to combine semantic differential scale scores…

  14. Exploiting Semantic Annotations and Q-Learning for Constructing an Efficient Hierarchy/Graph Texts Organization

    PubMed Central

    El-Said, Asmaa M.; Eldesoky, Ali I.; Arafat, Hesham A.

    2015-01-01

    Tremendous growth in the number of textual documents has produced daily requirements for effective development to explore, analyze, and discover knowledge from these textual documents. Conventional text mining and managing systems mainly use the presence or absence of key words to discover and analyze useful information from textual documents. However, simple word counts and frequency distributions of term appearances do not capture the meaning behind the words, which results in limiting the ability to mine the texts. This paper proposes an efficient methodology for constructing hierarchy/graph-based texts organization and representation scheme based on semantic annotation and Q-learning. This methodology is based on semantic notions to represent the text in documents, to infer unknown dependencies and relationships among concepts in a text, to measure the relatedness between text documents, and to apply mining processes using the representation and the relatedness measure. The representation scheme reflects the existing relationships among concepts and facilitates accurate relatedness measurements that result in a better mining performance. An extensive experimental evaluation is conducted on real datasets from various domains, indicating the importance of the proposed approach. PMID:25685832

  15. Learning with Retrieval-Based Concept Mapping

    ERIC Educational Resources Information Center

    Blunt, Janell R.; Karpicke, Jeffrey D.

    2014-01-01

    Students typically create concept maps while they view the material they are trying to learn. In these circumstances, concept mapping serves as an elaborative study activity--students are not required to retrieve the material they are learning. In 2 experiments, we examined the effectiveness of concept mapping when it is used as a retrieval…

  16. Supporting Learning Process with Concept Map Scripts.

    ERIC Educational Resources Information Center

    Rautama, Erkki; Sutinen, Erkki; Tarhio, Jorma

    1997-01-01

    Describes a framework for computer-aided concept mapping that provides the means to easily trace the learning process. Presents the construction of a concept map as a script which consists of elementary operations. This approach can be applied in presentation tools, in evaluating the learning process, and in computer-aided learning. (Author/AEF)

  17. Service Learning Triangle: Key Concepts, Partners, Relationships.

    ERIC Educational Resources Information Center

    McCarthy, Florence E.

    Using the concept of triangles as a schematic conceptualization of service learning is a useful pedagogical tool in helping faculty, students, and community members to see the linkages among the component concepts in service learning approaches. Service learning, which is the linking of academic instruction with community service as guided by…

  18. Conceptions of Learning and Approaches to Learning in Portuguese Students

    ERIC Educational Resources Information Center

    Duarte, Antonio M.

    2007-01-01

    The article describes a study that attempted to characterise Portuguese students' conceptions of learning and approaches to learning. A sample of university students answered open questions on the meaning, process and context of learning. Results, derived from content analysis, replicate most conceptions of learning described by phenomenographical…

  19. Collaborative Concept Mapping in a Web-Based Learning Environment: A Pedagogic Experience in Architectural Education.

    ERIC Educational Resources Information Center

    Madrazo, Leandro; Vidal, Jordi

    2002-01-01

    Describes a pedagogical work, carried out within a school of architecture, using a Web-based learning environment to support collaborative understanding of texts on architectural theory. Explains the use of concept maps, creation of a critical vocabulary, exploration of semantic spaces, and knowledge discovery through navigation. (Author/LRW)

  20. Semantics guide infants' vowel learning: Computational and experimental evidence.

    PubMed

    Ter Schure, S M M; Junge, C M M; Boersma, P P G

    2016-05-01

    In their first year, infants' perceptual abilities zoom in on only those speech sound contrasts that are relevant for their language. Infants' lexicons do not yet contain sufficient minimal pairs to explain this phonetic categorization process. Therefore, researchers suggested a bottom-up learning mechanism: infants create categories aligned with the frequency distributions of sounds in their input. Recent evidence shows that this bottom-up mechanism may be complemented by the semantic context in which speech sounds occur, such as simultaneously present objects. To test this hypothesis, we investigated whether discrimination of a non-native vowel contrast improves when sounds from the contrast were paired consistently or randomly with two distinct visually presented objects, while the distribution of speech tokens suggested a single broad category. This was assessed in two ways: computationally, namely in a neural network simulation, and experimentally, namely in a group of 8-month-old infants. The neural network, trained with a large set of sound-meaning pairs, revealed that two categories emerge only if sounds are consistently paired with objects. A group of 49 real 8-month-old infants did not immediately show sensitivity to the pairing condition; a later test at 18 months with some of the same infants, however, showed that this sensitivity at 8 months interacted with their vocabulary size at 18 months. This interaction can be explained by the idea that infants with larger future vocabularies are more positively influenced by consistent training (and/or more negatively influenced by inconsistent training) than infants with smaller future vocabularies. This suggests that consistent pairing with distinct visual objects can help infants to discriminate speech sounds even when the auditory information does not signal a distinction. Together our results give computational as well as experimental support for the idea that semantic context plays a role in disambiguating

  1. A framework of Chinese semantic text mining based on ontology learning

    NASA Astrophysics Data System (ADS)

    Zhang, Yu-Feng; Hu, Feng

    2011-12-01

    Text mining and ontology learning can be effectively employed to acquire the Chinese semantic information. This paper explores a framework of semantic text mining based on ontology learning to find the potential semantic knowledge from the immensity text information on the Internet. This framework consists of four parts: Data Acquisition, Feature Extraction, Ontology Construction, and Text Knowledge Pattern Discovery. Then the framework is applied into an actual case to try to find out the valuable information, and even to assist the consumers with selecting proper products. The results show that this framework is reasonable and effective.

  2. A framework of Chinese semantic text mining based on ontology learning

    NASA Astrophysics Data System (ADS)

    Zhang, Yu-feng; Hu, Feng

    2012-01-01

    Text mining and ontology learning can be effectively employed to acquire the Chinese semantic information. This paper explores a framework of semantic text mining based on ontology learning to find the potential semantic knowledge from the immensity text information on the Internet. This framework consists of four parts: Data Acquisition, Feature Extraction, Ontology Construction, and Text Knowledge Pattern Discovery. Then the framework is applied into an actual case to try to find out the valuable information, and even to assist the consumers with selecting proper products. The results show that this framework is reasonable and effective.

  3. Auditing the Semantic Completeness of SNOMED CT Using Formal Concept Analysis

    PubMed Central

    Jiang, Guoqian; Chute, Christopher G.

    2009-01-01

    Objective This study sought to develop and evaluate an approach for auditing the semantic completeness of the SNOMED CT contents using a formal concept analysis (FCA)–based model. Design We developed a model for formalizing the normal forms of SNOMED CT expressions using FCA. Anonymous nodes, identified through the analyses, were retrieved from the model for evaluation. Two quasi-Poisson regression models were developed to test whether anonymous nodes can evaluate the semantic completeness of SNOMED CT contents (Model 1), and for testing whether such completeness differs between 2 clinical domains (Model 2). The data were randomly sampled from all the contexts that could be formed in the 2 largest domains: Procedure and Clinical Finding. Case studies (n = 4) were performed on randomly selected anonymous node samples for validation. Measurements In Model 1, the outcome variable is the number of fully defined concepts within a context, while the explanatory variables are the number of lattice nodes and the number of anonymous nodes. In Model 2, the outcome variable is the number of anonymous nodes and the explanatory variables are the number of lattice nodes and a binary category for domain (Procedure/Clinical Finding). Results A total of 5,450 contexts from the 2 domains were collected for analyses. Our findings revealed that the number of anonymous nodes had a significant negative correlation with the number of fully defined concepts within a context (p < 0.001). Further, the Clinical Finding domain had fewer anonymous nodes than the Procedure domain (p < 0.001). Case studies demonstrated that the anonymous nodes are an effective index for auditing SNOMED CT. Conclusion The anonymous nodes retrieved from FCA-based analyses are a candidate proxy for the semantic completeness of the SNOMED CT contents. Our novel FCA-based approach can be useful for auditing the semantic completeness of SNOMED CT contents, or any large ontology, within or across domains. PMID

  4. Extracting semantic lexicons from discharge summaries using machine learning and the C-Value method.

    PubMed

    Jiang, Min; Denny, Josh C; Tang, Buzhou; Cao, Hongxin; Xu, Hua

    2012-01-01

    Semantic lexicons that link words and phrases to specific semantic types such as diseases are valuable assets for clinical natural language processing (NLP) systems. Although terminological terms with predefined semantic types can be generated easily from existing knowledge bases such as the Unified Medical Language Systems (UMLS), they are often limited and do not have good coverage for narrative clinical text. In this study, we developed a method for building semantic lexicons from clinical corpus. It extracts candidate semantic terms using a conditional random field (CRF) classifier and then selects terms using the C-Value algorithm. We applied the method to a corpus containing 10 years of discharge summaries from Vanderbilt University Hospital (VUH) and extracted 44,957 new terms for three semantic groups: Problem, Treatment, and Test. A manual analysis of 200 randomly selected terms not found in the UMLS demonstrated that 59% of them were meaningful new clinical concepts and 25% were lexical variants of exiting concepts in the UMLS. Furthermore, we compared the effectiveness of corpus-derived and UMLS-derived semantic lexicons in the concept extraction task of the 2010 i2b2 clinical NLP challenge. Our results showed that the classifier with corpus-derived semantic lexicons as features achieved a better performance (F-score 82.52%) than that with UMLS-derived semantic lexicons as features (F-score 82.04%). We conclude that such corpus-based methods are effective for generating semantic lexicons, which may improve named entity recognition tasks and may aid in augmenting synonymy within existing terminologies. PMID:23304311

  5. Structure at every scale: A semantic network account of the similarities between unrelated concepts.

    PubMed

    De Deyne, Simon; Navarro, Daniel J; Perfors, Amy; Storms, Gert

    2016-09-01

    Similarity plays an important role in organizing the semantic system. However, given that similarity cannot be defined on purely logical grounds, it is important to understand how people perceive similarities between different entities. Despite this, the vast majority of studies focus on measuring similarity between very closely related items. When considering concepts that are very weakly related, little is known. In this article, we present 4 experiments showing that there are reliable and systematic patterns in how people evaluate the similarities between very dissimilar entities. We present a semantic network account of these similarities showing that a spreading activation mechanism defined over a word association network naturally makes correct predictions about weak similarities, whereas, though simpler, models based on direct neighbors between word pairs derived using the same network cannot. (PsycINFO Database Record PMID:27560855

  6. Syntactic and Semantic Reasoning in Mathematics Teaching and Learning

    ERIC Educational Resources Information Center

    Easdown, David

    2009-01-01

    This article discusses a variety of examples in errors in mathematical reasoning, the source of which is due to the tension between the syntax (form of mathematical expression) and semantics (underlying ideas or meaning). This article suggests that the heightened awareness of syntactic and semantic reasoning, and the consequent resolution of the…

  7. Basic Concept Acquisition in Learning Disabled Children.

    ERIC Educational Resources Information Center

    DiNapoli, Nicholas Paul; And Others

    The Boehm Test of Basic Concepts (BTBC) (Boehm, 1971) was administered to 99 children (ages 7-10) who had been diagnosed as learning disabled and attended special schools in the New York area. It was hypothesized that the learning disabled children would exhibit a delay in the acquisition of the basic concepts, but would display a similar order of…

  8. Semantic Mistakes and Didactic Difficulties in Teaching the "Amount of Substance" Concept: A Useful Model

    ERIC Educational Resources Information Center

    Pekdag, Bulent; Azizoglu, Nursen

    2013-01-01

    Textbooks still have the distinction of being the most dominant teaching tool in science teaching. The manner in which a scientific concept is expressed in a textbook is of importance in the in-depth learning process of that concept. With this in mind, problems with expressing the "amount of substance" concept were reviewed in 15 chemistry…

  9. Semantic Event Fusion of Different Visual Modality Concepts for Activity Recognition.

    PubMed

    Crispim-Junior, Carlos F; Buso, Vincent; Avgerinakis, Konstantinos; Meditskos, Georgios; Briassouli, Alexia; Benois-Pineau, Jenny; Kompatsiaris, Ioannis Yiannis; Bremond, Francois

    2016-08-01

    Combining multimodal concept streams from heterogeneous sensors is a problem superficially explored for activity recognition. Most studies explore simple sensors in nearly perfect conditions, where temporal synchronization is guaranteed. Sophisticated fusion schemes adopt problem-specific graphical representations of events that are generally deeply linked with their training data and focused on a single sensor. This paper proposes a hybrid framework between knowledge-driven and probabilistic-driven methods for event representation and recognition. It separates semantic modeling from raw sensor data by using an intermediate semantic representation, namely concepts. It introduces an algorithm for sensor alignment that uses concept similarity as a surrogate for the inaccurate temporal information of real life scenarios. Finally, it proposes the combined use of an ontology language, to overcome the rigidity of previous approaches at model definition, and a probabilistic interpretation for ontological models, which equips the framework with a mechanism to handle noisy and ambiguous concept observations, an ability that most knowledge-driven methods lack. We evaluate our contributions in multimodal recordings of elderly people carrying out IADLs. Results demonstrated that the proposed framework outperforms baseline methods both in event recognition performance and in delimiting the temporal boundaries of event instances. PMID:26955015

  10. The neural correlates of semantic richness: evidence from an fMRI study of word learning.

    PubMed

    Ferreira, Roberto A; Göbel, Silke M; Hymers, Mark; Ellis, Andrew W

    2015-04-01

    We investigated the neural correlates of concrete nouns with either many or few semantic features. A group of 21 participants underwent two days of training and were then asked to categorize 40 newly learned words and a set of matched familiar words as living or nonliving in an MRI scanner. Our results showed that the most reliable effects of semantic richness were located in the left angular gyrus (AG) and middle temporal gyrus (MTG), where activation was higher for semantically rich than poor words. Other areas showing the same pattern included bilateral precuneus and posterior cingulate gyrus. Our findings support the view that AG and anterior MTG, as part of the multimodal network, play a significant role in representing and integrating semantic features from different input modalities. We propose that activation in bilateral precuneus and posterior cingulate gyrus reflects interplay between AG and episodic memory systems during semantic retrieval. PMID:25797097

  11. The Concept of Action Learning.

    ERIC Educational Resources Information Center

    Zuber-Skerritt, Ortrun

    2002-01-01

    Based on classic and emerging international literature, action learning is defined as learning form concrete experience and critical reflection on experience, focused on problem solving and change. Facilitators of action learning do not impose solutions but guide action learning teams through the process. (Contains 44 references.) (SK)

  12. International Concepts and Agendas of Lifelong Learning

    ERIC Educational Resources Information Center

    Schuetze, Hans G.

    2006-01-01

    International organisations were the main proponents of Lifelong Learning when the concept was first developed in the early 1970s. Although different organisations used different labels--Lifelong Learning, recurrent education, education permanente--they all emphasised that learning is a lifelong process and that all education should be organised…

  13. Student Conceptions of Peer-Assisted Learning

    ERIC Educational Resources Information Center

    Hodgson, Yvonne; Benson, Robyn; Brack, Charlotte

    2015-01-01

    This article reports on a programme in which peer-assisted learning (PAL) was combined with case-based learning (CBL) in a second-year radiologic biology unit of study. Our aim is to explore evidence of whether PAL supported the development of qualitative conceptions of learning. The programme involved students in small PAL groups preparing and…

  14. A Hybrid Knowledge-Based and Data-Driven Approach to Identifying Semantically Similar Concepts

    PubMed Central

    Pivovarov, Rimma; Elhadad, Noémie

    2012-01-01

    An open research question when leveraging ontological knowledge is when to treat different concepts separately from each other and when to aggregate them. For instance, concepts for the terms "paroxysmal cough" and "nocturnal cough" might be aggregated in a kidney disease study, but should be left separate in a pneumonia study. Determining whether two concepts are similar enough to be aggregated can help build better datasets for data mining purposes and avoid signal dilution. Quantifying the similarity among concepts is a difficult task, however, in part because such similarity is context-dependent. We propose a comprehensive method, which computes a similarity score for a concept pair by combining data-driven and ontology-driven knowledge. We demonstrate our method on concepts from SNOMED-CT and on a corpus of clinical notes of patients with chronic kidney disease. By combining information from usage patterns in clinical notes and from ontological structure, the method can prune out concepts that are simply related from those which are semantically similar. When evaluated against a list of concept pairs annotated for similarity, our method reaches an AUC (area under the curve) of 92%. PMID:22289420

  15. Recommendation of standardized health learning contents using archetypes and semantic web technologies.

    PubMed

    Legaz-García, María del Carmen; Martínez-Costa, Catalina; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

    2012-01-01

    Linking Electronic Healthcare Records (EHR) content to educational materials has been considered a key international recommendation to enable clinical engagement and to promote patient safety. This would suggest citizens to access reliable information available on the web and to guide them properly. In this paper, we describe an approach in that direction, based on the use of dual model EHR standards and standardized educational contents. The recommendation method will be based on the semantic coverage of the learning content repository for a particular archetype, which will be calculated by applying semantic web technologies like ontologies and semantic annotations. PMID:22874336

  16. Density: A measure of the diversity of concepts addressed in semantic networks

    NASA Astrophysics Data System (ADS)

    Pereira, H. B. B.; Fadigas, I. S.; Monteiro, R. L. S.; Cordeiro, A. J. A.; Moret, M. A.

    2016-01-01

    In this paper, we studied density effects in semantic networks constructed from a database of titles of papers published in scientific journals as a parameter to indicate the diversity of concepts in a journal. The proposed method essentially consists of fixing the number of titles for all of the studied scientific journals and analyzing the behavior of the density variation curves with regard to the inclusion of cliques (that is, complete networks associated with the titles). We observed that density behaves as a critically self-organized object when titles (cliques) are included in the network.

  17. Visual Statistical Learning Based on the Perceptual and Semantic Information of Objects

    ERIC Educational Resources Information Center

    Otsuka, Sachio; Nishiyama, Megumi; Nakahara, Fumitaka; Kawaguchi, Jun

    2013-01-01

    Five experiments examined what is learned based on the perceptual and semantic information of objects in visual statistical learning (VSL). In the familiarization phase, participants viewed a sequence of line drawings and detected repetitions of various objects. In a subsequent test phase, they watched 2 test sequences (statistically related…

  18. The Influence of Consistency, Frequency, and Semantics on Learning to Read: An Artificial Orthography Paradigm

    ERIC Educational Resources Information Center

    Taylor, J. S. H.; Plunkett, Kim; Nation, Kate

    2011-01-01

    Two experiments explored learning, generalization, and the influence of semantics on orthographic processing in an artificial language. In Experiment 1, 16 adults learned to read 36 novel words written in novel characters. Posttraining, participants discriminated trained from untrained items and generalized to novel items, demonstrating extraction…

  19. A Metadata Model for E-Learning Coordination through Semantic Web Languages

    ERIC Educational Resources Information Center

    Elci, Atilla

    2005-01-01

    This paper reports on a study aiming to develop a metadata model for e-learning coordination based on semantic web languages. A survey of e-learning modes are done initially in order to identify content such as phases, activities, data schema, rules and relations, etc. relevant for a coordination model. In this respect, the study looks into the…

  20. A Semantic-Oriented Approach for Organizing and Developing Annotation for E-Learning

    ERIC Educational Resources Information Center

    Brut, Mihaela M.; Sedes, Florence; Dumitrescu, Stefan D.

    2011-01-01

    This paper presents a solution to extend the IEEE LOM standard with ontology-based semantic annotations for efficient use of learning objects outside Learning Management Systems. The data model corresponding to this approach is first presented. The proposed indexing technique for this model development in order to acquire a better annotation of…

  1. Perceptual learning of contrast discrimination under roving: the role of semantic sequence in stimulus tagging.

    PubMed

    Cong, Lin-Juan; Zhang, Jun-Yun

    2014-01-01

    Perceptual learning may occur when multiple contrasts are practiced in a fixed, but not in a roving (random), temporal sequence. However, learning may escape roving disruption when each contrast is assigned a letter tag (i.e., A, B, C, D). Because these letter tags carry not only stimulus identity information, but also semantic sequence information, here we investigated whether the semantic sequence information is necessary for learning of tagged contrasts under the roving condition. We found that assigning number tags (i.e., 1, 2, 3, 4), which also contained both identity and semantic sequence information, to four roving contrasts enabled significant learning of discrimination of each contrast, confirming previous data. However, learning became insignificant when the contrast tags were replaced with Greek letters that were familiar to our Chinese observers except their sequence or Chinese characters that carried no sequence information. In addition, assigning orientation tags, which carried no sequence information either, to roving contrasts was ineffective as well because learning occurred only with sequenced but not roving contrasts. These results suggest that semantic sequence information is necessary for stimulus tagging to effectively enable perceptual learning of multiple contrast discrimination under roving. PMID:25368338

  2. Do semantic contextual cues facilitate transfer learning from video in toddlers?

    PubMed Central

    Zimmermann, Laura; Moser, Alecia; Grenell, Amanda; Dickerson, Kelly; Yao, Qianwen; Gerhardstein, Peter; Barr, Rachel

    2015-01-01

    Young children typically demonstrate a transfer deficit, learning less from video than live presentations. Semantically meaningful context has been demonstrated to enhance learning in young children. We examined the effect of a semantically meaningful context on toddlers’ imitation performance. Two- and 2.5-year-olds participated in a puzzle imitation task to examine learning from either a live or televised model. The model demonstrated how to assemble a three-piece puzzle to make a fish or a boat, with the puzzle demonstration occurring against a semantically meaningful background context (ocean) or a yellow background (no context). Participants in the video condition performed significantly worse than participants in the live condition, demonstrating the typical transfer deficit effect. While the context helped improve overall levels of imitation, especially for the boat puzzle, only individual differences in the ability to self-generate a stimulus label were associated with a reduction in the transfer deficit. PMID:26029131

  3. Do semantic contextual cues facilitate transfer learning from video in toddlers?

    PubMed

    Zimmermann, Laura; Moser, Alecia; Grenell, Amanda; Dickerson, Kelly; Yao, Qianwen; Gerhardstein, Peter; Barr, Rachel

    2015-01-01

    Young children typically demonstrate a transfer deficit, learning less from video than live presentations. Semantically meaningful context has been demonstrated to enhance learning in young children. We examined the effect of a semantically meaningful context on toddlers' imitation performance. Two- and 2.5-year-olds participated in a puzzle imitation task to examine learning from either a live or televised model. The model demonstrated how to assemble a three-piece puzzle to make a fish or a boat, with the puzzle demonstration occurring against a semantically meaningful background context (ocean) or a yellow background (no context). Participants in the video condition performed significantly worse than participants in the live condition, demonstrating the typical transfer deficit effect. While the context helped improve overall levels of imitation, especially for the boat puzzle, only individual differences in the ability to self-generate a stimulus label were associated with a reduction in the transfer deficit. PMID:26029131

  4. Concept Learning in Early Childhood.

    ERIC Educational Resources Information Center

    Fowler, William

    1965-01-01

    Because disadvantaged children have usually experienced sensory-cognitive deprivation or distortion, it is necessary to discover ways to offset this deficit. A program is being conducted to learn to what degree the introduction of systematic programing, while motivation techniques are retained, can reorient essentially noncognitive learning styles…

  5. An exploration of the semantic network in Alzheimer's disease: Influence of emotion and concreteness of concepts.

    PubMed

    Giffard, Bénédicte; Laisney, Mickaël; Desgranges, Béatrice; Eustache, Francis

    2015-08-01

    Semantic deficits are often reported in even the very early stages of Alzheimer's disease (AD), but investigations usually focus on concrete and non-emotional entities, ignoring the broad range of concepts that feature in everyday conversations. Emotional concepts (e.g., snake) have been found to be processed more accurately than neutral ones (e.g., chair) in AD. Our aim here was therefore to explore the dimensions of both concreteness and emotion within the semantic framework, and in particular to determine whether abstract emotional words (e.g., grief) are processed as accurately as concrete emotional ones (e.g., snake) in AD. We administered a semantic priming (SP) task (lexical decision), yielding an implicit measurement of semantic memory, to 15 patients with AD and 31 normal controls. Concrete and abstract word pairs either shared a semantic relationship (e.g., table-chair, motive-reason), a semantic and emotional relationship (e.g., snake-viper; grief-sadness), or no relationship at all (e.g., pencil-horse). On the basis of response time differences between these conditions, we obtained four SP scores: concrete neutral SP, abstract neutral SP, concrete emotional SP, and abstract emotional SP. In the AD group, the SP score for abstract neutral concepts was not significant, and significantly below the other three SP scores, that seems to reflect a major deterioration in these concepts. An abnormal hyperpriming effect was observed in the concrete neutral SP condition (SP score significantly higher than that of controls), reflecting a partial deterioration in these concepts. These results suggest that, without an emotional relationship, abstract words deteriorate more quickly than concrete words. No such dissociation linked to the concreteness effect was observed with emotional words. Therefore, in AD, emotional concepts would be affected later, be they concrete or abstract. PMID:26094148

  6. Optimization of Teaching and Learning of Concepts.

    ERIC Educational Resources Information Center

    Kotter, Ludwig; And Others

    1990-01-01

    Discussion of the optimization of the instruction of concepts emphasizes theories of cognitive psychology. The development of instruments to record the mastery of concepts by fifth graders is described, variables of both instruction and learning are discussed, and a field experiment that compared the effectiveness of video directed instruction and…

  7. Apples are not the only fruit: the effects of concept typicality on semantic representation in the anterior temporal lobe

    PubMed Central

    Woollams, Anna M.

    2012-01-01

    Intuitively, an apple seems a fairly good example of a fruit, whereas an avocado seems less so. The extent to which an exemplar is representative of its category, referred to here as concept typicality, has long been thought to be a key dimension determining semantic representation. Concept typicality is, however, correlated with a number of other variables, in particular age of acquisition (AoA) and name frequency. Consideration of picture naming accuracy from a large case-series of semantic dementia (SD) patients demonstrated strong effects of concept typicality that were maximal in the moderately impaired patients, over and above the impact of AoA and name frequency. Induction of a temporary virtual lesion to the left anterior temporal lobe, the region most commonly affected in SD, via repetitive Transcranial Magnetic Stimulation produced an enhanced effect of concept typicality in the picture naming of normal participants, but did not affect the magnitude of the AoA or name frequency effects. These results indicate that concept typicality exerts its influence on semantic representations themselves, as opposed to the strength of connections outside the semantic system. To date, there has been little direct exploration of the dimension of concept typicality within connectionist models of intact and impaired conceptual representation, and these findings provide a target for future computational simulation. PMID:22529789

  8. Children's Learning of Geometrical Concepts Through Logo.

    ERIC Educational Resources Information Center

    Noss, Richard

    1987-01-01

    Exploratory study aimed to investigate elements of geometrical concepts that children learn through Logo programing. A test designed to assess three components of length and angle was administered to 84 children who had learned Logo for one year and 92 who had not. Data indicated a positive effect of Logo work on some items, but not all.…

  9. Context and Concepts in Mobile Learning

    ERIC Educational Resources Information Center

    Jaldemark, Jimmy

    2013-01-01

    This reflective paper discusses the contextual and situated character of concepts in mobile learning. It aims at challenging current conceptualizations of mobile learning by utilizing ideas from pragmatist and socio-cultural perspectives. This challenge includes a framework that embraces a distinction between interactional and transactional…

  10. Actively learning human gaze shifting paths for semantics-aware photo cropping.

    PubMed

    Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

    2014-05-01

    Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons. PMID:24723578

  11. Vocabulary relearning in semantic dementia: Positive and negative consequences of increasing variability in the learning experience

    PubMed Central

    Hoffman, Paul; Clarke, Natasha; Jones, Roy W.; Noonan, Krist A.

    2015-01-01

    Anomia therapy typically aims to improve patients' communication ability through targeted practice in naming a set of particular items. For such interventions to be of maximum benefit, the use of trained (or relearned) vocabulary must generalise from the therapy setting into novel situations. We investigated relearning in three patients with semantic dementia, a condition that has been associated with poor generalisation of relearned vocabulary. We tested two manipulations designed to improve generalisation of relearned words by introducing greater variation into the learning experience. In the first study, we found that trained items were retained more successfully when they were presented in a variety of different sequences during learning. In the second study, we found that training items using a range of different pictured exemplars improved the patients' ability to generalise words to novel instances of the same object. However, in one patient this came at the cost of inappropriate over-generalisations, in which trained words were incorrectly used to name semantically or visually similar objects. We propose that more variable learning experiences benefit patients because they shift responsibility for learning away from the inflexible hippocampal learning system and towards the semantic system. The success of this approach therefore depends critically on the integrity of the semantic representations of the items being trained. Patients with naming impairments in the context of relatively mild comprehension deficits are most likely to benefit from this approach, while avoiding the negative consequences of over-generalisation. PMID:25585251

  12. New Semantic Learning in Patients With Large Medial Temporal Lobe Lesions

    PubMed Central

    Bayley, P.J.; O'Reilly, R.C.; Curran, T.; Squire, L.R.

    2008-01-01

    Two patients with large lesions of the medial temporal lobe were given four tests of semantic knowledge that could only have been acquired after the onset of their amnesia. In contrast to previous studies of postmorbid semantic learning, correct answers could be based on a simple, nonspecific sense of familiarity about single words, faces, or objects. According to recent computational models (for example, Norman and O'Reilly (2003) Psychol Rev 110:611–646), this characteristic should be optimal for detecting the kind of semantic learning that might be supported directly by the neocortex. Both patients exhibited some capacity for new learning, albeit at a level substantially below control performances. Notably, the correct answers appeared to reflect declarative memory. It was not the case that the correct answers simply popped out in some automatic way in the absence of any additional knowledge about the items. Rather, the few correct choices made by the patients tended to be accompanied by additional information about the chosen items, and the available knowledge appeared to be similar qualitatively to the kind of factual knowledge that healthy individuals gradually acquire over the years. The results are consistent with the idea that neocortical structures outside the medial temporal lobe are able to support some semantic learning, albeit to a very limited extent. Alternatively, the small amount of learning detected in the present study could depend on tissue within the posterior medial temporal lobe that remains intact in both patients. PMID:18306299

  13. Vocabulary relearning in semantic dementia: Positive and negative consequences of increasing variability in the learning experience.

    PubMed

    Hoffman, Paul; Clarke, Natasha; Jones, Roy W; Noonan, Krist A

    2015-09-01

    Anomia therapy typically aims to improve patients' communication ability through targeted practice in naming a set of particular items. For such interventions to be of maximum benefit, the use of trained (or relearned) vocabulary must generalise from the therapy setting into novel situations. We investigated relearning in three patients with semantic dementia, a condition that has been associated with poor generalisation of relearned vocabulary. We tested two manipulations designed to improve generalisation of relearned words by introducing greater variation into the learning experience. In the first study, we found that trained items were retained more successfully when they were presented in a variety of different sequences during learning. In the second study, we found that training items using a range of different pictured exemplars improved the patients' ability to generalise words to novel instances of the same object. However, in one patient this came at the cost of inappropriate over-generalisations, in which trained words were incorrectly used to name semantically or visually similar objects. We propose that more variable learning experiences benefit patients because they shift responsibility for learning away from the inflexible hippocampal learning system and towards the semantic system. The success of this approach therefore depends critically on the integrity of the semantic representations of the items being trained. Patients with naming impairments in the context of relatively mild comprehension deficits are most likely to benefit from this approach, while avoiding the negative consequences of over-generalisation. PMID:25585251

  14. A Proof-of-Concept for Semantically Interoperable Federation of IoT Experimentation Facilities.

    PubMed

    Lanza, Jorge; Sanchez, Luis; Gomez, David; Elsaleh, Tarek; Steinke, Ronald; Cirillo, Flavio

    2016-01-01

    The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. The potential of IoT technologies and deployments has been already demonstrated in a number of different application areas, including transport, energy, safety and healthcare. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming application silos. A lightweight data centric integration and combination of these silos presents several challenges that still need to be addressed. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potentiality of smart applications in terms of size, scope and targeted business context. In this article, a proof-of-concept implementation that federates two different IoT experimentation facilities by means of semantic-based technologies will be described. The specification and design of the implemented system and information models will be described together with the practical details of the developments carried out and its integration with the existing IoT platforms supporting the aforementioned testbeds. Overall, the system described in this paper demonstrates that it is possible to open new horizons in the development of IoT applications and experiments at a global scale, that transcend the (silo) boundaries of individual deployments, based on the semantic interconnection and interoperability of diverse IoT platforms and testbeds. PMID:27367695

  15. A Proof-of-Concept for Semantically Interoperable Federation of IoT Experimentation Facilities

    PubMed Central

    Lanza, Jorge; Sanchez, Luis; Gomez, David; Elsaleh, Tarek; Steinke, Ronald; Cirillo, Flavio

    2016-01-01

    The Internet-of-Things (IoT) is unanimously identified as one of the main pillars of future smart scenarios. The potential of IoT technologies and deployments has been already demonstrated in a number of different application areas, including transport, energy, safety and healthcare. However, despite the growing number of IoT deployments, the majority of IoT applications tend to be self-contained, thereby forming application silos. A lightweight data centric integration and combination of these silos presents several challenges that still need to be addressed. Indeed, the ability to combine and synthesize data streams and services from diverse IoT platforms and testbeds, holds the promise to increase the potentiality of smart applications in terms of size, scope and targeted business context. In this article, a proof-of-concept implementation that federates two different IoT experimentation facilities by means of semantic-based technologies will be described. The specification and design of the implemented system and information models will be described together with the practical details of the developments carried out and its integration with the existing IoT platforms supporting the aforementioned testbeds. Overall, the system described in this paper demonstrates that it is possible to open new horizons in the development of IoT applications and experiments at a global scale, that transcend the (silo) boundaries of individual deployments, based on the semantic interconnection and interoperability of diverse IoT platforms and testbeds. PMID:27367695

  16. "Clicking through" or Learning Concepts

    ERIC Educational Resources Information Center

    Stidwell, Peter

    2005-01-01

    The author has developed an innovative science website resource that also shows how engineers use science. As well as addressing scientific facts and concepts, the resource also engages children in the process of scientific enquiry, using graph tools and data interpretation. Part of the resource helps children to understand that much of what they…

  17. Context-Adaptive Learning Designs by Using Semantic Web Services

    ERIC Educational Resources Information Center

    Dietze, Stefan; Gugliotta, Alessio; Domingue, John

    2007-01-01

    IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources--whether data or services--within the learning design is done manually at design-time on the basis of the subjective appraisals…

  18. Semantic Search of Tools for Collaborative Learning with the Ontoolsearch System

    ERIC Educational Resources Information Center

    Vega-Gorgojo, Guillermo; Bote-Lorenzo, Miguel L.; Asensio-Perez, Juan I.; Gomez-Sanchez, Eduardo; Dimitriadis, Yannis A.; Jorrin-Abellan, Ivan M.

    2010-01-01

    This paper introduces Ontoolsearch, a new search system that can be employed by educators in order to find suitable tools for supporting collaborative learning settings. Current tool search facilities commonly allow simple keyword searches, limiting the accuracy of obtained results. In contrast, Ontoolsearch supports semantic querying of tool…

  19. The Effect of Semantic Feature Analysis on the Reading Comprehension of Learning Disabled Students.

    ERIC Educational Resources Information Center

    Anders, Patricia L.

    A study investigated whether semantic feature analysis (SFA) significantly improves the content related vocabulary knowledge and reading comprehension of adolescent, learning disabled readers. SFA is a set of vocabulary development activities designed to help students categorize vocabulary words and compare related ideas. Subjects, 62 learning…

  20. Contribution of Prior Semantic Knowledge to New Episodic Learning in Amnesia

    ERIC Educational Resources Information Center

    Kan, Irene P.; Alexander, Michael P.; Verfaellie, Mieke

    2009-01-01

    We evaluated whether prior semantic knowledge would enhance episodic learning in amnesia. Subjects studied prices that are either congruent or incongruent with prior price knowledge for grocery and household items and then performed a forced-choice recognition test for the studied prices. Consistent with a previous report, healthy controls'…

  1. Taxonomic Clustering and Frequency Associations as Features of Semantic Memory Development in Children with Learning Disabilities.

    ERIC Educational Resources Information Center

    Lee, Carolyn P.; Obrzut, John E.

    1994-01-01

    This study investigated taxonomic clustering and use of frequency associations as features in the semantic memory of children (n=30 in grades two and six) with learning disabilities (LD). Results suggested that, when individual child-generated word lists (i.e., meaningful) are used, children with LD may not be impaired in their ability to utilize…

  2. VastMM-Tag: Semantic Indexing and Browsing of Videos for E-Learning

    ERIC Educational Resources Information Center

    Morris, Mitchell J.

    2012-01-01

    Quickly accessing the contents of a video is challenging for users, particularly for unstructured video, which contains no intentional shot boundaries, no chapters, and no apparent edited format. We approach this problem in the domain of lecture videos though the use of machine learning, to gather semantic information about the videos; and through…

  3. Semantic Web-Driven LMS Architecture towards a Holistic Learning Process Model Focused on Personalization

    ERIC Educational Resources Information Center

    Kerkiri, Tania

    2010-01-01

    A comprehensive presentation is here made on the modular architecture of an e-learning platform with a distinctive emphasis on content personalization, combining advantages from semantic web technology, collaborative filtering and recommendation systems. Modules of this architecture handle information about both the domain-specific didactic…

  4. Investigating Orthographic and Semantic Aspects of Word Learning in Poor Comprehenders

    ERIC Educational Resources Information Center

    Ricketts, Jessie; Bishop, Dorothy V. M.; Nation, Kate

    2008-01-01

    This study compared orthographic and semantic aspects of word learning in children who differed in reading comprehension skill. Poor comprehenders and controls matched for age (9-10 years), nonverbal ability and decoding skill were trained to pronounce 20 visually presented nonwords, 10 in a consistent way and 10 in an inconsistent way. They then…

  5. Event-Related EEG Oscillations to Semantically Unrelated Words in Normal and Learning Disabled Children

    ERIC Educational Resources Information Center

    Fernandez, Thalia; Harmony, Thalia; Mendoza, Omar; Lopez-Alanis, Paula; Marroquin, Jose Luis; Otero, Gloria; Ricardo-Garcell, Josefina

    2012-01-01

    Learning disabilities (LD) are one of the most frequent problems for elementary school-aged children. In this paper, event-related EEG oscillations to semantically related and unrelated pairs of words were studied in a group of 18 children with LD not otherwise specified (LD-NOS) and in 16 children with normal academic achievement. We propose that…

  6. Word Learning by Preschoolers with Specific Language Impairment: Effect of Phonological or Semantic Cues

    ERIC Educational Resources Information Center

    Gray, Shelley

    2005-01-01

    Purpose: This study investigated whether phonological or semantic encoding cues promoted better word learning for children with specific language impairment (SLI) and whether this treatment differentially affected children with SLI and normal language (NL). Method: Twenty-four preschoolers ages 4;0 (years;months) to 5;11 with SLI and 24 age- and…

  7. Applying an exemplar model to an implicit rule-learning task: Implicit learning of semantic structure.

    PubMed

    Chubala, Chrissy M; Johns, Brendan T; Jamieson, Randall K; Mewhort, D J K

    2016-06-01

    Studies of implicit learning often examine peoples' sensitivity to sequential structure. Computational accounts have evolved to reflect this bias. An experiment conducted by Neil and Higham [Neil, G. J., & Higham, P. A.(2012). Implicit learning of conjunctive rule sets: An alternative to artificial grammars. Consciousness and Cognition, 21, 1393-1400] points to limitations in the sequential approach. In the experiment, participants studied words selected according to a conjunctive rule. At test, participants discriminated rule-consistent from rule-violating words but could not verbalize the rule. Although the data elude explanation by sequential models, an exemplar model of implicit learning can explain them. To make the case, we simulate the full pattern of results by incorporating vector representations for the words used in the experiment, derived from the large-scale semantic space models LSA and BEAGLE, into an exemplar model of memory, MINERVA 2. We show that basic memory processes in a classic model of memory capture implicit learning of non-sequential rules, provided that stimuli are appropriately represented. PMID:26730987

  8. A formal concept analysis and semantic query expansion cooperation to refine health outcomes of interest

    PubMed Central

    2015-01-01

    Background Electronic Health Records (EHRs) are frequently used by clinicians and researchers to search for, extract, and analyze groups of patients by defining Health Outcome of Interests (HOI). The definition of an HOI is generally considered a complex and time consuming task for health care professionals. Methods In our clinical note-based pharmacovigilance research, we often operate upon potentially hundreds of ontologies at once, expand query inputs, and we also increase the search space over clinical text as well as structured data. Such a method implies to specify an initial set of seed concepts, which are based on concept unique identifiers. This paper presents a novel method based on Formal Concept Analysis (FCA) and Semantic Query Expansion (SQE) to assist the end-user in defining their seed queries and in refining the expanded search space that it encompasses. Results We evaluate our method over a gold-standard corpus from the 2008 i2b2 Obesity Challenge. This experimentation emphasizes positive results for sensitivity and specificity measures. Our new approach provides better recall with high precision of the obtained results. The most promising aspect of this approach consists in the discovery of positive results not present our Obesity NLP reference set. Conclusions Together with a Web graphical user interface, our FCA and SQE cooperation end up being an efficient approach for refining health outcome of interest using plain terms. We consider that this approach can be extended to support other domains such as cohort building tools. PMID:26043839

  9. Learning computer science concepts with Scratch

    NASA Astrophysics Data System (ADS)

    Meerbaum-Salant, Orni; Armoni, Michal; (Moti) Ben-Ari, Mordechai

    2013-09-01

    Scratch is a visual programming environment that is widely used by young people. We investigated if Scratch can be used to teach concepts of computer science (CS). We developed learning materials for middle-school students that were designed according to the constructionist philosophy of Scratch and evaluated them in a few schools during two years. Tests were constructed based upon a novel combination of the revised Bloom taxonomy and the Structure of the Observed Learning Outcome taxonomy. These instruments were augmented with qualitative tools, such as observations and interviews. The results showed that students could successfully learn important concepts of CS, although there were problems with some concepts such as repeated execution, variables, and concurrency. We believe that these problems can be overcome by modifications to the teaching process that we suggest.

  10. A Concept Transformation Learning Model for Architectural Design Learning Process

    ERIC Educational Resources Information Center

    Wu, Yun-Wu; Weng, Kuo-Hua; Young, Li-Ming

    2016-01-01

    Generally, in the foundation course of architectural design, much emphasis is placed on teaching of the basic design skills without focusing on teaching students to apply the basic design concepts in their architectural designs or promoting students' own creativity. Therefore, this study aims to propose a concept transformation learning model to…

  11. Animated and Static Concept Maps Enhance Learning from Spoken Narration

    ERIC Educational Resources Information Center

    Adesope, Olusola O.; Nesbit, John C.

    2013-01-01

    An animated concept map represents verbal information in a node-link diagram that changes over time. The goals of the experiment were to evaluate the instructional effects of presenting an animated concept map concurrently with semantically equivalent spoken narration. The study used a 2 x 2 factorial design in which an animation factor (animated…

  12. Semantic Web Technologies for the Integration of Learning Tools and Context-Aware Educational Services

    NASA Astrophysics Data System (ADS)

    Jeremić, Zoran; Jovanović, Jelena; Gašević, Dragan

    One of the main software engineers' competencies, solving software problems, is most effectively acquired through an active examination of learning resources and work on real-world examples in small development teams. This obviously indicates a need for an integration of several existing learning tools and systems in a common collaborative learning environment, as well as advanced educational services that provide students with right in time advice about learning resources and possible collaboration partners. In this paper, we present how we developed and applied a common ontological foundation for the integration of different existing learning tools and systems in a common learning environment called DEPTHS (Design Patterns Teaching Help System). In addition, we present a set of educational services that leverages semantic rich representation of learning resources and students' interaction data to recommend resource relevant for students' current learning context.

  13. Timely Diagnostic Feedback for Database Concept Learning

    ERIC Educational Resources Information Center

    Lin, Jian-Wei; Lai, Yuan-Cheng; Chuang, Yuh-Shy

    2013-01-01

    To efficiently learn database concepts, this work adopts association rules to provide diagnostic feedback for drawing an Entity-Relationship Diagram (ERD). Using association rules and Asynchronous JavaScript and XML (AJAX) techniques, this work implements a novel Web-based Timely Diagnosis System (WTDS), which provides timely diagnostic feedback…

  14. Expert Concept Mapping Study on Mobile Learning

    ERIC Educational Resources Information Center

    Borner, Dirk; Glahn, Christian; Stoyanov, Slavi; Kalz, Marco; Specht, Marcus

    2010-01-01

    Purpose: The present paper introduces concept mapping as a structured participative conceptualization approach to identify clusters of ideas and opinions generated by experts within the domain of mobile learning. Utilizing this approach, the paper aims to contribute to a definition of key domain characteristics by identifying the main educational…

  15. Conceptions of Language and Language Learning.

    ERIC Educational Resources Information Center

    Benson, Phil; Lor, Winnie

    1999-01-01

    Questions whether the notion of learner beliefs as conceived in the second-language-acquisition literature is adequate to capture the complexity of learners' thinking about language learning. Proposes, as an alternative, an analytical framework based on three levels: conception, approach, and belief. Data are drawn from Hong Kong university…

  16. Learning Abstract Statistics Concepts Using Simulation

    ERIC Educational Resources Information Center

    Mills, Jamie D.

    2004-01-01

    The teaching and learning of statistics has impacted the curriculum in elementary, secondary, and post-secondary education. Because of this growing movement to expand and include statistics into all levels of education, there is also a considerable interest in how to teach statistics. For statistics concepts that tend to be very difficult or…

  17. Learning Computer Science Concepts with Scratch

    ERIC Educational Resources Information Center

    Meerbaum-Salant, Orni; Armoni, Michal; Ben-Ari, Mordechai

    2013-01-01

    Scratch is a visual programming environment that is widely used by young people. We investigated if Scratch can be used to teach concepts of computer science (CS). We developed learning materials for middle-school students that were designed according to the constructionist philosophy of Scratch and evaluated them in a few schools during two…

  18. Role of Concept Cartoons in Chemistry Learning

    ERIC Educational Resources Information Center

    Gafoor, Kunnathodi Abdul; Shilna, V.

    2013-01-01

    Cartoons are valuable aids that prompt interest and foster genuine student engagement in the classroom. Cartoons are part of a much larger effort to introduce rare and amusing activities to boost learning and student participation. Concept cartoons are visual tools composed of three or more characters' proposing ideas, discussing or thinking…

  19. Problem-Based Learning Supported by Semantic Techniques

    ERIC Educational Resources Information Center

    Lozano, Esther; Gracia, Jorge; Corcho, Oscar; Noble, Richard A.; Gómez-Pérez, Asunción

    2015-01-01

    Problem-based learning has been applied over the last three decades to a diverse range of learning environments. In this educational approach, different problems are posed to the learners so that they can develop different solutions while learning about the problem domain. When applied to conceptual modelling, and particularly to Qualitative…

  20. Relearning in Semantic Dementia Reflects Contributions from Both Medial Temporal Lobe Episodic and Degraded Neocortical Semantic Systems: Evidence in Support of the Complementary Learning Systems Theory

    ERIC Educational Resources Information Center

    Mayberry, Emily J.; Sage, Karen; Ehsan, Sheeba; Ralph, Matthew A. Lambon

    2011-01-01

    When relearning words, patients with semantic dementia (SD) exhibit a characteristic rigidity, including a failure to generalise names to untrained exemplars of trained concepts. This has been attributed to an over-reliance on the medial temporal region which captures information in sparse, non-overlapping and therefore rigid representations. The…

  1. Concept Learning for Achieving Personalized Ontologies: An Active Learning Approach

    NASA Astrophysics Data System (ADS)

    Şensoy, Murat; Yolum, Pinar

    In many multiagent approaches, it is usual to assume the existence of a common ontology among agents. However, in dynamic systems, the existence of such an ontology is unrealistic and its maintenance is cumbersome. Burden of maintaining a common ontology can be alleviated by enabling agents to evolve their ontologies personally. However, with different ontologies, agents are likely to run into communication problems since their vocabularies are different from each other. Therefore, to achieve personalized ontologies, agents must have a means to understand the concepts used by others. Consequently, this paper proposes an approach that enables agents to teach each other concepts from their ontologies using examples. Unlike other concept learning approaches, our approach enables the learner to elicit most informative examples interactively from the teacher. Hence, the learner participates to the learning process actively. We empirically compare the proposed approach with the previous concept learning approaches. Our experiments show that using the proposed approach, agents can learn new concepts successfully and with fewer examples.

  2. Evaluating Learning Objects across Boundaries: The Semantics of Localization

    ERIC Educational Resources Information Center

    Li, Jerry Z.; Nesbit, John C.; Richards, Griff

    2006-01-01

    Learning object repositories and evaluation tools have the potential to serve as sites for interaction among different cultures and communities of practice. This article outlines Web-based learning object evaluation tools that we have developed, describes our current efforts to extend those tools to a wider range of user communities, and considers…

  3. An Enhanced Personal Learning Environment Using Social Semantic Web Technologies

    ERIC Educational Resources Information Center

    Halimi, Khaled; Seridi-Bouchelaghem, Hassina; Faron-Zucker, Catherine

    2014-01-01

    Compared with learning in classrooms, classical e-learning systems are less adaptive and once a system that supports a particular strategy has been designed and implemented, it is less likely to change according to student's interactions and preferences. Remote educational systems should be developed to ensure as much as necessary the…

  4. Improving EFL Writing through Study of Semantic Concepts in Formulaic Language

    ERIC Educational Resources Information Center

    Schenck, Andrew D.; Choi, Wonkyung

    2015-01-01

    Within Asian EFL contexts such as South Korea, large class sizes, poor sources of input and an overreliance on the Grammar-Translation Method may negatively impact semantic and pragmatic development of writing content. Since formulaic language is imbued with syntactic, semantic and pragmatic linguistic features, it represents an ideal means to…

  5. What Is Learned when Concept Learning Fails?--A Theory of Restricted-Domain Relational Learning

    ERIC Educational Resources Information Center

    Wright, Anthony A.; Lickteig, Mark T.

    2010-01-01

    Two matching-to-sample (MTS) and four same/different (S/D) experiments employed tests to distinguish between item-specific learning and relational learning. One MTS experiment showed item-specific learning when concept learning failed (i.e., no novel-stimulus transfer). Another MTS experiment showed item-specific learning when pigeons'…

  6. The New Challenges for E-learning: The Educational Semantic Web

    ERIC Educational Resources Information Center

    Aroyo, Lora; Dicheva, Darina

    2004-01-01

    The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it?…

  7. Transforming Science and Learning Concepts of Physics Teachers.

    ERIC Educational Resources Information Center

    Flores, Fernando; Lopez, Angel; Gallegos, Leticia; Barojas, Jorge

    2000-01-01

    Addresses the influence that science and learning concepts have when teachers are submitted to assessment in an academic program. Reports changes shown by teachers in their epistemological and learning conceptions during the process of instruction. (Author/CCM)

  8. Lifelong learning: Established concepts and evolving values

    PubMed Central

    Talati, Jamsheer Jehangir

    2014-01-01

    Objective To summarise the concepts critical for understanding the content and value of lifelong learning (LL). Methods Ideas generated by personal experience were combined with those of philosophers, social scientists, educational institutions, governments and UNESCO, to facilitate an understanding of the importance of the basic concepts of LL. Results Autopoietic, continuous, self-determined, informal, vicarious, biographical, lifelong reflexive learning, from and for society, when supported by self-chosen formal courses, can build capacities and portable skills that allow useful responses to challenges and society’s new structures of governance. The need for LL is driven by challenges. LL flows continuously in pursuit of one agenda, which could either be citizenship, as is conventional, or as this article proposes, health. LL cannot be wholly centred on vocation. Continuous medical education and continuous professional development, important in their own right, cannot supply all that is needed. LL aids society with its learning, and it requires an awareness of the environment and structures of society. It is heavily vicarious, draws on formal learning and relies for effectiveness on reflection, self-assessment and personal shaping of views of the world from different perspectives. Conclusion Health is critical to rational thought and peace, and determines society’s capacity to govern itself, and improve its health. LL should be reshaped to focus on health not citizenship. Therefore, embedding learning in society and environment is critical. Each urologist must develop an understanding of the numerous concepts in LL, of which ‘biographicisation’ is the seed that will promote innovative strategies. PMID:26019932

  9. Concept Maps for Evaluating Learning of Sustainable Development

    ERIC Educational Resources Information Center

    Shallcross, David C.

    2016-01-01

    Concept maps are used to assess student and cohort learning of sustainable development. The concept maps of 732 first-year engineering students were individually analyzed to detect patterns of learning and areas that were not well understood. Students were given 20 minutes each to prepare a concept map of at least 20 concepts using paper and pen.…

  10. Semantic Linking of Learning Object Repositories to DBpedia

    ERIC Educational Resources Information Center

    Lama, Manuel; Vidal, Juan C.; Otero-Garcia, Estefania; Bugarin, Alberto; Barro, Senen

    2012-01-01

    Large-sized repositories of learning objects (LOs) are difficult to create and also to maintain. In this paper we propose a way to reduce this drawback by improving the classification mechanisms of the LO repositories. Specifically, we present a solution to automate the LO classification of the Universia repository, a collection of more than 15…

  11. Toward a Semantic Forum for Active Collaborative Learning

    ERIC Educational Resources Information Center

    Li, Yanyan; Dong, Mingkai; Huang, Ronghuai

    2009-01-01

    Online discussion forums provide open workspace allowing learners to share information, exchange ideas, address problems and discuss on specific themes. But the substantial impediment to its promotion as effective e-learning facility lies in the continuously increasing messages but with discrete and incoherent structure as well as the loosely-tied…

  12. Strengthening concept learning by repeated testing

    PubMed Central

    Wiklund-Hörnqvist, Carola; Jonsson, Bert; Nyberg, Lars

    2014-01-01

    The aim of this study was to examine whether repeated testing with feedback benefits learning compared to rereading of introductory psychology key-concepts in an educational context. The testing effect was examined immediately after practice, after 18 days, and at a five-week delay in a sample of undergraduate students (n = 83). The results revealed that repeated testing with feedback significantly enhanced learning compared to rereading at all delays, demonstrating that repeated retrieval enhances retention compared to repeated encoding in the short- and the long-term. In addition, the effect of repeated testing was beneficial for students irrespectively of working memory capacity. It is argued that teaching methods involving repeated retrieval are important to consider by the educational system. PMID:24313425

  13. Linking descriptive geology and quantitative machine learning through an ontology of lithological concepts

    NASA Astrophysics Data System (ADS)

    Klump, J. F.; Huber, R.; Robertson, J.; Cox, S. J. D.; Woodcock, R.

    2014-12-01

    Despite the recent explosion of quantitative geological data, geology remains a fundamentally qualitative science. Numerical data only constitute a certain part of data collection in the geosciences. In many cases, geological observations are compiled as text into reports and annotations on drill cores, thin sections or drawings of outcrops. The observations are classified into concepts such as lithology, stratigraphy, geological structure, etc. These descriptions are semantically rich and are generally supported by more quantitative observations using geochemical analyses, XRD, hyperspectral scanning, etc, but the goal is geological semantics. In practice it has been difficult to bring the different observations together due to differing perception or granularity of classification in human observation, or the partial observation of only some characteristics using quantitative sensors. In the past years many geological classification schemas have been transferred into ontologies and vocabularies, formalized using RDF and OWL, and published through SPARQL endpoints. Several lithological ontologies were compiled by stratigraphy.net and published through a SPARQL endpoint. This work is complemented by the development of a Python API to integrate this vocabulary into Python-based text mining applications. The applications for the lithological vocabulary and Python API are automated semantic tagging of geochemical data and descriptions of drill cores, machine learning of geochemical compositions that are diagnostic for lithological classifications, and text mining for lithological concepts in reports and geological literature. This combination of applications can be used to identify anomalies in databases, where composition and lithological classification do not match. It can also be used to identify lithological concepts in the literature and infer quantitative values. The resulting semantic tagging opens new possibilities for linking these diverse sources of data.

  14. The Influence of Prosodic Stress Patterns and Semantic Depth on Novel Word Learning in Typically Developing Children

    ERIC Educational Resources Information Center

    Gladfelter, Allison; Goffman, Lisa

    2013-01-01

    The goal of this study was to investigate the effects of prosodic stress patterns and semantic depth on word learning. Twelve preschool-aged children with typically developing speech and language skills participated in a word learning task. Novel words with either a trochaic or iambic prosodic pattern were embedded in one of two learning…

  15. Learning style preference and student aptitude for concept maps.

    PubMed

    Kostovich, Carol T; Poradzisz, Michele; Wood, Karen; O'Brien, Karen L

    2007-05-01

    Acknowledging that individuals' preferences for learning vary, faculty in an undergraduate nursing program questioned whether a student's learning style is an indicator of aptitude in developing concept maps. The purpose of this research was to describe the relationship between nursing students' learning style preference and aptitude for concept maps. The sample included 120 undergraduate students enrolled in the adult health nursing course. Students created one concept map and completed two instruments: the Learning Style Survey and the Concept Map Survey. Data included Learning Style Survey scores, grade for the concept map, and grade for the adult health course. No significant difference was found between learning style preference and concept map grades. Thematic analysis of the qualitative survey data yielded further insight into students' preferences for creating concept maps. PMID:17547346

  16. A Rational Analysis of Rule-Based Concept Learning

    ERIC Educational Resources Information Center

    Goodman, Noah D.; Tenenbaum, Joshua B.; Feldman, Jacob; Griffiths, Thomas L.

    2008-01-01

    This article proposes a new model of human concept learning that provides a rational analysis of learning feature-based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space--a concept language of logical rules. This article compares the model predictions to human generalization judgments in several…

  17. Learning from Concept Mapping and Hypertext: An Eye Tracking Study

    ERIC Educational Resources Information Center

    Amadieu, Franck; Salmerón, Ladislao; Cegarra, Julien; Paubel, Pierre-Vincent; Lemarié, Julie; Chevalier, Aline

    2015-01-01

    This study examined the effects of prior domain knowledge and learning sequences on learning with concept mapping and hypertext. Participants either made a concept map in a first step and then read the hypertext's contents combined with concept mapping (high activating condition), or they read the hypertext's contents first and then made a concept…

  18. Mining e-Learning Domain Concept Map from Academic Articles

    ERIC Educational Resources Information Center

    Chen, Nian-Shing; Kinshuk; Wei, Chun-Wang; Chen, Hong-Jhe

    2008-01-01

    Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials, designers need to refer to the concept map of a subject domain. Moreover, concept maps can show the whole picture and core knowledge about a subject domain. Research…

  19. CASE--A PROGRAM FOR SIMULATION OF CONCEPT LEARNING.

    ERIC Educational Resources Information Center

    BAKER, FRANK B.

    THE "CASE" PROGRAM WAS DEVELOPED TO PROVIDE A VEHICLE FOR UNDERSTANDING THE PSYCHOLOGICAL PROCESSES INVOLVED IN CONCEPT LEARNING BY MEANS OF COMPUTER SIMULATION TECHNIQUES. BECAUSE THE MAJORITY OF PUBLISHED "SIMULATION OF CONCEPT LEARNING" PROGRAMS PROVIDED FEW INSIGHTS INTO THE LEARNING PROCESS, THE "CASE" PROGRAM WAS DESIGNED TO PROVIDE A BETTER…

  20. Conception of Learning Outcomes in the Bloom's Taxonomy Affective Domain

    ERIC Educational Resources Information Center

    Savickiene, Izabela

    2010-01-01

    The article raises a problematic issue regarding an insufficient base of the conception of learning outcomes in the Bloom's taxonomy affective domain. The search for solutions introduces the conception of teaching and learning in the affective domain as well as presents validity criteria of learning outcomes in the affective domain. The…

  1. Effects of Variation and Prior Knowledge on Abstract Concept Learning

    ERIC Educational Resources Information Center

    Braithwaite, David W.; Goldstone, Robert L.

    2015-01-01

    Learning abstract concepts through concrete examples may promote learning at the cost of inhibiting transfer. The present study investigated one approach to solving this problem: systematically varying superficial features of the examples. Participants learned to solve problems involving a mathematical concept by studying either superficially…

  2. Using Online Concept Mapping with Peer Learning to Enhance Concept Application

    ERIC Educational Resources Information Center

    Chang, Shujen L.; Chang, Yegmin

    2008-01-01

    This study used an online concept mapping activity (CMA) featuring peer learning to enhance learning achievement in concept application. Ninety-seven graduate students participated in this study. The students who participated in the online CMA could later apply the concepts with significantly higher performance and greater fidelity than those who…

  3. The dark side of incremental learning: A model of cumulative semantic interference during lexical access in speech production

    PubMed Central

    Oppenheim, Gary M.; Dell, Gary S.; Schwartz, Myrna F.

    2010-01-01

    Naming a picture of a dog primes the subsequent naming of a picture of a dog (repetition priming) and interferes with the subsequent naming of a picture of a cat (semantic interference). Behavioral studies suggest that these effects derive from persistent changes in the way that words are activated and selected for production, and some have claimed that the findings are only understandable by positing a competitive mechanism for lexical selection. We present a simple model of lexical retrieval in speech production that applies error-driven learning to its lexical activation network. This model naturally produces repetition priming and semantic interference effects. It predicts the major findings from several published experiments, demonstrating that these effects may arise from incremental learning. Furthermore, analysis of the model suggests that competition during lexical selection is not necessary for semantic interference if the learning process is itself competitive. PMID:19854436

  4. Concept learning set-size functions for Clark's nutcrackers.

    PubMed

    Wright, Anthony A; Magnotti, John F; Katz, Jeffrey S; Leonard, Kevin; Kelly, Debbie M

    2016-01-01

    Same/Different abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana) was tested with novel stimuli following learning of training set expansion (8, 16, 32, 64, 128, 256, 512, and 1024 picture items). The resulting set-size function was compared to those from rhesus monkeys (Macaca mulatta), capuchin monkeys (Cebus apella), and pigeons (Columba livia). Nutcrackers showed partial concept learning following initial eight-item set learning, unlike the other species (Magnotti, Katz, Wright, & Kelly, 2015). The mean function for the nutcrackers' novel-stimulus transfer increased linearly as a function of the logarithm of training set size, which intersected its baseline function at the 128-item set size. Thus, nutcrackers on average achieved full concept learning (i.e., transfer statistically equivalent to baseline performance) somewhere between set sizes of 64 to 128 items, similar to full concept learning by monkeys. Pigeons required a somewhat larger training set (256 items) for full concept learning, but results from other experiments (initial training and transfer with 32- and 64-item set sizes) suggested carryover effects with smaller set sizes may have artificially prolonged the pigeon's full concept learning. We find it remarkable that these diverse species with very different neural architectures can fully learn this same/different abstract concept, and (at least under some conditions) do so with roughly similar sets sizes (64-128 items) and numbers of training exemplars, despite initial concept learning advantages (nutcrackers), learning disadvantages (pigeons), or increasing baselines (monkeys). PMID:26615450

  5. Threshold Concepts and Conceptions: Student Learning in Introductory Management Courses

    ERIC Educational Resources Information Center

    Wright, April L.; Gilmore, Anne

    2012-01-01

    This article explores how insights from the broader education literature on threshold concepts and conceptions can be applied to improve the teaching of undergraduate introductory management courses. The authors propose that these courses are underpinned by the threshold conception, or "underlying game," that management is a practice informed by…

  6. Microeconomic Concepts Students Should Learn before Intermediate Macroeconomics.

    ERIC Educational Resources Information Center

    Salemi, Michael K.

    1996-01-01

    Identifies four microeconomic concepts students should learn before entering the study of intermediate macroeconomics. Included are relative prices, general versus partial equilibrium, constrained optimization, and the nature of production concepts. Recommends making intermediate microeconomics a prerequisite for intermediate macroeconomics. (MJP)

  7. Learning from others: children's construction of concepts.

    PubMed

    Gelman, Susan A

    2009-01-01

    Much of children's knowledge is derived not from their direct experiences with the environment but rather from the input of others. However, until recently, the focus in studies of concept development was primarily on children's knowledge, with relatively little attention paid to the nature of the input. The past 10 years have seen an important shift in focus. This article reviews this approach, by examining the nature of the input and the nature of the learner, to shed light on early conceptual learning. These findings argue against the simple notion that conceptual development is either supplied by the environment or innately specified, and instead demonstrate how the two work together. The implications for how children reconcile competing belief systems are also discussed. PMID:18631027

  8. The Development of the Conceptions of Learning Management Inventory

    ERIC Educational Resources Information Center

    Lin, Hung-Ming; Tsai, Chin-Chung

    2013-01-01

    The purpose of this study was to develop a questionnaire (called the Conceptions of Learning Management [COLM] inventory) to assess students' six categories of learning management (i.e. the learning of management), including learning management as "memorizing," "testing,'" "applying," "gaining higher…

  9. Reflections on the Concept and the Logic of Learning.

    ERIC Educational Resources Information Center

    Koch, Lutz

    1988-01-01

    In the theory of learning, the psychological approach is predominant whereas the logic of cognitive learning has fallen into oblivion. Referring to these two approaches, the author specifies basic differentiations of the concept of learning and defines the main stages in the process of learning. (Author/BSR)

  10. A semantic-based method for extracting concept definitions from scientific publications: evaluation in the autism phenotype domain

    PubMed Central

    2013-01-01

    Background A variety of informatics approaches have been developed that use information retrieval, NLP and text-mining techniques to identify biomedical concepts and relations within scientific publications or their sentences. These approaches have not typically addressed the challenge of extracting more complex knowledge such as biomedical definitions. In our efforts to facilitate knowledge acquisition of rule-based definitions of autism phenotypes, we have developed a novel semantic-based text-mining approach that can automatically identify such definitions within text. Results Using an existing knowledge base of 156 autism phenotype definitions and an annotated corpus of 26 source articles containing such definitions, we evaluated and compared the average rank of correctly identified rule definition or corresponding rule template using both our semantic-based approach and a standard term-based approach. We examined three separate scenarios: (1) the snippet of text contained a definition already in the knowledge base; (2) the snippet contained an alternative definition for a concept in the knowledge base; and (3) the snippet contained a definition not in the knowledge base. Our semantic-based approach had a higher average rank than the term-based approach for each of the three scenarios (scenario 1: 3.8 vs. 5.0; scenario 2: 2.8 vs. 4.9; and scenario 3: 4.5 vs. 6.2), with each comparison significant at the p-value of 0.05 using the Wilcoxon signed-rank test. Conclusions Our work shows that leveraging existing domain knowledge in the information extraction of biomedical definitions significantly improves the correct identification of such knowledge within sentences. Our method can thus help researchers rapidly acquire knowledge about biomedical definitions that are specified and evolving within an ever-growing corpus of scientific publications. PMID:23937724

  11. Concept of coherence of learning physical optics

    NASA Astrophysics Data System (ADS)

    Colombo, Elisa M.; Jaen, Mirta; de Cudmani, Leonor C.

    1995-10-01

    The aim of the actual paper is to enhance achievements of the text 'Optica Fisica Basica: estructurada alrededor del concepto de coherencia luminosa' (in English 'Basic Physical Optics centered in the concept of coherence'). We consider that this book is a very worth tool when one has to learn or to teach some fundamental concepts of physical optics. It is well known that the topics of physical optics present not easy understanding for students. Even more they also present some difficulties for the teachers when they have to introduce them to the class. First, we think that different phenomena like diffraction and polarization could be well understood if the starting point is a deep comprehension of the concept of interference of light and, associated with this, the fundamental and nothing intuitive concept of coherence of the light. In the reference text the authors propose the use of expression 'stable interference pattern of no uniform intensity' instead of 'pattern of interference' and 'average pattern of uniform untested' instead of 'lack of interference' to make reference that light always interfere but just under restrictive conditions it can be got temporal and spatial stability of the pattern. Another idea we want to stand out is that the ability to observe a 'stable interference pattern of no uniform intensity' is associated not only with the coherence of the source but also with the dimensions of the experimental system and with the temporal and spatial characteristics of the detector used - human eye, photographic film, etc. The proposal is well support by quantitative relations. With an alternate model: a train of waves with a finite length of coherence, it is possible to get range of validity of models, to decide when a source could be considered a 'point' or 'monochromatic' or 'remote', an 'infinite' wave or a train of waves, etc. Using this concept it is possible to achieve a better understanding of phenomena like the polarization of light. Here, it

  12. Visual statistical learning based on the perceptual and semantic information of objects.

    PubMed

    Otsuka, Sachio; Nishiyama, Megumi; Nakahara, Fumitaka; Kawaguchi, Jun

    2013-01-01

    Five experiments examined what is learned based on the perceptual and semantic information of objects in visual statistical learning (VSL). In the familiarization phase, participants viewed a sequence of line drawings and detected repetitions of various objects. In a subsequent test phase, they watched 2 test sequences (statistically related triplets vs. unrelated foils) and decided whether the first or second sequence was more familiar based on the familiarization phase. In Experiment 1A, the test sequences comprised line drawings; in Experiment 1B, they comprised word stimuli representing each line drawing. The results showed that performance for statistically related triplets was greater than chance. In Experiments 2 and 3 containing the forward ABC and backward CBA triplets in the test, the results showed the importance of temporal order, especially in line drawings. In Experiment 4, in which the forward triplets were pitted against the backward triplets, we showed that temporal order is still important for the expression of VSL with word stimuli. Finally, in Experiment 5, we replicated the results of Experiments 2 and 3 even with the images of visual objects. These results suggest the parallel processes on the visual features and semantic information of objects in VSL. PMID:22686848

  13. From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

    PubMed

    De Meo, Rosanna; Bourquin, Nathalie M-P; Knebel, Jean-François; Murray, Micah M; Clarke, Stephanie

    2015-09-01

    Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra

  14. Concept Mapping Using Cmap Tools to Enhance Meaningful Learning

    NASA Astrophysics Data System (ADS)

    Cañas, Alberto J.; Novak, Joseph D.

    Concept maps are graphical tools that have been used in all facets of education and training for organizing and representing knowledge. When learners build concept maps, meaningful learning is facilitated. Computer-based concept mapping software such as CmapTools have further extended the use of concept mapping and greatly enhanced the potential of the tool, facilitating the implementation of a concept map-centered learning environment. In this chapter, we briefly present concept mapping and its theoretical foundation, and illustrate how it can lead to an improved learning environment when it is combined with CmapTools and the Internet. We present the nationwide “Proyecto Conéctate al Conocimiento” in Panama as an example of how concept mapping, together with technology, can be adopted by hundreds of schools as a means to enhance meaningful learning.

  15. Preservice Teacher Education Students' Epistemological Beliefs and Conceptions about Learning

    ERIC Educational Resources Information Center

    Chan, Kwok-Wai

    2011-01-01

    A questionnaire was administered to 231 Hong Kong preservice teacher education students to examine their epistemological beliefs and conceptions of learning. Pearson correlation analysis showed significant pairs of epistemological beliefs and conceptions of learning. Regression and path analysis showed epistemological beliefs had significant…

  16. Facilitating Image Search With a Scalable and Compact Semantic Mapping.

    PubMed

    Wang, Meng; Li, Weisheng; Liu, Dong; Ni, Bingbing; Shen, Jialie; Yan, Shuicheng

    2015-08-01

    This paper introduces a novel approach to facilitating image search based on a compact semantic embedding. A novel method is developed to explicitly map concepts and image contents into a unified latent semantic space for the representation of semantic concept prototypes. Then, a linear embedding matrix is learned that maps images into the semantic space, such that each image is closer to its relevant concept prototype than other prototypes. In our approach, the semantic concepts equated with query keywords and the images mapped into the vicinity of the prototype are retrieved by our scheme. In addition, a computationally efficient method is introduced to incorporate new semantic concept prototypes into the semantic space by updating the embedding matrix. This novelty improves the scalability of the method and allows it to be applied to dynamic image repositories. Therefore, the proposed approach not only narrows semantic gap but also supports an efficient image search process. We have carried out extensive experiments on various cross-modality image search tasks over three widely-used benchmark image datasets. Results demonstrate the superior effectiveness, efficiency, and scalability of our proposed approach. PMID:25248210

  17. GenieTutor: A Computer Assisted Second-Language Learning System Based on Semantic and Grammar Correctness Evaluations

    ERIC Educational Resources Information Center

    Kwon, Oh-Woog; Lee, Kiyoung; Kim, Young-Kil; Lee, Yunkeun

    2015-01-01

    This paper introduces a Dialog-Based Computer-Assisted second-Language Learning (DB-CALL) system using semantic and grammar correctness evaluations and the results of its experiment. While the system dialogues with English learners about a given topic, it automatically evaluates the grammar and content properness of their English utterances, then…

  18. The degraded concept representation system in semantic dementia: damage to pan-modal hub, then visual spoke.

    PubMed

    Hoffman, Paul; Jones, Roy W; Ralph, Matthew A Lambon

    2012-12-01

    The core clinical feature of semantic dementia is a progressive yet selective degradation of conceptual knowledge. Understanding the cognitive and neuroanatomical basis for this deficit is a key challenge for both clinical and basic science. Some researchers attribute the deficit to damage to pan-modal conceptual representations that are independent of any particular sensory-motor modality and are represented in the ventrolateral anterior temporal lobes. Others claim that damage to modality-specific visual feature representations in the occipitotemporal 'ventral stream' is responsible. In the present study, we tested the hypothesis that concept degradation in semantic dementia involves a combination of these pan-modal and modality-specific elements. We investigated factors influencing knowledge of object concepts by analysing 43 sets of picture-naming data from patients with semantic dementia. We found a strong influence of two pan-modal factors: highly familiar and typical items were named more accurately than less familiar/atypical items at all stages of the disorder. Items associated with rich sensory-motor information were also named more successfully at all stages, and this effect was present for sound/motion knowledge and tactile/action knowledge when these modalities were studied separately. However, there was no advantage for items rich in visual colour/form characteristics; instead, this factor had an increasingly negative impact in the later stages of the disorder. We propose that these results are best explained by a combination of (i) degradation of modality-independent conceptual representations, which is present throughout the disorder and is a consequence of atrophy focused on the ventrolateral anterior temporal lobes; and (ii) a later additional deficit for concepts that depend heavily on visual colour/form information, caused by the spreading of atrophy to posterior ventral temporal regions specialized for representing this information. This

  19. Development of Preschoolers' Learning, Retention, and Generalization of Concepts.

    ERIC Educational Resources Information Center

    Becker, Judith A.; Perlmutter, Marion

    This study, which indicates that both age and variation in training affect children's concept formation, provides a basis for explaining the effect of age. Sixty-four 4- and 5-year-olds learned three novel concepts (animal-like, plant-like, and machine-like). Subjects were presented with either four different examples of each concept (multiple…

  20. Teaching and Learning the Concept of Chemical Bonding

    ERIC Educational Resources Information Center

    Levy Nahum, Tami; Mamlok-Naaman, Rachel; Hofstein, Avi; Taber, Keith S.

    2010-01-01

    Chemical bonding is one of the key and basic concepts in chemistry. The learning of many of the concepts taught in chemistry, in both secondary schools as well as in the colleges, is dependent upon understanding fundamental ideas related to chemical bonding. Nevertheless, the concept is perceived by teachers, as well as by learners, as difficult,…

  1. Superior abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana)

    PubMed Central

    Magnotti, John F.; Katz, Jeffrey S.; Wright, Anthony A.; Kelly, Debbie M.

    2015-01-01

    The ability to learn abstract relational concepts is fundamental to higher level cognition. In contrast to item-specific concepts (e.g. pictures containing trees versus pictures containing cars), abstract relational concepts are not bound to particular stimulus features, but instead involve the relationship between stimuli and therefore may be extrapolated to novel stimuli. Previous research investigating the same/different abstract concept has suggested that primates might be specially adapted to extract relations among items and would require fewer exemplars of a rule to learn an abstract concept than non-primate species. We assessed abstract-concept learning in an avian species, Clark's nutcracker (Nucifraga columbiana), using a small number of exemplars (eight pairs of the same rule, and 56 pairs of the different rule) identical to that previously used to compare rhesus monkeys, capuchin monkeys and pigeons. Nutcrackers as a group (N = 9) showed more novel stimulus transfer than any previous species tested with this small number of exemplars. Two nutcrackers showed full concept learning and four more showed transfer considerably above chance performance, indicating partial concept learning. These results show that the Clark's nutcracker, a corvid species well known for its amazing feats of spatial memory, learns the same/different abstract concept better than any non-human species (including non-human primates) yet tested on this same task. PMID:25972399

  2. Superior abstract-concept learning by Clark's nutcrackers (Nucifraga columbiana).

    PubMed

    Magnotti, John F; Katz, Jeffrey S; Wright, Anthony A; Kelly, Debbie M

    2015-05-01

    The ability to learn abstract relational concepts is fundamental to higher level cognition. In contrast to item-specific concepts (e.g. pictures containing trees versus pictures containing cars), abstract relational concepts are not bound to particular stimulus features, but instead involve the relationship between stimuli and therefore may be extrapolated to novel stimuli. Previous research investigating the same/different abstract concept has suggested that primates might be specially adapted to extract relations among items and would require fewer exemplars of a rule to learn an abstract concept than non-primate species. We assessed abstract-concept learning in an avian species, Clark's nutcracker (Nucifraga columbiana), using a small number of exemplars (eight pairs of the same rule, and 56 pairs of the different rule) identical to that previously used to compare rhesus monkeys, capuchin monkeys and pigeons. Nutcrackers as a group (N = 9) showed more novel stimulus transfer than any previous species tested with this small number of exemplars. Two nutcrackers showed full concept learning and four more showed transfer considerably above chance performance, indicating partial concept learning. These results show that the Clark's nutcracker, a corvid species well known for its amazing feats of spatial memory, learns the same/different abstract concept better than any non-human species (including non-human primates) yet tested on this same task. PMID:25972399

  3. The Effect of the Superordinate Concept and Presentation Form of Examples on Concept Learning.

    ERIC Educational Resources Information Center

    Ranzijn, Frederick J. A.

    1989-01-01

    Describes research with Dutch secondary school students that studied the effects of the presentation of more general (superordinate) concepts on the attainment of basic concepts, and the effects of two different forms of example presentation on concept learning. Computer based instruction and interactive video used in the study are described. (18…

  4. Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation.

    PubMed

    Clark, Alex M; Bunin, Barry A; Litterman, Nadia K; Schürer, Stephan C; Visser, Ubbo

    2014-01-01

    Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers. PMID:25165633

  5. Fast and accurate semantic annotation of bioassays exploiting a hybrid of machine learning and user confirmation

    PubMed Central

    Bunin, Barry A.; Litterman, Nadia K.; Schürer, Stephan C.; Visser, Ubbo

    2014-01-01

    Bioinformatics and computer aided drug design rely on the curation of a large number of protocols for biological assays that measure the ability of potential drugs to achieve a therapeutic effect. These assay protocols are generally published by scientists in the form of plain text, which needs to be more precisely annotated in order to be useful to software methods. We have developed a pragmatic approach to describing assays according to the semantic definitions of the BioAssay Ontology (BAO) project, using a hybrid of machine learning based on natural language processing, and a simplified user interface designed to help scientists curate their data with minimum effort. We have carried out this work based on the premise that pure machine learning is insufficiently accurate, and that expecting scientists to find the time to annotate their protocols manually is unrealistic. By combining these approaches, we have created an effective prototype for which annotation of bioassay text within the domain of the training set can be accomplished very quickly. Well-trained annotations require single-click user approval, while annotations from outside the training set domain can be identified using the search feature of a well-designed user interface, and subsequently used to improve the underlying models. By drastically reducing the time required for scientists to annotate their assays, we can realistically advocate for semantic annotation to become a standard part of the publication process. Once even a small proportion of the public body of bioassay data is marked up, bioinformatics researchers can begin to construct sophisticated and useful searching and analysis algorithms that will provide a diverse and powerful set of tools for drug discovery researchers. PMID:25165633

  6. Ideal versus School Learning: Analyzing Israeli Secondary School Students' Conceptions of Learning

    ERIC Educational Resources Information Center

    Hadar, Linor

    2009-01-01

    This study explored 130 secondary school students' conceptions of learning using an open-ended task, analyzed both qualitatively and quantitatively. Students' reality of learning comprised two separate spheres, ideal learning and school learning, which rarely interacted. Generally, students commented more about school than ideal learning. Factor…

  7. The self concept of the adolescent with learning disabilities.

    PubMed

    Rosenberg, B S; Gaier, E L

    1977-01-01

    The Coopersmith Self Esteem Inventory (CSEI) was administered to 23 Ss diagnosed to have learning disabilities, and normally achieving seventh graders (N = 70) to investigate: a) whether differences exist between the self-esteem of the adolescent with learning disabilities and the normally achieving adolescent, b) the dimensions of self concept in which these differences occur, and c) the relationship between self concept and the number of years in the special classroom for the adolescent with learning disabilities. The data were fitted to a 2 X 2 (ability X school) fixed effects non-orthogonal multivariate analysis of variance model. A significant difference (p less than .05) in "social self-peer" self concept favoring the "normally" achieving S's was found. A trend was evidenced for more negative "general self" and "school-academic" self concepts for the learning disabilities sample. Number of years in the special class did not appear associated with self concept as measured by the CSEI. PMID:596262

  8. Concept Mapping as a Learning Tool in Occupational Therapy Education.

    PubMed

    Grice, Kimatha

    2016-07-01

    This paper describes concept mapping and its use as a teaching and learning tool in an entry level occupational therapy program. In order for students to demonstrate their mastery of the concepts associated with a particular topic or body of knowledge, assignments involving concept maps were developed and used in two courses in an entry level occupational therapy program. Students were then surveyed about their perceptions and attitudes regarding the assignments. Students found the process of creating concept maps valuable to their learning of the content and the majority also enjoyed the process as a learning activity. The use of concept mapping as a way to encourage independent, individualized, and student-centered learning is discussed. PMID:26914229

  9. Human-level concept learning through probabilistic program induction.

    PubMed

    Lake, Brenden M; Salakhutdinov, Ruslan; Tenenbaum, Joshua B

    2015-12-11

    People learning new concepts can often generalize successfully from just a single example, yet machine learning algorithms typically require tens or hundreds of examples to perform with similar accuracy. People can also use learned concepts in richer ways than conventional algorithms-for action, imagination, and explanation. We present a computational model that captures these human learning abilities for a large class of simple visual concepts: handwritten characters from the world's alphabets. The model represents concepts as simple programs that best explain observed examples under a Bayesian criterion. On a challenging one-shot classification task, the model achieves human-level performance while outperforming recent deep learning approaches. We also present several "visual Turing tests" probing the model's creative generalization abilities, which in many cases are indistinguishable from human behavior. PMID:26659050

  10. Temporal Representation in Semantic Graphs

    SciTech Connect

    Levandoski, J J; Abdulla, G M

    2007-08-07

    A wide range of knowledge discovery and analysis applications, ranging from business to biological, make use of semantic graphs when modeling relationships and concepts. Most of the semantic graphs used in these applications are assumed to be static pieces of information, meaning temporal evolution of concepts and relationships are not taken into account. Guided by the need for more advanced semantic graph queries involving temporal concepts, this paper surveys the existing work involving temporal representations in semantic graphs.

  11. Deep Learning through Concept-Based Inquiry

    ERIC Educational Resources Information Center

    Donham, Jean

    2010-01-01

    Learning in the library should present opportunities to enrich student learning activities to address concerns of interest and cognitive complexity, but these must be tasks that call for in-depth analysis--not merely gathering facts. Library learning experiences need to demand enough of students to keep them interested and also need to be…

  12. The Impact of Second Language Learning on Semantic and Nonsemantic First Language Reading

    PubMed Central

    Nosarti, Chiara; Mechelli, Andrea; Green, David W.

    2010-01-01

    The relationship between orthography (spelling) and phonology (speech sounds) varies across alphabetic languages. Consequently, learning to read a second alphabetic language, that uses the same letters as the first, increases the phonological associations that can be linked to the same orthographic units. In subjects with English as their first language, previous functional imaging studies have reported increased left ventral prefrontal activation for reading words with spellings that are inconsistent with their orthographic neighbors (e.g., PINT) compared with words that are consistent with their orthographic neighbors (e.g., SHIP). Here, using functional magnetic resonance imaging (fMRI) in 17 Italian–English and 13 English–Italian bilinguals, we demonstrate that left ventral prefrontal activation for first language reading increases with second language vocabulary knowledge. This suggests that learning a second alphabetic language changes the way that words are read in the first alphabetic language. Specifically, first language reading is more reliant on both lexical/semantic and nonlexical processing when new orthographic to phonological mappings are introduced by second language learning. Our observations were in a context that required participants to switch between languages. They motivate future fMRI studies to test whether first language reading is also altered in contexts when the second language is not in use. PMID:19478033

  13. Integrating Concept Mapping and the Learning Cycle To Teach Diffusion and Osmosis Concepts to High School Biology Students.

    ERIC Educational Resources Information Center

    Odom, Arthur L.; Kelly, Paul V.

    2001-01-01

    Explores the effectiveness of concept mapping, the learning cycle, expository instruction, and a combination of concept mapping/learning cycle in promoting conceptual understanding of diffusion and osmosis. Concludes that the concept mapping/learning cycle and concept mapping treatment groups significantly outperformed the expository treatment…

  14. Collocation, Semantic Prosody, and Near Synonymy: A Cross-Linguistic Perspective

    ERIC Educational Resources Information Center

    Xiao, Richard; McEnery, Tony

    2006-01-01

    This paper explores the collocational behaviour and semantic prosody of near synonyms from a cross-linguistic perspective. The importance of these concepts to language learning is well recognized. Yet while collocation and semantic prosody have recently attracted much interest from researchers studying the English language, there has been little…

  15. Semantic Domain-Specific Functional Integration for Action-Related vs. Abstract Concepts

    ERIC Educational Resources Information Center

    Ghio, Marta; Tettamanti, Marco

    2010-01-01

    A central topic in cognitive neuroscience concerns the representation of concepts and the specific neural mechanisms that mediate conceptual knowledge. Recently proposed modal theories assert that concepts are grounded on the integration of multimodal, distributed representations. The aim of the present work is to complement the available…

  16. Aging and Semantic Activation.

    ERIC Educational Resources Information Center

    Howard, Darlene V.

    Three studies tested the theory that long term memory consists of a semantically organized network of concept nodes interconnected by leveled associations or relations, and that when a stimulus is processed, the corresponding concept node is assumed to be temporarily activated and this activation spreads to nearby semantically related nodes. In…

  17. Introducing Machine Learning Concepts with WEKA.

    PubMed

    Smith, Tony C; Frank, Eibe

    2016-01-01

    This chapter presents an introduction to data mining with machine learning. It gives an overview of various types of machine learning, along with some examples. It explains how to download, install, and run the WEKA data mining toolkit on a simple data set, then proceeds to explain how one might approach a bioinformatics problem. Finally, it includes a brief summary of machine learning algorithms for other types of data mining problems, and provides suggestions about where to find additional information. PMID:27008023

  18. Using Concept Mapping to Measure Learning Quality

    ERIC Educational Resources Information Center

    Hay, David; Kinchin, Ian

    2008-01-01

    Purpose: This paper aims to describe a method of teaching that is based on Novak's concept-mapping technique. Design/methodology/approach: The paper shows how concept mapping can be used to measure prior knowledge and how simple mapping exercises can promote the integration of teachers' and students' understandings in ways that are meaningful.…

  19. Threshold Concepts, Systems and Learning for Sustainability

    ERIC Educational Resources Information Center

    Sandri, Orana Jade

    2013-01-01

    This paper presents a framework for understanding the role that systems theory might play in education for sustainability (EfS). It offers a sketch and critique of Land and Meyer's notion of a "threshold concept", to argue that seeing systems as a threshold concept for sustainability is useful for understanding the processes of…

  20. Situated Language Learning: Concept, Significance and Forms

    ERIC Educational Resources Information Center

    Abdallah, Mahmoud M. S.

    2015-01-01

    Currently, there is a shift in language learning from the "acquisition" metaphor to the "participation" metaphor. This involves viewing learners as active constructors of knowledge who can collaborate together to create meaningful language learning situations and contextualised practices. Thus, this worksheet aims at exploring…

  1. Brain Event-Related Potential Correlates of Concept Learning.

    ERIC Educational Resources Information Center

    Federico, Pat-Anthony

    An irrelevant auditory probe procedure was used to evoke brain event-related potentials (ERPs) in 56 Navy recruits while they learned pulsed radar concepts presented to them in study booklets. A mastery test was administered to assess concept acquisition. The research issue was whether brain ERPs recorded while students are in the process of…

  2. Conceptions of Efficiency: Applications in Learning and Problem Solving

    ERIC Educational Resources Information Center

    Hoffman, Bobby; Schraw, Gregory

    2010-01-01

    The purpose of this article is to clarify conceptions, definitions, and applications of learning and problem-solving efficiency. Conceptions of efficiency vary within the field of educational psychology, and there is little consensus as to how to define, measure, and interpret the efficiency construct. We compare three diverse models that differ…

  3. Factors Related to Students' Learning of Biomechanics Concepts

    ERIC Educational Resources Information Center

    Hsieh, ChengTu; Smith, Jeremy D.; Bohne, Michael; Knudson, Duane

    2012-01-01

    The purpose of this study was to replicate and expand a previous study to identify the factors that affect students' learning of biomechanical concepts. Students were recruited from three universities (N = 149) located in the central and western regions of the United States. Data from 142 students completing the Biomechanics Concept Inventory…

  4. Students' Modelling in Learning the Concept of Speed

    ERIC Educational Resources Information Center

    Khikmiyah, Fatimatul; Lukito, Agung; Patahudin, Sitti Maesuri

    2012-01-01

    Previous research shows that speed is one of the most difficult in the upper grades of primary school. It is because students must take into consideration two variables; distance and time. Nevertheless, Indonesian students usually learn this concept as a transmission subject and teacher more emphasizes on formal mathematics in which the concept of…

  5. Conceptions of Programming: A Study into Learning To Program.

    ERIC Educational Resources Information Center

    Booth, Shirley

    This paper reports the results of a phenomenographic study which focused on identifying and describing the conceptions of programming and related phenomena of about 120 computer science and computer engineering students learning to program. The report begins by tracing developments in the students' conceptions of programming and its parts, and…

  6. The Twisting Path of Concept Development in Learning to Teach.

    ERIC Educational Resources Information Center

    Smagorinsky, Peter; Cook, Leslie Susan; Johnson, Tara Star

    2003-01-01

    Asserts that teacher education programs should emphasize pedagogical concepts that interweave theory and practice so that preservice teachers learn consistent, unified approaches to teaching, noting that the theory-practice dichotomy lacks the richness of Vygotsky's notion of concepts and recommending that teacher educators strive to teach…

  7. Conceptualizing and Describing Teachers' Learning of Pedagogical Concepts

    ERIC Educational Resources Information Center

    González, María José; Gómez, Pedro

    2014-01-01

    In this paper, we propose a model to explore how teachers learn pedagogical concepts in teacher education programs that expect them to become competent in lesson planning. In this context, we view pedagogical concepts as conceptual and methodological tools that help teachers to design a lesson plan on a topic, implement this lesson plan and assess…

  8. Productive Failure in Learning the Concept of Variance

    ERIC Educational Resources Information Center

    Kapur, Manu

    2012-01-01

    In a study with ninth-grade mathematics students on learning the concept of variance, students experienced either direct instruction (DI) or productive failure (PF), wherein they were first asked to generate a quantitative index for variance without any guidance before receiving DI on the concept. Whereas DI students relied only on the canonical…

  9. Influence of Audio-Visual Presentations on Learning Abstract Concepts.

    ERIC Educational Resources Information Center

    Lai, Shu-Ling

    2000-01-01

    Describes a study of college students that investigated whether various types of visual illustrations influenced abstract concept learning when combined with audio instruction. Discusses results of analysis of variance and pretest posttest scores in relation to learning performance, attitudes toward the computer-based program, and differences in…

  10. Learning the Electric Field Concept as Oriented Research Activity

    ERIC Educational Resources Information Center

    Furio, C.; Guisasola, J.; Almudi, J. M.; Ceberio, M.

    2003-01-01

    This work is grounded in a constructivistic conception of the learning of science, more particularly on the model known as teaching-learning as oriented research. In accordance with this theoretical basis we have developed an empirical research project to investigate the teaching of electrostatics in high schools. The designs developed have…

  11. Threshold Concepts: Impacts on Teaching and Learning at Tertiary Level

    ERIC Educational Resources Information Center

    Peter, Mira; Harlow, Ann

    2014-01-01

    This project explored teaching and learning of hard-to-learn threshold concepts in first-year English, an electrical engineering course, leadership courses, and in doctoral writing. The project was envisioned to produce disciplinary case studies that lecturers could use to reflect on and refine their curriculum and pedagogy, thereby contributing…

  12. Learning Essential Terms and Concepts in Statistics and Accounting

    ERIC Educational Resources Information Center

    Peters, Pam; Smith, Adam; Middledorp, Jenny; Karpin, Anne; Sin, Samantha; Kilgore, Alan

    2014-01-01

    This paper describes a terminological approach to the teaching and learning of fundamental concepts in foundation tertiary units in Statistics and Accounting, using an online dictionary-style resource (TermFinder) with customised "termbanks" for each discipline. Designed for independent learning, the termbanks support inquiring students…

  13. Testing a Conception of How School Leadership Influences Student Learning

    ERIC Educational Resources Information Center

    Leithwood, Kenneth; Patten, Sarah; Jantzi, Doris

    2010-01-01

    Purpose: This article describes and reports the results of testing a new conception of how leadership influences student learning ("The Four Paths"). Framework: Leadership influence is conceptualized as flowing along four paths (Rational, Emotions, Organizational, and Family) toward student learning. Each path is populated by multiple variables…

  14. Conceptions of and Approaches to Learning through Online Peer Assessment

    ERIC Educational Resources Information Center

    Yang, Yu-Fang; Tsai, Chin-Chung

    2010-01-01

    The present study investigated junior college students' conceptions of and approaches to learning via online peer assessment (PA) using a phenomenographic approach. Participants were 163 college students. Students were asked to accomplish a given learning task via an online PA system. Of the participants, 62 were interviewed after the activity.…

  15. Thematic knowledge, artifact concepts, and the left posterior temporal lobe: Where action and object semantics converge.

    PubMed

    Kalénine, Solène; Buxbaum, Laurel J

    2016-09-01

    Converging evidence supports the existence of functionally and neuroanatomically distinct taxonomic (similarity-based; e.g., hammer-screwdriver) and thematic (event-based; e.g., hammer-nail) semantic systems. Processing of thematic relations between objects has been shown to selectively recruit the left posterior temporoparietal cortex. Similar posterior regions have also been shown to be critical for knowledge of relationships between actions and manipulable human-made objects (artifacts). Based on the hypothesis that thematic relationships for artifacts rely, at least in part, on action relationships, we assessed the prediction that the same regions of the left posterior temporoparietal cortex would be critical for conceptual processing of artifact-related actions and thematic relations for artifacts. To test this hypothesis, we evaluated processing of taxonomic and thematic relations for artifacts and natural objects as well as artifact action knowledge (gesture recognition) abilities in a large sample of 48 stroke patients with a range of lesion foci in the left hemisphere. Like control participants, patients identified thematic relations faster than taxonomic relations for artifacts, whereas they identified taxonomic relations faster than thematic relations for natural objects. Moreover, response times (RTs) for identifying thematic relations for artifacts selectively predicted performance in gesture recognition. Whole brain Voxel-based Lesion-Symptom Mapping (VLSM) analyses and Region of Interest (ROI) regression analyses further demonstrated that lesions to the left posterior temporal cortex, overlapping with LTO and visual motion area hMT+, were associated both with relatively slower RTs in identifying thematic relations for artifacts and poorer artifact action knowledge in patients. These findings provide novel insights into the functional role of left posterior temporal cortex in thematic knowledge, and suggest that the close association between thematic

  16. Motor Knowledge Is One Dimension for Concept Organization: Further Evidence from a Chinese Semantic Dementia Case

    ERIC Educational Resources Information Center

    Lin, Nan; Guo, Qihao; Han, Zaizhu; Bi, Yanchao

    2011-01-01

    Neuropsychological and neuroimaging studies have indicated that motor knowledge is one potential dimension along which concepts are organized. Here we present further direct evidence for the effects of motor knowledge in accounting for categorical patterns across object domains (living vs. nonliving) and grammatical domains (nouns vs. verbs), as…

  17. Concept-based word learning in human infants

    PubMed Central

    Yin, Jun; Csibra, Gergely

    2015-01-01

    It is debated whether infants initially learn object labels by mapping them onto similarity-defining perceptual features or onto concepts of object kinds. We addressed this question by attempting to teach infants words for behaviorally defined action roles. In a series of experiments, we found that 14-month-olds could rapidly learn a label for the role the chaser plays in a chasing scenario, even when the different instances of chasers did not share perceptual features. Furthermore, when infants could choose, they preferred to interpret a novel label as expressing the actor’s role within the observed interaction rather than as being associated with the actor’s appearance. These results demonstrate that infants can learn labels as easily, or even easier, for concepts identified by abstract behavioral characteristics than by perceptual features. Thus, already at early stages of word learning, infants expect that novel words express concepts. PMID:26195636

  18. Concept-Based Word Learning in Human Infants.

    PubMed

    Yin, Jun; Csibra, Gergely

    2015-08-01

    Whether infants initially learn object labels by mapping them onto similarity-defining perceptual features or onto concepts of object kinds remains under debate. We addressed this question by attempting to teach infants words for behaviorally defined action roles. In a series of experiments, we found that 14-month-olds could rapidly learn a label for the role played by the chaser in a chasing scenario, even when the different instances of chasers did not share perceptual features. Furthermore, when infants could choose, they preferred to interpret a novel label as expressing the agent's role within the observed interaction rather than as being associated with the agent's appearance. These results demonstrate that infants can learn labels as easily (or even more easily) for concepts identified by abstract behavioral characteristics as for objects identified by perceptual features. Thus, at early stages of word learning, infants already expect that novel words express concepts. PMID:26195636

  19. Semantically Interoperable XML Data.

    PubMed

    Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

    2013-09-01

    XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

  20. Semantically Interoperable XML Data

    PubMed Central

    Vergara-Niedermayr, Cristobal; Wang, Fusheng; Pan, Tony; Kurc, Tahsin; Saltz, Joel

    2013-01-01

    XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. PMID:25298789

  1. Learning Low-Dimensional Representations of Medical Concepts

    PubMed Central

    Choi, Youngduck; Chiu, Chill Yi-I; Sontag, David

    2016-01-01

    We show how to learn low-dimensional representations (embeddings) of a wide range of concepts in medicine, including diseases (e.g., ICD9 codes), medications, procedures, and laboratory tests. We expect that these embeddings will be useful across medical informatics for tasks such as cohort selection and patient summarization. These embeddings are learned using a technique called neural language modeling from the natural language processing community. However, rather than learning the embeddings solely from text, we show how to learn the embeddings from claims data, which is widely available both to providers and to payers. We also show that with a simple algorithmic adjustment, it is possible to learn medical concept embeddings in a privacy preserving manner from co-occurrence counts derived from clinical narratives. Finally, we establish a methodological framework, arising from standard medical ontologies such as UMLS, NDF-RT, and CCS, to further investigate the embeddings and precisely characterize their quantitative properties. PMID:27570647

  2. Learning Low-Dimensional Representations of Medical Concepts.

    PubMed

    Choi, Youngduck; Chiu, Chill Yi-I; Sontag, David

    2016-01-01

    We show how to learn low-dimensional representations (embeddings) of a wide range of concepts in medicine, including diseases (e.g., ICD9 codes), medications, procedures, and laboratory tests. We expect that these embeddings will be useful across medical informatics for tasks such as cohort selection and patient summarization. These embeddings are learned using a technique called neural language modeling from the natural language processing community. However, rather than learning the embeddings solely from text, we show how to learn the embeddings from claims data, which is widely available both to providers and to payers. We also show that with a simple algorithmic adjustment, it is possible to learn medical concept embeddings in a privacy preserving manner from co-occurrence counts derived from clinical narratives. Finally, we establish a methodological framework, arising from standard medical ontologies such as UMLS, NDF-RT, and CCS, to further investigate the embeddings and precisely characterize their quantitative properties. PMID:27570647

  3. Curious Conceptions: Learning to Be Old

    ERIC Educational Resources Information Center

    Carroll, Trish

    2007-01-01

    The ageing of the population in western societies has aroused great concern and interest in recent years as the so-called "baby-boomers" begin to retire, leaving a seemingly depleted workforce. Society and the individuals within it learn the "truths" of being aged or old through the normalizing of gerontological, demographic and economic…

  4. Semantics for E-Learning: An Advanced Knowledge Management Oriented Metadata Schema for Learning Purposes.

    ERIC Educational Resources Information Center

    Lytras, Miltiadis D.

    The research described in this paper is concentrated on the demand for high quality interchangeable knowledge objects capable of supporting dynamic learning initiatives. The general metadata models (Dublin Core, IMS, LOM, SCORM) for knowledge objects enrichment are reviewed and a critique is provided in order to claim the importance of the…

  5. The Analysis of High School Students' Conceptions of Learning in Different Domains

    ERIC Educational Resources Information Center

    Sadi, Özlem

    2015-01-01

    The purpose of this study is to investigate whether or not conceptions of learning diverge in different science domains by identifying high school students' conceptions of learning in physics, chemistry and biology. The Conceptions of Learning Science (COLS) questionnaire was adapted for physics (Conceptions of Learning Physics, COLP), chemistry…

  6. Decreased Fronto-Limbic Activation and Disrupted Semantic-Cued List Learning in Major Depressive Disorder

    PubMed Central

    Kassel, Michelle T.; Rao, Julia A.; Walker, Sara J.; Briceño, Emily M.; Gabriel, Laura B.; Weldon, Anne L.; Avery, Erich T.; Haase, Brennan D.; Peciña, Marta; Considine, Ciaran M.; Noll, Douglas C.; Bieliauskas, Linas A.; Starkman, Monica N.; Zubieta, Jon-Kar; Welsh, Robert C.; Giordani, Bruno; Weisenbach, Sara L.; Langenecker, Scott A.

    2016-01-01

    Objective Individuals with Major Depressive Disorder (MDD) demonstrate poorer learning and memory skills relative to never-depressed comparisons (NDC). Previous studies report decreased volume and disrupted function of frontal lobes and hippocampi in MDD during memory challenge. However, it has been difficult to dissociate contributions of short-term memory and executive functioning to memory difficulties from those that might be attributable to long-term memory deficits. Method Adult males (MDD, n=19; NDC, n=22) and females (MDD, n=23; NDC, n=19) performed the Semantic List Learning Task (SLLT) during fMRI. The SLLT Encoding condition consists of 15 lists, each containing 14 words. After each list, a Distractor condition occurs, followed by cued Silent Rehearsal instructions. Post-scan recall and recognition were collected. Groups were compared using block (Encoding-Silent Rehearsal) and event-related (Words Recalled) models. Results MDD displayed lower recall relative to NDC. NDC displayed greater activation in several temporal, frontal, and parietal regions, for both Encoding-Silent Rehearsal and the Words Recalled analyses. Groups also differed in activation patterns in regions of the Papez circuit in planned analyses. The majority of activation differences were not related to performance, presence of medications, presence of comorbid anxiety disorder, or decreased gray matter volume in MDD. Conclusions Adults with MDD exhibit memory difficulties during a task designed to reduce the contribution of individual variability from short-term memory and executive functioning processes, parallel with decreased activation in memory and executive functioning circuits. Ecologically valid long-term memory tasks are imperative for uncovering neural correlates of memory performance deficits in adults with MDD. PMID:26831638

  7. Remote semantic memory is impoverished in hippocampal amnesia.

    PubMed

    Klooster, Nathaniel B; Duff, Melissa C

    2015-12-01

    The necessity of the hippocampus for acquiring new semantic concepts is a topic of considerable debate. However, it is generally accepted that any role the hippocampus plays in semantic memory is time limited and that previously acquired information becomes independent of the hippocampus over time. This view, along with intact naming and word-definition matching performance in amnesia, has led to the notion that remote semantic memory is intact in patients with hippocampal amnesia. Motivated by perspectives of word learning as a protracted process where additional features and senses of a word are added over time, and by recent discoveries about the time course of hippocampal contributions to on-line relational processing, reconsolidation, and the flexible integration of information, we revisit the notion that remote semantic memory is intact in amnesia. Using measures of semantic richness and vocabulary depth from psycholinguistics and first and second language-learning studies, we examined how much information is associated with previously acquired, highly familiar words in a group of patients with bilateral hippocampal damage and amnesia. Relative to healthy demographically matched comparison participants and a group of brain-damaged comparison participants, the patients with hippocampal amnesia performed significantly worse on both productive and receptive measures of vocabulary depth and semantic richness. These findings suggest that remote semantic memory is impoverished in patients with hippocampal amnesia and that the hippocampus may play a role in the maintenance and updating of semantic memory beyond its initial acquisition. PMID:26474741

  8. Kindergarteners' concept development in science and literacy learning through Concept-Oriented Reading Instruction (CORI)

    NASA Astrophysics Data System (ADS)

    Moffit, Char Adelia

    The notion that "real work" is somehow different from authentic and engaging discovery is troublesome. (Passman, 2001, p.196) This qualitative case study examined science concept and literacy learning along with engagement of the students in a Kindergarten class in which science and literacy instruction was integrated through Concept-Oriented Reading Instruction (CORI). CORI is an instructional framework created to increase reading engagement by teaching reading comprehension strategies along with science concepts (Guthrie, et al., 1996). This study explored CORI at the Kindergarten level to examine how this curriculum framework engaged young learners in science concept and literacy learning. The study was grounded in the belief that concept learning can be engaging and motivating (Csikszentmihalyi, 1978). Data analysis resulted in five metaphors that show how the students took on multiple identities while engaged in learning concepts during CORI. Students took on the following identities: learner as docent, learner as explorer, learner as researcher, learner as author, and learner as expert. Prior to this study, the lowest grade level that CORI had been researched was 3rd grade. The present study examined the benefits of utilizing CORI with early literacy at the Kindergarten level and contributes to the body of CORI research demonstrating the potential of utilizing CORI at lower grade levels.

  9. Bow Your Head in Shame, or, Hold Your Head Up with Pride: Semantic Processing of Self-Esteem Concepts Orients Attention Vertically

    PubMed Central

    Taylor, J. Eric T.; Lam, Timothy K.; Chasteen, Alison L.; Pratt, Jay

    2015-01-01

    Embodied cognition holds that abstract concepts are grounded in perceptual-motor simulations. If a given embodied metaphor maps onto a spatial representation, then thinking of that concept should bias the allocation of attention. In this study, we used positive and negative self-esteem words to examine two properties of conceptual cueing. First, we tested the orientation-specificity hypothesis, which predicts that conceptual cues should selectively activate certain spatial axes (in this case, valenced self-esteem concepts should activate vertical space), instead of any spatial continuum. Second, we tested whether conceptual cueing requires semantic processing, or if it can be achieved with shallow visual processing of the cue words. Participants viewed centrally presented words consisting of high or low self-esteem traits (e.g., brave, timid) before detecting a target above or below the cue in the vertical condition, or on the left or right of the word in the horizontal condition. Participants were faster to detect targets when their location was compatible with the valence of the word cues, but only in the vertical condition. Moreover, this effect was observed when participants processed the semantics of the word, but not when processing its orthography. The results show that conceptual cueing by spatial metaphors is orientation-specific, and that an explicit consideration of the word cues’ semantics is required for conceptual cueing to occur. PMID:26368276

  10. Bow Your Head in Shame, or, Hold Your Head Up with Pride: Semantic Processing of Self-Esteem Concepts Orients Attention Vertically.

    PubMed

    Taylor, J Eric T; Lam, Timothy K; Chasteen, Alison L; Pratt, Jay

    2015-01-01

    Embodied cognition holds that abstract concepts are grounded in perceptual-motor simulations. If a given embodied metaphor maps onto a spatial representation, then thinking of that concept should bias the allocation of attention. In this study, we used positive and negative self-esteem words to examine two properties of conceptual cueing. First, we tested the orientation-specificity hypothesis, which predicts that conceptual cues should selectively activate certain spatial axes (in this case, valenced self-esteem concepts should activate vertical space), instead of any spatial continuum. Second, we tested whether conceptual cueing requires semantic processing, or if it can be achieved with shallow visual processing of the cue words. Participants viewed centrally presented words consisting of high or low self-esteem traits (e.g., brave, timid) before detecting a target above or below the cue in the vertical condition, or on the left or right of the word in the horizontal condition. Participants were faster to detect targets when their location was compatible with the valence of the word cues, but only in the vertical condition. Moreover, this effect was observed when participants processed the semantics of the word, but not when processing its orthography. The results show that conceptual cueing by spatial metaphors is orientation-specific, and that an explicit consideration of the word cues' semantics is required for conceptual cueing to occur. PMID:26368276