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INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN learning 2018年第11期13卷 130-143页

作者： Chen, Yuhang Hohai Univ Sch Publ Adm Nanjing 210098 Jiangsu Peoples R China

To manage the educational resources of the grid community based on the standard of learning object metadata, the resource classification standard of the learning object metadata standard is taken as the basis of the grid community division. According to the principle of the classification of educational resources, and based on the characteristics of the grid management system and the features of the grid community, the construction and internal structure of grid community are discussed, and the idea of constructing peer community group is proposed. In accordance with the idea of peer community, similar educational resources achieve a logical connection between peer communities. The results show that the mechanism of information sharing and information diffusion is established among communities, and the framework of educational resource management is constructed through simulation and evaluation.

关键词： learning object metadata grid community educational resources

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Recommendation System for Personalized Contextual Pedagogical Resources Based on learning Style 26th

Recommendation System for Personalized Contextual Pedagogica...

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26th International Conference on Interactive Collaborative learning (ICL) - Towards a Hybrid, Flexible and Socially Engaged Higher Education / 52nd IGIP International Conference on Engineering Pedagogy

作者： Benabbes, Khalid Housni, Khalid Zellou, Ahmed Hmedna, Brahim El Mezouary, Ali Ibn Tofail Univ LARI Lab MISC Team Fac Sci Kenitra Morocco Mohammed V Univ SPM Res Team ENSIAS Rabat Morocco Ibn Zohr Univ IMIS Lab Fac Sci Agadir Morocco Ibn Zohr Univ EST IRF SIC Lab Agadir Morocco

ISBN: (纸本)9783031526664;9783031526671

E-learning systems have undergone a significant transformation in the field of education, providing valuable support to learners and trainers. Among the emerging technologies, recommender systems have proven essential in supporting learners in selecting learning resources that best fit their preferences and requirements. However, learning is not limited to specific times or physical environments, making it necessary to customize resources that reflect learners' contextual backgrounds. To address this challenge, this paper proposes an intelligent recommendation approach that offers highly personalized learning objects using contextual information and the Felder-Silverman learning Style Model (FSLSM). In order to automatically model the learner, we analyze the learner's interaction traces and sensor log data. By extracting relevant features, we cluster a population of 624 learners enrolled in two agronomy courses at IAV Hassan II, based on their preferred learning style (global or sequential). To achieve the objective of this study, we developed an innovative rule-based classification model. The results of this study outperform all alternative recommendation methods on both quality and accuracy, with a high precision rate of over 96%. This performance reflects the seamless incorporation of current learner contextual factors.

关键词： E-learning Adaptative learning Context-awareness learning styles Recommender System learning object metadata

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Design and Realization of Educational Resources Management System Based on learning object metadata

Design and Realization of Educational Resources Management S...

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7th International Conference on Internet Computing for Engineering and Science (ICICSE)

作者： Zheng, Weiyong Shanghai Univ Int Business & Econ Foreign Language Sch Shanghai Peoples R China

ISBN: (纸本)9780769551180

In this paper, the design and realization of education resources management system based on learning object metadata (hereinafter referred to as "THE SYSTEM") was discussed on the basis of introducing the contents related to learning object metadata, which provides guarantee for description, distribution, inquiry and application standardization of resources.

关键词： metadata learning object learning object metadata CELTS-3 XML DOM

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A Semantic Distances-Based Approach for a Deeply Indexing of learning objects

INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING

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INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN learning 2019年第6期14卷 27-40页

作者： El Guemmat, Kamal Ouahabi, Sara Hassan II Univ Casablanca Morocco

Educational search engines are important for users to find learning objects (LO). However, these engines have not reached maturity in terms of searching, they suffer from several worries like the deep extraction of notions which diminishes their performance. The purpose of this paper is to propose a new approach that allows depth extraction of LO's notions to increase the relevance level of educational search engines. The proposed approach focuses on semi-automatic indexing of textual LO and more precisely the deeper relations of sentences that flesh out explanations. It based on linguistic structures and semantic distances between specific and generic notions according to OntOAlgO ontology. The notions obtained will be improved by learning object metadata (LOM) and will be represented semantically in final index. The tests performed on algorithmic LO, proving the usefulness of our approach to educational search engines. It increases the degree of precision and recall of notions extracted from LO.

关键词： Educational search engine learning object Linguistic structure Semantic distance Ontology learning object metadata

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Capturing AIS Behavior Using xAPI-like Statements 1st

Capturing AIS Behavior Using xAPI-like Statements

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1st International Conference on Adaptive Instructional Systems (AIS) Held as Part of the 21st HCI International Conference on Human-Computer Interaction (HCII)

作者： Hu, Xiangen Cai, Zhiqiang Hampton, Andrew J. Cockroft, Jody L. Graesser, Arthur C. Copland, Cameron Folsom-Kovarik, Jeremiah T. Univ Memphis Memphis TN 38104 USA Cent China Normal Univ Wuhan 430072 Hubei Peoples R China SoarTech Orlando FL 32836 USA

ISBN: (纸本)9783030223410;9783030223403

In this paper, we consider a minimalistic and behavioristic view of AIS to enable a standardizable mapping of both the behavior of the system and of the learner. In this model, the learners interact with the learning resources in a given learning environment following preset steps of learning processes. From this foundation, we make several subsequent arguments. (1) All intelligent digital resources such as intelligent tutoring systems (ITS) need to be well-documented with standardized metadata scheme. We propose a learning science extension of IEEE learning object metadata (LOM). specifically, we need to consider cognitive learning principles that have been used in creating the intelligent digital resources. (2) We need to consider AIS as whole when we record system behavior. Specifically, we need to record all four components delineated above (the learners, the resources, the environments, and the processes). We point to selected learning principles from the literature as examples for implementation of this approach. We concretize this approach using Auto-Tutor, a conversation-based ITS, serving as a typical intelligent digital resource.

关键词： Experience API Intelligent tutoring systems learning object metadata learning principles

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A MULTILAYER NETWORK APPROACH FOR REAL-TIME ADAPTIVE PERSONALIZED learning

A MULTILAYER NETWORK APPROACH FOR REAL-TIME ADAPTIVE PERSONA...

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作者： Jan-Daniel Cleven Naval Postgraduate School

学位级别：硕士

Traditional classroom instruction provides all students with the same topics, at the same time, at the same speed. However, personalized learning systems that take into account students' individual interests, skills, and preferences have been shown to be more effective. Our goal is to develop an adaptive teaching-learning method for enhanced and personalized education, which we call Curated Heuristic Using a Network of Knowledge for Continuum of learning (CHUNK learning). CHUNK learning will provide a curated way of moving through a network of modules composed of educational material joined together by common attributes (i. e., tagged with competency or skill levels). Here, we use a network science approach to develop an initial software prototype, which recommends learning content to students based on their current interests. We establish methods to automatically extract metadata tags to describe course content and student profiles. These tags are used by the software to match courses with individual interests. Moreover, our software is able to simulate student feedback, which helps us test the updating features of our software. This allows us to adapt course recommendations to interest changes throughout the study period and to improve course recommendations for future students. This prototype builds the basis for a CHUNK learning platform, in which the learner can heuristically discover or learn based on personal background, interests, and skills.

关键词： personalized adaptive learning network modeling network analysis modular learning network of educational modules continuum of learning learning object metadata educational modules tagging learning analytics

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A Survey on the Importance of learning object metadata for Relevance Judgment

A Survey on the Importance of Learning Object Metadata for R...

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5th International Conference on metadata and Semantic Research

作者： Balatsoukas, Panos Garoufallou, Emmanouel Asderi, Stella Siatri, Rania Univ Strathclyde Dept Comp & Informat Sci Glasgow G1 1XQ Lanark Scotland ATEI Thessaloniki Dept Library Sci & Informat Syst Thessaloniki Greece Amer Coll Library Greece

ISBN: (纸本)9783642247309

The purpose of this study was to investigate university students' perceptions about the usefulness - importance of learning object metadata elements of the UK LOM Core application profile when judging the relevance of learning objects. In order to address this objective an online questionnaire survey was conducted among university students using a clustered sampling technique. A total of 252 students respondent to the questionnaire. Participants represented different disciplines (for example, from Humanities & Social Sciences to Sciences & Engineering), levels of familiarization with the web and educational level (postgraduates and undergraduates). The results showed that participants preferred content related and educational metadata elements as well as metadata elements about the date and the language of a learning object as opposed to technical metadata elements or metadata elements about the version of the learning object. The conclusions show that these findings can have implications in the design and use of learning object metadata schemas for students in the UK Higher Education.

关键词： learning object metadata LOM educational metadata usefulness relevance judgment

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On the Use of learning object metadata: The GLOBE Experience

On the Use of Learning Object Metadata: The GLOBE Experience

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6th European Conference on Technology-Enhanced learning (EC-TEL)

作者： Ochoa, Xavier Klerkx, Joris Vandeputte, Bram Duval, Erik Escuela Super Politecn Litoral Ctr Informat Technol Guayaquil Ecuador Katholieke Univ Leuven Dept Compwetenschappen B-3001 Heverlee Belgium

ISBN: (纸本)9783642239847

Since IEEE LTSC LOM. was published in 2002, it is one of the widest adopted standard for the description of educational resources. The GLOBE (Global learning objects Brokered Exchange) alliance enables share and reuse between several learning object Repositories worldwide. Being the largest and more diverse collection of learning object metadata, it is an ideal place to perform an analysis of the actual use of the LOM standard in the real world. This paper presents an in-depth analysis of the use and quality of 630.317 metadata instances.

关键词： Interoperability learning object metadata

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A Recommender System for learning objects on a learning Management System: Implementation Experience 11

A Recommender System for Learning Objects on a Learning Mana...

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11th Latin American Conference on learning objects and Technologies (LACLO)

作者： Solis-Cespedes, Jacqueline Chacon-Rivas, Mario Inst Tecnol Costa Rica Tec Digital Cartago Costa Rica

ISBN: (纸本)9781509061495

This paper aims to present the experience of implementing a recommender system for selecting learning objects (LO) for lessons through the learning Management System (LMS) of Costa Rica Institute of Technology. Our implementation approach is made up of three components: A user model based on the descriptions of the lessons of a course given in an Instructional Design (ID), a serie of items which constitute the metadata bank of resources described using IEEE Standard for learning object metadata model (IEEE-LOM) and harvested by Open Archives Initiative Protocol for metadata Harvesting (OAI-PMH) and finally, an utility function derived from the weighting between the collaborative assessment of LO and similarity measures to compare LO's metadata with descriptions of activities given for course. As validation mechanism, ID's tests were conducted in order to determine whether or not recover resources for lessons and precision tests with a pilot plan remained pending.

关键词： learning object metadata Recommender Systems Educational metadata LOM-IEEE SQI OAI-PMH

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An SOA Approach to Virtual Classroom with Content Repurposing

INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN LEARNING

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INTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES IN learning 2014年第1期9卷 61-65页

作者： Kong Xiangsheng Xin Xiang Univ Dept Comp Engn Xin Xiang Peoples R China

Existing M-learnings lack security, privacy and wireless accessibility features so that they are prevented from expanding widely and usually have problems that they lack S.C.A.L.E. (Scalability, Connectivity, Adaptability, Liability, and Ease-of-use) design factors that a typical ubiquitous system must support. One of the ways lies in the evolution of learning environments into Service Governance of Service Oriented Architecture. The implementation of this architecture will allow the creation of Mobiles and external tools that can work with the resources contained in the platform, and give trainers and learners a freedom of movement that they did not have before.

关键词： LMS virtual classroom Service Governance learning object metadata

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