Enhancing Emerging Learning Objects with Contextual Metadata Using the Linked Data Approach

According to recent studies, the social interactions of users such as sharing, rating, and reviewing can improve the value of digital learning objects and resources on the web. Linked data techniques, on the other hand, make different kinds of data available and reusable for other applications on the web. Exposing (meta)data, especially with a complex structure, as resource description framework (RDF) requires an ontology to bring all the data types under one umbrella. In this article, the authors propose an ontology in which social activities of users are exposed as linked data by reusing existing vocabularies. The proposed ontology has been implemented in a federated open educational resources (OER) portal, in which they published ratings, shares, comments, and other social activities assigned to around 1,000 OERs. This exposure allows other datasets, including harvested repositories, to explore the exposed social data related to e-learning objects according to the users' social engagement.

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Recommending Metadata Contents for Learning Objects Through Linked Data

10.1007/978-3-030-85710-3_10 ◽

2021 ◽

pp. 115-126

Author(s):

André Behr ◽

Armando Mendes ◽

Paulo Trigo ◽

José Cascalho ◽

Hélia Guerra ◽

...

Keyword(s):

Linked Data ◽

Learning Objects

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A learning object ontology repository to support annotation and discovery of educational resources using semantic thesauri

IFLA Journal ◽

10.1177/0340035217737559 ◽

2017 ◽

Vol 44 (1) ◽

pp. 4-22 ◽

Cited By ~ 5

Author(s):

Dimitrios A. Koutsomitropoulos ◽

Georgia D. Solomou

Keyword(s):

Linked Data ◽

Learning Objects ◽

Open Educational Resources ◽

Educational Resources ◽

Learning Object ◽

Management Tools ◽

Ontology Repository ◽

Web Of Data ◽

Object Ontology ◽

Knowledge Value

Open educational resources are currently becoming increasingly available from a multitude of sources and are consequently annotated in many diverse ways. Interoperability concerns that naturally arise can often be resolved through the semantification of metadata descriptions, while at the same time strengthening the knowledge value of resources. SKOS can be a solid linking point offering a standard vocabulary for thematic descriptions, by referencing semantic thesauri. We propose the enhancement and maintenance of educational resources’ metadata in the form of learning object ontologies and introduce the notion of a learning object ontology repository that can help towards their publication, discovery and reuse. At the same time, linking to thesauri datasets and contextualized sources interrelates learning objects with linked data and exposes them to the Web of Data. We build a set of extensions and workflows on top of contemporary ontology management tools, such as WebProtégé, that can make it suitable as a learning object ontology repository. The proposed approach and implementation can help libraries and universities in discovering, managing and incorporating open educational resources and enhancing current curricula.

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Re-Mar: Repository of Marine Learning Objects

10.5753/wcama.2021.15745 ◽

2021 ◽

Author(s):

André Behr ◽

José Cascalho ◽

Hélia Guerra ◽

Ana Costa ◽

Manuela Parente ◽

...

Keyword(s):

Artificial Intelligence ◽

Environmental Education ◽

Open Source Software ◽

Linked Data ◽

Learning Objects ◽

Learning Object ◽

Ocean Literacy ◽

Learning Object Repository ◽

Learning Object Repositories ◽

And Coping

Current literature shows the lack of learning object repositories exclusively related to environmental education and that there is no predominant software. This paper presents Re-Mar, a marine learning object repository based on open source software. Re-Mar is a part of an effort to promote ocean literacy through educational content for students and teachers. The repository is supported by computational technologies to catalog and organize learning objects to retrieve and reuse. Our prototype shows that is possible to store, catalog, retrieve, and link learning objects to support environmental education and coping with learning objects lifecycle. This is the first step to future aggregation of linked data, ontologies, and artificial intelligence aspects.

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The Linked Data Enterprise as Enabler for both Intra- and Inter-organizational Business Data Integration and Usage

2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO) ◽

10.23919/mipro48935.2020.9245320 ◽

2020 ◽

Author(s):

A M. Tjoa

Keyword(s):

Data Integration ◽

Linked Data ◽

Business Data

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Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

JOIV International Journal on Informatics Visualization ◽

10.30630/joiv.2.4.158 ◽

2018 ◽

Vol 2 (4) ◽

pp. 271 ◽

Cited By ~ 3

Author(s):

Outmane Bourkoukou ◽

Essaid El Bachari

Keyword(s):

Learning Style ◽

Recommender System ◽

Adaptive Learning ◽

Learning Objects ◽

Research Field ◽

Learning System ◽

K Nearest Neighbors ◽

E Learning ◽

Hybrid Recommender System ◽

Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

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Evaluasi Aksesibilitas Learning Object Berdasarkan Web Content Accessibility Guidelines 2.0

Jurnal ULTIMATICS ◽

10.31937/ti.v9i2.602 ◽

2017 ◽

Vol 9 (2) ◽

pp. 67-71

Author(s):

Herru Darmadi ◽

Yan Fi ◽

Hady Pranoto

Keyword(s):

Learning Objects ◽

Authoring Tool ◽

Learning Object ◽

Web Content ◽

Web Browser ◽

E Learning ◽

Index Terms ◽

Accessibility Guidelines ◽

Content Accessibility

Learning Object (LO) is a representation of interactive content that are used to enrich e-learning activities. The goals of this case study were to evaluate accessibility and compatibility factors from learning objects that were produced by using BINUS E-learning Authoring Tool. Data were compiled by using experiment to 30 learning objects by using stratified random sampling from seven faculties in undergraduate program. Data were analyzed using accessibility and compatibility tests based on Web Content Accessibility Guidelines 2.0 Level A. Results of the analysis for accessibility and compatibility tests of Learning Objects was 90% better than average. The result shows that learning objects is fully compatible with major web browser. This paper also presents five accessibility problems found during the test and provide recommendation to overcome the related problems. It can be concluded that the learning objects that were produced using BINUS E-learning Authoring Tool have a high compatibility, with minor accessibility problems. Learning objects with a good accessibility and compatibility will be beneficial to all learner with or without disabilities during their learning process. Index Terms—accessibility, compatibility, HTML, learning object, WCAG2.0, web

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Proposal of an instrument to evaluate interaction spaces in a VLE

Journal of Teaching and Educational Research ◽

10.35429/jter.2019.15.5.1.13 ◽

2019 ◽

pp. 1-13

Author(s):

Rubí Estela Morales-Salas ◽

Daniel Montes-Ponce

Keyword(s):

Learning Environment ◽

Design Space ◽

Collaborative Work ◽

Virtual Learning ◽

Interaction Space ◽

Learning Objects ◽

Traditional Education ◽

Virtual Learning Environment ◽

Discussion Forums ◽

Exhibition Space

A virtual learning environment is conceived as an interaction space that ease the realization of mediated activities by technology, in this case the internet; besides using multimedia materials, learning objects, social networks, among others; which have changed imminently the traditional education. In this article an instrument is proposed in a checklist format, to evaluate any platform that has interaction spaces such as a Virtual Learning Environment, in this case responding to four spaces or general indicators: information Space, Mediation / Interaction Space, Instructional Design Space and Exhibition Space. Criteria are used according to the interactions and activities carried out by the consultant and virtual student. These, in turn, come up from the analysis and interaction of the advisers achieved in the discussion forums and portfolio activities through collaborative work. It was situated as a qualitative research, with a descriptive nature since it is not limited to data collection only, but also it refers and analyzes the interaction of the advisers achieved in the discussion forums and portfolio activities through the collaborative work of the workshop course "Virtual Learning Environments" developed in a virtual learning environment.

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