Ontology-Based Representation of Learner Profiles for Accessible OpenCourseWare Systems

Elias, Mirette; Lohmann, Steffen; Auer, Sören

doi:10.1007/978-3-319-69548-8_19

Cited by 7 publications

(7 citation statements)

References 6 publications

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“…it takes 10 week to complete), we will update the Preferred Long property of the user and decrease its value in order to provide shorter OERs in the future. Along the same line, with assigning positive ratings to accessible OERs, learners can enhance their accessibility criterion and increase their Preferred Accessibility value to receive content with accessibility support (critical for instance for visually impaired learners (Elias et al, 2017)). Table 2 shows OER properties.…”

Section: Methods For Updating Learners' Propertiesmentioning

confidence: 99%

Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners

Tavakoli

Mol

Kismihók

2020

Proceedings of the 12th International Conference on Computer Supported Education

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In this paper, we suggest a novel method to aid lifelong learners to access relevant OER based learning content to master skills demanded on the labour market. Our software prototype 1) applies Text Classification and Text Mining methods on vacancy announcements to decompose jobs into meaningful skills components, which lifelong learners should target; and 2) creates a hybrid OER Recommender System to suggest personalized learning content for learners to progress towards their skill targets. For the first evaluation of this prototype we focused on two job areas: Data Scientist, and Mechanical Engineer. We applied our skill extractor approach and provided OER recommendations for learners targeting these jobs. We conducted in-depth, semi-structured interviews with 12 subject matter experts to learn how our prototype performs in terms of its objectives, logic, and contribution to learning. More than 150 recommendations were generated, and 76.9% of these recommendations were treated as useful by the interviewees. Interviews revealed that a personalized OER recommender system, based on skills demanded by labour market, has the potential to improve the learning experience of lifelong learners.

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Section: Methods For Updating Learners' Propertiesmentioning

confidence: 99%

Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners

Tavakoli

Mol

Kismihók

2020

Proceedings of the 12th International Conference on Computer Supported Education

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“…Such meta-data could be used to report decks that contain slides that have been checked for accessibility or to report the complexity of the text within the slides. This could be linked to the needs for learners to filter search results [6].…”

Section: Accessibility Requirements Of Slidesmentioning

confidence: 99%

Towards an Open Authoring Tool for Accessible Slide Presentations

Elias

James

Lohmann

et al. 2018

Lecture Notes in Computer Science

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Creating and sourcing accessible Open Educational Resources is a challenge. Although slides are one of the primary forms of educational resources, there has been little focus on what is required to make slides containing different media accessible and how to encourage authors to improve accessibility. This paper examines the components within slide presentations that impact accessibility and will evaluates six different approaches for encouraging authors to add accessibility issues. Authors indicated a preference for being encouraged and guided to resolve issues rather than allowing for automatic corrections.

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“…This phase focused on formalizing the learners' needs and preferences, together with the properties of the educational resources, in an ontology in order to provide a standard representation and allow reuse of these concepts. In our previous research [2], we reviewed the state of the art and selected the most relevant specifications and guidelines to built our AccessibleOCW ontology [3]. The ontology provides a structured schema for defining the metadata of the learner's profile and the educational resources.…”

Section: Formalizing Ocw Concepts In An Ontologymentioning

confidence: 99%

“…It is is available and deployed in a VoCol [11] environment (http://vocol.iais.fraunhofer.de/accessibilityOnto/) (a visual representation of the ontology, created with WebVOWL [12], is shown in Figure A1 in Appendix A of this article). It contains two main classes, as introduced in Section 2.1, Learners and Digital Resources, with their relevant properties and other classes that are used to describe the different representations of the educational resources and preferences of the learners [3]. The ontology had been revised and extended since we introduced it in our previous work.…”

Section: Accessibleocw Ontologymentioning

confidence: 99%

“…This article is an extension to our previous work [3], where the main objective of the research was to define a way to represent the needs and preferences of learners, the properties of educational materials, and the conditions to map them to each other. In that work, we created an ontology, which we call AccessibleOCW, to represent these accessibility needs in order to structure the knowledge and to access the information for recommendations and adaptations in e-learning contexts, with the goal to help in the process of generating a personalized OCW experience.…”

Section: Introductionmentioning

confidence: 99%

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Ontology-Based Representation for Accessible OpenCourseWare Systems

2018

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OpenCourseWare (OCW) systems have been established to provide open educational resources that are accessible by anyone, including learners with special accessibility needs and preferences. We need to find a formal and interoperable way to describe these preferences in order to use them in OCW systems and retrieve relevant educational resources. This formal representation should use standard accessibility definitions of OCW that can be reused by other OCW systems to represent accessibility concepts. In this article, we present an ontology to represent the accessibility needs of learners with respect to the IMS AfA specifications. The ontology definitions together with rule-based queries are used to retrieve relevant educational resources. Related to this, we developed a user interface component that enables users to create accessibility profiles representing their individual needs and preferences based on our ontology. We evaluated the approach with five examples profiles.

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Ontology-Based Representation of Learner Profiles for Accessible OpenCourseWare Systems

Cited by 7 publications

References 6 publications

Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners

Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners

Towards an Open Authoring Tool for Accessible Slide Presentations

Ontology-Based Representation for Accessible OpenCourseWare Systems

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