A model for generating proactive context-aware recommendations in e-Learning systems

Gallego, Daniel; Barra, Enrique; Aguirre, Sandra; Huecas, Gabriel

doi:10.1109/fie.2012.6462246

Cited by 23 publications

(27 citation statements)

References 20 publications

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“…To mitigate the searching problem, Learning Object Repositories (LORs) use ranking metrics and sorting algorithms to order the search results ( [10], [11], [12]). Another approach to help educators to find suitable resources is the use of LO recommender systems ( [13], [14]). However, these solutions by themselves are insufficient to generalize the use of LOs since educators are limited to the resources stored in the repositories and their content cannot be customized.…”

Section: Introductionmentioning

confidence: 99%

Facilitating the creation of interactive multi-device Learning Objects using an online authoring tool

Gordillo

Barra

Quemada

2014

2014 IEEE Frontiers in Education Conference (FIE) Proceedings

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Abstract-Learning Objects facilitate reuse leading to cost and time savings as well as to the enhancement of the quality of educational resources. However, teachers find it difficult to create or to find high quality Learning Objects, and the ones they find need to be customized. Teachers can overcome this problem using suitable authoring systems that enable them to create high quality Learning Objects with little effort. This paper presents an open source online e-Learning authoring tool called ViSH Editor together with four novel interactive Learning Objects that can be created with it: Flashcards, Virtual Tours, Enriched Videos and Interactive Presentations. All these Learning Objects are created as web applications, which can be accessed via mobile devices. Besides, they can be exported to SCORM including their metadata in IEEE LOM format. All of them are described in the paper including an example of each. This approach for creating Learning Objects was validated through two evaluations: a survey among authors and a formal quality evaluation of 209 Learning Objects created with the tool. The results show that ViSH Editor facilitates educators the creation of high quality Learning Objects.

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Section: Introductionmentioning

confidence: 99%

Facilitating the creation of interactive multi-device Learning Objects using an online authoring tool

Gordillo

Barra

Quemada

2014

2014 IEEE Frontiers in Education Conference (FIE) Proceedings

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“…Bearing in mind the previous scenario, in this paper we present a new general model to improve previous work on proactive context-aware recommendations in e-Learning systems [3] to be applied in online e-Learning authoring tools. It covers several use cases related to common situations involved in the use of authoring tools to create new LOs based on existing educational resources.…”

Section: Introductionmentioning

confidence: 99%

“…[10] propose a proactive recommender system in computer-supported learning that works on LO repositories and adapts to a student's profile. Whereas in [3] we propose a proactive context-aware recommender system capable of recommending both, LOs and similar peers in an e-Learning social network based on social, location and user context-awareness information. Fig.…”

Section: Introductionmentioning

confidence: 99%

Enhanced recommendations for e-Learning authoring tools based on a proactive context-aware recommender

Gallego

Barra

Gordillo

et al. 2013

2013 IEEE Frontiers in Education Conference (FIE)

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Abstract-Authoring tools are powerful systems in the area of e-Learning that make easier for teachers to create new learning objects by reusing or editing existing educational resources coming from learning repositories or content providers. However, due to the overwhelming number of resources these tools can access, sometimes it is difficult for teachers to find the most suitable resources taking into account their needs in terms of content (e.g. topic) or pedagogical aspects (e.g. target level associated to their students). Recommender systems can take an important role trying to mitigate this problem. In this paper we propose a new model to generate proactive context-aware recommendations on resources during the creation process of a new learning object that a teacher carries out by using an authoring tool. The common use cases covered by the model for having recommendations in online authoring tools and details about the recommender model itself are presented.

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“…Following the model we proposed in [3], in this paper we present the methods needed to incorporate proactivity in a context-aware recommender system for e-learning platforms. In addition, we evaluate the appropriateness of proactivity when recommending learning content to educators in order to help them creating better educational material for their daily classes attending to their students' necessities.…”

Section: Introductionmentioning

confidence: 99%

Incorporating proactivity to context-aware recommender systems for e-learning

Gallego¹,

Barra²,

Rodríguez³

et al. 2013

2013 World Congress on Computer and Information Technology (WCCIT)

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Abstract-Recommender systems in e-learning have proved to be powerful tools to find suitable educational material during the learning experience. But traditional user request-response patterns are still being used to generate these recommendations. By including contextual information derived from the use of ubiquitous learning environments, the possibility of incorporating proactivity to the recommendation process has arisen. In this paper we describe methods to push proactive recommendations to e-learning systems users when the situation is appropriate without being needed their explicit request. As a result, interesting learning objects can be recommended attending to the user's needs in every situation. The impact of this proactive recommendations generated have been evaluated among teachers and scientists in a real e-learning social network called Virtual Science Hub related to the GLOBAL excursion European project. Outcomes indicate that the methods proposed are valid to generate such kind of recommendations in e-learning scenarios. The results also show that the users' perceived appropriateness of having proactive recommendations is high.

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A model for generating proactive context-aware recommendations in e-Learning systems

Cited by 23 publications

References 20 publications

Facilitating the creation of interactive multi-device Learning Objects using an online authoring tool

Facilitating the creation of interactive multi-device Learning Objects using an online authoring tool

Enhanced recommendations for e-Learning authoring tools based on a proactive context-aware recommender

Incorporating proactivity to context-aware recommender systems for e-learning

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