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

Gallego Vico, Daniel and Barra Arias, Enrique and Gordillo Méndez, Aldo and Huecas Fernández Toribio, Gabriel (2013). Enhanced recommendations for e-learning authoring tools based on a proactive context-aware recommender. In: "2013 IEEE Frontiers in Education Conference", 23/10/2013 - 26/10/2013, Oklahoma City, Oklahoma, USA. pp. 1-3.

Description

Title: Enhanced recommendations for e-learning authoring tools based on a proactive context-aware recommender
Author/s:
  • Gallego Vico, Daniel
  • Barra Arias, Enrique
  • Gordillo Méndez, Aldo
  • Huecas Fernández Toribio, Gabriel
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2013 IEEE Frontiers in Education Conference
Event Dates: 23/10/2013 - 26/10/2013
Event Location: Oklahoma City, Oklahoma, USA
Title of Book: 2013 IEEE Frontiers in Education Conference
Date: 2013
Subjects:
Freetext Keywords: Authoring tools; Recommender systems; Learning objects; Proactivity; Context-awareness
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería de Sistemas Telemáticos [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

More information

Item ID: 25764
DC Identifier: http://oa.upm.es/25764/
OAI Identifier: oai:oa.upm.es:25764
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6685060
Deposited by: Memoria Investigacion
Deposited on: 11 May 2014 07:21
Last Modified: 22 Sep 2014 11:38
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