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Authors: Carlo De Medio 1 ; Fabio Gasparetti 2 ; Carla Limongelli 2 ; Filippo Sciarrone 2 and Marco Temperini 1

Affiliations: 1 Sapienza University of Rome, Italy ; 2 Roma Tre University, Italy

ISBN: 978-989-758-179-3

Keyword(s): E-learning, Data Mining, Wikipedia.

Related Ontology Subjects/Areas/Topics: Authoring Tools and Content Development ; Computer-Supported Education ; e-Learning ; Information Technologies Supporting Learning ; Instructional Design ; Learning/Teaching Methodologies and Assessment

Abstract: Selecting and sequencing a set of Learning Objects (LOs) to build a course may turn out to be quite a challenging task. In this paper we focus on such an aspect, related to the verification and respect of the relationships of pedagogical dependence existing between two LOs added to a course (meaning that if a given LO has another one as “pre-requisite”, then any sequencing of the LOs in the course will need to have the latter LO taken by the learners before of the former). In our approach the sequencing of LOs in the course can still be managed by the instructor, basing on her/his taste and preferences, yet s/he can also be helped by a set of suggestions, related to the pre-requisite relationships existing among the LOs selected for the course. Such suggestions (such relationships, in effect) can be computed automatically and provide the instructor with significant help and guidance. We show a light-weight formalization of the LO, and how it can be “represented” by a set of WikiPedia Pages (“topics”); then we show how such set of topics, together with a set of relevant hypotheses we previously defined, can help establish the dependence relationship existing between two LOs. In this endeavor we exploit the classification in categories available for the WikiPedia topics, and obtain interesting results for our framework, in terms of precision and recall of the dependence relationships. (More)

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Paper citation in several formats:
De Medio, C.; Gasparetti, F.; Limongelli, C.; Sciarrone, F. and Temperini, M. (2016). A Machine Learning Approach to Identify Dependencies Among Learning Objects.In Proceedings of the 8th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-179-3, pages 345-352. DOI: 10.5220/0005800503450352

@conference{csedu16,
author={Carlo De Medio. and Fabio Gasparetti. and Carla Limongelli. and Filippo Sciarrone. and Marco Temperini.},
title={A Machine Learning Approach to Identify Dependencies Among Learning Objects},
booktitle={Proceedings of the 8th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2016},
pages={345-352},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005800503450352},
isbn={978-989-758-179-3},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - A Machine Learning Approach to Identify Dependencies Among Learning Objects
SN - 978-989-758-179-3
AU - De Medio, C.
AU - Gasparetti, F.
AU - Limongelli, C.
AU - Sciarrone, F.
AU - Temperini, M.
PY - 2016
SP - 345
EP - 352
DO - 10.5220/0005800503450352

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