Extraction of Relevant Terms and Learning Outcomes from Online Courses

Authors

  • Isabel Guitart Open University of Catalonia Rambla del poblenou, 156 08018 - Barcelona
  • Jordi Conesa Open University of Catalonia Rambla del poblenou, 156 08018 - Barcelona https://orcid.org/0000-0001-6481-3324
  • David Baneres Open University of Catalonia Rambla del poblenou, 156 08018 - Barcelona
  • Joaquim Moré Open University of Catalonia Rambla del poblenou, 156 08018 - Barcelona
  • Jordi Duran Open University of Catalonia Rambla del poblenou, 156 08018 - Barcelona
  • David Gañan Open University of Catalonia Rambla del poblenou, 156 08018 - Barcelona

DOI:

https://doi.org/10.3991/ijet.v11i10.5928

Keywords:

Information retrieval, analytics, learning analytics, natural language processing, eLearning, learning outcomes discovery

Abstract


Nowadays, universities (on-site and online) have a large competition in order to attract more students. In this panorama, learning analytics can be a very useful tool since it allows instructors (and university managers) to get a more thorough view of their context, to better understand the environment, and to identify potential improvements. In order to perform analytics efficiently, it is necessary to have as much information as possible about the instructional context. The paper proposes a novel approach to gather information from different aspects within courses. In particular, the approach applies natural language processing (NLP) techniques to analyze the course’s materials and discover what concepts are taught, their relevancy in the course and their alignment with the learning outcomes of the course. The contribution of the paper is a semi-automatic system that allows obtaining a better understanding of courses. A validation experiment on a master of the Open University of Catalonia is presented in order to show the quality of the results. The system can be used to analyze the suitability of course’s materials and to enrich and contextualize other analytical processes.

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Published

2016-10-27

How to Cite

Guitart, I., Conesa, J., Baneres, D., Moré, J., Duran, J., & Gañan, D. (2016). Extraction of Relevant Terms and Learning Outcomes from Online Courses. International Journal of Emerging Technologies in Learning (iJET), 11(10), pp. 22–30. https://doi.org/10.3991/ijet.v11i10.5928

Issue

Vol. 11 No. 10 (2016)

Section

Papers

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