Validating the learning outcomes of an e-learning system using NLP

Aeiad, E; Meziane, F

Abstract

Despite the development and the wide use of E-Learning,
developing an adaptive personalised E-Learning system tailored to the
needs of individual learners remains a challenge. In an early work, the
authors proposed APELS that extracts freely available resources on
the web using an ontology to model the leaning topics and optimise
the information extraction process. APELS takes into consideration the
leaner’s needs and background. In this paper, we developed an approach
to evaluate the topics’ content extracted previously by APELS against a
set of learning outcomes as defined by standard curricula. Our validation
approach is based on finding patterns in part of speech and grammatical
dependencies using the Stanford English Parser. As a case study, we use
the computer science field with the IEEE/ACM Computing curriculum
as the standard curriculum.

Citation

Aeiad, E., & Meziane, F. (2016). Validating the learning outcomes of an e-learning system using NLP. Lecture notes in computer science, 9612, 292-300. https://doi.org/10.1007/978-3-319-41754-7_27

• Journal Article Type: Article
• Conference Name: Proceedings of the 21st International Conference on Applications of Natural Language to Information Systems, NLDB 2016
• Conference Location: Salford, UK
• Start Date: Jun 22, 2023
• End Date: Jun 24, 2023
• Acceptance Date: Apr 15, 2016
• Publication Date: Jun 1, 2016
• Deposit Date: Jun 24, 2016
• Publicly Available Date: Jul 1, 2017
• Journal: Natural Language Processing and Information Systems
• Print ISSN: 0302-9743
• Publisher: Springer Verlag
• Volume: 9612
• Pages: 292-300
• DOI: https://doi.org/10.1007/978-3-319-41754-7_27
• Publisher URL: http://dx.doi.org/10.1007/978-3-319-41754-7_27
• Related Public URLs: http://dx.doi.org/10.1007/978-3-319-41754-7
• Additional Information: Event Type : Conference