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

Journal article

Aeiad, E and Meziane, F. 2016. Validating the learning outcomes of an e-learning system using NLP. Natural Language Processing and Information Systems. Vol 9612, pp. 292 - 300. https://doi.org/10.1007/978-3-319-41754-7_27
AuthorsAeiad, E and 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.

KeywordsDependency relation; Key phrases; Keyword extraction; NLP
Year2016
JournalNatural Language Processing and Information Systems
Journal citationVol 9612, pp. 292 - 300
PublisherSpringer
ISSN03029743
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-41754-7_27
Web address (URL)http://dx.doi.org/10.1007/978-3-319-41754-7_27
Output statusPublished
Publication dates17 Jun 2016
Publication process dates
Deposited05 Jun 2023
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