About this paper

Appears in:
Pages: 9424-9428
Publication year: 2017
ISBN: 978-84-617-8491-2
ISSN: 2340-1079
doi: 10.21125/inted.2017.2223

Conference name: 11th International Technology, Education and Development Conference
Dates: 6-8 March, 2017
Location: Valencia, Spain

TOWARD NEW METHOD FOR ADAPTIVE LEARNING IN MOOC

S. Aammou1, Y. Jdidou2, A. Jdidou3

1Abdelmalek Essaadi University, Ecole Normale Supérieure (MOROCCO)
2Abdelmalek Essaadi University, Faculty of Sciences (MOROCCO)
3Abdelmalek Essaadi University (MOROCCO)
Adaptive learning allows learners to choose their modular components to customize their learning-centered learning environments. It offers flexible solutions that dynamically adapt content to the real-time learning needs of individuals. While, adaptive learning systems and adaptive learning content according to the needs of learners use the system. Most adaptive techniques are constraints by the pedagogical preference of the author of the system and are always constrained to the system for the people who have been developed and to the content of the domain.

Research question:
• This research is involved with the following research question: Is it possible to construct an automated learning component that generates instructional content suited to the cognitive ability and pedagogical preference of a learner?
Research goal:
• The goal of this research is to describe a suitable personal profile, consisting of the cognitive ability and pedagogical preference of a learner that has associated cognitive metrics found within instructional content. This thesis discusses the design, construction and evaluation of an automated learning component that is built to automatically generate instructional content using an evolutionary strategy, suited to the defined optimal personal profile.
• This paper presents a new method for adapting content in MOOC. A personal profile can be used to automatically generate pedagogical content according to the learning preference and the cognitive ability of a learner in real time. This research deals the manifestation of measurable cognitive traits in MOOC and identifies the cognitive resources within the pedagogical content that can be used to stimulate these manifestations.

Methodology:
• There exists two main components for the learning component: Content Analyser and a Selection Model. The Content Analyser is used to automatically generate metadata to encapsulate cognitive resources within instructional content. The analyser is designed to bridge the perceived gap found within instructional repositories between inconsistent metadata created for instructional content and multiple metadata standards being used. All instructional content that is analysed is repackaged as Sharable Content Object Reference Model (SCORM) conforming content.
• The Selection Model uses an evolutionary algorithm to evolve instructional content to a Minimum Expected Learning Experience to suit the cognitive ability and pedagogical preference of a learner. The Minimum is an approximation to the expected exam result of a learner after a learning experience has taken place. Additionally the research investigates the correlation between the cognitive ability and pedagogic preference of an author of instructional content and the cognitive resources used to generate instructional content. Furthermore the effectiveness of the learning component is investigated by analysing the learners increase in performance using the learning component against a typical classroom environment.
@InProceedings{AAMMOU2017TOW2,
author = {Aammou, S. and Jdidou, Y. and Jdidou, A.},
title = {TOWARD NEW METHOD FOR ADAPTIVE LEARNING IN MOOC},
series = {11th International Technology, Education and Development Conference},
booktitle = {INTED2017 Proceedings},
isbn = {978-84-617-8491-2},
issn = {2340-1079},
doi = {10.21125/inted.2017.2223},
url = {http://dx.doi.org/10.21125/inted.2017.2223},
publisher = {IATED},
location = {Valencia, Spain},
month = {6-8 March, 2017},
year = {2017},
pages = {9424-9428}}
TY - CONF
AU - S. Aammou AU - Y. Jdidou AU - A. Jdidou
TI - TOWARD NEW METHOD FOR ADAPTIVE LEARNING IN MOOC
SN - 978-84-617-8491-2/2340-1079
DO - 10.21125/inted.2017.2223
PY - 2017
Y1 - 6-8 March, 2017
CI - Valencia, Spain
JO - 11th International Technology, Education and Development Conference
JA - INTED2017 Proceedings
SP - 9424
EP - 9428
ER -
S. Aammou, Y. Jdidou, A. Jdidou (2017) TOWARD NEW METHOD FOR ADAPTIVE LEARNING IN MOOC, INTED2017 Proceedings, pp. 9424-9428.
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