The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A New Approach of an Intelligent E-Learning System Based on Learners' Skill Level and Learners' Success Rate
Abstract
Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper, the authors propose an online course generation based not only on the difficulty level of a learning unit, but also the changing learning performance of the individual learner during the learning process. Therefore, considering learner's skill level and learners' success rate can promote personalized learning performance. Learners' skill level is obtained from pre-test result analysis, while learners' success rate is acquired through specific tests after completing a learning unit. After computing success rate of a learning unit, the system then modifies the difficulty level of the corresponding learning unit to update courseware material sequencing. Experiment results indicate that applying the proposed intelligent e-learning system can generate high quality learning paths, and help learners to learn more effectively.
Related Content
|
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
|
Stavros Kaperonis.
© 2024.
25 pages.
|
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
|
Nuno Geada.
© 2024.
12 pages.
|
|
|