Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles
ARTICLE
Tzu-Chi Yang, Gwo-Jen Hwang, Stephen Jen-Hwa Yang
Journal of Educational Technology & Society Volume 16, Number 4, ISSN 1176-3647 e-ISSN 1176-3647
Abstract
In this study, an adaptive learning system is developed by taking multiple dimensions of personalized features into account. A personalized presentation module is proposed for developing adaptive learning systems based on the field dependent/independent cognitive style model and the eight dimensions of Felder-Silverman's learning style. An experiment has been conducted to evaluate the performance of the proposed approach in a computer science course. Fifty-four participants were randomly assigned to an experimental group which learned with an adaptive learning system developed based on the personalized presentation module, and a control group which learned with the conventional learning system without personalized presentation. The experimental results showed that the experimental group students revealed significantly better learning achievements than the control group students, implying that the proposed approach is able to assist the students in improving their learning performance. (Contains 8 tables and 6 figures.)
Citation
Yang, T.C., Hwang, G.J. & Yang, S.J.H. (2013). Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles. Journal of Educational Technology & Society, 16(4), 185-200. Retrieved March 19, 2024 from https://www.learntechlib.org/p/131570/.
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Keywords
- Cognitive Ability
- Cognitive Processes
- Cognitive Style
- computer science education
- Computer Uses in Education
- Control Groups
- Difficulty Level
- Experimental Groups
- Foreign Countries
- goal orientation
- Graduate students
- Individualized Instruction
- Learning Motivation
- Multimedia Instruction
- Pretests Posttests
- Questionnaires
- Self Efficacy
- teaching methods
- Test Anxiety
- undergraduate students
Cited By
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SVM and PCA Based Learning Feature Classification Approaches for E-Learning System
Aditya Khamparia & Babita Pandey, Lovely Professional University, Jalandhar, India
International Journal of Web-Based Learning and Teaching Technologies Vol. 13, No. 2 (April 2018) pp. 32–45
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