Abstract
Adaptive learning plays a significant role in online learning. It enables the students, to decide what to select, how to learn and how to assess themselves. This method provides a personalized learning path and enabling them to involve in, as they advance through the learning resources. To demonstrate, this study has developed an adaptive e-learning system (AeLS), using Lesson activity in Moodle, to teach a course in Computer Graphics, for the undergraduate students of Computer Applications Programme. The Felder-Silverman Learning Style Model has also employed with the intention of integrating diverse learning styles of students. To evaluate the effectiveness of the system, the study has resorted to the use of the statistical method; independent two-sample t-test among two groups of slow learners. Experimental evaluation demonstrates that AeLS is able to achieve comparable performance on a group of slow learners, than who used traditional face-to-face class room teaching method.
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Joseph, L., Abraham, S. (2019). Adaptive e-Learning System for Slow Learners Based on Felder-Silverman Learning Style Model. In: Luhach, A., Jat, D., Hawari, K., Gao, XZ., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2019. Communications in Computer and Information Science, vol 1075. Springer, Singapore. https://doi.org/10.1007/978-981-15-0108-1_13
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