YA-HUEI WANGHUNG-CHANG LIAO2026-10-162026-10-162011-06-01Pure ID: 15346861Pure UUID: 0520fd9d-2a5a-48ee-8c9e-89ee1a11900210.1016/j.eswa.2010.11.098https://www.scopus.com/pages/publications/79951578290https://scholars.csmu.edu.tw/handle/123456789/23819This study proposes an Adaptive Learning in Teaching English as a Second Language (TESL) for e-learning system (AL-TESL-e-learning system) that considers various student characteristics. This study explores the learning performance of various students using a data mining technique, an artificial neural network (ANN), as the core of AL-TESL-e-learning system. Three different levels of teaching content for vocabulary, grammar, and reading were set for adaptive learning in the AL-TESL-e-learning system. Finally, this study explores the feasibility of the proposed AL-TESL-e-learning system by comparing the results of the regular online course control group with the AL-TESL-e-learning system adaptive learning experiment group. Statistical results show that the experiment group had better learning performance than the control group; that is, the AL-TESL-e-learning system was better than a regular online course in improving student learning performance.6enjournal article