Adaptive e-learning web-based English tutor using data mining techniques and Jackson's learning styles

Yahya M. Tashtoush, Majd Al-Soud, Manar Fraihat, Walaa Al-Sarayrah, M. Alsmirat
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引用次数: 11

Abstract

With the emanation of educational data mining field, it is being increasingly connected to a number of research areas such as adaptive and intelligent web-based tutors, intelligent educational applications and other accommodating online educational data mining systems. The applications of educational data mining takes into account the system academic aspects, the academic background, and the learner's classification. This paper proposes a new adaptive e-learning system. The proposed system integrates a well known intelligent web-based English e-learning tutor with data mining techniques. Also, the data minig techniques are used in order to cluster students' learning styles according to Jackson's learning styles. The ultimate goal of the proposed system is to determine the best teaching pattern for each learner. The proposed system can be made available through the web Everywhere as well as Every Time (EWET). It also offers adaptive facilities such as learning videos, adaptive presentations, and quizzes for the students. Moreover, it helps both teachers and students to follow the best learning process and achieve the highest academic rates. The results show that the highest student's achievement pattern is the pattern (Speaking — Reading — Grammar — Writing) with score of at least 87.4%.
使用数据挖掘技术和杰克逊学习风格的自适应电子学习网络英语家教
随着教育数据挖掘领域的兴起,它越来越多地与自适应智能网络导师、智能教育应用和其他适应在线教育数据挖掘系统的研究领域联系在一起。教育数据挖掘的应用考虑到系统的学术方面、学术背景和学习者的分类。本文提出了一种新的自适应电子学习系统。该系统将基于网络的智能英语在线学习辅导系统与数据挖掘技术相结合。同时,运用数据挖掘技术,根据Jackson的学习风格对学生的学习风格进行聚类。该系统的最终目标是为每个学习者确定最佳的教学模式。所提出的系统可以通过网络随时随地(EWET)提供。它还为学生提供适应性设施,如学习视频、适应性演示和测验。此外,它帮助教师和学生遵循最好的学习过程,并取得最高的学习成绩。结果显示,学生成绩最高的模式为(口语-阅读-语法-写作)模式,得分不低于87.4%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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