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Perception and Attitude Toward Self-Regulated Learning in Educational Data Mining

机译:教育数据挖掘中自我调节学习的知觉和态度

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The Self-Regulated Learning (SRL) strategies can be the best achieved by achieving a sub-goal that will lead to a broader future in the younger generation. This paper proposes the process of developing factors (attributes) related to the development of learning styles through SRL strategies. The objectives of this paper are (1) to study the perception and attitude toward the attributes of students with SRL of the students in higher education, and (2) to find the level of acceptance towards the factor of SRL using applied statistics and machine learning. The results show that the two tools have proved that the respondents accept the factors of SRL in the accepted level. Besides, the results show that Thai higher education students still focus on formal learning. For the future, the authors aim to develop and apply an SRL strategies model with a combination of collaborative learning strategies of blended learning for undergraduate students.
机译:通过实现子目标可以最好地实现自我调节学习(SRL)策略,这将导致年轻一代的更广阔的未来。本文提出了通过SRL策略发展与学习风格发展有关的因素(属性)的过程。本文的目的是(1)研究高等教育学生对具有SRL的学生的属性的看法和态度,以及(2)使用应用统计数据和机器学习来确定对SRL因子的接受程度。结果表明,这两种工具已证明受访者在可接受水平上接受了SRL的因素。此外,结果表明,泰国的高等教育学生仍然侧重于正规学习。对于未来,作者旨在开发和应用SRL策略策略模型,并结合面向大学生的混合学习协作学习策略。

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