消除自学在线STEM教育中的学习障碍

Hongxin Yan, Dr. Fuhua Lin, Dr. Kinshuk
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引用次数: 0

摘要

自定进度在线学习为学习提供了很大的灵活性,但由于这种教育模式的性质,它带来了一些固有的学习障碍。这篇综述文章提出了一些相应的策略来解决这些障碍,以创造一个更支持性的自定进度在线学习环境。这些策略包括a)提高学生的自我学习意识,b)识别困难学生,c)促进掌握学习。本文以科学、技术、工程和数学(STEM)学科的自主在线学习为重点,回顾了形成性评估在学习中的作用。提出系统地设计和嵌入STEM课程中的适应性实践将是实施这些策略的有效学习设计解决方案。通过检查本研究中所要求的适应性实践的目标和上下文,描述了这种适应性实践模型的特征需求。然后对可用于适应性评估的模型和技术进行了审查。基于研究结果,本文认为基于强化学习的自适应练习模型将是满足这些特征需求的最佳选择。最后,我们指出了该领域的研究空白,并为我们和其他研究者提出了未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Removing Learning Barriers in Self-paced Online STEM Education
Self-paced online learning provides great flexibility for learning, yet it brings some inherent learning barriers because of the nature of this educational paradigm. This review paper suggests some corresponding strategies to address these barriers in order to create a more supportive self-paced online learning environment. These strategies include a) increasing students’ self-awareness of learning, b) identifying struggling students, and c) facilitating mastery learning.Focusing on Science, Technology, Engineering, and Mathematics (STEM) disciplines’ delivery of self-paced online learning, this paper reviewed the role of formative assessment for learning. It is proposed that systematically designing and embedding adaptive practicing in STEM courses would be an effective learning design solution to implement these strategies. By examining the goals and context of adaptive practicing requested in this study, the feature requirements are depicted for such an adaptive practicing model. The models and techniques that can be used for adaptive assessment were then reviewed. Based on the review results, this paper argues that a reinforcement learning-based adaptive practicing model would be the best option to meet those feature requirements. Finally, we point out a research gap in this field and suggest a future research direction for ourselves and other researchers.
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CiteScore
1.70
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15
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