在翻转课堂课程中,学生自我报告和观察的学习方法之间的一致性水平:它如何影响学生的学术学习成果?
Feifei Han1,2
1Institute for Learning Sciences and Teacher Education, Australia Catholic University, Brisbane, Australia.
PloS one
|June 13, 2023
概括
这项研究比较了在翻转计算机科学课程中自我报告和观察到的学生学习方法. 结果显示中等的一致性,但强调报告和观察到的深度或表面学习方法之间的差异不会显著影响学术成果.
科学领域:
- 教育心理学教育心理学
- 计算机科学教育计算机科学教育
- 学习科学 学习科学
背景情况:
- 了解学生的学习方法对于有效的教学至关重要,特别是在翻转教室等创新的学习环境中.
- 学生学习方法 (SAL) 框架为分类深度与表面学习策略提供了理论基础.
- 自我认知和实际行为之间的差异可能会影响学习成果,需要强有力的评估方法.
研究的目的:
- 在翻转计算机科学课程中,调查自我报告和观察学生学习方法之间的一致性.
- 确定学术学习成果是否基于报告与观察研究方法的一致性而有所不同.
- 分析来自不同数据源的深度/表面和主动/被动研究方法分类之间的关系.
主要方法:
- 采用混合方法方法,使用来自修订研究过程问卷的自我报告数据和来自在线学习活动的观察日志数据.
- 将143名计算机科学本科生分为深度/表面 (自我报告) 和主动/被动 (观察) 研究方法组.
- 使用2x2交叉表格分析两种类型的学习方法数据之间的关联及其对课程成绩的影响.
主要成果:
- 在自我报告和观察研究方法之间发现了中等的积极关联.
- 报告深度学习方法的学生主要表现出积极学习方法 (80.7%),而报告表面学习方法的学生则更倾向于被动学习方法 (51.2%).
- 观察到的积极但自我报告的表面方法和观察到的积极但自我报告的表面方法的学生之间没有明显的课程成绩差异,也没有观察到一致的糟糕方法和观察到的被动但自我报告的深度方法.
结论:
- 虽然自我报告和观察研究方法显示了中等的对齐,但存在不一致性,特别是在翻转的学习环境中.
- 观察到的研究行为,而不是仅仅是自我报告的方法,在所有不一致的情况下可能与学术结果没有直接的相关性.
- 未来的研究应该结合定性方法来探索自我报告和观察到的学习策略之间的不一致的根本原因.
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