Using Student Generated Videos to Facilitate Discussion for Collaborative Flipped Classrooms

G. Wong, Paulina Pui Yun Wong, R. Wang, Daniel Jiandong Shen, Haoran Xie
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Abstract

The purpose of this study is to incorporate a collaborative flipped classroom technique using student-generated videos to increase classroom participation. Traditional flipped classroom methods depend on educators to spend resources to produce video content. However, there is uncertainty whether a scalable and sustainable method with student-generated content can be used. Student-generated videos may provide opportunities for increasing collaboration and online engagement. The lack of knowledge and evidence has motivated this pilot study for which students record short reflective videos prior or after class using a private social media application, Soqqle. This was performed across three classes of differing modules in Hong Kong and Thailand. Evaluation and analysis of the classes differ, between participation and learning improvements, although having a similar teaching method of using student-generated videos. Results were mixed. In some cases, the predictors of correlational analysis were contradicting. In one group, results show a 64.2% increase in participation compared to the COVID-19 period. In another group, a regression analysis was able to predict learning performance with 41.2% accuracy $(\mathrm{p}= <. 001)$, using the number of videos watched and average duration as predictors. A teaching and learning framework for using the collaborative flipped classroom model is proposed and can be adapted by future researchers. Suggestions to further enhance the model are discussed.
利用学生制作的视频促进合作翻转课堂的讨论
本研究的目的是结合合作翻转课堂技术,使用学生制作的视频来提高课堂参与度。传统的翻转课堂方法依赖于教育者花费资源来制作视频内容。然而,是否有一个可扩展的和可持续的方法与学生生成的内容可以使用的不确定性。学生制作的视频可以提供增加合作和在线参与的机会。知识和证据的缺乏促使了这项试点研究,学生们在课前或课后使用私人社交媒体应用程序Soqqle录制简短的反思视频。这是在香港和泰国进行的三个不同模块的课程。尽管采用了类似的教学方法,即使用学生制作的视频,但在参与和学习改进方面,对课程的评估和分析有所不同。结果喜忧参半。在某些情况下,相关分析的预测因子是相互矛盾的。在一组中,结果显示,与COVID-19期间相比,参与人数增加了64.2%。在另一组中,回归分析能够预测学习表现,准确率为41.2% $(\ mathm {p}= <)。001)$,使用观看的视频数量和平均持续时间作为预测指标。本文提出了一个使用协作式翻转课堂模式的教与学框架,可供未来的研究者采用。讨论了进一步完善该模型的建议。
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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