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作 者:李彤彤 马梦纯 刘金佑 边雨迎 王英 吴燕 LI Tongtong;MA Mengchun;LIU Jinyou;BIAN Yuying;WANG Ying;WU Yan(Faculty of Education,Tianjin Normal University,Tianjin 300387,China)
出 处:《开放学习研究》2024年第6期30-40,共11页Journal of Open Learning
基 金:2022年度国家自然科学基金青年课题“在线异步讨论中交互深度的智能评价与人机协同促进机制研究”(课题编号:62207019)的研究成果。
摘 要:在线异步讨论作为师生、生生交互的重要途径,能够弥补因师生分离所带来的互动不足与学习低效等问题。已有研究表明,教师反馈是影响在线讨论效果的关键因素之一。然而,关于不同类型的教师反馈如何具体影响在线异步讨论的交互深度,尚缺乏直接且明确的实证支持。文章将教师反馈分为无反馈、鼓励型、提示型、澄清请求型以及混合型五类,从客观维度的交互行为和交互意义以及主观维度的在线临场感与深度学习数据衡量交互深度,进而采用准实验法探究不同类型的教师反馈对讨论中交互深度的影响。研究发现:混合型反馈在提升交互频度、关联度、增强教学与社会临场感、激发学生深层学习动机和能力方面具有显著优势,澄清请求型反馈的持续时间长且交互频繁,在促进学生深度学习能力上体现出了优势。针对上述结论,文章提出了以下建议:教师应采取混合反馈策略,针对不同情况提供多种不同类型的反馈,反馈内容要充分关注学生的情感体验,且应关注如何引导学生更深层次的“反思”等认知交互行为,反馈形式也应走向人机协同,以期通过更精准、有效、个性化的反馈提升在线异步讨论的交互深度。As an important way of interaction between teachers and students,online asynchronous discussion can make up for the lack of interaction and low learning efficiency caused by the separation of teachers and students.Studies have shown that teacher feedback is one of the key factors affecting online discussion effect.However,there is still a lack of direct and explicit empirical study on how different types of teacher feedback specifically affect the depth of interaction in online asynchronous discussions.In this article,teacher feedback is divided into five categories:no feedback,encouragement,suggestion,clarification request and mixed feedback.Interaction depth is measured by interactive behavior and interaction meaning in objective dimension and online presence and deep learning data in subjective dimension.Then,a quasi-experimental method is used to explore the influence of different types of teacher feedback on discussion interaction depth.It is found that mixed feedback has significant advantages in improving interaction frequency and correlation,enhancing the sense of teaching and society presence,while stimulating the motivation and ability of students’deep learning.The clarification request feedback group has a long duration and frequent interaction,and shows advantages in promoting students’deep learning ability.In view of the above conclusions,the following suggestions are put forward:adopting a mixed feedback strategy to provide different types of feedback according to different situations,paying full attention to students’emotional experience and guiding students to deeper cognitive interaction behaviors such as“reflection”,moving towards human-computer collaboration to enhance the interactive depth of online asynchronous discussion through more accurate,effective and personalized feedback.
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