失败还是通过?调查 MOOC 讨论板中的学习体验和互动角色

IF 8.9 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Education Pub Date : 2024-05-09 DOI:10.1016/j.compedu.2024.105073
Xin Wei , Yajun Chen , Jianhua Shen , Liang Zhou
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引用次数: 0

摘要

在大规模开放在线课程(MOOC)的讨论区中,学生的学习经历反映了学生的内隐认知和情感状态,与学生的学习效果和课程完成率相关。关于MOOC中学习体验识别的研究大多依赖于事后问卷调查,这可能会遇到个人偏见、记忆模糊或时间限制等问题,而且在MOOC中发放问卷也很困难。此外,学生在学习过程中的互动也会影响学习体验,但两者之间的关系尚未得到深入探讨。本研究旨在解决这些问题。首先,它提出了一种基于人工智能的文本分析方法,用于从 MOOC 讨论板中的大规模学生帖子中自动识别学习经验模式。与其他竞争方法相比,该方法在准确性方面具有优势。其次,本研究从MOOC讨论区的社会关系和互动行为两方面定义了学生的互动角色,并分析了不同互动角色对应的学习经验。对于高参与度、低影响力的学生来说,容易产生流动感和厌倦感;而对于低参与度、高影响力的学生来说,容易产生焦虑感和冷漠感。最后,本研究揭示了互动角色方面的学习经验对学习成绩的影响。对于参与度高的学生,其学习成绩受学习经验的影响较小,而对于互动不积极的学生,流动与良好的学习成绩有关。总之,本研究对自动学习经验识别具有重要的方法论意义。此外,本研究还揭示了互动角色在描述学习经验与学习成绩之间相互作用时的重要性,并为改进 MOOCs 提供了建议。
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Fail or pass? Investigating learning experiences and interactive roles in MOOC discussion board

In massive open online course (MOOC) discussion board, students' learning experience, reflecting implicit cognitive and affective states, is related to their learning outcomes and course's completion rates. The majority of researches about learning experience identification in MOOCs depend on post-hoc questionnaires, which may encounter issues such as personal biases, hazy memories, or time constraints, and distribution difficulty in MOOCs. Moreover, learning experience is influenced by students' interactions during learning but their relationship has not been thoroughly explored. This study aimed to address these issues. Firstly, it proposed an artificial intelligence-based text analysis approach for automatically identifying patterns of learning experiences from the large-scale students' posts in MOOC discussion board. It had performance advantage in terms of accuracy when compared with the other competing approaches. Secondly, this study defined students' interactive roles from both social relations and interaction behaviors in MOOC discussion board, and analyzed learning experiences corresponding to the different interactive roles. For students with high participation and low influence in interactions, flow and boredom were prone to happen, while for students with low participation and high influence in interactions, anxiety and apathy were easy to generate. Finally, this study revealed the effect of learning experience on learning achievement with respect to interactive role. For students with high participation characteristics, their learning achievements were less affected by learning experience, while for students less active in interaction, flow was related with good learning achievements. In summary, this study had significant methodological implications for automated learning experience identification. Moreover, this study revealed importance of interactive role in describing the interplay between learning experience and learning achievement, and provided suggestions for the improvement of MOOCs.

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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
期刊介绍: Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.
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