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MOOC学习者在线学习行为和学习绩效评估模型研究 被引量:56

Towards a model for evaluating students’ online learning behaviors and learning performance
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摘要 MOOC的自主性和灵活性特征,使得学习者具有多样化的学习行为模式,很多研究指出学习者在线学习行为模式与学习成果具有高度相关性。线上授课的教学方式因为其便捷等各种优点,广泛被学生群体所接受,虽然线上授课弥补了传统教学的不可重复性等缺陷,但是由于每个学生的在线学习行为不同,其教学效果也因人而异,本研究尝试从国内最早的MOOC平台"学堂在线"上获取学生的学习行为数据,建立学生在线学习行为与在线学习绩效评估模型,并进行抽样逐步回归,以了解学生在线学习行为对其学习成绩的影响。结果表明,学生某些在线学习行为,如作业完成比例、视频完成率等对其学习效果产生重要的正面影响,反之部分在线学习行为对学习效果会产生不良影响。因此,根据本研究结果对教师设计在线学习、对学生开展线上学习提供意见和建议,将有效提高在线学习的效率和效果。 The flexibility of MOOCs leads to learner autonomy and diversity in learning behaviors.Studies show that learners’ online learning behaviors are highly correlated with their learning outcomes.Online learning is widely accepted by students for its convenience and other advantages.Despite the fact that it can overcome the one-off nature of traditional teaching,different online learning behaviors may result in different learning outcomes.Based on learning behavior data from the MOOC platform XuetangX,this study constructs a model for evaluating online learning behaviors and learning performance,and conducts sampling and regression analysis to elaborate on the impact of learning behaviors on learning performance.The results show that certain online learning behaviors,such as homework completion rate and video completion rate,have an important positive impact on their learning effectiveness,whereas some other online learning behaviors have a negative impact.Suggestions can be drawn from the present study for teachers and students as to how to design online learning and facilitate students’ engagement,leading to enhancement of learning effectiveness.
作者 沈欣忆 刘美辰 吴健伟 董现垒 Xinyi Shen;Meichen Liu;Jianwei Wu;Xianlei Dong
出处 《中国远程教育》 CSSCI 北大核心 2020年第10期1-8,76,共9页 Chinese Journal of Distance Education
关键词 在线学习行为 学习绩效评估模型 在线学习者 教育大数据 数据挖掘 学堂在线 PYTHON online learning behavior learning performance evaluation model online learner education big data data mining XuetangX Python
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