mooc的心理测量学:学习者熟练程度的测量。

IF 2.7 4区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY Psychologica Belgica Pub Date : 2020-05-22 DOI:10.5334/pb.515
Dmitry Abbakumov, Piet Desmet, Wim Van den Noortgate
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引用次数: 6

摘要

大规模在线开放课程(MOOCs)产生学习者的表现数据,可以用来了解学习者的熟练程度,提高他们的效率。然而,目前使用的方法,如评估评估中正确回答的比例,过于简化,可能导致糟糕的结论和决定,因为它们没有考虑到关于学习者、内容和背景的额外信息。mooc需要有理论基础的、数据驱动的、可解释的教育测量方法。在这篇概念性的论文中,我们试图建立心理测量学(一门涉及教育和心理测量技术的科学学科)与mooc之间的联系。首先,我们描述了学习者在教育中的熟练程度的传统测量的一般原则。其次,我们讨论了阻碍基于这些一般原则的方法直接应用的mooc的质量。第三,我们讨论了测量能力的最新发展,这可能与分析MOOC数据有关。最后,我们提出了心理测量建模的方向,这些方向可能对未来的MOOC研究很有意义。
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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Psychometrics of MOOCs: Measuring Learners' Proficiency.

Massive open online courses (MOOCs) generate learners' performance data that can be used to understand learners' proficiency and to improve their efficiency. However, the approaches currently used, such as assessing the proportion of correct responses in assessments, are oversimplified and may lead to poor conclusions and decisions because they do not account for additional information on learner, content, and context. There is a need for theoretically grounded data-driven explainable educational measurement approaches for MOOCs. In this conceptual paper, we try to establish a connection between psychometrics, a scientific discipline concerned with techniques for educational and psychological measurement, and MOOCs. First, we describe general principles of traditional measurement of learners' proficiency in education. Second, we discuss qualities of MOOCs which hamper direct application of approaches based on these general principles. Third, we discuss recent developments in measuring proficiency that may be relevant for analyzing MOOC data. Finally, we draw directions in psychometric modeling that might be interesting for future MOOC research.

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来源期刊
Psychologica Belgica
Psychologica Belgica PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
4.00
自引率
5.00%
发文量
22
审稿时长
4 weeks
期刊最新文献
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