Explaining learning performance using response-time, self-regulation and satisfaction from content: an fsQCA approach

Z. Papamitsiou, A. Economides, I. Pappas, M. Giannakos
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引用次数: 24

Abstract

This study focuses on compiling students' response-time allocated to answer correctly or wrongly, their self-regulation, as well as their satisfaction from content, in order to explain high or medium/low learning performance. To this end, it proposes a conceptual model in conjunction with research propositions. For the evaluation of the approach, an empirical study with 452 students was conducted. The fuzzy set qualitative comparative analysis (fsQCA) revealed five configurations driven by the admitted factors that explain students' high performance, as well as five additional patterns, interpreting students' medium/low performance. These findings advance our understanding of the relations between actual usage and latent behavioral factors, as well as their combined effect on students' test score. Limitations and potential implications of these findings are also discussed.
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用反应时间、自我调节和内容满意度来解释学习表现:fsQCA方法
本研究的重点是整理学生答对或答错的反应时间、自我调节和对内容的满意度,以解释高或中/低的学习表现。为此,本文结合研究命题,提出了一个概念模型。为了对该方法进行评价,我们对452名学生进行了实证研究。模糊集定性比较分析(fsQCA)揭示了由录取因素驱动的五种配置,解释了学生的高成绩,以及五种额外的模式,解释了学生的中/低成绩。这些发现促进了我们对实际使用和潜在行为因素之间的关系的理解,以及它们对学生考试成绩的综合影响。本文还讨论了这些发现的局限性和潜在意义。
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