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

Papamitsiou, Zacharoula; Economides, Anastasios; Pappas, Ilias; Giannakos, Michail
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Accepted version
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Papamitsiou (807.7Kb)
URI
http://hdl.handle.net/11250/2595315
Date
2018
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  • Institutt for datateknologi og informatikk [3881]
  • Publikasjoner fra CRIStin - NTNU [21058]
Original version
10.1145/3170358.3170397
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.
Publisher
Association for Computing Machinery (ACM)

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