Z. Papamitsiou, A. Economides, I. Pappas, M. Giannakos
{"title":"Explaining learning performance using response-time, self-regulation and satisfaction from content: an fsQCA approach","authors":"Z. Papamitsiou, A. Economides, I. Pappas, M. Giannakos","doi":"10.1145/3170358.3170397","DOIUrl":null,"url":null,"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.","PeriodicalId":437369,"journal":{"name":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th International Conference on Learning Analytics and Knowledge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3170358.3170397","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.