Zakaria Bousalem, Aimad Qazdar, Inssaf El Guabassi
{"title":"Cooperative Learning Groups: A New Approach Based on Students’ Performance Prediction","authors":"Zakaria Bousalem, Aimad Qazdar, Inssaf El Guabassi","doi":"10.3991/ijoe.v19i12.41181","DOIUrl":null,"url":null,"abstract":"Cooperative learning is a pedagogical approach in which students collaborate in small groups to attain a shared academic objective. In the classroom, cooperative learning aims to enhance learning outcomes by promoting the exchange of information, social, and personal resources among students. Group formation is a critical and complex step that significantly impacts the effectiveness of cooperative learning. In this article, we propose a novel approach for constructing cooperative learning groups that employs machine learning to predict student performance and incorporates the most common grouping strategies to recommend optimal group formation.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Online and Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3991/ijoe.v19i12.41181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Cooperative learning is a pedagogical approach in which students collaborate in small groups to attain a shared academic objective. In the classroom, cooperative learning aims to enhance learning outcomes by promoting the exchange of information, social, and personal resources among students. Group formation is a critical and complex step that significantly impacts the effectiveness of cooperative learning. In this article, we propose a novel approach for constructing cooperative learning groups that employs machine learning to predict student performance and incorporates the most common grouping strategies to recommend optimal group formation.