{"title":"基于学习分析的反馈对混合式英语课程中学生自我调节学习和学业成绩的影响","authors":"Jing Chen","doi":"10.1016/j.system.2024.103388","DOIUrl":null,"url":null,"abstract":"<div><p>This study explores the impact of learning analytics (LA)-based feedback on students' self-regulated learning (SRL) and academic achievement in a blended English-as-a-foreign-language (EFL) course. Employing a quasi-experimental research design, this study utilized propensity score matching (PSM) to form a treatment group (<em>N</em> = 160) from the 2023 undergraduate student cohort, receiving LA-based feedback, and matched it with a comparison group of equivalent size from the 2021 and 2022 cohorts without such feedback. Guided by Winne and Hadwin's COPES model (1998), SRL was operationalized at a coarse level with students' online log data and course assessment scores representing their SRL operations and products of SRL in the course, respectively. Results of mixed ANOVAs and chi-square tests of independence showed that the LA-based feedback enhanced students' completion rate of online learning activities and their study regularity. The treatment group exhibited superior performance in the final examination compared to the comparison group, providing evidence of the positive impact of LA-based feedback on students' course performance. The study represents an initial effort to utilize LA-based feedback to support students' SRL operations and course performance in an EFL context.</p></div>","PeriodicalId":4,"journal":{"name":"ACS Applied Energy Materials","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effects of learning analytics-based feedback on students’ self-regulated learning and academic achievement in a blended EFL course\",\"authors\":\"Jing Chen\",\"doi\":\"10.1016/j.system.2024.103388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study explores the impact of learning analytics (LA)-based feedback on students' self-regulated learning (SRL) and academic achievement in a blended English-as-a-foreign-language (EFL) course. Employing a quasi-experimental research design, this study utilized propensity score matching (PSM) to form a treatment group (<em>N</em> = 160) from the 2023 undergraduate student cohort, receiving LA-based feedback, and matched it with a comparison group of equivalent size from the 2021 and 2022 cohorts without such feedback. Guided by Winne and Hadwin's COPES model (1998), SRL was operationalized at a coarse level with students' online log data and course assessment scores representing their SRL operations and products of SRL in the course, respectively. Results of mixed ANOVAs and chi-square tests of independence showed that the LA-based feedback enhanced students' completion rate of online learning activities and their study regularity. The treatment group exhibited superior performance in the final examination compared to the comparison group, providing evidence of the positive impact of LA-based feedback on students' course performance. The study represents an initial effort to utilize LA-based feedback to support students' SRL operations and course performance in an EFL context.</p></div>\",\"PeriodicalId\":4,\"journal\":{\"name\":\"ACS Applied Energy Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Energy Materials\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0346251X24001702\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Energy Materials","FirstCategoryId":"98","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0346251X24001702","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Effects of learning analytics-based feedback on students’ self-regulated learning and academic achievement in a blended EFL course
This study explores the impact of learning analytics (LA)-based feedback on students' self-regulated learning (SRL) and academic achievement in a blended English-as-a-foreign-language (EFL) course. Employing a quasi-experimental research design, this study utilized propensity score matching (PSM) to form a treatment group (N = 160) from the 2023 undergraduate student cohort, receiving LA-based feedback, and matched it with a comparison group of equivalent size from the 2021 and 2022 cohorts without such feedback. Guided by Winne and Hadwin's COPES model (1998), SRL was operationalized at a coarse level with students' online log data and course assessment scores representing their SRL operations and products of SRL in the course, respectively. Results of mixed ANOVAs and chi-square tests of independence showed that the LA-based feedback enhanced students' completion rate of online learning activities and their study regularity. The treatment group exhibited superior performance in the final examination compared to the comparison group, providing evidence of the positive impact of LA-based feedback on students' course performance. The study represents an initial effort to utilize LA-based feedback to support students' SRL operations and course performance in an EFL context.
期刊介绍:
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.