{"title":"第二语言学习动机模式的测量及其与学习成绩的关系——以混合式学习课程为例","authors":"Zahra AZIZAH, Tomoya OHYAMA, Xiumin ZHAO, Yuichi OHKAWA, Takashi MITSUISHI","doi":"10.1587/transinf.2023edp7052","DOIUrl":null,"url":null,"abstract":"Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.","PeriodicalId":55002,"journal":{"name":"IEICE Transactions on Information and Systems","volume":"50 9","pages":"0"},"PeriodicalIF":0.6000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course\",\"authors\":\"Zahra AZIZAH, Tomoya OHYAMA, Xiumin ZHAO, Yuichi OHKAWA, Takashi MITSUISHI\",\"doi\":\"10.1587/transinf.2023edp7052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.\",\"PeriodicalId\":55002,\"journal\":{\"name\":\"IEICE Transactions on Information and Systems\",\"volume\":\"50 9\",\"pages\":\"0\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEICE Transactions on Information and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1587/transinf.2023edp7052\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEICE Transactions on Information and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1587/transinf.2023edp7052","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Measuring Motivational Pattern on Second Language Learning and its Relationships to Academic Performance: A Case Study of Blended Learning Course
Learning analytics (LA) has emerged as a technique for educational quality improvement in many learning contexts, including blended learning (BL) courses. Numerous studies show that students' academic performance is significantly impacted by their ability to engage in self-regulated learning (SRL). In this study, learning behaviors indicating SRL and motivation are elucidated during a BL course on second language learning. Online trace data of a mobile language learning application (m-learning app) is used as a part of BL implementation. The observed motivation were of two categories: high-level motivation (study in time, study again, and early learning) and low-level motivation (cramming and catch up). As a result, students who perform well tend to engage in high-level motivation. While low performance students tend to engage in clow-level motivation. Those findings are supported by regression models showing that study in time followed by early learning significantly influences the academic performance of BL courses, both in the spring and fall semesters. Using limited resource of m-learning app log data, this BL study could explain the overall BL performance.
期刊介绍:
Published by The Institute of Electronics, Information and Communication Engineers
Subject Area:
Mathematics
Physics
Biology, Life Sciences and Basic Medicine
General Medicine, Social Medicine, and Nursing Sciences
Clinical Medicine
Engineering in General
Nanosciences and Materials Sciences
Mechanical Engineering
Electrical and Electronic Engineering
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Economics, Business & Management
Psychology, Education.