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Direct linkGülay Öztüre Yavuz; Gökhan Akçapinar; Hatice Çirali Sarica; Yasemin Koçak Usluel – Education and Information Technologies, 2024
This study aims to develop a predictive model for predicting gifted students' engagement levels and to investigate the features that are important in such predictions. Features reflecting students' emotions, social-emotional learning skills, learning approaches and video-watching behaviours were used in the prediction models. The study group…
Descriptors: Secondary School Students, Academically Gifted, Gifted Education, Learner Engagement
Han, Feifei; Ellis, Robert A. – Education and Information Technologies, 2023
This study investigated the extent to which self-report and digital-trace measures of students' self-regulated learning in blended course designs align with each other amongst 145 first-year computer science students in a blended "computer systems" course. A self-reported Motivated Strategies for Learning Questionnaire was used to…
Descriptors: Computer Science Education, Independent Study, College Freshmen, Blended Learning
Trabelsi, Zouheir; Al Matrooshi, Mohammed; Al Bairaq, Saeed; Ibrahim, Walid; Masud, Mohammad M. – Education and Information Technologies, 2017
As mobile devices grow increasingly in popularity within the student community, novel educational activities and tools, as well as learning approaches can be developed to get benefit from this prevalence of mobile devices (e.g. mobility and closeness to students' daily lives). Particularly, information security education should reflect the current…
Descriptors: Telecommunications, Handheld Devices, Student Interests, Best Practices
