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Teresa M. Ober; Ying Cheng; Matthew F. Carter; Cheng Liu – Journal of Computer Assisted Learning, 2024
Background: Students' tendencies to seek feedback are associated with improved learning. Yet, how soon this association becomes robust enough to make predictions about learning is not fully understood. Such knowledge has strong implications for early identification of students at-risk for underachievement via digital learning platforms.…
Descriptors: Academic Achievement, Feedback (Response), Student Behavior, At Risk Students
Eshuis, Elise H.; ter Vrugte, Judith; Anjewierden, Anjo; de Jong, Ton – Journal of Computer Assisted Learning, 2022
Background: Creating concept maps can help students overcome challenges of accurate knowledge monitoring and thus foster learning. However, students' knowledge often contains gaps and misconceptions, even after concept map creation. Theoretically, students could benefit from additional support, but it is unclear whether this might also be the case…
Descriptors: Reflection, Concept Mapping, Knowledge Representation, Instructional Effectiveness
Katharina Alexandra Whalen; Alexander Renkl; Alexander Eitel; Inga Glogger-Frey – Journal of Computer Assisted Learning, 2024
Background: Students often show unfavourable attribution: they attribute poor school performance to stable factors such as lack of ability and good school performance to variable factors such as effort. However, attribution can be influenced by individualized digital re-attributional feedback leading to positive motivational effects and higher…
Descriptors: Feedback (Response), Computer Mediated Communication, Secondary School Mathematics, Student Motivation
Fangzhou Jin; Xiangmei Peng; Lanfang Sun; Zicong Song; Keyi Zhou; Chin-Hsi Lin – Journal of Computer Assisted Learning, 2025
Background: There are various challenges to teachers' use of generative artificial intelligence (GenAI) for professional learning. Although GenAI is expected to play a transformative role in teachers' learning, its impact on them remains subtle. Objectives: Guided by community of practice, this paper examines the integration of GenAI into an…
Descriptors: Artificial Intelligence, Communities of Practice, Technology Uses in Education, Experienced Teachers
Menabò, Laura; Sansavini, Alessandra; Brighi, Antonella; Skrzypiec, Grace; Guarini, Annalisa – Journal of Computer Assisted Learning, 2021
Background: The rapid spread of COVID-19 forced many countries to adopt severe containment measures, transferring all didactic activities into virtual environments. However, the integration of technology in teaching may present difficulties, especially in some countries, such as Italy. Objectives: The present study analyzed how the two main…
Descriptors: Technology Integration, Intention, Adoption (Ideas), Electronic Learning
Truzoli, Roberto; Pirola, Veronica; Conte, Stella – Journal of Computer Assisted Learning, 2021
The lockdown due to COVID-19 in Italy resulted in the sudden closure of schools, with a shift from traditional teaching to the online one. Through an online questionnaire, this survey explores teachers' experience of online teaching, the level of risk factors (e.g., stress) and protective factors (e.g., locus of control) and their impact on…
Descriptors: Risk, Stress Variables, Depression (Psychology), Mental Health
Lin, C.-C.; Guo, K.-H.; Lin, Y.-C. – Journal of Computer Assisted Learning, 2016
This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…
Descriptors: Remedial Instruction, Artificial Intelligence, Intelligent Tutoring Systems, Electronic Learning
Beal, C. R.; Qu, L.; Lee, H. – Journal of Computer Assisted Learning, 2008
The study was conducted to investigate the relation of adolescent students' mathematics motivation and achievement to their appropriate help-seeking and inappropriate guessing behaviour while using instructional software. High school students (n = 90) completed brief assessments of mathematics motivation and then worked with software for geometry…
Descriptors: Mathematics Achievement, Student Motivation, Courseware, Mathematics Teachers
Lu, M. – Journal of Computer Assisted Learning, 2008
Whereas the penetration of mobile phones in Asian countries keeps climbing, little research has explored the application of the short message service (SMS) in second language learning. This study aims to examine the effectiveness of SMS vocabulary lessons of limited lexical information on the small screens of mobile phones. Thirty high school…
Descriptors: High School Students, English (Second Language), Interviews, Pretests Posttests