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Yang Jiang; Beata Beigman Klebanov; Jiangang Hao; Paul Deane; Oren E. Livne – Journal of Computer Assisted Learning, 2025
Background: Writing is integral to educational success at all levels and to success in the workplace. However, low literacy is a global challenge, and many students lack sufficient skills to be good writers. With the rapid advance of technology, computer-based tools that provide automated feedback are being increasingly developed. However, mixed…
Descriptors: Feedback (Response), Writing Evaluation, Middle School Students, High School Students
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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
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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
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Arguedas, Marta; Daradoumis, Thanasis – Journal of Computer Assisted Learning, 2021
There is a lack of studies that examine the role of a pedagogical agent on student development in a specific learning situation that involves psychological and cognitive preparatory activities in high school settings. We examined the effectiveness of pedagogical agent (APT) cognitive and affective feedback on learner motivation and well-being. We…
Descriptors: High School Students, Feedback (Response), Learning Motivation, Well Being
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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