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Marlene Steinbach; Johanna Fleckenstein; Livia Kuklick; Jennifer Meyer – Journal of Computer Assisted Learning, 2025
Background: Providing students with information on their current performance could help them improve by stimulating their reflection, but negative feedback that saliently mirrors task-related failure can harm motivation. In the context of automated scoring based on artificial intelligence, we explored how feedback on written texts might be…
Descriptors: Student Motivation, Academic Achievement, Low Achievement, Feedback (Response)
Joshua Weidlich; Aron Fink; Ioana Jivet; Jane Yau; Tornike Giorgashvili; Hendrik Drachsler; Andreas Frey – Journal of Computer Assisted Learning, 2024
Background: Developments in educational technology and learning analytics make it possible to automatically formulate and deploy personalized formative feedback to learners at scale. However, to be effective, the motivational and emotional impacts of such automated and personalized feedback need to be considered. The literature on feedback…
Descriptors: Emotional Response, Student Motivation, Feedback (Response), Automation
Papadopoulos, Pantelis M.; Obwegeser, Nikolaus; Weinberger, Armin – Journal of Computer Assisted Learning, 2022
Background: The feedback offered to students in audience response systems may enhance conformity bias, while asking closed-type questions alone does not allow students to externalize and elaborate on their knowledge. Objectives: The study explores how writing short justifications and accessing peer justifications as collective feedback could…
Descriptors: Written Language, Academic Achievement, Self Esteem, Student Attitudes
Ignacio Máñez; Noemi Skrobiszewska; Adela Descals; María José Cantero; Raquel Cerdán; Óscar Fernando García; Rafael García-Ros – Journal of Computer Assisted Learning, 2024
Background: Delivering effective feedback to large groups of students represents a challenge for the academic staff at universities. Research suggests that undergraduate students often ignore the Elaborated Feedback (EF) received via digital learning environments. This may be because instructors provide feedback in written format instead of using…
Descriptors: Feedback (Response), Audiovisual Aids, Higher Education, College Students
Hatice Yildiz Durak – Journal of Computer Assisted Learning, 2024
Background: Collaboration is a crucial concept in learning and has the potential to foster learning. However, the fact that collaborative groups act with a common understanding in a common task brings many difficulties. Therefore, there is a need for group regulation and guidance to support effective group regulation in collaborative learning. On…
Descriptors: Feedback (Response), Groups, Group Guidance, Cooperation
Roberta Di Palma; Simon Beausaert; Dominik Mahr; Jonas Heller; Tim Hilken – Journal of Computer Assisted Learning, 2025
Background: Despite the recognised potential of Virtual Reality (VR) in education, the role of VR in enhancing presentation skills remains uncertain. Mixed findings, coupled with low adoption rates in educational settings, highlight the need to investigate how current VR applications are designed to facilitate effective learning outcomes for…
Descriptors: Computer Simulation, Computer Uses in Education, Public Speaking, Communication Skills
Vu Thanh Tam Nguyen; Hsiu-Ling Chen; Van Tran Kieu Nguyen – Journal of Computer Assisted Learning, 2025
Background: Social-emotional practices are crucial in today's educational landscape, fostering students' emotional intelligence, resilience and interpersonal skills. Integrating these practices into the gamified flipped classroom approach creates an enriched learning environment. However, there exists a notable research gap regarding the specific…
Descriptors: Social Emotional Learning, Gamification, Flipped Classroom, Emotional Response
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
Yorganci, Serpil – Journal of Computer Assisted Learning, 2022
Background: Continuous advances in mobile and multimedia technologies have increased interest in the use of e-books in educational settings. Objectives: The current study investigated how the e-book technology and different types of feedback influenced the learning, motivation, and cognitive load of students within the differentiation unit of…
Descriptors: Books, Electronic Publishing, Video Technology, Feedback (Response)
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

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