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Ute Mertens; Marlit A. Lindner – Journal of Computer Assisted Learning, 2025
Background: Educational assessments increasingly shift towards computer-based formats. Many studies have explored how different types of automated feedback affect learning. However, few studies have investigated how digital performance feedback affects test takers' ratings of affective-motivational reactions during a testing session. Method: In…
Descriptors: Educational Assessment, Computer Assisted Testing, Automation, Feedback (Response)
Yun Zhang; Fangzheng Zhao; Richard E. Mayer – Journal of Computer Assisted Learning, 2025
Background and Objective: The positivity principle states that students learn better from instructors who display positive rather than negative or neutral emotions in multimedia lessons (Lawson et al. 2021a). This study extends this work by exploring the role of affective and social cues displayed by feedback providers, such as their emotional…
Descriptors: Multimedia Instruction, Psychological Patterns, Feedback (Response), Gender Differences
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
Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
Olga Viberg; Martine Baars; Rafael Ferreira Mello; Niels Weerheim; Daniel Spikol; Cristian Bogdan; Dragan Gasevic; Fred Paas – Journal of Computer Assisted Learning, 2024
Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported…
Descriptors: Feedback (Response), Peer Evaluation, Computer Assisted Instruction, Cooperative Learning
Seyma Çaglar-Özhan; Perihan Tekeli; Selay Arkün-Kocadere – Journal of Computer Assisted Learning, 2025
Background: Feedback is an essential part of the educational process as it enriches students' learning experiences, provides information about their current performance, shows them what is lacking in achieving goals, and provides guidance on the strategies needed to achieve those goals. Teachers, especially in crowded classrooms, often have…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Role, Technology Uses in Education
Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
Byunghoon Ahn; Negar Matin; Myriam Johnson; So Yeon Lee; Ning-Zi Sun; Jason M. Harley – Journal of Computer Assisted Learning, 2025
Background: High fidelity simulations can be an effective tool for anti-harassment education. While emotions have been identified as crucial in simulation-based education, their role in anti-harassment education within medical training remains underexplored. Objectives: We aimed to investigate emotional profiles of medical residents during…
Descriptors: Medical Students, Psychological Patterns, Bullying, Prevention
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
Bhagya Maheshi; Wei Dai; Roberto Martinez-Maldonado; Yi-Shan Tsai – Journal of Computer Assisted Learning, 2024
Background: Feedback is central to formative assessments but aligns with a one-way information transmission perspective obstructing students' effective engagement with feedback. Previous research has shown that a responsive, dialogic feedback process that requires educators and students to engage in ongoing conversations can encourage student…
Descriptors: Feedback (Response), Learning Analytics, Dialogs (Language), Learner Engagement
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
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
Ignacio Villagrán; Rocío Hernández; Javiera Fuentes-Cimma; Constanza Miranda; Julián Varas; Andrés Neyem; Gabriela Sepúlveda; Bárbara Catril; Patricio García; Isabel Hilliger; Eduardo Fuentes-Lopez – Journal of Computer Assisted Learning, 2025
Background: Before they graduate, higher education students must demonstrate technical skills in different procedures, where health degrees such as physiotherapy stand out for their practical nature. Procedural skill development requires students to uptake feedback continuously, which is costly in terms of time and effort. Although the…
Descriptors: Allied Health Occupations Education, Undergraduate Students, Trainees, Physical Therapy
Richard Say; Denis Visentin; Annette Saunders; Iain Atherton; Andrea Carr; Carolyn King – Journal of Computer Assisted Learning, 2024
Background: Formative online multiple-choice tests are ubiquitous in higher education and potentially powerful learning tools. However, commonly used feedback approaches in online multiple-choice tests can discourage meaningful engagement and enable strategies, such as trial-and-error, that circumvent intended learning outcomes. These strategies…
Descriptors: Feedback (Response), Self Management, Formative Evaluation, Multiple Choice Tests

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