Publication Date
| In 2026 | 0 |
| Since 2025 | 6 |
| Since 2022 (last 5 years) | 11 |
| Since 2017 (last 10 years) | 20 |
| Since 2007 (last 20 years) | 24 |
Descriptor
Source
| Journal of Computer Assisted… | 24 |
Author
| Adela Descals | 1 |
| Anquetil, Éric | 1 |
| Argelagós, E. | 1 |
| Barr, M. L. | 1 |
| Baylor, A. L. | 1 |
| Bird, R. J. | 1 |
| Brownie, S. | 1 |
| Chen, Wenli | 1 |
| Cheng, S. T. | 1 |
| Chia-Ju Lin | 1 |
| Chung, L. M. Y. | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 24 |
| Reports - Research | 24 |
Education Level
| Higher Education | 24 |
| Postsecondary Education | 21 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
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)
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
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
Papadopoulos, Pantelis M.; Natsis, Antonis; Obwegeser, Nikolaus; Weinberger, Armin – Journal of Computer Assisted Learning, 2019
The aim of the present study (n = 113) was to examine how (objective and subjective) information on peers' preparation, confidence, and past performance can support students in answering correctly in audience response systems (aka clickers). The result analysis shows that in the "challenging" questions, in which answers diverged,…
Descriptors: Feedback (Response), Audience Response Systems, Self Esteem, Student Attitudes
Yueh-Min Huang; Wei-Sheng Wang; Hsin-Yu Lee; Chia-Ju Lin; Ting-Ting Wu – Journal of Computer Assisted Learning, 2024
Background: Virtual reality (VR) offers significant potential for hands-on learning environments by providing immersive and visually stimulating experiences. Interacting with such environments can bring numerous benefits to learning, including enhanced engagement, knowledge construction, and higher-order thinking. However, many current VR studies…
Descriptors: Computer Simulation, Feedback (Response), Reflection, Experiential Learning
Kühl, Tim; Münzer, Stefan – Journal of Computer Assisted Learning, 2021
According to the personalization principle, addressing learners by means of a personalized compared to a nonpersonalized message can foster learning. Interestingly, though, a recent study found that the personalization principle can invert for aversive contents. The present study investigated whether the negative effect of a personalized message…
Descriptors: Diseases, Information Dissemination, Psychological Patterns, College Students
Wang, Xinghua; Wang, Zhuo; Wang, Qiyun; Chen, Wenli; Pi, Zhongling – Journal of Computer Assisted Learning, 2021
Digital competence is critical for university students to adapt to and benefit from digitally enhanced learning. Prior studies on its measurement mostly focus on educators and relied on factor analyses. However, there is a lack of valid and convenient tools to measure university students' digital competence. This study aimed to develop a digital…
Descriptors: Electronic Learning, Technological Literacy, College Students, Measures (Individuals)
Wang, Cong; Zhu, Sida; Zhang, Haijing – Journal of Computer Assisted Learning, 2023
Background: Since the outbreak of COVID-19, universities in Hong Kong have implemented online and hybrid teaching modes, making computer-assisted language learning (CALL) a primary way for English learning. Research on English learning motivation and self-regulation has seldom considered learners' emotions (satisfaction and preparedness) and the…
Descriptors: Foreign Countries, Student Motivation, Online Courses, English (Second Language)
Michinov, Nicolas; Anquetil, Éric; Michinov, Estelle – Journal of Computer Assisted Learning, 2020
Peer Instruction is an active learning method widely used in higher education, whereby students answer a series of questions twice, once before and once after peer discussion. There is an ongoing debate as to whether a collective feedback should be given after the students' initial answer, and if so, how the frequently observed group conformity…
Descriptors: Peer Teaching, Feedback (Response), Discussion, Active Learning
Previous Page | Next Page »
Pages: 1 | 2
Peer reviewed
Direct link
