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Deniz Yesi?l; Fatma Bayrak – Open Praxis, 2025
Feedback is a critical component of the learning process and is essential to reinforce the effect of feedback with affective elements. Due to technological developments, providing automated feedback has become easy. Therefore, this study examined the effect of automated elaborated feedback provided with affective feedback on situational intrinsic…
Descriptors: Feedback (Response), Automation, Student Motivation, Self Efficacy
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)
Leonie Brummer; Hester de Boer; Jolien M. Mouw; Jan-Willem Strijbos – Learning Environments Research, 2024
Even though context, content, and task factors are considered essential parts of digitally delivered instructional feedback, their effects on learning performance are most often studied separately. A meta-analysis was carried out to address the effects of context, content, and task factors of digitally delivered instructional feedback on learning…
Descriptors: Feedback (Response), Teacher Response, Computer Mediated Communication, Computer Assisted Instruction
Shujun Liu; Azzeddine Boudouaia; Xinya Chen; Yan Li – Asia-Pacific Education Researcher, 2025
The application of Automated Writing Evaluation (AWE) has recently gained researchers' attention worldwide. However, the impact of AWE feedback on student writing, particularly in languages other than English, remains controversial. This study aimed to compare the impacts of Chinese AWE feedback and teacher feedback on Chinese writing revision,…
Descriptors: Foreign Countries, Middle School Students, Grade 7, Writing Evaluation
Febe Demedts; Sameh Said-Metwaly; Kristian Kiili; Manuel Ninaus; Antero Lindstedt; Bert Reynvoet; Delphine Sasanguie; Fien Depaepe – Journal of Computer Assisted Learning, 2025
Background: The potential of adaptive feedback in digital educational games remains largely unexplored. Fractions are a suitable topic for investigating the effectiveness of adaptive feedback, as the complexity of this domain highlights the need for adequate feedback. Objectives: This study examines the effectiveness of explanatory adaptive…
Descriptors: Grade 4, Educational Games, Video Games, Feedback (Response)
Simon Kitto; H. L. Michelle Chiang; Olivia Ng; Jennifer Cleland – Advances in Health Sciences Education, 2025
There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic…
Descriptors: Feedback (Response), Learning Analytics, Educational Technology, Allied Health Occupations Education
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
Kirk Vanacore; Ashish Gurung; Adam Sales; Neil Heffernan – Society for Research on Educational Effectiveness, 2024
Background: Gaming the system -- attempting to progress through a learning activity without learning (R. Baker et al., 2008) -- is an enduring problem that reduces the efficacy of Computer Based Learning Platforms (CBLPs). Researchers made substantial progress in identifying instances when students are gaming the system (Baker et al., 2006; Dang…
Descriptors: Gamification, Program Effectiveness, Computer Assisted Instruction, Feedback (Response)
Rui Li – British Journal of Educational Technology, 2025
Despite the proliferation of help options for computer-based second language (L2) listening comprehension, little attention has been given to a comprehensive understanding of the pedagogical effects. To gain a thorough understanding of the overall and moderator effects, drawing on the activity theory (AT), this study conducted a meta-analysis of…
Descriptors: Computer Assisted Instruction, Second Language Instruction, English (Second Language), Listening Comprehension
Rusen Meylani; Gary G. Bitter – International Society for Technology, Education, and Science, 2023
The use of online learning objects in teaching algebra is examined in this research, emphasizing its benefits, such as accessibility, flexibility, interactive involvement, differentiated instruction, quick feedback, and links to real-world situations. Strategies include conceptual comprehension, interactive practice, individualized learning,…
Descriptors: Algebra, Electronic Learning, Mathematics Instruction, Mathematical Concepts
Johann Chevalère; M. Berthon; N. Rocher; D. Pailler; V. Mazenod; P. Huguet – Education and Information Technologies, 2025
Computer-assisted instruction (CAI) is a valuable approach for managing classroom heterogeneity by providing feedback tailored to students' individual needs. While previous research has primarily focused on the cognitive mechanisms underlying CAI's effectiveness, it has often overlooked the social-cognitive processes that may contribute to its…
Descriptors: Computer Assisted Instruction, Self Esteem, Feedback (Response), Geography Instruction
Learners' Use of Audio/Video Playback Controls in Technology-Enhanced Listening: A Systematic Review
Natalia Andrea Roldán-Mora; Mónica Stella Cárdenas-Claros – JALT CALL Journal, 2024
This systematic review investigates learner use of audio/video playback (AVP) controls in technology-enhanced listening environments. To this aim, 61 academic works produced from 2000-2021 underwent inclusion/exclusion criteria and were analyzed. The resulting corpus was made up of 16 peer-reviewed articles. We first situate the studies examined…
Descriptors: Technology Uses in Education, Audio Equipment, Video Technology, Feedback (Response)
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
Tan, Jesmine S. H.; Chen, Wenli; Su, Junzhu; Su, Guo – International Journal of Computer-Supported Collaborative Learning, 2023
Peer feedback is known to have positive effects on knowledge improvement in a collaborative learning environment. Attributed to technology affordances, class-wide peer feedback could be garnered at a wider range in the networked learning environment. However, more empirical studies are needed to explore further the effects of type and depth of…
Descriptors: Peer Evaluation, Feedback (Response), Cooperative Learning, Computer Assisted Instruction
Ignacio Villagran; Rocio Hernandez; Gregory Schuit; Andres Neyem; Javiera Fuentes-Cimma; Constanza Miranda; Isabel Hilliger; Valentina Duran; Gabriel Escalona; Julian Varas – IEEE Transactions on Learning Technologies, 2024
This article presents a controlled case study focused on implementing and using generative artificial intelligence, specifically large language models (LLMs), in physiotherapy education to assist instructors with formulating effective technology-mediated feedback for students. It outlines how these advanced technologies have been integrated into…
Descriptors: Artificial Intelligence, Physical Therapy, Technology Uses in Education, Case Studies

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