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Fateme Ashrafzade; Yousef Mahdavinasab; Nasrin Mohammadhasani; Mahsa Moradi – Journal of Computer Assisted Learning, 2025
Background: The integration of pedagogical agents (PAs) into educational settings has become widespread, yet the impact of humorous versus non-humorous PAs on student academic performance and engagement remains underexplored. Although research highlights the benefits of PAs, the specific role of humour in enhancing educational outcomes is not well…
Descriptors: Grade 5, Elementary School Students, Learner Engagement, Academic Achievement
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J. Weidlich; D. Gaševic; H. Drachsler; P. Kirschner – Journal of Computer Assisted Learning, 2025
Background: As researchers rush to investigate the potential of AI tools like ChatGPT to enhance learning, well-documented pitfalls threaten the validity of this emerging research. Issues of media comparison research, where the confounding of instructional methods and technological affordances is unrecognised, may render effects uninterpretable.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Barriers
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Tacoma, Sietske; Drijvers, Paul; Jeuring, Johan – Journal of Computer Assisted Learning, 2021
Intelligent tutoring systems (ITSs) can provide inner loop feedback about steps within tasks, and outer loop feedback about performance on multiple tasks. While research typically addresses these feedback types separately, many ITSs offer them simultaneously. This study evaluates the effects of providing combined inner and outer loop feedback on…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Statistics Education, Higher Education
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Chen, Fei; Xia, Quansheng; Feng, Yan; Wang, Lan; Peng, Gang – Journal of Computer Assisted Learning, 2023
Background: Teaching Mandarin as a second language (L2) has become an important profession and an important research area. The acquisition of unaspirated and aspirated consonants in Mandarin has been reported to be rather challenging for L2 learners. Objectives: In the current study, a 3-D airflow model was integrated into the virtual talking head…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Mandarin Chinese, Models
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Lodder, Josje; Heeren, Bastiaan; Jeuring, Johan – Journal of Computer Assisted Learning, 2019
This article describes an experiment with LogEx, an e-learning environment that supports students in learning how to prove the equivalence between two logical formulae, using standard equivalences such as DeMorgan. In the experiment, we compare two groups of students. The first group uses the complete learning environment, including hints, next…
Descriptors: Logical Thinking, Feedback (Response), Instructional Effectiveness, Intelligent Tutoring Systems
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Wang, Dongqing; Han, Hou – Journal of Computer Assisted Learning, 2021
With the development of a technology-supported environment, it is plausible to provide rich process-oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process-oriented feedback in iTutor to offer learners their final scores, sub-scale reports, and corresponding suggestions on further…
Descriptors: Learning Analytics, Educational Technology, Feedback (Response), Intelligent Tutoring Systems
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Munshi, Anabil; Biswas, Gautam; Baker, Ryan; Ocumpaugh, Jaclyn; Hutt, Stephen; Paquette, Luc – Journal of Computer Assisted Learning, 2023
Background: Providing adaptive scaffolds to help learners develop effective self-regulated learning (SRL) behaviours has been an important goal for intelligent learning environments. Adaptive scaffolding is especially important in open-ended learning environments (OELE), where novice learners often face difficulties in completing their learning…
Descriptors: Scaffolding (Teaching Technique), Metacognition, Independent Study, Intelligent Tutoring Systems
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Serrano, M.-Á.; Vidal-Abarca, E.; Ferrer, A. – Journal of Computer Assisted Learning, 2018
The use of documents to perform tasks is a continuous task demand in the current knowledge-based society that involves making a series of decisions to self-regulate the use of text information. Low-skilled comprehenders have serious problems monitoring and self-regulating their decisions in these task-oriented reading situations, which has a…
Descriptors: Metacognition, Teaching Methods, Learning Strategies, Intelligent Tutoring Systems
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Lin, C.-C.; Guo, K.-H.; Lin, Y.-C. – Journal of Computer Assisted Learning, 2016
This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…
Descriptors: Remedial Instruction, Artificial Intelligence, Intelligent Tutoring Systems, Electronic Learning
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Hsiao, I.-H.; Sosnovsky, S.; Brusilovsky, P. – Journal of Computer Assisted Learning, 2010
Rapid growth of the volume of interactive questions available to the students of modern E-Learning courses placed the problem of personalized guidance on the agenda of E-Learning researchers. Without proper guidance, students frequently select too simple or too complicated problems and ended either bored or discouraged. This paper explores a…
Descriptors: Electronic Learning, Guidance, Individualized Instruction, Computer Software
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Popescu, E. – Journal of Computer Assisted Learning, 2010
Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization criterion called learning style-based adaptive educational systems. The paper presents an innovative approach based on an integrative set of learning preferences that alleviates…
Descriptors: Electronic Learning, Undergraduate Students, Cognitive Style, Individualized Instruction