Publication Date
In 2025 | 5 |
Since 2024 | 10 |
Since 2021 (last 5 years) | 12 |
Since 2016 (last 10 years) | 15 |
Since 2006 (last 20 years) | 17 |
Descriptor
Source
Journal of Computer Assisted… | 17 |
Author
Abdulhadi Kazem | 1 |
Alex Shum | 1 |
Anouschka van Leeuwen | 1 |
Anthony J. Taiki Kawakubo | 1 |
Bersimis, S. | 1 |
Chen, Mei-Shan | 1 |
Chih-Cheng Lin | 1 |
Chimos, K. | 1 |
Chung, Ching-Jung | 1 |
Chung, H. C. | 1 |
Chunqi Li | 1 |
More ▼ |
Publication Type
Journal Articles | 17 |
Reports - Research | 17 |
Information Analyses | 2 |
Education Level
Higher Education | 17 |
Postsecondary Education | 17 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Mohamad Iyad Al-Khiami; Martin Jaeger; Sayed Mohamad Soleimani; Abdulhadi Kazem – Journal of Computer Assisted Learning, 2024
Background Study: The research discusses the need for a paradigm shift in engineering education current practices to accommodate the digital native students. The paper emphasizes the importance of integrating disruptive technologies, namely Virtual Reality (VR) through Head Mounted Displays VR (HMD VR) and Desktop Based VR (DB VR) and comparing it…
Descriptors: Undergraduate Students, Engineering Education, Computer Simulation, Student Motivation
Chunqi Li; Lishi Liang; Luke K. Fryer; Alex Shum – Journal of Computer Assisted Learning, 2024
Background: Leaderboards are among the most popular gamification elements in education. Some studies have implemented leaderboards and reported their individual effects on students' learning. Despite the emergence of relevant empirical studies, most of the existing reviews have only investigated the holistic impact of gamification. No previous…
Descriptors: Higher Education, Gamification, Evidence Based Practice, Learning Motivation
Jun Oshima; Ritsuko Oshima; Anthony J. Taiki Kawakubo – Journal of Computer Assisted Learning, 2025
Background: This study aimed to develop and test new analytics for knowledge-building practices from the transactive perspective. Based on a literature review, network analysis was identified as a promising analytical tool for these practices. We observed two aspects of network analysis that could be further developed: the multilayers of networks…
Descriptors: Network Analysis, Concept Formation, Learning Processes, Performance
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Jiang Xiaxia; Li Yahong; Kuang Ziyi; Yu Jiajun – Journal of Computer Assisted Learning, 2025
Background: Video conferencing technology has moved online education into a new stage of real-time video interaction. However, shortcomings such as students' lack of concentration and substantive engagement during video conferencing greatly limit the improvement of online learning effectiveness. According to social presence theory and the…
Descriptors: College Faculty, College Students, Electronic Learning, Distance Education
Muhammet Fidan; Mustafa Fidan – Journal of Computer Assisted Learning, 2024
Background: Flipped classroom (FC) model has become increasingly popular in dental education (DE) with its strengths for students. However, major concerns are lack of interaction, unwillingness to complete the assignments, low engagement during the pre-class activities because of an unwell-designed instructional setting of FC. Objectives: The…
Descriptors: Flipped Classroom, Dentistry, Graduate Students, Video Technology
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)
Xin Tang; Zhiqiang Yuan; Shaojun Qu – Journal of Computer Assisted Learning, 2025
Background: Generative artificial intelligence (AI) represents a significant technological leap, with platforms like OpenAI's ChatGPT and Baidu's Ernie Bot at the forefront of innovation. This technology has seen widespread adoption across various sectors of society and is anticipated to revolutionise the educational landscape, especially in the…
Descriptors: Influences, College Students, Student Behavior, Intention
Yi-Fan Li; Jue-Qi Guan; Xiao-Feng Wang; Qu Chen; Gwo-Jen Hwang – Journal of Computer Assisted Learning, 2024
Background: Self-regulated learning (SRL) is a predictive variable in students' academic performance, especially in virtual reality (VR) environments, which lack monitoring and control. However, current research on VR encounters challenges in effective interventions of cognitive and affective regulation, and visualising the SRL processes using…
Descriptors: Electronic Learning, Individualized Instruction, Learning Processes, Performance
Hui-Tzu Hsu; Chih-Cheng Lin – Journal of Computer Assisted Learning, 2024
Background: Behavioural intention (BI) has been predicted using other variables by adopting the technology acceptance model (TAM). However, few studies have examined whether BI can predict learning performance. Objectives: The present study used an extended TAM to investigate whether students' BI is a predictor of their listening learning…
Descriptors: Intention, Vocabulary Development, Handheld Devices, College Students
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
Wu, Jiun-Yu – Journal of Computer Assisted Learning, 2020
Online search involves multitasking and may demand better working-memory capacities (WMC) and additional cognitive aids. Given the constraints of human cognition, we tested the effectiveness of note-taking strategies on university students' online search performance. Also examined were the profile configurations of WMC tests in silence and in…
Descriptors: Predictive Validity, Short Term Memory, Notetaking, Online Searching
Tsay, Crystal Han-Huei; Kofinas, Alexander K.; Trivedi, Smita K.; Yang, Yang – Journal of Computer Assisted Learning, 2020
Learners in the higher education context who engage with computer-based gamified learning systems often experience the novelty effect: a pattern of high activity during the gamified system's introduction followed by a drop in activity a few weeks later, once its novelty has worn off. We applied a two-tiered motivational, online gamified learning…
Descriptors: Higher Education, College Students, Computer Games, Game Based Learning
Yang, Jie Chi; Chung, Ching-Jung; Chen, Mei-Shan – Journal of Computer Assisted Learning, 2022
Background: Performance goal orientations are influential motivational factors for predicting learning performance. However, a lack of attention has been paid to investigating the effects of performance goal orientations on learning performance and in-game performance in the context of digital game-based learning. Objectives: This study…
Descriptors: Educational Games, Game Based Learning, Academic Achievement, Goal Orientation
Song, H. S.; Kalet, A. L.; Plass, J. L. – Journal of Computer Assisted Learning, 2016
This study examined the direct and indirect effects of medical clerkship students' prior knowledge, self-regulation and motivation on learning performance in complex multimedia learning environments. The data from 386 medical clerkship students from six medical schools were analysed using structural equation modeling. The structural model revealed…
Descriptors: Prior Learning, Self Management, Self Control, Student Motivation
Previous Page | Next Page ยป
Pages: 1 | 2