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Tamisha Thompson; Jennifer St. John; Siddhartha Pradhan; Erin Ottmar – Journal of Computer Assisted Learning, 2025
Background: Educational technologies typically provide teachers with analytics regarding student proficiency, but few digital tools provide teachers with process-based information about students' variable problem-solving strategies as they solve problems. Utilising design thinking and co-designing with teachers can provide insight to researchers…
Descriptors: Mathematics Instruction, Educational Technology, Problem Solving, Instructional Design
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Peijian Paul Sun; Zeqi Ren; Xian Zhao – Journal of Computer Assisted Learning, 2025
Background: Student engagement has been conceptualised and operationalised in various learning environments. However, there is currently a lack of established scales to measure student engagement in synchronous online learning. One possible reason is the existence of the conceptual and structural ambiguity regarding student engagement. Objective:…
Descriptors: Student Participation, Second Language Learning, Synchronous Communication, Electronic Learning
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Slaviša Radovic; Niels Seidel; Joerg M. Haake; Regina Kasakowskij – Journal of Computer Assisted Learning, 2024
Background: Self-assessment serves to improve learning through timely feedback on one's solution and iterative refinement as a way to improve one's competence. However, the complexity of the self-assessment process is widely recognized, as well as that students can benefit from it only if their assessment is accurate enough. Objectives: In order…
Descriptors: Self Evaluation (Individuals), Distance Education, Student Behavior, Accuracy
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Lanqin Zheng; Yunchao Fan; Zichen Huang; Lei Gao – Journal of Computer Assisted Learning, 2024
Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building,…
Descriptors: Cooperative Learning, Electronic Learning, College Students, Learning Strategies
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Shuang Li; Jingxi Chen; Sizhuo Liu – Journal of Computer Assisted Learning, 2024
Background: Enhancing the effectiveness of online learning has become a key challenge with regard to the ability of blended learning to reach its full potential. However, mechanisms by which students' self-regulated learning (SRL) skills influence their online learning engagement in blended learning and subsequent learning achievement have yet to…
Descriptors: Blended Learning, Elementary Secondary Education, Self Management, Self Evaluation (Individuals)
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Teresa M. Ober; Ying Cheng; Matthew F. Carter; Cheng Liu – Journal of Computer Assisted Learning, 2024
Background: Students' tendencies to seek feedback are associated with improved learning. Yet, how soon this association becomes robust enough to make predictions about learning is not fully understood. Such knowledge has strong implications for early identification of students at-risk for underachievement via digital learning platforms.…
Descriptors: Academic Achievement, Feedback (Response), Student Behavior, At Risk Students
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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
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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
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Bacca-Acosta, Jorge; Avila-Garzon, Cecilia – Journal of Computer Assisted Learning, 2021
Research on mobile-based assessment systems is still an emerging topic in the mobile learning field. Current research has demonstrated that the use of mobile-based assessment systems seems to have a positive impact on students' learning outcomes and motivation. The paper identifies some factors that influence student engagement with mobile-based…
Descriptors: Learner Engagement, Handheld Devices, Computer Assisted Testing, Electronic Learning
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Yang, Weipeng; Huang, Runke; Li, Yongyan; Li, Hui – Journal of Computer Assisted Learning, 2021
Collective academic supervision (CAS) is a collective model for students' academic supervision to reduce their isolation and as a measure to establish a congenial culture and to develop networks with their peers. Most studies focus on the benefits of online CAS, leaving the pedagogical process and students' learning experiences understudied. This…
Descriptors: Teacher Researchers, Graduate Students, Masters Programs, Supervision
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Gökçearslan, Sahin; Yildiz Durak, Hatice; Esiyok, Elif – Journal of Computer Assisted Learning, 2023
Background: The COVID-19 pandemic has spread quickly, e-learning became compulsory and disseminated throughout the world. During the pandemic, smartphones are frequently used to access e-learning content, but connecting to technological tools increased the risk of cyberloafing during e-courses. Currently, there are a limited number of studies on…
Descriptors: Students, Emotional Response, Psychological Patterns, Self Management
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Zohre Mohammadi Zenouzagh; Wilfried Admiraal; Nadira Saab – Journal of Computer Assisted Learning, 2024
Background study: Although the number of computer-based instruction has increased drastically, the understanding of how design features of learning modality can affect learning remains incomplete. This partly stems from studies' heavy focus on modified output. Therefore, how interactive nature of computer-mediated learning feeds into learning is…
Descriptors: Computer Mediated Communication, Communication Skills, Self Control, Learner Engagement
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Yazici, Sedat; Yildiz Durak, Hatice; Aksu Dünya, Beyza; Sentürk, Burcu – Journal of Computer Assisted Learning, 2023
Background: During the COVID-19 period, academics and higher education institutions have shown deep concern about academic integrity related to measurement and evaluation issues that have arisen in online education. Objectives: To address this concern, this paper examined the prevalence of cheating behaviour among university students before and…
Descriptors: Foreign Countries, College Students, Cheating, Student Behavior
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Jeske, D.; Backhaus, J.; Stamov Roßnagel, C. – Journal of Computer Assisted Learning, 2014
The current paper examined the relationship between perceived characteristics of the learning environment in an e-module in relation to test performance among a group of e-learners. Using structural equation modelling, the relationship between these variables is further explored in terms of the proposed double mediation as outlined by Ning and…
Descriptors: Electronic Learning, Self Control, Correlation, Educational Environment
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Graf, S.; Liu, T.-C.; Kinshuk, – Journal of Computer Assisted Learning, 2010
Providing adaptive features and personalized support by considering students' learning styles in computer-assisted learning systems has high potential in making learning easier for students in terms of reducing their efforts or increasing their performance. In this study, the navigational behaviour of students in an online course within a learning…
Descriptors: Cognitive Style, Management Systems, Online Courses, Computer Assisted Instruction