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Ahmad Uzir, Nora'ayu; Gaševic, Dragan; Matcha, Wannisa; Jovanovic, Jelena; Pardo, Abelardo – Journal of Computer Assisted Learning, 2020
This paper aims to explore time management strategies followed by students in a flipped classroom through the analysis of trace data. Specifically, an exploratory study was conducted on the dataset collected in three consecutive offerings of an undergraduate computer engineering course (N = 1,134). Trace data about activities were initially coded…
Descriptors: Time Management, Blended Learning, Learning Analytics, Undergraduate Students
Wang, Yi-Hsuan – Journal of Computer Assisted Learning, 2021
The study designed WebQuest activities and explored the learning performance of learners to understand the suitability of using WebQuest in a college programming course. The study modified the processes of WebQuest based on social constructivism and scaffolding learning, and included programming tasks such as debugging practice to encourage…
Descriptors: Learning Activities, Programming, Academic Achievement, Educational Technology
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
Exploring Learner Motivation and Mobile-Assisted Peer Feedback in a Business English Speaking Course
Xu, Qi; Peng, Hongying – Journal of Computer Assisted Learning, 2022
Background: Peer-to-peer feedback exchanges have been recognized as crucial to language learning. While studies on peer feedback proliferate, little is known about whether and how peer feedback is affected by learners' motivational levels. Objectives: Situated in a mobile collaborative learning context, the current study examined how English as a…
Descriptors: Student Motivation, Electronic Learning, Handheld Devices, Peer Evaluation
Liu, Chen-Chung; Lin, Tsun-Wei; Cheng, Chia-Hui; Wen, Cai-Ting; Chang, Ming-Hua; Fan Chiang, Shih-Hsun; Tsai, Meng-Jung; Lin, Hung-Ming; Hwang, Fu-Kwun – Journal of Computer Assisted Learning, 2022
Background: Collaborative computer simulations are available on some online platforms which support students at distributed locations to synchronously collaborate on the simulations to learn sciences. However, how students collaborate with each other in collaborative simulations is not clear. Objectives: The aim of this study was to investigate…
Descriptors: Computer Simulation, Cooperative Learning, Electronic Learning, Student Attitudes
Flor, Michael; Andrews-Todd, Jessica – Journal of Computer Assisted Learning, 2022
Background: Collaborative problem solving (CPS) is important for success in the 21st century, especially for teamwork and communication in technology-enhanced environments. Measurement of CPS skills has emerged as an essential aspect in educational assessment. Modern research in CPS relies on theory-driven measurements that are usually carried out…
Descriptors: Automation, Documentation, Cooperative Learning, Teamwork
Hanna Järvenoja; Tiina Törmänen; Marjo Turunen; Emma Lehtoaho – Journal of Computer Assisted Learning, 2025
Background: Collaborative learning offers benefits, but its potential is often undermined by motivational challenges. This study uses the situated expectancy-value theory to explore how students' expectancies for success relate to group-level regulation of learning during collaborative interactions. The study considers success expectancies both as…
Descriptors: Cooperative Learning, Success, Expectation, Student Motivation
Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Enzo Simonnet; Mathieu Loiseau; Élise Lavoué – Journal of Computer Assisted Learning, 2025
Background: Vocabulary learning is an essential dimension of foreign language learning. The learners have a huge responsibility in this task. Among other factors, time constraints and an overall lack of maintained motivation on the part of students makes it especially challenging. Consequently, improving vocabulary learning requires strategies to…
Descriptors: Vocabulary Skills, Technology Uses in Education, Educational Technology, Motivation
Johanna Pöysä-Tarhonen; Shupin Li; Jarkko Hautala; Nafisa Awwal; Päivi Häkkinen – Journal of Computer Assisted Learning, 2025
Background: Collaborative problem-solving (CPS), encompassing social and cognitive domains, is recognised as a critical competency for current and future learners. While the cognitive domain, rooted in individual problem-solving, is relatively well understood, the social domain, manifested through social interaction, remains a challenge,…
Descriptors: Problem Solving, Distance Education, Attention Control, Cooperative Learning
Yerin Seung; James D. Basham; Taehyun Kim; Jennifer Lohoefener – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) can support more personalised learning in K-12 education, reshaping the educational experience for all students. However, little is known about how AI is being designed and implemented to support accessible and equitable learning experiences for all students, including those with disabilities and academic…
Descriptors: Artificial Intelligence, Technology Uses in Education, Elementary Secondary Education, Student Diversity
Atezaz Ahmad; Jan Schneider; Dai Griffiths; Daniel Biedermann; Daniel Schiffner; Wolfgang Greller; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: During the past decade, the increasingly heterogeneous field of learning analytics has been critiqued for an over-emphasis on data-driven approaches at the expense of paying attention to learning designs. Method and objective: In response to this critique, we investigated the role of learning design in learning analytics through a…
Descriptors: Instructional Design, Learning Analytics, Data Use, Literature Reviews
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
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
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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