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Ke Xu; Xin Guo; Xinjing Zhang; Yi Zhang; Zhongling Pi; Jiumin Yang – Journal of Computer Assisted Learning, 2025
Background: Previous studies have indicated that encouraging learners to teach to their peers has been proven effective in second language learning. However, to date, no research has focused on how learners teaching to peers of varying proficiency levels impacts video learning performance and the cognitive neuroscience mechanisms of learners.…
Descriptors: Peer Teaching, Second Language Learning, Video Technology, Electronic Learning
Yanqing Wang; Shaoying Gong; Ning Jia; Ying Liu – Journal of Computer Assisted Learning, 2025
Background: Online learning is becoming increasingly popular among learners. To enhance the effectiveness of online learning, researchers have embedded an affective pedagogical agent (PA) on the computer screen to help regulate learners' emotions and support their learning. However, previous research has paid little attention to the effects of…
Descriptors: Metacognition, Prompting, Electronic Learning, Computer Uses in Education
Zeng-Wei Hong; Che-Lun Liang; Ming-Chi Liu – Journal of Computer Assisted Learning, 2025
Background: Online video-based learning often leads to fatigue, which detracts from engagement and learning outcomes. Previous studies have examined monitoring mental states like attention through electroencephalography (EEG) headsets, but limitations such as high costs, discomfort, and limited scalability persist. Objectives: This study evaluates…
Descriptors: Technology Uses in Education, Electronic Learning, Video Technology, Fatigue (Biology)
Guo, Liming; Du, Junlei; Zheng, Qinhua – Journal of Computer Assisted Learning, 2023
Background: There is a strong association between interactions and cognitive engagement, which is crucial for constructing new cognition and knowledge. Although interactions and cognitive engagement have attracted extensive attention in online learning environments, few studies have revealed the evolution of cognitive engagement with interaction…
Descriptors: Cognitive Ability, Learner Engagement, Electronic Learning, Technology Uses in Education
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
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
Meysam Muhammadpour; Abdorreza Tahriri; Seyyed Ayatollah Razmjoo; Jaleh Hassaskhah – Journal of Computer Assisted Learning, 2025
Background: Recent years have witnessed a surge of technology use and online learning environments, especially during the post-COVID era. The widespread use of technology has sparked a sudden transition from conventional face-to-face learning to online digital-based learning platforms, such as Adobe Connect. Although EFL teachers have implemented…
Descriptors: Foreign Countries, Second Language Learning, English (Second Language), Language Attitudes
Lin, Jian-Wei; Huang, Hsieh-Hong; Tsai, Chia-Wen – Journal of Computer Assisted Learning, 2023
Background: Social network awareness (SNA) enables students to know the online learning context of peers in computer-supported collaborative learning (CSCL) and it has been used to improve peer interaction and participation in collaborative learning tasks. Mobile learning enables students to access learning content and discuss content with peers…
Descriptors: Electronic Learning, Handheld Devices, Cooperative Learning, Social Networks
Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo – Journal of Computer Assisted Learning, 2023
Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…
Descriptors: Data Use, Group Dynamics, College Students, Cooperative Learning
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
Ignacio Máñez; Noemi Skrobiszewska; Adela Descals; María José Cantero; Raquel Cerdán; Óscar Fernando García; Rafael García-Ros – Journal of Computer Assisted Learning, 2024
Background: Delivering effective feedback to large groups of students represents a challenge for the academic staff at universities. Research suggests that undergraduate students often ignore the Elaborated Feedback (EF) received via digital learning environments. This may be because instructors provide feedback in written format instead of using…
Descriptors: Feedback (Response), Audiovisual Aids, Higher Education, College Students
Lanqin Zheng; Zichen Huang; Lei Gao; Yunchao Fan – Journal of Computer Assisted Learning, 2025
Background: Online collaborative learning has been broadly applied in the field of higher education. Nevertheless, not all types of collaborative learning can produce the desired learning results. Objectives: To facilitate online collaborative learning, the present study proposed an innovative artificial intelligence-enabled group cognitive…
Descriptors: Artificial Intelligence, Technology Uses in Education, Electronic Learning, Online Courses
Chen, Xiuyu; Feng, Shihui – Journal of Computer Assisted Learning, 2023
Background: Video-based learning (VBL) is the learning process of acquiring defined knowledge, competence, and skills with the systematic use of video resources. Currently, the relationship between teaching presence and social presence in VBL is underexamined. Objectives: This study examined the relationships between social presence and teaching…
Descriptors: Teacher Student Relationship, Social Behavior, Electronic Learning, Video Technology
Robert F. Siegle; Scotty D. Craig – Journal of Computer Assisted Learning, 2024
Background: The voices virtual on-screen characters use has been shown to impact learning and perception outcomes. Recent replication research on these voices showed that synthetic voices were not a detriment if produced by a high-quality engine with clear articulation. The current manuscript examines previous accent research that utilized now…
Descriptors: Acoustics, Artificial Intelligence, Electronic Learning, Quality Assurance
Yujen Ho – Journal of Computer Assisted Learning, 2024
Background Study: Asynchronous online discussions are vital venues for collaborative knowledge construction. However, the lack of appropriate instruction designs poses challenges in promoting deep and substantive engagement with the core subject matter. This paper explores how to enhance adult students' knowledge construction in the context of…
Descriptors: Asynchronous Communication, Adult Students, Electronic Learning, Instructional Design

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