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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
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Zhihao Cui; Oi-Lam Ng; Morris Siu-yung Jong; Xiaojing Weng – Journal of Computer Assisted Learning, 2025
Background: Amidst the increasing application of online education in the post-COVID era, new challenges in student engagement have emerged. However, most studies on online engagement have adopted macro-level approaches and relied on self-report measures of retrospective engagement. Few have examined micro-level engagement in terms of real-time and…
Descriptors: Middle School Students, Learner Engagement, Attention, Synchronous Communication
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Zixuan Cheng; Peijian Paul Sun – Journal of Computer Assisted Learning, 2025
Background: While a substantial number of studies have investigated English-as-a-foreign-language (EFL/L2 English) anxiety, they predominantly examined it from a unidimensional perspective, overlooking the potential insights offered by examining language-skill-specific L2 anxiety from a multidimensional lens. Moreover, prior research has…
Descriptors: Second Language Learning, Speech Communication, Anxiety, In Person Learning
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Hui Shi; Nuodi Zhang; Secil Caskurlu; Hunhui Na – Journal of Computer Assisted Learning, 2025
Background: The growth of online education has provided flexibility and access to a wide range of courses. However, the self-paced and often isolated nature of these courses has been associated with increased dropout and failure rates. Researchers employed machine learning approaches to identify at-risk students, but multiple issues have not been…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, At Risk Students
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Okan Bulut; Guher Gorgun; Seyma Nur Yildirim-Erbasli – Journal of Computer Assisted Learning, 2025
Background: Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress.…
Descriptors: Formative Evaluation, Academic Achievement, Student Participation, Learning Processes
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Schmitz, Birgit; Hanke, Katja – Journal of Computer Assisted Learning, 2023
Background: The COVID-19 lockdown forced students and teachers to adjust to remote lecturers and digital learning material and design criteria for online classes became the centre of discussion. Objectives: The purpose of this empirical study was to investigate the relationship between design principles of educational online practices in higher…
Descriptors: Learner Engagement, Expectation, Instructional Effectiveness, Instructional Design
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Özüdogru, Melike – Journal of Computer Assisted Learning, 2022
Background: There is a scarcity of studies on online flipped learning in teacher education classes. Many studies have found that student learning is improved in flipped learning environments; however, this is still an open question. Much of the literature employs quantitative methods to reveal the effect of flipped learning on certain variables…
Descriptors: Student Experience, Preservice Teachers, Electronic Learning, Flipped Classroom
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Jia Li; Novera Roihan; Matthew McGravey – Journal of Computer Assisted Learning, 2025
Background: Online learning has become a popular form of education. Prior to the COVID-19 pandemic, online learning was mainly associated with higher education, with an incremental growth at the K-12 level. The pandemic changed this situation rapidly. Online instruction has been increasingly integrated into secondary schools and has significantly…
Descriptors: High School Students, Student Attitudes, Electronic Learning, Student Experience
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Yawen Yu; Yang Tao; Gaowei Chen; Can Sun – Journal of Computer Assisted Learning, 2024
Background: Deep discussions play an important role in students' online learning. However, researchers have largely focused on engaging students in deep discussions in online asynchronous forums. Few studies have investigated how to promote deep discussion via mobile instant messaging (MIM). Objectives: In this study, we applied learning…
Descriptors: Learning Analytics, College Students, Epistemology, Computer Mediated Communication
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Wang, Yang; Liu, Qingtang – Journal of Computer Assisted Learning, 2020
This study analysed the instructors' teaching presence of three courses conducted by an instructor to explore the effects of the instructors' online teaching presence on students' interactions and collaborative knowledge constructions. Content analysis, social network analysis, and lag sequential analysis were used to explore the mechanism of…
Descriptors: Online Courses, Teacher Student Relationship, Cooperative Learning, Electronic Learning
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Asare, Andy Ohemeng; Yap, Robin; Truong, Ngoc; Sarpong, Eric Ohemeng – Journal of Computer Assisted Learning, 2021
The current educational disruption caused by the COVID-19 pandemic has fuelled a plethora of investments and the use of educational technologies for Emergency Remote Learning (ERL). Despite the significance of online learning for ERL across most educational institutions, there are wide mixed perceptions about online learning during this pandemic.…
Descriptors: COVID-19, Pandemics, School Closing, Online Courses
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Lahza, Hatim; Khosravi, Hassan; Demartini, Gianluca – Journal of Computer Assisted Learning, 2023
Background: The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.…
Descriptors: Learning Analytics, Learning Strategies, Electronic Learning, Independent Study
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Ucar, Hasan; Kumtepe, Alper Tolga – Journal of Computer Assisted Learning, 2020
This exploratory experimental study investigates the impact of motivational strategies based on the Attention, Relevance, Confidence, Satisfaction, and Volition (ARCS-V) model on online learners' academic performance, motivation, volition, and course interest. The research was conducted over an 11-week semester with 122 undergraduate online…
Descriptors: Motivation Techniques, Student Motivation, Online Courses, Electronic Learning
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Xiaojing Liu; Chunmiao Zhou – Journal of Computer Assisted Learning, 2024
Background: The global introduction of complex measures directed at the containment of the COVID-19 spread has spurred a massive shift to distance learning among educational institutions. As far as such a learning mode is rather forced and, probably, only a few establishments faced no difficulties with it, the matter of assuring teaching…
Descriptors: Teacher Role, Educational Technology, Technology Uses in Education, Distance Education
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Lange, C.; Costley, J. – Journal of Computer Assisted Learning, 2018
Highly interactive and complex content within e-learning induces high levels of intrinsic load. Self-regulated effort represents one strategy that may help learners overcome such issues within e-learning. Using intrinsic load items representative of content complexity, germane load items representative of learning, and self-regulated effort items…
Descriptors: Metacognition, Electronic Learning, Independent Study, Correlation
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