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Showing 1 to 15 of 76 results Save | Export
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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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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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García-Martínez, Carlos; Cerezo, Rebeca; Bermúdez, Manuel; Romero, Cristóbal – Journal of Computer Assisted Learning, 2019
Most massive open online courses (MOOC) use simple schemes for aggregating peer grades, taking the mean or the median, or compute weights from information other than the instructor's opinion about the students' knowledge. To reduce the difference between the instructor and students' aggregated scores, some proposals compute specific weights to…
Descriptors: Scores, Online Courses, Grades (Scholastic), Peer Groups
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Ma, Long; Lee, Chei Sian – Journal of Computer Assisted Learning, 2019
In spite of the potentials promised by MOOCs (massive open online courses), the adoption rate of MOOCs is still low, especially in developing countries. Research on the adoption of MOOCs in developing countries is also limited. To fill this research gap, this research aims to study the adoption of MOOCs by extending current research on innovation…
Descriptors: Educational Technology, Technology Uses in Education, Large Group Instruction, Online Courses
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Blieck, Yves; Kauwenberghs, Kurt; Zhu, Chang; Struyven, Katrien; Pynoo, Bram; DePryck, Koen – Journal of Computer Assisted Learning, 2019
Online and blended learning (OBL) is valued, but it also offers challenges. Literature indicates that OBL can enhance access to education and increase flexibility for students. However, the reported dropout rates indicate that student participation in OBL programmes is a concern. Scientifically valid knowledge about how factors that help students…
Descriptors: Online Courses, Blended Learning, Educational Technology, Technology Uses in Education
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Heckel, Christian; Ringeisen, Tobias – Journal of Computer Assisted Learning, 2019
The current study validated the proposed structure of relationships among outcome-related achievement emotions (pride and anxiety), their cognitive predictors (appraisals und online-learning-related self-efficacy), and learning outcomes (competence gain and satisfaction) in the context of online learning in higher education. On the basis of a…
Descriptors: Emotional Response, Anxiety, Predictor Variables, Student Satisfaction
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Filius, Renée M.; de Kleijn, Renske A. M.; Uijl, Sabine G.; Prins, Frans J.; van Rijen, Harold V. M.; Grobbee, Diederick E. – Journal of Computer Assisted Learning, 2019
We investigated the relation between providing and receiving audio peer feedback with a deep approach to learning within online education. Online students were asked to complete peer feedback assignments. Data through a questionnaire with 108 respondents and 14 interviews were used to measure to what extent deep learning was perceived and why.…
Descriptors: Feedback (Response), Peer Influence, Online Courses, Educational Technology
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Soffer, Tal; Cohen, Anat – Journal of Computer Assisted Learning, 2019
This study examined students' engagement characteristics in online courses and their impact on academic achievements, trying to distinguish between course completers and noncompleters. Moreover, this research is intended to differentiate between those who pass the final exam and those who do not. Four online courses were examined with a similar…
Descriptors: Learner Engagement, Student Participation, Online Courses, Educational Technology
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Conijn, R.; Van den Beemt, A.; Cuijpers, P. – Journal of Computer Assisted Learning, 2018
Predicting student performance is a major tool in learning analytics. This study aims to identify how different measures of massive open online course (MOOC) data can be used to identify points of improvement in MOOCs. In the context of MOOCs, student performance is often defined as course completion. However, students could have other learning…
Descriptors: Predictor Variables, Academic Achievement, Blended Learning, Online Courses
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Cohen, A.; Holstein, S. – Journal of Computer Assisted Learning, 2018
This research examines the characteristics that contributed to the success of massive open online courses (MOOCs) in the fields of software, sciences, and management using data mining and semantic analysis together with content analysis. A total of 3,460 reviews regarding 5 different MOOCs that received a 5/5 grade were extracted from the…
Descriptors: Online Courses, Communities of Practice, Instructional Effectiveness, Outcomes of Education
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Soffer, Tal; Nachmias, Rafi – Journal of Computer Assisted Learning, 2018
This study examined the effectiveness of 3 online courses compared with the same 3 courses in a face-to-face (F2F) format, which had the same characteristics (e.g., the same instructor and final exam content and place). Effectiveness was examined by utilizing a wide range of variables, including 2 objective measures (N = 968): grades and…
Descriptors: Instructional Effectiveness, Teaching Methods, Conventional Instruction, Online Courses
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Yen, M.-H.; Chen, S.; Wang, C.-Y.; Chen, H.-L.; Hsu, Y.-S.; Liu, T.-C. – Journal of Computer Assisted Learning, 2018
This article develops a framework for self-regulated digital learning, which supports for self-regulated learning (SRL) in e-learning systems. The framework emphasizes 8 features: learning plan, records/e-portfolio and sharing, evaluation, human feedback, machine feedback, visualization of goals/procedures/concepts, scaffolding, and agents. Each…
Descriptors: Independent Study, Electronic Learning, Models, Online Courses
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Paans, Cindy; Segers, Eliane; Molenaar, Inge; Verhoeven, Ludo – Journal of Computer Assisted Learning, 2018
In the present study, we investigated whether online learning behaviours (navigation and writing activities) mediated the relation between learner characteristics (prior knowledge, vocabulary knowledge, working memory, and motivation) and declarative knowledge. Specifically, we investigated whether the quality of participants' written assignments…
Descriptors: Assignments, Grade 5, Elementary School Students, Navigation (Information Systems)
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Riehemann, J.; Jucks, R. – Journal of Computer Assisted Learning, 2018
If learning materials are presented in either a conversational or formal language style, people will process them differently. This study reports an experiment in which 64 high school students watched an educational video in a massive open online course scenario in which the instructions were phrased either conversationally or formally. The video…
Descriptors: High School Students, Online Courses, Large Group Instruction, Educational Technology
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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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