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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
Gabriela Trindade Perry; Marlise Bock Santos – Journal of Computer Assisted Learning, 2024
Background: Instances of academic dishonesty are common in online learning environments because difficulties in their detection result in considerably low degrees of risks. However, if not identified, the noise introduced by dishonest learners in MOOCs' clickstream data could lead to biased results and conclusions in scientific research.…
Descriptors: Foreign Countries, MOOCs, Distance Education, Electronic Learning
Qian Tian; Xudong Zheng – Journal of Computer Assisted Learning, 2024
Background: During the COVID-19 pandemic, online collaborative problem solving (online CPS) has become one of the most crucial learning methods to develop students' learning performance. However, it remains unclear of the effectiveness of the online CPS method on students' learning performance. Objectives: To explore the overall effect of online…
Descriptors: Electronic Learning, COVID-19, Pandemics, Teaching Methods
Yingbin Zhang; Yafei Ye; Luc Paquette; Yibo Wang; Xiaoyong Hu – Journal of Computer Assisted Learning, 2024
Background: Learning analytics (LA) research often aggregates learning process data to extract measurements indicating constructs of interest. However, the warranty that such aggregation will produce reliable measurements has not been explicitly examined. The reliability evidence of aggregate measurements has rarely been reported, leaving an…
Descriptors: Learning Analytics, Learning Processes, Test Reliability, Psychometrics
van Harsel, Milou; Hoogerheide, Vincent; Verkoeijen, Peter; van Gog, Tamara – Journal of Computer Assisted Learning, 2022
Nowadays, students often practice problem-solving skills in online learning environments with the help of examples and problems. This requires them to self-regulate their learning. It is questionable how novices self-regulate their learning from examples and problems and whether they need support. The present study investigated the open questions:…
Descriptors: Sequential Learning, Independent Study, Problem Solving, Electronic Learning
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
Jyun-Chen Chen; Chia-Yu Liu – Journal of Computer Assisted Learning, 2025
Background: Based on the embodied cognition perspective, interdisciplinary hands-on learning combines several disciplines, such as science, technology, engineering and mathematics (STEM), to improve students' capacity to solve real-world problems. Despite the popularity of interdisciplinary hands-on learning, particularly the six-phase 6E model,…
Descriptors: Interdisciplinary Approach, Experiential Learning, STEM Education, Problem Solving
Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
Saleh Alhazbi; Afnan Al-ali; Aliya Tabassum; Abdulla Al-Ali; Ahmed Al-Emadi; Tamer Khattab; Mahmood A. Hasan – Journal of Computer Assisted Learning, 2024
Background: Measuring students' self-regulation skills is essential to understand how they approach their learning tasks in order to identify areas where they might need additional support. Traditionally, self-report questionnaires and think aloud protocols have been used to measure self-regulated learning skills (SRL). However, these methods are…
Descriptors: Learning Analytics, Independent Study, Higher Education, College Students
Sidi, Yael; Blau, Ina; Shamir-Inbal, Tamar – Journal of Computer Assisted Learning, 2022
Background: Hyper-video technology allows reflection on learning materials by writing personal notes and by interactions with lecturers and peers through shared posts and replies. While research shows that integrating hyper-videos in educational systems can promote the learning processes and outcomes, an open question remains regarding its actual…
Descriptors: Active Learning, Cooperative Learning, College Students, Documentation
John L. Nietfeld; Kristin F. Hoffmann – Journal of Computer Assisted Learning, 2024
Background: Goal setting has been established in the literature as a critical component of self-regulated learning and for effective problem-solving. Yet, surprisingly little attention has been focused on goal-directed behaviour in digital game-based learning environments (GBLEs) despite their expanding use in educational contexts. Objectives: The…
Descriptors: Game Based Learning, Educational Environment, Goal Orientation, Electronic Learning
Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
Fan, Ting-Yu; Chen, Hsiu-Ling – Journal of Computer Assisted Learning, 2023
Background Study: English education has been promoted in Taiwan for many years. Recently, content and language integrated learning (CLIL) has received attention as an effective way to integrate English into real-life contexts. With advances in technology, digital storytelling is suitable for students to develop multiple skills such as narrating…
Descriptors: Cooperative Learning, Content and Language Integrated Learning, Elementary School Students, Electronic Learning
Theelen, Hanneke; van Breukelen, Dave H. J. – Journal of Computer Assisted Learning, 2022
Background: Since about 2010 e-learning has been embedded in educational practice and has become, surely due to the COVID-19 pandemic, increasingly important. Objectives: Although much has been written about e-learning, little is known about crucial didactic and pedagogical design principles for e-learning. This review tried to fill that gap.…
Descriptors: Instructional Design, Electronic Learning, Higher Education, COVID-19
Muhammad Ashraf Fauzi; Zuria Akmal Saad; Muhammad Ariff Aripin; Noraina Mazuin Sapuan – Journal of Computer Assisted Learning, 2025
Background Study: Gamification is an effective and interactive approach to engaging students in teaching and learning. As digital technology develops, higher education institutions (HEIs) must embrace and keep pace with gamification for interactive teaching and learning approaches. Objective: The purpose of this study is to review gamification in…
Descriptors: State of the Art Reviews, Gamification, Game Based Learning, Bibliometrics

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