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Tornike Giorgashvili; Ioana Jivet; Cordula Artelt; Daniel Biedermann; Daniel Bengs; Frank Goldhammer; Carolin Hahnel; Julia Mendzheritskaya; Julia Mordel; Monica Onofrei; Marc Winter; Ilka Wolter; Holger Horz; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: Learning analytics dashboards (LAD) have been developed as feedback tools to help students self-regulate their learning (SRL) by using the large amounts of data generated by online learning platforms. Despite extensive research on LAD design, there remains a gap in understanding how learners make sense of information visualised on LADs…
Descriptors: Field Studies, Student Reaction, Feedback (Response), Learning Analytics
Zehang Xie; Xinzhu Wu; Yunxiang Xie – Journal of Computer Assisted Learning, 2024
Background: With the development of artificial intelligence (AI) technology, generative AI has been widely used in the field of education and represents a groundbreaking shift in overcoming the constraints of time and space within educational activities. However, previous literature has not paid enough attention to AI-involved teaching patterns,…
Descriptors: Longitudinal Studies, Undergraduate Students, Robotics, Technology Uses in Education
Qian Fu; Xinyi Zhou; Yafeng Zheng; Zhenyi Wang – Journal of Computer Assisted Learning, 2025
Background: Understanding algorithms is crucial for programming education, yet their abstract nature often challenges students. Algorithm visualisation (AV) has been proven effective in enhancing algorithmic thinking among university students. However, its efficacy for elementary school students and the optimal forms of AV tools remain unclear.…
Descriptors: Algorithms, Visualization, Elementary School Students, Learning Motivation
Flora Ji-Yoon Jin; Debarshi Nath; Rui Guan; Tongguang Li; Xinyu Li; Rafael Ferreira Mello; Luiz Rodrigues; Cleon Pereira Junior; Heba Abuzayyad-Nuseibeh; Mladen Rakovic; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Computer Assisted Learning, 2025
Background: A key skill for self-regulated learners is the ability to critically interpret and act on feedback--key components of feedback literacy. Yet, the connection between feedback literacy and self-regulated learning (SRL) remains underexplored, particularly in terms of how different levels of feedback literacy influence SRL processes in…
Descriptors: Independent Study, Learning Analytics, Feedback (Response), Literacy
Li, Yuhao; Chang, Mengyi; Zhao, Hanxuan; Jiang, Caihong; Xu, Sihua – Journal of Computer Assisted Learning, 2023
Background: Mobile devices facilitate learning activities in a self-paced way. However, the current understanding of learning participation and its consequence are minimal when learners take advantage of opportunities provided by mobile technologies worldwide. Aims: The primary purpose of this study is to examine the effectiveness of environmental…
Descriptors: Anxiety, Computer Software, Computer Assisted Instruction, Learning Processes
Min Young Doo; Meina Zhu – Journal of Computer Assisted Learning, 2024
Background: Online learning has become more prevalent over the past three decades, especially during the COVID-19 pandemic. Educators and scholars have increasingly emphasized the significance of self-directed learning (SDL) on successful learning outcomes in online learning environments. Objectives: The purpose of this study was to synthesize the…
Descriptors: Electronic Learning, Independent Study, Virtual Classrooms, Academic Achievement
Blaženka Divjak; Barbi Svetec; Damir Horvat – Journal of Computer Assisted Learning, 2024
Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic…
Descriptors: Automation, Formative Evaluation, Test Validity, Test Reliability
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
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Shuhan Zhang; Gary K. W. Wong – Journal of Computer Assisted Learning, 2024
Background: Computational thinking (CT) has emerged as a critical component of 21st-century skills, and increasing effort was seen in exploring the development of CT skills in K-12 students. Despite cumulative research on exploring students' CT acquisition and its influencing factors, learners' development of the skill over time and the underlying…
Descriptors: Individual Differences, Computation, Thinking Skills, Elementary School Students
Patricia Feubli; Douglas MacKevett; Jürg Schwarz – Journal of Computer Assisted Learning, 2024
Background: This research paper presents a cross-sectional study that examinefs the preferences of students for hybrid teaching and learning scenarios. Unlike previous studies that merely describe hybrid scenarios, this research prioritizes them, offering evidence-based findings for informed policy decisions. Methods: The data collection method…
Descriptors: Blended Learning, Preferences, Foreign Countries, Educational Environment
Guo, Lin – Journal of Computer Assisted Learning, 2022
Background: It has been assumed that prompting students to plan, monitor and evaluate their learning process could stimulate strategy use and thereby improve learning outcomes. Objectives: This study aimed to examine the effects of metacognitive prompts on students' self-regulated learning (SRL) and learning outcomes in the context of…
Descriptors: Metacognition, Independent Study, Learning Processes, Outcomes of Education
Tingting Wang; Alejandra Ruiz-Segura; Shan Li; Susanne P. Lajoie – Journal of Computer Assisted Learning, 2024
Background: Scholars have confirmed the vital roles of self-regulated learning (SRL) behaviours in predicting task performance, especially within non-linear technology-rich learning environments (TREs). However, few studies focused on the learning costs (e.g., study effort and time-on-task) related to SRL and the efficiency outcome of SRL (i.e.,…
Descriptors: Problem Solving, Educational Environment, Efficiency, Student Behavior
Min Young Doo; Yeonjeong Park – Journal of Computer Assisted Learning, 2024
Background: Despite the many advantages of flipped learning, it is challenging for educators to ensure that students complete the pre-class learning assignments before the in-class session. Objectives: Using a learning analytics approach, this study analysed students' pre-class video-watching behaviour in flipped learning with a focus on learners'…
Descriptors: Flipped Classroom, Video Technology, Student Behavior, Learning Strategies
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

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