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Showing 1 to 15 of 60 results Save | Export
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von Hoyer, Johannes F.; Kimmerle, Joachim; Holtz, Peter – Journal of Computer Assisted Learning, 2022
Background: Explorative online information search activities are self-regulated learning processes that require monitoring in the form of accurate metacognitive judgments about one's own knowledge. People have to judge what they know, but also understand what they do not know. Previous research has explored those two aspects in relation to each…
Descriptors: Self Esteem, Search Strategies, Internet, Metacognition
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Halima Alnashiri; Mladen Rakovic; Sadia Nawaz; Xinyu Li; Joni Lamsa; Lyn Lim; Maria Bannert; Sanna Jarvela; Dragan Gasevic – Journal of Computer Assisted Learning, 2025
Background: Integrating information from multiple sources is a common yet challenging learning task for secondary school students. Many underuse metacognitive skills, such as monitoring and control, which are essential for promoting engagement and effective learning outcomes. Objective: This study aims to examine the relationship between…
Descriptors: Secondary School Students, Metacognition, Writing (Composition), English
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Changhong Peng; Weixing Gu; Liping Jiang – Journal of Computer Assisted Learning, 2025
Background Study: In the field of English as a foreign language education, receptive skills such as listening and reading play a vital role in learners' academic success and professional development. These skills not only improve language comprehension but also facilitate language production. Objectives: Therefore, the primary objective of this…
Descriptors: Foreign Countries, Telecommunications, Metacognition, Second Language Learning
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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
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Fan, Yizhou; Rakovic, Mladen; van der Graaf, Joep; Lim, Lyn; Singh, Shaveen; Moore, Johanna; Molenaar, Inge; Bannert, Maria; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Many learners struggle to productively self-regulate their learning. To support the learners' self-regulated learning (SRL) and boost their achievement, it is essential to understand the cognitive and metacognitive processes that underlie SRL. To measure these processes, contemporary SRL researchers have largely utilized think aloud or…
Descriptors: Learning Strategies, Self Management, Protocol Analysis, Data Analysis
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Yuqin Yang; Xueqi Feng; Gaoxia Zhu; Kui Xie – Journal of Computer Assisted Learning, 2024
Background: Undergraduates' collective epistemic agency is critical for their productive collaborative inquiry and knowledge building (KB). However, fostering undergraduates' collective epistemic agency is challenging. Studies have demonstrated the potential of computer-supported collaborative inquiry approaches, such as KB--the focus of this…
Descriptors: Undergraduate Students, Cooperative Learning, Epistemology, Inquiry
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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
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Ren-Zhi Luo; Yue-Liang Zhou – Journal of Computer Assisted Learning, 2024
Background: The COVID-19 has accelerated the transition to blended learning (BL) in higher education, prompting a need for further investigation into the efficacy of self-regulated learning strategies (SRLS) in these new educational environments. Objective: The primary goal of this research is to assess the effectiveness of SRLS in BL in higher…
Descriptors: Learning Strategies, Blended Learning, Self Management, Higher Education
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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
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Liu, Cheng-Ye; Li, Wei; Huang, Ji-Yi; Lei, Lu-Yuan; Zhang, Pei-Rou – Journal of Computer Assisted Learning, 2023
Background: Socially shared regulation is a vital factor that affects students' collaborative programming performance. However, students' weak group metacognitive skills or inability to adopt shared regulation mechanisms lead to unsatisfactory collaborative programming learning. Objectives: This study proposes an approach to support socially…
Descriptors: Cooperative Learning, Programming, Academic Achievement, Metacognition
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Hatice Yildiz Durak – Journal of Computer Assisted Learning, 2024
Background: Collaboration is a crucial concept in learning and has the potential to foster learning. However, the fact that collaborative groups act with a common understanding in a common task brings many difficulties. Therefore, there is a need for group regulation and guidance to support effective group regulation in collaborative learning. On…
Descriptors: Feedback (Response), Groups, Group Guidance, Cooperation
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Malmberg, Jonna; Fincham, Oliver; Pijeira-Díaz, Héctor J.; Järvelä, Sanna; Gaševic, Dragan – Journal of Computer Assisted Learning, 2021
Using hidden Markov models (HMM), the current study looked at how learners' metacognitive monitoring is related to their physiological reactivity in the context of collaborative learning. The participants (N = 12, age 16-17 years, three females and nine males) in the study were high school students enrolled in an advanced physics course. The…
Descriptors: Physiology, Metacognition, Cooperative Learning, High School Students
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Marquès Puig, Joan Manuel; Daradoumis, Thanasis; Arguedas, Marta; Calvet Liñan, Laura – Journal of Computer Assisted Learning, 2022
Background: Recent research in online settings reports that supporting self-regulated learning (SRL) strategy use could lead to greater online academic success. A growing number of studies have started to investigate SRL supports in online environments recently, which indicates a great interest in this matter. Though several systems for automatic…
Descriptors: Cognitive Processes, Metacognition, Critical Thinking, Electronic Learning
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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
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Safaa M. Abdelhalim – Journal of Computer Assisted Learning, 2024
Background: Introducing new technologies in education sparks debates, disrupting traditional practices, and requiring teacher adaptation. ChatGPT is an example. Research explores its benefits and concerns in education, with recommendations for classroom use. Nevertheless, limited evidence supports ChatGPT as a tool for supporting English as a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Second Language Learning
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