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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
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
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
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
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
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
Sepp, Stoo; Wong, Mona; Hoogerheide, Vincent; Castro-Alonso, Juan Cristobal – Journal of Computer Assisted Learning, 2022
Background: As a result of the COVID-19 pandemic, many teachers found themselves making a rapid and often challenging shift from in-person classroom teaching to teaching in an online environment. As teachers continue to learn about working in this new environment, research in cognitive and learning sciences, specifically findings from cognitive…
Descriptors: COVID-19, Pandemics, Online Courses, Teaching Methods
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
Zhidkikh, Denis; Saarela, Mirka; Kärkkäinen, Tommi – Journal of Computer Assisted Learning, 2023
Background: Measurement of students' self-regulation skills is an active topic in education research, as effective assessment helps devising support interventions to foster academic achievement. Measures based on event tracing usually require large amounts of data (e.g., MOOCs and large courses), while aptitude measures are often qualitative and…
Descriptors: Independent Study, Junior High School Students, Secondary School Mathematics, Mathematics Education
Qiao, Shen; Chu, Samuel Kai Wah; Shen, Xiaoai; Yeung, Susanna Siu-sze – Journal of Computer Assisted Learning, 2022
Background: Morphological awareness (MA) is the awareness and ability to manipulate morphemes, the smallest units of meaning in a language. It is identified as a strong cognitive precursor of word reading and reading comprehension. The current MA instructions are limited to classroom settings and delivered by teachers or experimenters. Few studies…
Descriptors: Middle School Students, English (Second Language), Second Language Learning, Game Based Learning
Bai, Xuemei; Gu, Xiaoqing – Journal of Computer Assisted Learning, 2022
Background: Self-regulated learning (SRL) ability is the key determinant of the success of full-time online learning. Thus, exploring the influencing factors of SRL and their influencing mechanisms is necessary to improve this ability among K-12 students. Objectives: The purpose of this study was to investigate the influence mechanism of teacher…
Descriptors: Personal Autonomy, Electronic Learning, COVID-19, Pandemics
Aydin Bulut; Mustafa Yildiz – Journal of Computer Assisted Learning, 2024
Background: The use of computer-assisted reading comprehension is of critical importance in the context of promoting effective and engaging literacy education in the digital age. It provides students with the opportunity to work at their own pace and convenience, thereby facilitating self-directed learning and accommodating various learning…
Descriptors: Computer Assisted Instruction, Direct Instruction, Reading Comprehension, Technology Uses in Education
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

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