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Lishan Zhang; Lili Liu; Shuwen Wang; Min Xu; Sixv Zhang; Yun Tang – Journal of Computer Assisted Learning, 2025
Background: Collaborative reading can facilitate students' understanding of complex learning materials. High-quality annotations provided by peer learners are essential for successful collaborative reading. However, it remains to be understood how annotation quality affects reading comprehension. Objectives: A simulated collaborative reading…
Descriptors: Educational Quality, Documentation, Reading Processes, Eye Movements
Lanqin Zheng; Yunchao Fan; Zichen Huang; Lei Gao – Journal of Computer Assisted Learning, 2024
Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building,…
Descriptors: Cooperative Learning, Electronic Learning, College Students, Learning Strategies
Akbar Bahari; Parviz Alavinia; Mohammad Mohammadi – Journal of Computer Assisted Learning, 2024
Background: This study investigates the effects of higher and lower-level text processing strategies on both higher and lower-level processing skills and cognitive load using the computer-assisted interactive reading model (CAIRM) as the educational intervention framework. Objectives: The objectives of this study are to examine the effects of the…
Descriptors: Computer Assisted Instruction, Experiential Learning, Reading, Cognitive Processes
Rafael Mellado; Claudio Cubillos – Journal of Computer Assisted Learning, 2024
Background: Effective learning in computer programming courses has been a constant challenge for university teachers and has become a relevant competence for current professionals. The literature on gamification in learning presents mixed results, mainly due to problems in instructional design and inconsistency in gamification. Studies with…
Descriptors: Engineering Education, College Students, Computer Software, Technical Occupations
Jiang, Michael Yi-Chao; Jong, Morris Siu-Yung; Lau, Wilfred Wing-Fat; Chai, Ching-Sing; Wu, Na – Journal of Computer Assisted Learning, 2023
Background: While automatic speech recognition (ASR) is increasingly used for commercial purposes, its influence on the learners' linguistic performance in terms of oral complexity, accuracy and fluency was under-explored. To date, few studies have been conducted to investigate how the dictation ASR technology could be incorporated into language…
Descriptors: Speech Communication, Automation, Accuracy, Language Fluency
Gruss, Richard; Clemons, Josh – Journal of Computer Assisted Learning, 2023
Background: The sudden growth in online instruction due to COVID-19 restrictions has given renewed urgency to questions about remote learning that have remained unresolved. Web-based assessment software provides instructors an array of options for varying testing parameters, but the pedagogical impacts of some of these variations has yet to be…
Descriptors: Test Items, Test Format, Computer Assisted Testing, Mathematics Tests
Lion Sieg; Hendrik Eismann; Bertrand Schneider; Jan Karsten; Dogus Darici – Journal of Computer Assisted Learning, 2025
Background: Research in social cognition suggests that learning effectiveness in teacher-learner pairs may be influenced by how well their attention aligns with each other. However, we currently have limited understanding of how common distractions in real-world environments affect teacher-student interactions, specifically the synchronisation of…
Descriptors: Attention Control, Social Cognition, Teacher Student Relationship, Interaction
Huang, Xiaoshan; Li, Shan; Wang, Tingting; Pan, Zexuan; Lajoie, Susanne P. – Journal of Computer Assisted Learning, 2023
Background: Medical students use a variety of self-regulated learning (SRL) strategies in different medical reasoning (MR) processes to solve patient cases of varying complexity. However, the interplay between SRL and MR processes is still unclear. Objectives: This study investigates how self-regulated learning (SRL) and medical reasoning (MR)…
Descriptors: Medical Students, Self Management, Problem Solving, Logical Thinking
Joo, Hyun; Park, Jongchan; Kim, Dongsik – Journal of Computer Assisted Learning, 2021
In their prior research on adaptive instruction for multi-representational learning, the researchers explored various perspectives on designing visual representations and scaffolds. However, controversies and discrepancies regarding the fidelity of visual representations and self-explanation prompts have yet to be resolved. This research thus…
Descriptors: Visual Aids, Fidelity, Cues, College Students
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
Andersen, Martin S.; Makransky, Guido – Journal of Computer Assisted Learning, 2021
Measuring cognitive load is important in virtual learning environments (VLE). Thus, valid and reliable measures of cognitive load are important to support instructional design in VLE. Through three studies, we investigated the validity and reliability of Leppink's Cognitive Load Scale (CLS) and developed the extraneous cognitive load (EL)…
Descriptors: Test Construction, Test Validity, Test Reliability, Cognitive Processes
Luciana Maria Cavichioli Gomes Almeida; Stefan Münzer; Tim Kühl – Journal of Computer Assisted Learning, 2024
Background: According to the personalization effect in multimedia learning, the use of personal and possessive pronouns in instructional materials (e.g., 'you' and 'your') is beneficial. However, current research suggests that the personalization effect is inverted for emotionally aversive content (e.g., illnesses). Objective: This study…
Descriptors: Foreign Countries, Health Education, Health Promotion, Information Sources
Angelica Ronconi; Lucia Mason; Lucia Manzione; Anne Schüler – Journal of Computer Assisted Learning, 2025
Background: During digital reading on internet-connected devices, students may be exposed to a variety of on-screen distractions. Learning by reading can therefore become a fragmented experience with potentially negative consequences for reading processes and outcomes. Objectives: This study investigated the effects of on-screen distractions, as…
Descriptors: Eye Movements, Electronic Learning, Computer Uses in Education, Reading
Papadopoulos, Pantelis M.; Natsis, Antonis; Obwegeser, Nikolaus; Weinberger, Armin – Journal of Computer Assisted Learning, 2019
The aim of the present study (n = 113) was to examine how (objective and subjective) information on peers' preparation, confidence, and past performance can support students in answering correctly in audience response systems (aka clickers). The result analysis shows that in the "challenging" questions, in which answers diverged,…
Descriptors: Feedback (Response), Audience Response Systems, Self Esteem, Student Attitudes
Chew, Chiou Sheng; Idris, Norisma; Loh, Er Fu; Wu, Wen-Chi Vivian; Chua, Yan Piaw; Bimba, Andrew Thomas – Journal of Computer Assisted Learning, 2019
This paper focuses on the design and evaluation of a theory-based computer-assisted summary writing learning environment called Summary Writing-PAL (SW-PAL). The SW-PAL was developed based on four aspects: summarizing strategies, learning theories, prior knowledge, and cognitive load. A quasi-experiment that involved 58 undergraduates majoring in…
Descriptors: Writing Instruction, Writing (Composition), Educational Technology, Computer Uses in Education
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