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Lucia Mason; Angelica Ronconi; Barbara Carretti; Sara Nardin; Christian Tarchi – Journal of Computer Assisted Learning, 2024
Background: Digital texts are progressively becoming the medium of learning for students, but research has indicated that students tend to process information more superficially while reading on screen. It is therefore relevant to examine what strategies can support digital text comprehension. Objectives: This study aimed to investigate the…
Descriptors: College Students, Books, Electronic Publishing, Handheld Devices
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
Qin, Chao; Liu, Yanjia; Zhang, Hemei – Journal of Computer Assisted Learning, 2023
Background: Being easy to learn and fun, block-based programming tools are widely used to teach students introductory programming. Scratch and LEGO robots are two popular block-based programming tools. However, the objects they manipulate are completely different. Scratch manipulates graphical virtual sprites, whereas LEGO robots manipulate…
Descriptors: Foreign Countries, Undergraduate Students, Learner Engagement, Robotics
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
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
Charlotte H. Müller; Markus Reiher; Manu Kapur – Journal of Computer Assisted Learning, 2024
Background: Haptic feedback has been shown to be an effective facilitator of the learning of scientific concepts in a series of studies. However, little is known about the underlying salient learning mechanisms, which are activated when learning from haptic feedback. Objectives: We investigate the learning mechanism in a higher chemistry education…
Descriptors: Quantum Mechanics, Chemistry, Feedback (Response), Cognitive Processes
Yorganci, Serpil – Journal of Computer Assisted Learning, 2022
Background: Continuous advances in mobile and multimedia technologies have increased interest in the use of e-books in educational settings. Objectives: The current study investigated how the e-book technology and different types of feedback influenced the learning, motivation, and cognitive load of students within the differentiation unit of…
Descriptors: Books, Electronic Publishing, Video Technology, Feedback (Response)
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
Zhang, Ruonan; Bi, Nicky Chang; Mercado, Trinidee – Journal of Computer Assisted Learning, 2023
Background: Online learning and teaching were globally popularized due to the impact of COVID-19. The pandemic has made both synchronous and asynchronous online learning inevitable in regions privileged with the technological affordance. Aims: This study was designed to examine and compare the effectiveness of both learning modes through the…
Descriptors: Undergraduate Students, Synchronous Communication, Asynchronous Communication, Electronic Learning
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
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