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Mengshi Xiao; Weizi Li; Lei Han; Shasha Zheng – Journal of Computer Assisted Learning, 2025
Background: In multimedia learning environments, pedagogical agents have emerged as an innovative tool to enhance digital instruction, yet optimising their design for maximal learning effectiveness remains underexplored. Objectives: This study aimed to investigate how specific design elements of pedagogical agents, namely appearance and voice…
Descriptors: Multimedia Instruction, Instructional Design, Computer Simulation, Student Attitudes
Idit Adler; Liat Liberman; Ilana Dubovi – Journal of Computer Assisted Learning, 2025
Background: This study investigates the effect of immersion levels in virtual reality (VR) learning environments on the acquisition of declarative and procedural knowledge. Prior research indicates that immersion affects cognitive load, but its impact on declarative and procedural knowledge outcomes remains unclear. This study utilises a…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Outcomes of Education
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
Meier, Julius; Jong, Bastian; Montfort, Dorien Preusterink; Verdonschot, Anouk; Wermeskerken, Margot; Gog, Tamara – Journal of Computer Assisted Learning, 2023
Background: There are only few guidelines on how instructional videos should be designed to optimize learning. Recently, the effects of social cues on attention allocation and learning in instructional videos have been investigated. Due to inconsistent results, it has been suggested that the visual complexity of a video influences the effect of…
Descriptors: Video Technology, Cues, Attention, Social Influences
Yuko Suzuki; Fridolin Wild; Eileen Scanlon – Journal of Computer Assisted Learning, 2024
Background: Cognitive load during AR use has been measured conventionally by performance tests and subjective rating. With the growing interest in physiological measurement using non-invasive biometric sensors, unbiased real-time detection of cognitive load in AR is expected. However, a range of sensors and parameters are used in various subject…
Descriptors: Computer Simulation, Cognitive Processes, Difficulty Level, Physiology
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
Baceviciute, Sarune; Lucas, Gordon; Terkildsen, Thomas; Makransky, Guido – Journal of Computer Assisted Learning, 2022
Background: The increased availability of immersive virtual reality (IVR) has led to a surge of immersive technology applications in education. Nevertheless, very little is known about how to effectively design instruction for this new media, so that it would benefit learning and associated cognitive processing. Objectives: This experiment…
Descriptors: Computer Simulation, Simulated Environment, Eye Movements, Diagnostic Tests
Ziyi Kuang; Fuxing Wang; Frank Andrasik; Xiangen Hu – Journal of Computer Assisted Learning, 2024
Background: Little is known about the effectiveness of instructors when presenting content in videos alone. In recent years, researchers have increasingly begun to explore the effects of instructors' social cues (e.g., eye gaze, body orientation, etc.) on learning. However, previous studies exploring the effects of eye gaze have confounded the…
Descriptors: Teacher Behavior, Eye Movements, Human Body, Teacher Effectiveness
Korbach, Andreas; Ginns, Paul; Brünken, Roland; Park, Babette – Journal of Computer Assisted Learning, 2020
Given the widespread use of touch screen devices, the effect of the users' fingers on information processing and learning is of growing interest. The present study drew on cognitive load theory and embodied cognition perspectives to investigate the effects of pointing and tracing gestures on the surface of a multimedia learning instruction.…
Descriptors: Eye Movements, Cognitive Processes, Difficulty Level, Human Body
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
Malone, Sarah; Altmeyer, Kristin; Vogel, Markus; Brünken, Roland – Journal of Computer Assisted Learning, 2020
Multiple external representations (MERs) play an important role in the learning field of mathematics. Whereas the cognitive theory of multimedia learning and the integrative text and picture comprehension model assume that the heterogeneous combination of symbolic and analogous representations fosters learning; the design, functions, and tasks…
Descriptors: Problem Solving, Equations (Mathematics), Eye Movements, Multimedia Instruction
Huh, Dami; Kim, Ji-Hyun; Jo, Il-Hyun – Journal of Computer Assisted Learning, 2019
One of the golden rules in instructional design methods is to optimize the use of working memory capacity and avoid cognitive overload. The study of cognitive load has historically relied on one's introspection. However, it is difficult to capture changes in cognitive load levels during learning sensitively. This paper suggests an approach to…
Descriptors: Cognitive Processes, Difficulty Level, Change, Video Technology
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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