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Thao Pham; Wu-Yuin Hwang; Xuan-Lam Pham – Journal of Computer Assisted Learning, 2024
Background: Examining student attention in physical classrooms is crucial, but it faces challenges due to the lack of accurate monitoring. Constraints posed by device limitations and the design of educational materials impede the integration of eye-tracking technology in these settings. Objectives: This study aims to (1) develop a wearable…
Descriptors: Attention, Eye Movements, Physical Environment, Classroom Environment
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Ranieri, Maria; Luzzi, Damiana; Cuomo, Stefano; Bruni, Isabella – Journal of Computer Assisted Learning, 2022
Background: Over recent years, interest towards the use of immersive technologies has grown in parallel with the lowering of equipment costs: educators have started embedding them into their teaching practices at different levels of the educational system, from primary school to higher education. In general, immersive technologies are seen as…
Descriptors: Educational Technology, Video Technology, Technology Uses in Education, Transfer of Training
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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
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Pi, Zhongling; Deng, Lixia; Wang, Xu; Guo, Peirong; Xu, Tao; Zhou, Yun – Journal of Computer Assisted Learning, 2022
Background: Video lectures which include the instructor's presence are becoming increasingly popular. Presenting a real human does, however, entail higher financial and time costs in making videos, and one innovative approach to reduce costs has been to generate a virtual speaking instructor. Objectives: The current study examined whether the use…
Descriptors: Video Technology, Lecture Method, Computer Simulation, Instructional Effectiveness
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Xie, Heping; Zhao, Tingting; Deng, Sue; Peng, Ji; Wang, Fuxing; Zhou, Zongkui – Journal of Computer Assisted Learning, 2021
Eye movement modelling examples (EMME) are computer-based videos displaying the visualized eye gaze behaviour of a domain expert person (model) while carefully executing the learning or problem-solving task. The role of EMME in promoting cognitive performance (i.e., final scores of learning outcome or problem solving) has been questioned due to…
Descriptors: Eye Movements, Attention, Cognitive Ability, Learning Processes
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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
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Chisari, Lucia B.; Mockeviciute, Akvile; Ruitenburg, Sterre K.; van Vemde, Lian; Kok, Ellen M.; van Gog, Tamara – Journal of Computer Assisted Learning, 2020
Eye movement modelling examples (EMMEs) are instructional videos of a model's demonstration and explanation of a task that also show where the model is looking. EMMEs are expected to synchronize students' visual attention with the model's, leading to better learning than regular video modelling examples (MEs). However, synchronization is seldom…
Descriptors: Eye Movements, Video Technology, Models, Attention
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Yawen Shi; Zengzhao Chen; Mengke Wang; Shaohui Chen; Jianwen Sun – Journal of Computer Assisted Learning, 2024
Background: Guided gaze is the instructor's gaze towards teaching materials to guide students' attention, and it plays a vital role in enhancing video-based education. The duration of guided gaze, indicating how long instructors focus on teaching materials, varies based on the lecture design. Nevertheless, the impact of varying durations of guided…
Descriptors: Teacher Behavior, Eye Movements, Lecture Method, Video Technology
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Wang, Hongyan; Pi, Zhongling; Hu, Weiping – Journal of Computer Assisted Learning, 2019
Instructor behaviour is known to affect learning performance, but it is unclear which specific instructor behaviours can optimize learning. We used eye-tracking technology and questionnaires to test whether the instructor's gaze guidance affected learners' visual attention, social presence, and learning performance, using four video lectures:…
Descriptors: Video Technology, Lecture Method, Nonverbal Communication, Eye Movements
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Rekik, Ghazi; Khacharem, Aïmen; Belkhir, Yosra; Bali, Naila; Jarraya, Mohamed – Journal of Computer Assisted Learning, 2019
Recent studies exploring the effects of dynamic visualizations on learning compared with static visualizations have yielded mixed results. Procedural motor learning is one of the few fields in which dynamic representations have shown to be effective. Many of the studies have suggested that this advantage is mainly due to the activation of the…
Descriptors: Visualization, Physical Education, Video Technology, Photography
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van Wermeskerken, Margot; Grimmius, Bianca; van Gog, Tamara – Journal of Computer Assisted Learning, 2018
We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate…
Descriptors: Video Technology, Autism, Pervasive Developmental Disorders, Outcomes of Education