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Zheng, Lanqin; Long, Miaolang; Niu, Jiayu; Zhong, Lu – International Journal of Computer-Supported Collaborative Learning, 2023
Learning engagement has gained increasing attention in the field of education. Previous studies have adopted conventional methods to analyze learning engagement, but these methods cannot provide timely feedback for learners. This study analyzed automated group learning engagement via deep neural network models in a computer-supported collaborative…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Learner Engagement, Automation
Kaitlyn Tracy; Ourania Spantidi – IEEE Transactions on Learning Technologies, 2025
Virtual reality (VR) has emerged as a transformative educational tool, enabling immersive learning environments that promote student engagement and understanding of complex concepts. However, despite the growing adoption of VR in education, there remains a significant gap in research exploring how generative artificial intelligence (AI), such as…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Simulation, Educational Technology
Ahmed Hosny Saleh Metwally; Ronghuai Huang; Paula Toledo Palomino; Ahmed Mohamed Fahmy Yousef – Education and Information Technologies, 2024
Gamifying online homework activities and learning assignments is an effective approach to facilitate students' engagement and enjoyment. While incorporating game elements to gamify homework and learning assignments promoted positive psychological and learning outcomes, the mere use of these elements brings several flaws associated with the gameful…
Descriptors: Gamification, Homework, Instructional Effectiveness, Motivation
Sijia Chen; Jan-Louis Kruger – Interpreter and Translator Trainer, 2024
Following a preliminary study that examined the potential effectiveness of a computer-assisted consecutive interpreting (CACI) mode, this paper presents a further trial of the CACI workflow. The workflow involves respeaking using speech recognition (SR) in phase I and production assisted by the SR text and its machine translation (MT) output in…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Translation, Speech Communication
Skulmowski, Alexander – Education and Information Technologies, 2022
Realistic visualizations are abundantly used in digital education. However, the use of realism is still thought to risk a cognitive overload due to excessive details. Moreover, it is still not precisely known whether there is an optimal level of realism that benefits learners the most. In two experimental studies, different versions of anatomical…
Descriptors: Visual Aids, Computer Assisted Instruction, Cognitive Processes, Difficulty Level
Bahari, Akbar; Wu, Sumei; Ayres, Paul – Educational Psychology Review, 2023
A contemporary review (over a 10-year period) was conducted into studies that used computer-assisted language learning (CALL) strategies to learn a second language (L2) by considering the impact of cognitive load. Twelve affordances were identified that led to enhanced learning, namely, online annotations and glosses, captioning, digital…
Descriptors: Computer Assisted Instruction, Second Language Learning, Cognitive Processes, Difficulty Level
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
Ruiqi Deng; Yi Yang; Suqin Shen – Education and Information Technologies, 2025
Empirical evidence has consistently shown that interactive questions are an effective strategy for strengthening student learning through instructional videos. However, research has not directly addressed the crucial question of whether the beneficial effects of interactive questions in instructional videos are attributable to the presence of…
Descriptors: Educational Technology, Technology Uses in Education, Video Technology, Questioning Techniques
Huan Kang; Hong Chen – Education and Information Technologies, 2025
This study investigates the effects of online instructors' use of initiation and maintenance rapport-building strategies (RBS) on Chinese EFL learners' CALL motivation and cognitive load management. Mixed methods research was used to concurrently triangulate different strands of data on the effects of RBS on 86 randomly sampled EFL learners. The…
Descriptors: English (Second Language), Second Language Learning, Teacher Student Relationship, Cognitive Processes
Daniel Laumann; Maurice Krause; Fabienne E. Kremer; Barbara Leibrock; Malte S. Ubben; Boris Forthmann; Robin Janzik; Dörthe Masemann; Felix Reer; Cornelia Denz; Gilbert Greefrath; Susanne Heinicke; Annette Marohn; Thorsten Quandt; Elmar Souvignier; Stefan Heusler – Education and Information Technologies, 2025
In recent years, the importance of mobile devices has increased for education in general and more specifically for science and mathematics education. In the classroom, approaches for teaching with mobile devices include using student-owned devices ("bring your own device"; BYOD approach) or using school-owned devices from central pools…
Descriptors: Electronic Learning, Technology Uses in Education, Educational Technology, Handheld Devices
Xueye Yan; Peng Peng; Yuting Liu – Grantee Submission, 2024
Mayer (2017, 2020) proposed three major design features of computer-assisted instructions (CAI) within the Cognitive Theory of Multimedia Learning: reducing extraneous processing (i.e., excluding irrelevant content), managing essential processing (i.e., focusing on the complex but essential learning materials), and fostering generative processing…
Descriptors: Computer Assisted Instruction, Reading Instruction, Instructional Design, Reading Difficulties
Rawad Chaker; Mélanie Gallot; Ayodélé Madi; Christian Collet; Nady Hoyek – Anatomical Sciences Education, 2025
During the COVID-19 pandemic, anatomy educators have demonstrated their ability to respond to face-to-face (F2F) teaching restrictions and offer emergency remote teaching and learning (ERTL) approach. Another educational model that was intensified during COVID-19 was blended learning (BL) which is a combination of F2F and online settings. Studies…
Descriptors: Anatomy, Human Body, Kinesiology, Science Instruction
Guillaume Decormeille; Thomas Geeraerts; Médéric Descoins; Nathalie Huet – Applied Cognitive Psychology, 2025
Screen-based simulation (SBS) can complement traditional nursing courses. We compared the effect of innovative virtual environments not widespread in French nursing schools on self-efficacy, quiz performance, and self-regulated learning behaviors. This quasi-experimental study involved 1183 student nurses. Participants were divided into an…
Descriptors: Foreign Countries, Nursing Education, Nursing Students, Computer Simulation
Ali, Numan; Ullah, Sehat; Khan, Dawar – Education and Information Technologies, 2022
Virtual Chemistry Laboratories (VCLs) are used as an alternative to the physical laboratories, where users can enhance their performance for hands-on chemistry experiments. However, cognitive load and other issues make the VCLs impractical. The issue of cognitive load arises due to the complexity of the environment by displaying a number of…
Descriptors: Cognitive Processes, Difficulty Level, Electronic Learning, Chemistry
Zhen Wang; Xinrui Pei; Hejie Zhu; Shaoying Gong; Enguo Wang – Journal of Educational Computing Research, 2024
This research aims to expand our understanding of how to facilitate student feedback engagement processes in a computer-based formative assessment environment. In the present research, we designed a new type of elaborated feedback in terms of combining the correct solution and the erroneous solution, and the erroneous solution matched the…
Descriptors: Junior High School Students, Junior High School Teachers, Feedback (Response), Computer Assisted Instruction