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Direct linkJiu Yong; Jianguo Wei; Yangping Wang; Jianwu Dang; Xiaomei Lei; Wenhuan Lu – IEEE Transactions on Learning Technologies, 2023
Extended reality (XR) is a general term for virtual reality (VR), augmented reality (AR), and mixed reality (MR). By converting abstract digital expressions into intelligent feedback through figures, one can effectively compensate for the poor performance of traditional learning in deep cognitive processing and operational skills training.…
Descriptors: Computer Simulation, Cognitive Processes, Undergraduate Students, Majors (Students)
Song, Yanjie; Cao, Jiaxin; Wu, Kaiyi; Yu, Philip Leung Ho; Lee, John Chi-Kin – IEEE Transactions on Learning Technologies, 2023
Despite the metaverse having been increasingly designed, developed, and applied to education, critical issues regarding the lack of truly immersive learning environments, custom tools, clear instructional design, and inconvenience of using the platform, and ethics and privacy concerns exist. This study aimed to design and develop a 3-D metaverse…
Descriptors: Computer Simulation, Computer Uses in Education, Cognitive Processes, Assistive Technology
Jingjing Chen; Rao Muhammad Aqib Hassan; Shuai Sun; Yilin Mo; Dan Zhang – IEEE Transactions on Learning Technologies, 2025
The lightboard, an affordable and readily accessible tool, has become a promising approach for enhancing engagement in instructional videos. Despite its potential, previous studies have primarily highlighted the benefits of lightboard videos by evaluating learners' subjective experiences, with limited empirical research examining their impact on…
Descriptors: College Students, Mathematics Skills, Mathematics Achievement, Video Technology
Papamitsiou, Zacharoula; Pappas, Ilias O.; Sharma, Kshitij; Giannakos, Michail N. – IEEE Transactions on Learning Technologies, 2020
Investigating and explaining the patterns of learners' engagement in adaptive learning conditions is a core issue towards improving the quality of personalized learning services. This article collects learner data from multiple sources during an adaptive learning activity, and employs a fuzzy set qualitative comparative analysis (fsQCA) approach…
Descriptors: Undergraduate Students, Individualized Instruction, Learner Engagement, Reaction Time
Jiaqi Yin; Tiong-Thye Goh; Yi Hu – IEEE Transactions on Learning Technologies, 2024
This study aimed to examine sustainable effects of chatbot-based formative feedback on intrinsic motivation, cognitive load, and learning performance. A longitudinal quasi-experimental design with 173 undergraduate students was conducted. The experiment is a between-subject design. Students either received formative feedback from a chatbot or a…
Descriptors: Artificial Intelligence, Synchronous Communication, Feedback (Response), Longitudinal Studies
Biswas, Gautam; Rajendran, Ramkumar; Mohammed, Naveeduddin; Goldberg, Benjamin S.; Sottilare, Robert A.; Brawner, Keith; Hoffman, Michael – IEEE Transactions on Learning Technologies, 2020
Intelligent learning environments can be designed to support the development of learners' cognitive skills, strategies, and metacognitive processes as they work on complex decision-making and problem-solving tasks. However, the complexity of the tasks may impede the progress of novice learners. Providing adaptive feedback to learners who face…
Descriptors: Decision Making, Difficulty Level, Hierarchical Linear Modeling, Cognitive Processes
