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Direct linkChing-Jung Chung; Yen-Hsun Huang; Jie Chi Yang; Ying-Ying Yang; Shiau-Shian Huang; Sheng-Min Lin; Jiing-Feng Lirng; Tzu-Hao Li; Chen-Huan Chen; Yung-Yang Lin – Interactive Learning Environments, 2024
This prospective longitudinal study assessed the effects of the course management system, EDU3, on the effectiveness of the dissemination of holistic health care and evidence-based medicine (EBM) courses. Between January 2014 and December 2021, delinked data (n = 354,229) from EDU3 were analyzed. In addition to analyzing the main educational team…
Descriptors: Evidence Based Practice, Medical Education, Learning Management Systems, Holistic Approach
Yu-Yin Wang; Yu-Wei Chuang – Interactive Learning Environments, 2024
A review of the literature shows that much academic effort has been expended studying information system usage and information technology adoption. However, these theories/models based on psychological research are not specific to the virtual reality context and may not fully capture the nature of virtual reality-based learning system (VR-BLS)…
Descriptors: Computer Simulation, Electronic Learning, Technology Uses in Education, Learning Management Systems
Chen, Chih-Ming; Li, Ming-Chaun; Huang, Ya-Ling – Interactive Learning Environments, 2023
By applying two-mode social networks and Chinese word segmentation technologies, a novel visualization tool, the instant semantic analysis and feedback system (ISAFS), is designed in this study to present the semantic networks of co-words and non-co-words used in learners' discussion processes and assist learners in grasping the discussion…
Descriptors: Foreign Countries, High School Students, Semantics, Feedback (Response)
Yung-Hsiang Hu; Jo Shan Fu; Hui-Chin Yeh – Interactive Learning Environments, 2024
Artificial intelligence aims to restructure and process re-engineering education and teaching processes and accelerate the evolution of the whole education system from information to intelligence. Robotic Process Automation (RPA) robots learn by observing people at work, analyzing user processes repeatedly, and adjusting or correcting automated…
Descriptors: Intelligent Tutoring Systems, Robotics, Automation, Instructional Effectiveness
Ai-Jou Pan; Yu-Che Huang; Chin-Feng Lai – Interactive Learning Environments, 2024
Engineering education emphasizes experiential learning and laboratory experience, an approach which has faced significant challenges during the COVID-19 pandemic. The inability to conduct hands-on laboratory experiments in engineering courses can significantly impede the student's learning experience, as well as their acquisition and retention of…
Descriptors: Learning Management Systems, Hands on Science, Distance Education, Laboratories
Min-Chi Chiu; Gwo-Jen Hwang; Lu-Ho Hsia; Fong-Ming Shyu – Interactive Learning Environments, 2024
In a conventional art course, it is important for a teacher to provide feedback and guidance to individual students based on their learning status. However, it is challenging for teachers to provide immediate feedback to students without any aid. The advancement of artificial intelligence (AI) has provided a possible solution to cope with this…
Descriptors: Art Education, Artificial Intelligence, Teaching Methods, Comparative Analysis
