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Wu, Ting-Ting; Lee, Hsin-Yu; Wang, Wei-Sheng; Lin, Chia-Ju; Huang, Yueh-Min – International Journal of Educational Technology in Higher Education, 2023
In the field of Science, Technology, Engineering, and Mathematics (STEM) education, which aims to cultivate problem-solving skills, accurately assessing learners' engagement remains a significant challenge. We present a solution to this issue with the Real-time Automated STEM Engagement Detection System (RASEDS). This innovative system capitalizes…
Descriptors: STEM Education, Learner Engagement, Self Efficacy, Problem Solving
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Hyeon Jo – International Journal of Educational Technology in Higher Education, 2024
Artificial Intelligence (AI) chatbots are increasingly becoming integral components of the digital learning ecosystem. As AI technologies continue to evolve, it is crucial to understand the factors influencing their adoption and use among students in higher education. This study is undertaken against this backdrop to explore the behavioral…
Descriptors: Artificial Intelligence, Computer Software, Educational Technology, Technology Uses in Education
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Stojanov, Ana – International Journal of Educational Technology in Higher Education, 2023
ChatGPT, an artificial intelligence language model introduced in November 2022, is potentially applicable in many contexts, including higher education. Although academics are already using it to draft papers or develop search queries for systematic reviews, its use as a tool aiding the learning process has not been examined. To address this…
Descriptors: Technology Uses in Education, Artificial Intelligence, Autobiographies, Ethnography
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Essel, Harry Barton; Vlachopoulos, Dimitrios; Tachie-Menson, Akosua; Johnson, Esi Eduafua; Baah, Papa Kwame – International Journal of Educational Technology in Higher Education, 2022
Chatbot usage is evolving rapidly in various fields, including higher education. The present study's purpose is to discuss the effect of a virtual teaching assistant (chatbot) that automatically responds to a student's question. A pretest-posttest design was implemented, with the 68 participating undergraduate students being randomly allocated to…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Teaching Assistants, Undergraduate Students