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Unggi Lee; Yeil Jeong; Junbo Koh; Gyuri Byun; Yunseo Lee; Youngsun Hwang; Hyeoncheol Kim; Cheolil Lim – Educational Technology & Society, 2024
Debate is a universally acknowledged competency for its vital role in fostering essential skills such as analytical reasoning, eloquent communication, and persuasive argument construction. This is relevant in both formal educational settings like classrooms and informal venues such as after-school clubs. Traditional debate training methods often…
Descriptors: Artificial Intelligence, Debate, Computer Oriented Programs, Technology Uses in Education
Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
George Hanshaw; Joanna Vance; Craig Brewer – Open Praxis, 2024
This study examines the impact of AI course assistants on student learning experiences in online undergraduate courses at Los Angeles Pacific University. A controlled experiment involving 92 students across treatment and control groups was conducted to evaluate the effectiveness of AI assistants developed by Nectir. The treatment group had access…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Student Experience, Undergraduate Students
Liu, Chengyuan; Cui, Jialin; Shang, Ruixuan; Xiao, Yunkai; Jia, Qinjin; Gehringer, Edward – International Educational Data Mining Society, 2022
An online peer-assessment system typically allows students to give textual feedback to their peers, with the goal of helping the peers improve their work. The amount of help that students receive is highly dependent on the quality of the reviews. Previous studies have investigated using machine learning to detect characteristics of reviews (e.g.,…
Descriptors: Peer Evaluation, Feedback (Response), Computer Mediated Communication, Teaching Methods
Akpinar, Nil-Jana; Ramdas, Aaditya; Acar, Umut – International Educational Data Mining Society, 2020
Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…
Descriptors: Learning Strategies, Blended Learning, Learning Analytics, Student Behavior