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Tsubasa Minematsu; Atsushi Shimada – International Association for Development of the Information Society, 2024
In using large language models (LLMs) for education, such as distractors in multiple-choice questions and learning by teaching, error-containing content is used. Prompt tuning and retraining LLMs are possible ways of having LLMs generate error-containing sentences in the learning content. However, there needs to be more discussion on how to tune…
Descriptors: Educational Technology, Technology Uses in Education, Error Patterns, Sentences
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Mohammad Rajiur Rahman; Raga Shalini Koka; Shishir K. Shah; Thamar Solorio; Jaspal Subhlok – Education and Information Technologies, 2024
Video is an increasingly important resource in higher education. A key limitation of lecture video is that it is fundamentally a sequential information stream. Quickly accessing the content aligned with specific learning objectives in a video recording of a classroom lecture is challenging. Recent research has enabled automatic reorganization of a…
Descriptors: Lecture Method, Video Technology, Navigation (Information Systems), Artificial Intelligence
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Luis Alberto Laurens-Arredondo – Education and Information Technologies, 2024
The use of technologies in the classroom has become one of the main allies for university teachers in pedagogical innovation, especially during, and after the pandemic. Therefore, the main objective of this article is to investigate how different types of innovative technologies are most effective in increasing motivation among university…
Descriptors: Educational Technology, Student Motivation, Technology Uses in Education, College Students
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Karasavvidis, Ilias; Papadimas, Charalampos; Ragazou, Vasiliki – Themes in eLearning, 2022
The digital trails that students leave behind on e-learning environments have attracted considerable attention in the past decade. Typically, some of these traces involve the production of different kinds of texts. While students routinely produce a bulk of texts in online learning settings, the potential of such linguistic features has not been…
Descriptors: Video Technology, Electronic Learning, Prediction, Academic Achievement
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Selay Arkün-Kocadere; Seyma Çaglar-Özhan – International Review of Research in Open and Distributed Learning, 2024
Via AI video generators, it is possible to create educational videos with humanistic instructors by simply providing a script. The characteristics of video types and features of instructors in videos impact video engagement and, consequently, performance. This study aimed to compare the impact of human instructors and AI-generated instructors in…
Descriptors: Video Technology, Lecture Method, Artificial Intelligence, Animation
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use