A Conversational AI Bot for Efficient Learning: A Prototypical Design
In an ideal world, how individuals learn should align with the methods they are taught. However, this is not always the case, and it is necessary to reconsider the approach to teaching in academic institutions, such as universities, to help students learn at their own pace. Innovative technology pla...
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Published in: | IEEE access Vol. 12; pp. 154877 - 154887 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Piscataway
IEEE
2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects: | |
Online Access: | Get full text |
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Summary: | In an ideal world, how individuals learn should align with the methods they are taught. However, this is not always the case, and it is necessary to reconsider the approach to teaching in academic institutions, such as universities, to help students learn at their own pace. Innovative technology plays a vital role in achieving this objective. This study proposes using Artificial Intelligence (AI) to teach in academic institutions. Specifically, an AI-powered conversational bot called Conversational AI Bot for Efficient Learning (COFFEE) is designed, implemented, and will be used as an adaptive learning technology. COFFEE will analyze students' learning habits and adjust the teaching style based on their strengths and weaknesses. Teaching and learning are closely linked to the disciplinary areas of education, behavior, and technology. Combining these areas into a conversational bot equipped with AI algorithms and access to big data makes it possible to disrupt traditional teaching methods. This will benefit students who require special attention, such as those with severe learning disabilities who cannot receive adequate support from instructors due to time constraints or lack of experience. COFFEE is a valuable tool that can be used in academic institutions at all levels, including primary and secondary education. It will be based on the latest advancements in AI and data science and is designed to be feasible, reliable, and customizable. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2024.3476953 |