Title:
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GENERATING EXPLANATORY TEXTS ON
RELATIONSHIPS BETWEEN SUBJECTS AND THEIR
POSITIONS IN A CURRICULUM USING GENERATIVE AI |
Author(s):
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Ryusei Munemura, Fumiya Okubo, Tsubasa Minematsu, Yuta Taniguchi and Atsushi Shimada |
ISBN:
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978-989-8704-61-0 |
Editors:
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Demetrios G. Sampson, Dirk Ifenthaler and Pedro Isaías |
Year:
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2024 |
Edition:
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Single |
Keywords:
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Course Planning, Syllabus, Curriculum, Generative AI, Classification of Course Relationships, Text Generation |
Type:
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Full |
First Page:
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159 |
Last Page:
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166 |
Language:
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English |
Cover:
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Full Contents:
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Paper Abstract:
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Course planning is essential for academic success and the achievement of personal goals. Although universities provide
course syllabi and curriculum maps for course planning, integrating and understanding these resources by the learners
themselves for effective course planning is time-consuming and difficult. To address this issue, this study proposes a
method that uses generative AI to classify relationships between subjects and generate explanatory texts describing the
connections of subjects and positions of subjects within the curriculum based on subject and curriculum information. An
evaluation experiment involving learners demonstrated a classification accuracy of approximately 70% for inter-subject
relationships. Furthermore, our experimental results confirm that that the generated explanatory texts significantly enhance
the understanding of relationships between subjects, and are thus effective for course planning. |
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