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Leveraging ChatGPT for Automated Knowledge Concept Generation

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Title: Leveraging ChatGPT for Automated Knowledge Concept Generation
Language: English
Authors: Tianyuan Yang, Baofeng Ren, Chenghao Gu, Boxuan Ma, Shin 'ichi Konomi
Source: International Association for Development of the Information Society. 2024.
Availability: International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org
Peer Reviewed: Y
Page Count: 8
Publication Date: 2024
Document Type: Speeches/Meeting Papers
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Concept Formation, Artificial Intelligence, Computer Uses in Education, MOOCs, Higher Education, Course Descriptions, Accuracy, Educational Technology, Natural Language Processing
Abstract: As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information about the knowledge concepts covered in a course can help students make more informed decisions. However, manually constructing this knowledge concept information is a labor-intensive and time-consuming task. In this paper, we explore the capability of ChatGPT in generating relevant knowledge concepts from course syllabi and evaluate the accuracy and consistency of these AI-generated concepts against course content using four assessment techniques at both the concept level and course level. We investigate the feasibility of using ChatGPT-generated concepts as a direct educational resource, as well as their potential integration into broader educational technologies, such as interpretable course recommendation systems. [For the full proceedings, see ED665357.]
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED665511
Database: ERIC
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  Data: Leveraging ChatGPT for Automated Knowledge Concept Generation
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  Data: As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information about the knowledge concepts covered in a course can help students make more informed decisions. However, manually constructing this knowledge concept information is a labor-intensive and time-consuming task. In this paper, we explore the capability of ChatGPT in generating relevant knowledge concepts from course syllabi and evaluate the accuracy and consistency of these AI-generated concepts against course content using four assessment techniques at both the concept level and course level. We investigate the feasibility of using ChatGPT-generated concepts as a direct educational resource, as well as their potential integration into broader educational technologies, such as interpretable course recommendation systems. [For the full proceedings, see ED665357.]
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      – SubjectFull: Computer Uses in Education
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      – TitleFull: Leveraging ChatGPT for Automated Knowledge Concept Generation
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            NameFull: Tianyuan Yang
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            NameFull: Chenghao Gu
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            NameFull: Boxuan Ma
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            NameFull: Shin 'ichi Konomi
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              Y: 2024
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