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A Three-Step Knowledge Graph Approach Using LLMs in Collaborative Problem Solving-Based STEM Education

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Title: A Three-Step Knowledge Graph Approach Using LLMs in Collaborative Problem Solving-Based STEM Education
Language: English
Authors: Li Chen, Gen Li, Boxuan Ma, Cheng Tang, Masanori Yamada
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
Descriptors: Concept Mapping, Graphs, Cooperative Learning, Problem Solving, STEM Education, Artificial Intelligence, Natural Language Processing
Abstract: This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge graph from learning material contents, establishing a reference framework that represents the target knowledge structure of the course. Second, customized knowledge graphs were generated by analyzing the scientific concepts and knowledge based on the discussion dialogues, showing students activated knowledge structures. Finally, the dialogue-based knowledge graphs were integrated into textbook-based target knowledge, to identify the activated and non-activated knowledge nodes and connections, as well as the related activated knowledge nodes and connections from other previous lectures or experiences. This three-step approach visualizes students knowledge activation, and the learning gaps remain. This paper presented three examples of integrated knowledge graphs based on the different group formations. The findings of three different groups were discussed, and some educational implications were provided. [For the full proceedings, see ED665357.]
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED665562
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED665562
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  Data: A Three-Step Knowledge Graph Approach Using LLMs in Collaborative Problem Solving-Based STEM Education
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Li+Chen%22">Li Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Gen+Li%22">Gen Li</searchLink><br /><searchLink fieldCode="AR" term="%22Boxuan+Ma%22">Boxuan Ma</searchLink><br /><searchLink fieldCode="AR" term="%22Cheng+Tang%22">Cheng Tang</searchLink><br /><searchLink fieldCode="AR" term="%22Masanori+Yamada%22">Masanori Yamada</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22International+Association+for+Development+of+the+Information+Society%22"><i>International Association for Development of the Information Society</i></searchLink>. 2024.
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  Data: International Association for the Development of the Information Society. e-mail: secretariat@iadis.org; Web site: http://www.iadisportal.org
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  Data: 8
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  Data: 2024
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  Data: Speeches/Meeting Papers<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Concept+Mapping%22">Concept Mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Graphs%22">Graphs</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+Learning%22">Cooperative Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+Solving%22">Problem Solving</searchLink><br /><searchLink fieldCode="DE" term="%22STEM+Education%22">STEM Education</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+Language+Processing%22">Natural Language Processing</searchLink>
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  Label: Abstract
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  Data: This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge graph from learning material contents, establishing a reference framework that represents the target knowledge structure of the course. Second, customized knowledge graphs were generated by analyzing the scientific concepts and knowledge based on the discussion dialogues, showing students activated knowledge structures. Finally, the dialogue-based knowledge graphs were integrated into textbook-based target knowledge, to identify the activated and non-activated knowledge nodes and connections, as well as the related activated knowledge nodes and connections from other previous lectures or experiences. This three-step approach visualizes students knowledge activation, and the learning gaps remain. This paper presented three examples of integrated knowledge graphs based on the different group formations. The findings of three different groups were discussed, and some educational implications were provided. [For the full proceedings, see ED665357.]
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      – Text: English
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        PageCount: 8
    Subjects:
      – SubjectFull: Concept Mapping
        Type: general
      – SubjectFull: Graphs
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      – SubjectFull: Cooperative Learning
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      – SubjectFull: Problem Solving
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      – SubjectFull: STEM Education
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      – SubjectFull: Artificial Intelligence
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      – SubjectFull: Natural Language Processing
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      – TitleFull: A Three-Step Knowledge Graph Approach Using LLMs in Collaborative Problem Solving-Based STEM Education
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            NameFull: Gen Li
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            NameFull: Boxuan Ma
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            NameFull: Cheng Tang
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            NameFull: Masanori Yamada
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              Type: published
              Y: 2024
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            – TitleFull: International Association for Development of the Information Society
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