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Quality of Collaborative Learning Discovered by Data Mining and Visualization

    • Xi'an Jiaotong-Liverpool University

    Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

    Abstract

    As collaborative work becomes increasingly important in various fields, cultivating teamwork skills is crucial for students' growth and future professional development. This study investigates the impact of team allocation methods on student teamwork in the context of software engineering projects and explored how teachers can provide targeted guidance to fully utilize the strengths and advantages of team members. We use statistical analysis of assignment scores and data visualization techniques for survey questionnaires to understand the dynamics of team allocation and its impact on academic performance and teamwork experience. Our research findings indicate that students in self-organized teams not only outperform teams assigned by teachers, but also demonstrate excellent team cohesion, communication, and collaborative experiences. Therefore, educators should encourage students to form their own teams and track team dynamics in a timely manner to enhance the learning experience.

    Original languageEnglish
    Title of host publication2025 International Conference on Artificial Intelligence and Education, ICAIE 2025
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages327-332
    Number of pages6
    ISBN (Electronic)9798331522957
    ISBN (Print)9798331522964
    DOIs
    Publication statusPublished - 2025
    Event2025 International Conference on Artificial Intelligence and Education, ICAIE 2025 - Suzhou, China
    Duration: 14 May 202516 May 2025

    Publication series

    NameInternational Conference on Artificial Intelligence and Education, ICAIE

    Conference

    Conference2025 International Conference on Artificial Intelligence and Education, ICAIE 2025
    Country/TerritoryChina
    CitySuzhou
    Period14/05/2516/05/25

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