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ChatGPT-Supported Education in Primary Schools: The Potential of ChatGPT for Sustainable Practices

Author

Listed:
  • Hilal Uğraş

    (Department of Child Development, Karakocan Vocational School, Firat University, 23000 Elazığ, Turkey)

  • Mustafa Uğraş

    (Department of Preschool Teacher Education, Faculty of Education, Fırat University, 23000 Elazığ, Turkey)

  • Stamatios Papadakis

    (Department of Preschool Education, Faculty of Education, University of Crete, 74100 Crete, Greece)

  • Michail Kalogiannakis

    (Department of Special Education, School of Humanities and Social Sciences, University of Thessaly, 38221 Volos, Greece)

Abstract

This study aims to evaluate the potential of using ChatGPT at the primary school level from the teachers’ perspective within a sustainability framework. The research was conducted as a qualitative case study involving 40 primary school teachers in Turkey during the 2023–2024 academic year, all of whom had no prior experience with ChatGPT. Data collection tools included semi-structured interview forms and researcher diaries developed by the researchers. The data obtained were analysed using content analysis. The findings indicate that most primary school teachers believe ChatGPT is suitable for primary education and can contribute to Sustainable Development Goal (SDG) 4. Additionally, teachers noted that ChatGPT enriches the teaching process and is user-friendly. These findings suggest potential contributions to SDG 4.1 and SDG 4.2. However, concerns were raised regarding ChatGPT’s potential to provide false information, which may negatively impact SDG 4.7. The study also identified that ChatGPT is particularly suitable for mathematics, Turkish, and English courses. This study’s main contribution is that it shows how ChatGPT can help sustainable practices in primary education by getting teachers more involved and meeting specific curriculum needs. This gives us useful information for incorporating AI tools into education that is in line with SDG 4. It is recommended that training programs about ChatGPT and similar AI-supported tools be organised for teachers and parents.

Suggested Citation

  • Hilal Uğraş & Mustafa Uğraş & Stamatios Papadakis & Michail Kalogiannakis, 2024. "ChatGPT-Supported Education in Primary Schools: The Potential of ChatGPT for Sustainable Practices," Sustainability, MDPI, vol. 16(22), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9855-:d:1519134
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    References listed on IDEAS

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    1. Thomas Adams & Syed Muslim Jameel & Jamie Goggins, 2023. "Education for Sustainable Development: Mapping the SDGs to University Curricula," Sustainability, MDPI, vol. 15(10), pages 1-32, May.
    2. Mustafa Uğraş & Erdal Zengin & Stamatis Papadakis & Michail Kalogiannakis, 2023. "Early Childhood Learning Losses during COVID-19: Systematic Review," Sustainability, MDPI, vol. 15(7), pages 1-29, April.
    3. Christina Marouli, 2021. "Sustainability Education for the Future? Challenges and Implications for Education and Pedagogy in the 21st Century," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    4. Jussi S. Jauhiainen & Agustín Garagorry Guerra, 2023. "Generative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson," Sustainability, MDPI, vol. 15(18), pages 1-22, September.
    5. Teresa Monte & Pedro Reis, 2021. "Design of a Pedagogical Model of Education for Environmental Citizenship in Primary Education," Sustainability, MDPI, vol. 13(11), pages 1-23, May.
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    Cited by:

    1. Thivyasiny Saravanan & Nurul Aisyah Kamrozzaman, 2025. "Artificial Intelligence in Primary Education: Teacher Perceptions, Instructional Decisions, and Integration Challenges in Urban Malaysia," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(9), pages 9393-9406, September.
    2. Yoonsung Choi, 2025. "Exploring the Scientific Validity of ChatGPT’s Responses in Elementary Science for Sustainable Education," Sustainability, MDPI, vol. 17(7), pages 1-19, March.
    3. Liuyi Yang & Sinan Chen & Jialong Li, 2025. "Enhancing Sustainable AI-Driven Language Learning: Location-Based Vocabulary Training for Learners of Japanese," Sustainability, MDPI, vol. 17(6), pages 1-24, March.

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