A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Generative AI and education: dynamic personalization of pupils' school learning material with ChatGPT
Tekijät: Jauhiainen, Jussi S.; Garagorry Guerra, Agustín
Kustantaja: FRONTIERS MEDIA SA
Kustannuspaikka: LAUSANNE
Julkaisuvuosi: 2024
Journal: Frontiers in Education
Tietokannassa oleva lehden nimi: FRONTIERS IN EDUCATION
Lehden akronyymi: FRONT EDUC
Artikkelin numero: 1288723
Vuosikerta: 9
Sivujen määrä: 12
eISSN: 2504-284X
DOI: https://doi.org/10.3389/feduc.2024.1288723
Verkko-osoite: https://doi.org/10.3389/feduc.2024.1288723
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/477220653
The widespread use of generative AI tools like ChatGPT has seen significant growth. This rise prompted discussions on integrating these technologies into school education. However, the practical implementation, testing, and assessment of generative AI in primary and secondary education remained largely unexplored. This article examines the application of ChatGPT-3.5 and 4 in primary school education. A study involving 110 students aged 8-14 across grades 4-6 in two Uruguayan schools was conducted. The focus was on using generative AI for dynamic personalization of educational content during classroom lessons. In these sessions, instructional content followed the curriculum goals, and text, illustrations, and exercises were generated and dynamically adjusted based on generative AI. The findings indicate that generative AI effectively tailors school materials to match varying pupil knowledge levels. Real-time adjustments during lessons cater to individual learning needs, enhancing cognitive ergonomics. This approach not only boosts pupil motivation but also improves their performance, facilitating more effective achievement of the curriculum's learning objectives. These results suggest a promising avenue for leveraging generative AI to personalize and optimize primary school education.
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The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The research was partially funded by the University of Turku and by the Business Finland co-creation project Digileac.
