A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

Exploring pre-service teachers’ generative AI readiness and behavioral intentions




TekijätBui, Phuong; Korhonen, Tiina; Kontkanen, Sini; Karme, Sorella; Piispa-Hakala, Satu; Veermans, Marjaana

KustantajaValtakunnallinen LUMA-keskus

Julkaisuvuosi2025

JournalLUMAT: International Journal on Math, Science and Technology Education

Artikkelin numero8

Vuosikerta13

Numero1

eISSN2323-7112

DOIhttps://doi.org/10.31129/LUMAT.13.1.2755

Verkko-osoitehttps://journals.helsinki.fi/lumat/article/view/2755/2268

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/500031013


Tiivistelmä

Generative Artificial Intelligence (GenAI) has rapidly emerged as a field capable of creating unique content across various areas. While offering significant potential, it presents challenges including ethical concerns, content inaccuracies, and increased challenges for educators who must adapt to fast-evolving technologies. Integrating GenAI tools into teacher education represents an urgent global research priority. This pilot study explores GenAI readiness, experiences, perceptions, and behavioral intentions among Finnish pre-service teachers while examining the feasibility of the GenAI Readiness Scale as a measurement instrument. Using a mixed-methods approach combining quantitative survey data (N=77) with qualitative responses (n=56) from open-ended questions, the research provides a nuanced analysis of future educators’ positioning toward GenAI integration in educational settings. Findings reveal a significant adoption gap, with 27% of participants never used GenAI tools as of April-June 2024, while majority engaged sporadically. Despite low perceived accuracy, frequent users continued utilizing GenAI, suggesting that usability, efficiency, and creative support outweigh accuracy concerns. Ideation and content creation emerged as the most common GenAI-supported tasks, while self-regulated and adaptive learning remained underutilized, indicating limited awareness of GenAI’s broader potential. Challenges primarily involved output quality and prompting difficulties. Participants preferred modifying AI outputs rather than refining prompts, employing strategies like output modification and external verification, though critical evaluation wasn’t always explicit. These findings highlight the need for structured AI literacy training in teacher education, emphasizing prompt engineering, evaluative judgment, and strategic AI integration. This study underscores the importance of developing GenAI competencies among pre-service teachers to ensure effective, responsible, and pedagogically meaningful AI adoption. Future research should explore longitudinal adoption trends, and impact of AI literacy training on teaching and learning practices.


Ladattava julkaisu

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Julkaisussa olevat rahoitustiedot
Phuong Bui is a postdoc fellow at Karlstad University. This work was also partly financially supported by the Finnish Cultural Foundation (SKR) to Phuong Bui (Grant number 00240334).


Last updated on 2025-19-09 at 10:42