Pre-service science teachers' AI literacy, subjective norm, attitude, perceived behavioral control, and perceived usefulness significantly influence their intention to use AI for inquiry-based learning, while their concerns about generative AI and perceived skill readiness do not significantly affect this intention.

Objective: The main goal of this study was to investigate pre-service science teachers' intention to use generative artificial intelligence (AI) in inquiry-based teaching using Azjen's Theory of Planned Behavior. The research aimed to identify which constructs of intention are statistically significant predictors of this intention, assess the appropriateness of the Theory of Planned Behavior as a conceptual framework, and explore how pre-service teachers explain their intentions to use AI in inquiry-based teaching.

Methods: The study employed a sequential explanatory mixed methods design:

1. Quantitative Phase:
   • A survey questionnaire was administered to pre-service teachers enrolled in an undergraduate teacher education degree at a South African public university.
   • The instrument comprised 40 items measuring constructs such as AI literacy, perceived usefulness, perceived behavioral control, attitude, behavioral intention, subjective norm, actual learning, concerns about generative AI, and perceived skill readiness.
   • Data were analyzed using partial least squares structural equation modeling (PLS-SEM).
2. Qualitative Phase:
   • Focus group interviews were conducted with three groups of six students each.
   • Interviews were semi-structured, audio-recorded, transcribed, and analyzed thematically.

Key Findings:

1. Quantitative Results:
   • Pre-service teachers' AI literacy, subjective norm, attitude to the use of AI, perceived behavioral control, and perceived usefulness significantly affect their intention to use AI for inquiry-based learning.
   • Concerns about generative AI and perceived skill readiness did not significantly influence intention to use AI.
   • Subjective norm was the strongest predictor of intention to use AI for inquiry-based teaching.
   • The model accounted for 59.1% of the variance in pre-service teachers' behavioral intention to use AI.
2. Qualitative Results (Themes):
   • AI Supporting Inquiry Learning in the Pre-Investigative Phase: Pre-service teachers recognized AI's value in supporting orientation and conceptualization phases of inquiry.
   • AI Supports Learner Autonomy and Accommodates Individual Learner Needs: AI was seen as promoting autonomous learning and addressing diverse student needs.
   • AI Simulates Experiments: Pre-service teachers highlighted AI's potential to simulate experiments that are difficult or dangerous to conduct in schools.
   • Checking the Correctness of the Procedure: AI was viewed as a tool for students to verify their experimental procedures before teacher review.
   • Concerns about using AI for Inquiry-Based Teaching: Issues raised included potential inaccuracies, the need for proper training, and the risk of over-reliance on AI.

Implications: The findings provide insights into potential enablers and inhibitors of AI use in inquiry-based science teaching. From a practical perspective, these results can inform teacher educators on key issues to address when discussing AI use with pre-service teachers. The strong influence of subjective norm highlights the importance of teacher educators, mentor teachers, and peers in shaping pre-service teachers' intentions to adopt AI.

Limitations:

1. Small sample size limited to a single institution in South Africa, affecting generalizability.
2. Initial reliability and validity issues with the survey instrument, though addressed through item removal.
3. Pre-service teachers may have had limited experience with AI, potentially affecting the validity of their claims.

Future Directions:

1. Conduct research with larger and more diverse samples to allow for cross-national comparisons of pre-service science teachers' intentions to use AI for inquiry-based teaching.
2. Compare pre-service and in-service teachers' intentions to use AI to understand how different contextual factors influence these intentions.
3. Investigate the long-term effects of AI integration in inquiry-based science teaching on student learning outcomes.
4. Explore the development of AI literacy among pre-service teachers and its impact on their teaching practices.
5. Examine the ethical implications of AI use in science education and how to address these concerns in teacher preparation programs.

Title and Authors: "Pre-Service Science Teachers' Intention to use Generative Artificial Intelligence in Inquiry-Based Teaching" by Umesh Ramnarain, Ayodele Abosede Ogegbo, Mafor Penn, Segun Ojetunde, and Noluthando Mdlalose.

Published On: September 12, 2024

Published By: Journal of Science Education and Technology