article · Journal for STEM Education Research
This study investigates the factors influencing South African pre-service life sciences teachers and their intentions to adopt artificial intelligence in the classroom. Through qualitative semi-structured interviews with ten selected student teachers, the research analyses perspectives using the Theory of Planned Behaviour framework. The findings demonstrate that intentions to use AI depend on a combination of attitudes, behavioral beliefs, and subjective norms. Participants recognised clear pedagogical benefits but also noted practical limitations and philosophical concerns. Furthermore, intentions were shaped by broader environmental conditions, such as inter-generational differences, administrative challenges, resource constraints, and parental expectations. Organisational authority, peer opinions, and policy funding also play decisive roles. Overall, the findings underline the necessity of structured training initiatives and dedicated resource distribution to enable the effective integration of AI tools into life sciences education.
As artificial intelligence tools enter education, understanding the readiness of upcoming teachers is vital. Identifying the practical barriers, beliefs, and institutional pressures that influence educators helps policymakers and educational institutions design effective teacher training programmes and target resource funding where it is needed most.
This early-stage qualitative research informs educational authorities, policy makers, and teacher training programmes looking to implement AI strategies. While the study does not present a commercial product, its insights into user attitudes and operational barriers can guide educational technology developers in designing tools that address teachers' practical limitations and classroom resource constraints.
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Abstract This paper explores pre-service life sciences teachers’ behavioral intentions toward integrating artificial intelligence into life sciences teaching. Despite the growing influence of AI in education, there is limited understanding of the factors affecting teachers’ willingness to integrate AI into life sciences teaching. These factors could inform policy-making and educational practice for AI adoption in the life sciences teaching. The current research aimed to identify key determinants influencing teachers’ behavioral intentions to adopt AI in life sciences teaching. The research followed a qualitative approach involving semi-structured interviews with 10 purposively selected pre-service life sciences teachers in South Africa. Thematic analysis was employed to analyze the data. The findings reveal that behavioral intentions are shaped by multiple factors within the framework of the Theory of Planned Behavior. Attitudes toward AI integration in life sciences education included themes such as pedagogical benefits, practical limitations, and philosophical concerns. Behavioral beliefs encompassed the advantages and disadvantages of AI adoption. Subjective norms highlighted inter-generational differences, administrative issues, stakeholder roles, and resource constraints. Normative beliefs included organizational authority, peer influence, parental concerns, and policy funding. The findings have important implications for policy and practice, highlighting the need for targeted training and resource allocation for effective AI integration in life sciences education.
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DOI: 10.1007/s41979-024-00128-x
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