What motivates future teachers? The influence of Artificial Intelligence on student teachers’ career choice

Abstract

Artificial Intelligence in Education (AIEd) is reshaping not only the educational landscape but also potentially influencing the motivations of aspiring teachers. This paper explores whether considerations related to AIEd play a role in student teachers' decision to become teachers. For this aim, the study introduces a new AI subscale within the (D)FIT-Choice scale's Social Utility Value (SUV) factor and validates its effectiveness with a sample of 183 student teachers. Descriptive statistics reveal high mean scores for traditional motivators like Intrinsic Value Teaching, while AI-related factors, although considered, exhibit lower influence. A noticeable disconnection exists between digital motivations and the aspiration to shape the future, suggesting a potential gap in student teachers' understanding of digitalization's future impact. An extreme group analysis reveals a subset of student teachers who significantly consider AI. This group also gives value to Job Security and Make a Social Contribution, suggesting an awareness of AI's societal and professional impacts. Based on these findings, it is recommended to put a focus on teacher education programs to ensure student teachers' understanding of the impact of AI on education and society.