Measuring Pre-Service Teachers' Attitudes and Experiences with Artificial Intelligence: A Three-Year Longitudinal Analysis
Le résumé fourni par la source
The advent of generative artificial intelligence is fundamentally transforming the educational environment, thereby placing new demands on the quality and content of undergraduate training for future teachers. This study presents the results of a longitudinal research project, whose primary objective was to analyze the dynamics of change in the theoretical understanding, practical experiences, and normative attitudes of pre-service teachers toward the integration of AI into education. Quantitative data analysis was conducted on a research sample of 1,432 respondents using nonparametric statistical tests. The results identified a three-phase cycle of technology adoption: from initial ethical caution, through a phase of massive saturation and technological optimism, to a period of pragmatic stabilization and institutional correction, evidenced by a significant decline in reported AI use for academic purposes. The comparative analysis revealed a marked attitudinal dichotomy conditioned by the study mode—while full-time students have long dominated as proactive digital pragmatists, part-time students maintain a critical distance and more strongly articulate demands for stricter regulation. A key finding of the study is the identification of an intergenerational competence-value paradox: while incoming freshmen demonstrate the highest level of practical experience, students in their final years approach AI more cautiously, yet reflect all the more intensely on the deficit in their own methodological competencies and call for formal didactic training with high statistical significance. The study concludes by emphasizing the necessity of updating curricula and transitioning from restrictive institutional policies to the proactive development of comprehensive and ethically grounded AI literacy among future educators.
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