Exploring Artificial Intelligence Through Robotics and Machine Learning: Perceptions of Pre-Service Teachers, Elementary School Students, and In-Service Teachers

This study examined how educational robotics and machine learning activities contributed to the understanding of artificial intelligence (AI) among elementary school students, pre-service teachers, and practicing teachers. The intervention involved 1207 participants, including 1009 fifth-grade students, 93 practicing elementary school teachers, and 105 pre-service teachers. Participants engaged in a series of structured activities focused on educational robotics, visual block-based programming, and machine learning concepts. A pre-experimental design was employed to assess changes in understanding and to explore participants’ perceptions of the learning experience. Statistical analyses included Student’s t-tests, the Kruskal–Wallis H test, and Bonferroni-corrected post hoc comparisons. Results indicated pre–post gains in elementary school students’ understanding of machine learning, AI modeling processes, and fundamental computational concepts following participation in the intervention. Across the three groups, participants reported positive perceptions of the activities and recognized their value for learning about AI. Elementary school students reported higher motivation and stronger engagement in coding-related tasks, likely reflecting their previous experience with Scratch in school settings. Practicing teachers expressed a more interdisciplinary perspective on the educational applications of AI, whereas pre-service teachers demonstrated stronger conceptual understanding of the underlying principles. Overall, the findings suggest that educational robotics and machine learning activities are associated with positive learning experiences and observed gains in AI-related understanding. However, given the pre-experimental design without a control group or random assignment, the results should be interpreted as evidence of observed changes and participant perceptions rather than demonstrated effectiveness.