@article{article_1458322, title={Can Machine Learning Be Taught to Pre-service Teachers in the STEM Fields?}, journal={Instructional Technology and Lifelong Learning}, volume={5}, pages={214–236}, year={2024}, DOI={10.52911/itall.1458322}, author={Özen, Esma Nur and Polat, Elif and Samur, Yavuz}, keywords={Machine learning, machine learning instruction, STEM, artificial intelligence, preservice teachers}, abstract={Machine Learning (ML) trainings provide students with 21st century skills and enable students to find solutions to their own problems. The purpose of this study is to design, implement, and evaluate ML training for pre-service teachers in the STEM field in order to contribute to the future workforce in the field of computer science. The participants of the study were 74 pre-service teachers who are studying in the departments of Computer Education and Instructional Technology (CEIT), science education, and mathematics education (STEM fields) at a state university in Istanbul. Convenience sampling method was used in the study. In the research, a single-group pre-test-post-test weak quasi-experimental design was used by using the quantitative method in order to evaluate the training by giving ML training. The training was implemented on the online platform for 3 hours for 8 weeks. "Pretest - Posttest Achievement Test," "Online Student Engagement Scale," "Moodle Activity Data," “Demographic Form,” and "Attendance Forms" were used to collect data. There is a significant difference between the pre-test and post-test averages in favor of the post-test. There is a significant difference between the pretest and posttest scores according to the departments. It has been concluded that the provided training is effective in the success of pre-service teachers. It can be suggested to offer training to different branches and to select participants from elementary and middle school students.}, number={2}, publisher={Mustafa SARITEPECİ}