Literaturnachweis - Detailanzeige
Autor/inn/en | Tang, Jingwan; Zhou, Xiaofei; Wan, Xiaoyu; Daley, Michael; Bai, Zhen |
---|---|
Titel | ML4STEM Professional Development Program: Enriching K-12 STEM Teaching with Machine Learning |
Quelle | In: International Journal of Artificial Intelligence in Education, 33 (2023) 1, S.185-224 (40 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Zusatzinformation | ORCID (Bai, Zhen) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1560-4292 |
DOI | 10.1007/s40593-022-00292-4 |
Schlagwörter | STEM Education; Artificial Intelligence; Elementary School Teachers; Secondary School Teachers; Faculty Development; Technology Integration; Educational Innovation; Program Effectiveness; Teacher Attitudes |
Abstract | The advances of machine learning (ML) in scientific discovery (SD) reveal exciting opportunities to utilize it as a cross-cutting tool for inquiry-based learning in K-12 STEM classrooms. There are, however, limited efforts on providing teachers with sufficient knowledge and skills to integrate ML into teaching. Our study addresses this gap by proposing a professional development (PD) program named ML4STEM. Based on existing research on supporting teacher learning in innovative technology integration, ML4STEM is composed of Teachers-as-Learners and Teachers-as-Designers sessions. It integrates an accessible ML learning platform designed for students with limited math and computing skills. We implemented this PD program and evaluated its effectiveness with 18 K-12 STEM teachers. Findings confirm that ML4STEM successfully develops teachers' understanding of teaching STEM with ML as well as fosters positive attitudes toward applying the ML as an in-class teaching technology. Discussions on the implications of our findings from ML4STEM are provided for future PD researchers and designers. (As Provided). |
Anmerkungen | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |