DOI: 10.3390/educsci14040417 ISSN: 2227-7102

The Impact of Teachable Machine on Middle School Teachers’ Perceptions of Science Lessons after Professional Development

Terri L. Kurz, Suren Jayasuriya, Kimberlee Swisher, John Mativo, Ramana Pidaparti, Dawn T. Robinson
  • Public Administration
  • Developmental and Educational Psychology
  • Education
  • Computer Science Applications
  • Computer Science (miscellaneous)
  • Physical Therapy, Sports Therapy and Rehabilitation

Technological advances in computer vision and machine learning image and audio classification will continue to improve and evolve. Despite their prevalence, teachers feel ill-prepared to use these technologies to support their students’ learning. To address this, in-service middle school teachers participated in professional development, and middle school students participated in summer camp experiences that included the use of Google’s Teachable Machine, an easy-to-use interface for training machine learning classification models. An overview of Teachable Machine is provided. As well, lessons that highlight the use of Teachable Machine in middle school science are explained. Framed within Personal Construct Theory, an analysis of the impact of the professional development on middle school teachers’ perceptions (n = 17) of science lessons and activities is provided. Implications for future practice and future research are described.

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