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Interdisciplinary STEM education is a pedagogical approach that allows students to understand the interconnectedness of the disciplines of STEM. The interdisciplinary approach introduces problem-based learning, cooperative learning, expands problem-solving skills, and introduces students to the use of engineering design. Tinkercad is a visual computing tool that models mathematical and scientific concepts and support interdisciplinary STEM learning and experiences. In this session, participants will explore Tinkercad in the context of middle school curriculum. Free, accessible lessons that highlight the use of Tinkercad in the middle school classroom will be shared from our project. Participants will explore the gravity feature and ways to use this feature to explore mathematical and scientific concepts. 

Artificial intelligence is impacting society on a very large scale and should be included in K-12 educational content in some capacity to provide meaningful STEM experiences. Computer vision (a field of research that heavily leverages artificial intelligence) was emphasized in professional development for in-service teachers. The teachers received two to three weeks of training across two states (Arizona and Georgia) that emphasized image processing, computer vision, and machine learning using visual media. Personal Construct Theory (Kelly, 1955) was used to map changes in thinking using hierarchical cluster analysis. The research question was: How did in-service teachers' thinking regarding artificial intelligence change after partaking in remote professional development emphasizing computer vision? Dendrograms and descriptive statistics showed changes in thinking for in-service teachers in relation to artificial intelligence. There were four clusters in both the pre- and post-professional development dendrograms, but constructs shifted within clusters. Implications for practice and research are discussed. 

For decades, the use of computer vision as a component of STEM learning has been encouraged at all levels of education—from K-12 to the university levels. A program was developed to support in-service teachers’ development of computer vision. Professional development was provided to middle school teachers while middle school students also attended a summer camp on computer vision. Our research question was: After in-service teachers engaged in artificial intelligence professional development emphasizing computer vision, how did their perceptions of computer vision change? Personal Construct Theory (Kelly, 1955) was used as our methodology. Pairwise comparisons yielded constructs administered in the form of repertory grids. Hierarchical cluster analysis was performed and clusters were identified. Results showed that in-service teachers’ perspectives of computer vision changed after engaging in computer vision-based professional development. 

Artificial intelligence is a continually growing field that should be part of the educational process. Middle school teachers received two- to three-weeks of training across two states that emphasized image processing and machine learning using visual media. Personal Construct Theory (Kelly, 1955) was used to explore what changes in thinking occurred in relation to artificial intelligence. Dendrograms and descriptive statistics showed changes in thinking in relation to artificial intelligence. The dendrograms indicated shifts in constructs across the clusters. 

Artificial intelligence is impacting society on a very large scale and should be included in K-12 educational content in some capacity to provide meaningful STEM experiences. Computer vision (a field of research that heavily leverages artificial intelligence) was emphasized in professional development for in-service teachers. The teachers received two to three weeks of training across two states (Arizona and Georgia) that emphasized image processing, computer vision, and machine learning using visual media. Personal Construct Theory (Kelly, 1955) was used to map changes in thinking using hierarchical cluster analysis. The research question was: How did in-service teachers’ thinking regarding artificial intelligence change after partaking in remote professional development emphasizing computer vision? Dendrograms and descriptive statistics showed changes in thinking for in-service teachers in relation to artificial intelligence. There were four clusters in both the pre- and post-professional development dendrograms, but constructs shifted within clusters. Implications for practice and research are discussed.