Abstract Computer vision is the automated analysis of visual imagery by computer algorithms that includes, but not limited to object detection and identification, three-dimensional shape estimation, material recognition, and segmentation. The intervention consisted of two to three weeks of professional development that emphasized computer vision technologies with middle school teachers from Title I schools/districts in the states of Arizona and Georgia. Each location trained six in-service teachers. The questions answered through this research were: After in-service teachers engage in professional development emphasizing computer vision: (a) how do their perceptions of computer vision change? (b) how do their perceptions of human vision change? And (c) what are the differences between their perceptions of computer vision and human vision? Personal Construct Theory (Kelly, 1955) was used to explore our research questions. Elements ( n = 2; computer vision and human vision) were defined and pairwise comparisons yielded constructs ( n = 18) 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 with construct shifts within all four dendrograms that contained between one to eight constructs; all clusters yielded mean increases. Perspectives of human vision stayed relatively consistent across two clusters. The element human vision had a 6% ( n = 1) shift in cluster membership, and the element computer vision generated a 72% ( n = 13) change in the number of constructs that shifted clusters. Comparisons of computer vision and human vision indicated that in-service teachers had richer perspectives of computer vision after professional development. The significance of this study rests in its contribution to the limited research on computer vision in teacher education. The results show that a relatively short (two to three weeks) professional development experience can have an impact on in-service teachers’ perspectives of computer vision classroom use.
Kurz et al. (Fri,) studied this question.