Abstract
With teachers continuing to report challenges in classroom management and difficulties in implementing scientific inquiry, the current manner in which science practical work is conducted in schools suggests the need for added teacher support. In this regard, we can leverage computer vision to provide instructional support by relieving teachers of the need to carry out mundane observations and perform basic interpretations of student activity. However, to our knowledge, little is known about the noticing practices of teachers during practical work, and the support preferences of such a computer vision system have not been studied before. To this end, we recruited 17 science educators with different teaching expertise for a qualitative investigation into the noticing practices and support preferences of science teachers. Results revealed seven major categories and 36 minor categories of student activity that teachers typically observe, which enabled us to derive observation routines that can emulate quality teacher noticing for computer vision input. Our obtained list of observation categories represents a first-of-its-kind list which takes into account concrete noticing practices of science teachers and remains applicable across all types of practical tasks. From participants’ ranking of computer vision models, we further understood the type of computer vision output that teachers prefer for instructional support. To our best of knowledge, no prior research has examined the connection between teacher noticing and computer vision in such detail. Using these findings, we can then pursue the development of computer vision for instructional support in science practical work in an informed manner, taking into account the realities of science laboratories and proclivities of science teachers.
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The data that support the findings of this study are available from Harvard University and Nanyang Technological University, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. The data are, however, available from the authors upon reasonable request and with the permission of Harvard University and Nanyang Technological University.
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The sole author (Edwin Chng) contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Edwin Chng. The first and subsequent drafts of the manuscript were written by Edwin Chng. Edwin Chng read and approved the final manuscript.
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The survey, interviews, and methodology for this study were approved by Harvard University-Area Committee on the Use of Human Subjects (IRB22-1470) and Nanyang Technological University Institutional Review Board (IRB-2022–991).
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Chng, E. Designing Computer Vision Support for Science Practical Work: A Qualitative Investigation into the Noticing Practices and Support Preferences of Science Teachers. J Sci Educ Technol (2024). https://doi.org/10.1007/s10956-024-10116-w
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DOI: https://doi.org/10.1007/s10956-024-10116-w