  This preliminary study explores the integration of GPT-4 Vision (GPT-4V)
technology into teacher analytics, focusing on its applicability in
observational assessment to enhance reflective teaching practice. This research
is grounded in developing a Video-based Automatic Assessment System (VidAAS)
empowered by GPT-4V. Our approach aims to revolutionize teachers' assessment of
students' practices by leveraging Generative Artificial Intelligence (GenAI) to
offer detailed insights into classroom dynamics. Our research methodology
encompasses a comprehensive literature review, prototype development of the
VidAAS, and usability testing with in-service teachers. The study findings
provide future research avenues for VidAAS design, implementation, and
integration in teacher analytics, underscoring the potential of GPT-4V to
provide real-time, scalable feedback and a deeper understanding of the
classroom.
