EAGER: Early Stage Research on Automatically Identifying Instructional Moves in Mathematics

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This is an Early-concept Grant for Exploratory Research research project to develop automated tools to aid in the development of mathematics teaching expertise in preservice teachers. Current research on preservice mathematics teacher instruction relies on observing preservice teachers interacting with students and recording their mathematical interactions to provide guidance and advice as how the preservice teachers can improve their teaching. This research requires highly trained observers and highly trained analysts to record and interpret the student teacher verbal interactions in order to give teachers feed back in how to improve their instruction. The aim of this project is to automate the observation, recording, and interpretation of student-teacher interactions. This would result in more effective research on instructional strategies for the preservice teachers and ultimately lead to changes in teacher professional development when feedback only available in research environments becomes feasible for all preservice teacher professional development. The project will use as an initial basis the observation toolkit Accountablity Talk for providing teachers with both formative and summative feedback on their instruction. Automatic speech recognition and natural language technologies will be used to record and interpret student teacher verbal interactions. The results of this research have the potential to democratize preservice mathematics teacher professional development and, over time, provide insight into teacher learning that can result in restructuring teacher learning environment to make them more effective in developing high quality mathematics teachers.