Eager: Inq-Blotter: Designing Supports for Teachers' Real Time Instruction

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Teachers are often frustrated because large-scale assessment data are neither timely nor adequate to understand students' needs so they can improve science instruction. What is missing are diagnostic, real-time tools to support teachers' practices and, in turn, students' learning. To address this challenge, the principal investigators will utilize Inq-Blotter, a dashboard, that lets teachers know who needs the most help and on which inquiry practices. Inq-Blotter will be integrated with Inq-ITS (Inquiry Intelligent Tutoring System) for middle school science, a learning environment in which students "show what they know" by conducting inquiry within virtual labs. Early data on dashboards for other domains (e.g. Mathematics) are promising, and pilot data collected with Inq-Blotter also shows promise in that it supports teachers' assessment practices. This project aims to develop Inq-ITS within virtual laboratories and to develop teacher professional development materials for supporting teachers content knowledge or inquiry practices.Specifically, the principal investigators will develop instructional scripts, with which teachers can initiate class discussion or provide 1:1 support to students. They will conduct analyses to evaluate if the discourse afforded by the scripts helps to foster students' inquiry practices on their next inquiry activity (compared to control teachers who will not be provided instructional scripts). Important to the topic of classroom orchestration, the principal investigators will analyze teachers' discourse to study how alerting and scripts supports students' inquiry. The project combines techniques to measure students' inquiry practices at scale to study how teachers interact with their students when provided real-time alerts. In doing so, it can realize teachers' needs for formative assessments for science practices as well as students' needs' for learning inquiry. It will provide principles that can guide the design and development of alerting tools for teachers by advancing the stateof-the-art using a technologically-based approach to close the formative assessment loop for an ill-defined domain, namely, science inquiry. This work contributes to the well-acknowledged need to better support teachers' data use in classrooms, as well as support students in STEM learning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.