Propelling Teacher Professional Development Through FAAST Feedback on Student Epistemic Views

Supported by: TIER-Ed Pilot Projects Program ($15,000)
PIs: Stina Krist (C&I), Eric Kuo (Physics), & Joshua Rosenberg (TPTE, University of Tennessee Knoxville)
Student Research Assistants: Kevin Hall (PhD, C&I), Nolan Weinlader (BA, CS, University of PIttsburgh), & Cameron Schwing (MA, Biology and C&I)

​This project proposes to implement a feedback system for formative, automated assessment of student thinking (FAAST) and to use this feedback to fuel teacher professional development. The FAAST feedback system uses a blend of machine-learning techniques and human-driven inductive coding to provide immediate feedback to students and teachers on classroom-level patterns in thinking. In phase 1, we propose to continue development on a FAAST feedback system designed to categorize students’ epistemic views in science around one particular issue: How much a scientific explanation should be specific to particular phenomena or general across different phenomena. In phase 2, we will use these FAAST feedback results to prompt teacher reflection around epistemic learning objectives in science. 

We have currently completed data collection for this project and are working on publications. Stay tuned!

Presentations:
​TIER-Ed Community Meeting. April 22, 2021. "Propelling teacher professional development through FAAST feedback on students’ epistemic views"