Current Practices in Instructional Decision Making for Teachers of Students With Extensive Support Needs (Poster 24)

• In Event: AERA Poster Session Four
  In Poster Session: What We Know: Evidence, Practices, and Needs in Special and Inclusive Education

Abstract

Data-based decision-making (DBDM) is a promising strategy to improve student academic outcomes with a substantial research base for whole-class instruction and tiered support models for students with disabilities. However, students with extensive support needs (ESN) are typically not included in this literature (Thurlow et al., 2020). The purpose of this mixed methods study is to explore how teachers of students with ESN use data in the context of academic instructional decision-making and what factors influence their decision-making. Over 400 teachers across nine states completed a survey on their data use and perceptions of data. Fourteen teachers participated in a follow-up interview. Results will inform future research in academic decision-making for teachers of students with ESN and potentially new DBDM models.

Authors

• Lindsay Ruhter, University of Kansas
  Presenting Author

• Meagan Karvonen, University of Kansas
  Presenting Author

• Amy Clark, University of Kansas
  Presenting Author