Exploring School Leadership’s Influence on Student Achievement: Machine Learning insights from Missouri’s Largest Teacher Evaluation System

• In Event: AERA Roundtable Session Saturday 7:45 am
  In Roundtable Session: Examining Leadership's Direct and Indirect Effects on Student Outcomes

Abstract

This exploratory study utilizes machine learning methods to investigate relationships between school leadership practices and student achievement using operational data from more than 400 Missouri schools. Principal classroom observations, feedback sentiment, leadership efficacy, and contextual school factors were analyzed to predict student proficiency rates in math and ELA. Instructional leadership efficacy and observation scores positively correlated with student outcomes, whereas managerial efficacy showed a negative relationship. Surprisingly, feedback sentiment and quantity of observations did not significantly influence achievement suggesting that the quantity of observation visits and feedback loaded with superficial sentiments are not sufficient to promote teaching and learning outcomes. Results emphasize prioritizing instructional leadership training and actionable feedback mechanisms.

Authors

• Xintong Li, University of Missouri

• Thomas Hairston, University of Missouri