Longitudinal associations between learning assistants and instructor effectiveness

TL;DR

This study investigates how instructor experience and use of Learning Assistants (LAs) influence student learning in college physics, revealing that LAs help maintain instructor effectiveness over time.

Contribution

It provides the first longitudinal analysis showing that LAs help sustain instructor effectiveness as they gain teaching experience.

Findings

Instructor effectiveness declines with experience without LAs.

LA-supported environments prevent decline in instructor effectiveness.

Data from 4,365 students across 93 courses analyzed.

Abstract

A central goal of the Learning Assistant (LA) model is to improve students' learning of science through the transformation of instructor practices. There is minimal existing research on the impact of college physics instructor experiences on their effectiveness. To investigate the association between college introductory physics instructors' experiences with and without LAs and student learning, we drew on data from the Learning About STEM Student Outcomes (LASSO) database. The LASSO database provided us with student-level data (concept inventory scores and demographic data) for 4,365 students and course-level data (instructor experience and course features) for the students' 93 mechanics courses. We performed Hierarchical Multiple Imputation to impute missing data and Hierarchical Linear Modeling to nest students within courses when modeling the associations between instructor experience and student learning. Our models predict that instructors' effectiveness decreases as they gain experience teaching without LAs. However, LA supported environments appear to remediate this decline in effectiveness as instructor effectiveness is maintained while they gain experience teaching with LAs.