Measuring fidelity of implementation of named active learning methods in physics

TL;DR

This study assesses how closely physics instructors' implementation of active learning methods matches high-fidelity models, revealing substantial variation in style but no clear link to student learning gains.

Contribution

It identifies critical components of active learning methods and evaluates implementation fidelity across diverse instructors, highlighting variation in operationalization.

Findings

Similar class time spent on critical components as high-fidelity models

Substantial variation in implementation styles among instructors

No clear correlation between fidelity and student learning gains

Abstract

Various active learning methods have been developed for introductory physics, and these methods are increasingly being adopted by instructors. However, instructors often do not implement these methods exactly as was originally intended by the developers, as they may face issues related to funding and institutional support for active learning and/or have different instructional contexts (e.g., student populations) and environments (e.g., physical classroom layouts) than the developers. Existing research does not sufficiently capture the range of variation in instructor implementation of established active learning methods, especially in comparison to high-fidelity implementations. In this study, we first identify the critical components (i.e., components without which the active learning method cannot be said to have been implemented) of three named active learning methods: SCALE-UP, ISLE, and Tutorials. We then evaluate the fidelity with which 18 different introductory physics instructors implement these methods by analyzing classroom observations and comparing the extent to which these broader implementations use each critical component in their classroom to high-fidelity implementations. We find across all three active learning methods that broader implementations spend similar amounts of class time on the critical components as high-fidelity implementations. At the same time, we observe substantial variation in the specific styles that broader implementers operationalize these critical components (e.g., doing a few long activities versus many short activities). Finally, we find no clear relationship between fidelity of implementation and student conceptual learning gains for our study's sample of instructors, providing preliminary evidence that different ways of implementing the critical components of active learning method may all effectively improve student understanding.