Exploratory factor analysis of approaches to teaching inventory (ATI): Use in an evidence-based faculty development program for promoting active learning pedagogical strategies

Kristi Glassmeyer, Lydia Ross, Eugene Judson, Stephen J. Krause, Lindy Hamilton Mayled

Research output: Contribution to journalConference articlepeer-review

Abstract

While surveys/inventories can be very informative for researchers to better understand latent constructs within social science research, critical analysis of these instruments is essential when they are used outside of their initial contexts. This complete research paper reports on an exploratory factor analysis of the Approaches to Teaching Inventory (ATI) as adapted for use in measuring relational change of engineering faculty's (N=65) instructional intent and teaching strategies in their undergraduate engineering classes. Parallel analysis of data collected during the JTFD professional development program, a National Science Foundation (NSF) funded project, suggested an underlying structure of two or three factors. While the survey creators, Trigwell and Prosser [1], claim a two-factor structure, each with two underlying subscales, in the ATI, exploratory factor analyses global model fit suggested a three-factor model to be a better fit. Interpretation of loading patterns and magnitudes indicated concerns with both two- and three- factor models. Although the small sample size presents a limitation to the findings, critical analysis of the ATI's use in other disciplines should be considered.

Original languageEnglish (US)
Article number681
JournalASEE Annual Conference and Exposition, Conference Proceedings
Volume2020-June
StatePublished - Jun 22 2020
Event2020 ASEE Virtual Annual Conference, ASEE 2020 - Virtual, Online
Duration: Jun 22 2020Jun 26 2020

ASJC Scopus subject areas

  • Engineering(all)

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