TY - JOUR
T1 - Exploratory factor analysis of approaches to teaching inventory (ATI)
T2 - 2020 ASEE Virtual Annual Conference, ASEE 2020
AU - Glassmeyer, Kristi
AU - Ross, Lydia
AU - Judson, Eugene
AU - Krause, Stephen J.
AU - Mayled, Lindy Hamilton
N1 - Funding Information: The authors gratefully acknowledge support of this work by the National Science Foundation under Grant No. 1524527.
PY - 2020/6/22
Y1 - 2020/6/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85095721992&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85095721992&partnerID=8YFLogxK
M3 - Conference article
SN - 2153-5965
VL - 2020-June
JO - ASEE Annual Conference and Exposition, Conference Proceedings
JF - ASEE Annual Conference and Exposition, Conference Proceedings
M1 - 681
Y2 - 22 June 2020 through 26 June 2020
ER -