A Measurement Invariance Analysis of the Motivation to Teach Computer Science (MTCS) Scale among Female and Male Educators

Understanding teachers' motivation to teach computer science (CS) plays a significant role in recruiting, supporting, and retaining CS teachers. Prior literature has identified the existence of differences among female and male teachers in terms of their motivation to teach. The goal of the current study was to examine the psychometric properties and measurement invariance of the Revised Motivation to Teach Computer Science (MTCS_R) scale between female and male groups. The MTCS_R scale is a shortened, more concise version of the original Motivation to Teach Computer Science (MTCS) scale, which measures teachers' motivation to teach CS on a continuum from external to internal motivation. We used the MTCS_R scale to collect survey data during 2022 and 2023 from 310 educators enrolled in a professional learning course designed to prepare teachers for a CS certification exam. We then conducted a confirmatory factor analysis with all survey respondents (N=310) and further examined measurement invariance among those who disclosed their gender (N=298). Results from the confirmatory factor analysis suggested satisfactory psychometric properties of the MTCS_R scale. In addition, we identified strong evidence to support the configural, metric, and scalar invariance across the gender groups, confirming that the MTCS_R scale is a valid measure of motivation to teach CS for both females and males. This study represents a significant advancement in the measurement of motivation to teach CS. Implications of using this instrument to assess teachers' motivation in CS teaching and further refinement of the instrument are discussed.