The Motivation and Engagement Scale: Theoretical Framework, Psychometric Properties, and Applied Yields

Abstract

The Motivation and Engagement Wheel is a multidimensional conceptual framework that represents salient cognitive and behavioural dimensions relevant to motivation and engagement. The Wheel and its accompanying assessment tool—the Motivation and Engagement Scale (MES)—comprise eleven first‐order factors (under four higher‐order factors): self‐efficacy, valuing, and mastery orientation (adaptive cognition); planning, task management, and persistence (adaptive behaviour); anxiety, failure avoidance, and uncertain control (impeding/maladaptive cognition); and self‐handicapping and disengagement (maladaptive behaviour). We describe theoretical foundations of the MES, summarise corresponding forms of the MES for use in academic, work, sport, and music settings, and report on their psychometric properties in local and cross‐cultural settings. We then review MES research addressing substantive and applied issues, focusing on educational research (i.e., looking at use of the MES to explore the effects of gender, grade retention, delayed school entry, taking a gap year, and the role of the home on motivation and engagement). Through psychometric and substantive applications, it is proposed that this integrative approach to multidimensional motivation and engagement instrumentation has utility across diverse performance and cultural settings, educational levels, and academic subjects. As such, it can be considered a meaningful recent contribution to psycho‐educational measurement, research, theory, and practice.

Key words:

• engagement
• measurement
• motivation
• validity

Acknowledgement

The authors wish to express their gratitude for Reviewer and Editorial feedback and advice on this article.

Notes

1. In evaluating the fit of the data to alternative models in CFA, a range of goodness‐of‐fit indices were assessed. Following recommendations on establishing model fit (e.g., Marsh, Hau, & Wen, 2004), the Comparative Fit Index (CFI), the Non‐Normed Fit Index (NNFI), the Root Mean Square Error of Approximation (RMSEA), the χ² test statistic, and an evaluation of parameter estimates were used in the present research to assess model fit. The RMSEA index is less affected by sample size than the χ² test statistic, and values at or less than 0.08 and 0.05 are taken to reflect acceptable and excellent fit, respectively (see Marsh, Balla, & Hau, 1996; Yuan, 2005). The NNFI and CFI vary along a 0‐to‐1 continuum in which values at or greater than 0.90 and 0.95 are typically taken to reflect acceptable and excellent fit to the data, respectively (McDonald & Marsh, 1990). The CFI contains no penalty for a lack of parsimony so that improved fit due to the introduction of additional parameters may reflect capitalisation on chance, whereas the NNFI and RMSEA contain penalties for a lack of parsimony (Yuan, 2005).

2. It is important to note that evidence for between‐group invariance in key measurement parameters (correlations, uniquenesses, and especially, factor loadings) is a basic prerequisite in validly performing mean comparisons between groups (Marsh & Hau, 2007). Although Martin and Hau (2010) found congruencies in motivation and engagement factors between their Australian and Hong Kong samples, they revealed differences “of degree,” identifying mean‐level differences between the two cultural groups on some factors in the Wheel. Consistent with the prerequisite in conducting mean comparisons (e.g., Marsh & Hau, 2007), the identified differences were regarded “trustworthy” as measurement properties between the two groups were invariant.