Examining Metamotivational Awareness as a Component of Optimal Strategy Use

• In Event: Exploring the Optimal Use of Motivation Regulation Strategies for Academic Success

Abstract

Aims/Background
Prior research on motivation regulation (MR) has focused on examining which MR strategies are predictive of student behaviors/outcomes (see Fong et al., 2024). However, the optimal use of MR strategies is not simply about selecting the best strategy, it is also about noticing motivational obstacles and knowing when it may be necessary to implement one or more MR strategies. Drawing on Miele and Scholer’s (2018) metamotivational framework, we posit that optimal strategy use begins with attending to metamotivational feelings that signal potential problems with one’s current motivational state (e.g., boredom). In the model that we developed (Figure 1), students’ awareness of their metamotivational feelings (combined with the belief that motivation is modifiable) positively influences their achievement and well-being via their use of MR and emotion regulation (ER) strategies.
We initially tested this model in a previous study (Authors, 2025) by developing a questionnaire that assesses several dimensions of students’ metamotivational awareness (see Table 1) and then examining the extent to which the subscales correlated with various measures of self-regulation and well-being. In the present study, we administered the questionnaire to a substantially larger sample of students and examined its factor structure and concurrent validity using SEM.
Method
The full metamotivation questionnaire includes six subscales. Three of these measure students’ attention to the “bodily sensations, feelings, and emotions” associated with their motivation. Two subscales assess students’ efficacy/agency for identifying and modifying motivational states. The final subscale did not function as intended in the initial study and was not a focus of the present analyses.
For the present study, we administered our measure to 1,203 students across three Chilean universities. The final sample consisted of 1,048 participants after exclusions (59.5% female; Mage = 19.9). The full survey included measures of MR strategy use, ER dysfunction, and well-being (see Table 2), as well as several measures that were not a focus of the present analyses.
Results/Discussion
To examine the measure’s dimensionality, we conducted a series of CFAs. The correlated-factors models indicated high correlations between some subscales. Thus, we also examined bifactor models that accounted for the conceptual overlap between subscales. Here we present a bifactor S-1 model (see Eid et al., 2017) with two general factors and two specific factors (Figure 2); the items from one of the primary subscales did not load well onto either general factor and were excluded. One general factor represents students’ ability to direct attention to their metamotivational feelings and the other represents the perceived utility of detecting metamotivational feelings. In a subsequent CFA, we included this bifactor representation of our measure in a model that also included bifactor representations of the MR strategy and ER dysfunction measures, as well as a single well-being factor. The results showed that the two general metamotivational factors were correlated with each other, as well as with all of the other constructs in the model (Figure 3). These results suggest that directing attention to one’s metamotivational feelings may be an important aspect of using motivation regulation strategies in an optimal manner.

Authors

• Erika Alvarez-Atencio, Universidad Complutense de Madrid

• David B. Miele, Boston College

• Jesús M. Alvarado, Universidad Complutense de Madrid