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Students’ multidimensional profiles of math engagement: Predictors and outcomes from a self‐system motivational perspective
Author(s) -
Miller Chyna J.,
Perera Harsha N.,
Maghsoudlou Alireza
Publication year - 2021
Publication title -
british journal of educational psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.557
H-Index - 95
eISSN - 2044-8279
pISSN - 0007-0998
DOI - 10.1111/bjep.12358
Subject(s) - generality , psychology , perspective (graphical) , student engagement , test (biology) , class (philosophy) , structural equation modeling , developmental psychology , cognition , academic achievement , social psychology , mathematics education , mathematics , statistics , geometry , paleontology , artificial intelligence , neuroscience , computer science , psychotherapist , biology
Background Math engagement research has been largely limited to examining the unique and additive relations of engagement dimensions with outcomes. However, an emerging perspective is that students may simultaneously invest varying degrees of their distinct energetic resources (e.g., cognitive vs. emotional) in their interactions with the math learning environment. Aims Adopting a person‐centred perspective, we examined unique latent subpopulations of adolescents’ multidimensional math engagement. Importantly, we did so while accounting for generality and specificity in engagement data, including general engagement and specific cognitive, emotional, and social engagement dimensions. Additionally, we examined students’ math self‐efficacy, outcome expectations, and gender as predictors, and math achievement indices as outcomes, of profile membership. Sample The sample comprised 400 Australian school students taking mandatory math classes. Methods Data on students’ multidimensional engagement, math self‐efficacy, math outcome expectations, and demographic characteristics were collected at the beginning of the academic semester. Standardized test scores and class grades were retrieved at the end of the semester. Results Latent profile analyses, based on preliminary bifactor exploratory structural equation models intended to tease apart generality from specificity in engagement data, revealed ‘Minimally Engaged’, ‘Emotionally Disengaged’, and ‘Moderately‐to‐Highly Engaged’ profiles. Additionally, math self‐efficacy, outcome expectations, and gender were found to predict the likelihood of profile membership. Finally, class grades, but not standardized test scores, were found to significantly differ across the profiles, accounting for prior achievement, gender, and grade level. Conclusions The findings replicate previous work that has shown profiles of student engagement and extend this work by (1) accounting for known generality and specificity in engagement data and (2) obtaining evidence for relations of profile membership with gender, self‐beliefs, and achievement.