Not all engaged students are alike: patterns of engagement and burnout among elementary students using a person-centered approach

Autor: Dong Yang, Zhenyu Cai, Chaoyi Wang, Chen Zhang, Peng Chen, Ronghuai Huang
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: BMC Psychology, Vol 11, Iss 1, Pp 1-12 (2023)
Druh dokumentu: article
ISSN: 2050-7283
DOI: 10.1186/s40359-023-01071-z
Popis: Abstract Due to its potential to address low achievement, high dropout rates, and misbehavior among students, school engagement has become an important topic in contemporary developmental psychology and educational research. Although there is a wealth of literature on the causes and effects of student engagement, the current understanding of how student engagement varies in response to different teaching styles is limited. This study examined the engagement and burnout profiles of elementary school pupils (N = 798; 51% females; Mage = 11.54, SDage = 0.72) and the interactions between those profiles, students’ characteristics and their perceptions of instructional behaviors (e.g., supporting criticism, suppressing criticism & independent viewpoints, intruding). Latent profile analysis revealed five types of profiles: moderately burned out, slightly burned out, moderately engaged, highly engaged, and highly burned out. Follow-up logistic regression analysis found that students clustered into engagement groups were likely to report higher autonomy support from teachers, especially when teachers permit criticism and independent thinking from students. In contrast, students clustered into burned out profiles were more likely to rate teacher strategies as autonomy suppressive. This became more obvious when instructors imposed meaningless and uninteresting activities. Taken together, this study indicated that autonomy-supportive teaching behaviors are pivotal in understanding student engagement and school burnout. The significance of the findings was addressed, along with implications and limitations.
Databáze: Directory of Open Access Journals