Exploring the Hedonic and Eudaimonic Motivations of Teachers for Pursuing Graduate Studies

• Published in: The Asia-Pacific education researcher 2022-04, Vol.31 (2), p.105-122
• Main Authors: Ramirez, Antonio, Himang, Celbert, Selerio, Egberto, Manalastas, Rebecca, Himang, Melanie, Giango, Wilma, Tenerife, Perla, Ocampo, Lanndon
• Format: Article
• Language: English
• Subjects: Academic degrees; Cluster analysis; Education; Educational Policy and Politics; Graduate Students; Graduate studies; Graduate Study; International and Comparative Education; Learning and Instruction; Motivation; Multivariate Analysis; Predictor Variables; Regular Article; Sociology of Education; Statistical Analysis; Teacher education; Teacher Education Programs; Teacher Motivation; Well Being
• ISSN: 0119-5646; 2243-7908
• DOI: 10.1007/s40299-020-00542-w

Alongside the current demand for advanced degrees, teachers are often compelled with the professional duty to study further. Since motivation is a critical concept in understanding the participation of these individuals in pursuing advanced learning, this exploratory research aims to provide a deeper understanding of the motivational dynamics of the graduate students of education (GSEs) through the hedonic and eudaimonic lenses, which is a relatively new setting for this idea. The self-determination theory juxtaposed this in a simple query about whether graduate students are studying for pleasure, virtue, or both. The method in this work is described in two parts. First, the hedonic and eudaimonic motivation of 594 samples of GSEs was measured through a developed Integrated Hedonic–Eudaimonic Motivation Scale. Second, cluster analysis of the survey results was employed with K-means clustering and ANOVA to determine the distinct groups of GSEs and their characteristics. The findings of this study suggest that GSEs, in general, have a high level of both hedonic and eudaimonic motivation and, thus, classified under the “flourishing” typology. Based on their characteristics, the cluster analysis generated three distinct clusters: passionate cluster, progressive cluster, and struggling cluster. Using ANOVA, the following variables were identified as the major contributors to the distinction of the three clusters: hedonic motivation, age, master’s degree major, doctor’s degree institution, doctor’s degree program, sources of funding, the support given to parents, and net income.