Developing authentic happiness: Growth curve models to assess lifelong happiness

COVID-19's impact on learning processes in Australian university students

The novel coronavirus SARS-CoV-2 (COVID-19) has accentuated the role and interplay of numerous educational factors, inviting pedagogical research concerning online education. Using self-determination theory's basic psychological needs and fundamental learning theories, identified educational factors were integrated into three pathways: (1) autonomy, technology acceptance, and self-regulation of learning; (2) relatedness, authentic happiness, and a classroom community; and (3) competency, harmonious passion, and trait conscientiousness. This study extends educational research by elucidating the relationships between psychological need fulfilment, educational factors, and students' expectations of their future grades during the impact of COVID-19. Australian university students (N = 226, 77% female) completed questionnaires assessing their experience of home isolation, factors of each hypothesised pathway, and their expected grades. Structural equation modelling revealed that higher need fulfilment significantly predicted engagement in educational factors and that educational factors are complexly interrelated, providing resilience, motivation, and the mechanisms that facilitate learning. Most importantly, relatedness between academics and students positively influenced all learning pathways. Reciprocal determinism demonstrated the most substantial association with expected grades, and new insight was gained into the interrelationships of passion, trait conscientiousness, and self-regulation of learning.

Leisure Factors Predicting the Happiness of Self-Employed Workers in South Korea

South Korea’s employment status is characterized by a high rate of self-employment and many small-scale self-employed businesses with no employees. This study explored leisure factors relating to self-employed individuals’ subjective happiness based on data from the 2019 National Leisure Activity Survey. The extracted data (N = 2343) were analyzed using descriptive statistics, t-test, ANOVA, Pearson’s correlation coefficient, Kendall’s τ_b coefficient, Eta correlation coefficient, phi coefficient, and Cramer’s V. And a three-step hierarchical regression analysis was performed to identify multidimensional variables that predict happiness more effectively. In Model 3, which additionally inserted positive and intrinsic factors into Model 2, the explanatory power was significantly increased. The predictors of subjective happiness among self-employed people identified in the final regression model were high economic status (β = 0.05), perceived health status (β = 0.32), financial constraints (β = −0.09), leisure recognition (β = 0.20), and work–life balance (leisure-oriented β = 0.09; work-oriented β = −0.13). This study’s findings will contribute to the establishment of basic data, to prepare empirical measures to improve self-employed individuals’ quality of life.