Researchers in educational psychology have researched Teacher Self-Concept (TSC) and Teacher Efficacy (TE) as two main predictors predicting burnout. Guided by a model developed by Zhu, Liu, Fu, Yang, Zhang & Shi (2018), the researchers aimed at building a model involving TSC, TE, and three components of burnout; Emotional Exhaustion (EE), Depersonalization (DP), and Reduced Personal Accomplishment (RPA) through Structural Equation Modeling (SEM). The researchers investigated predicting factors of burnout by reporting TSC and TE that might directly affect the components and examine the probability of TE to become a mediator of the correlation between TSC and burnout. This research also examined whether the difference emerges constantly among demographic information (gender and teaching experience) regarding all involved variables. A sample of 876 teachers across three Indonesian provinces completed a printed form of questionnaires. Some statistical procedures namely Content Validity Index (CVI), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), Covariance-Based Structural Equation Modeling (CB-SEM), and t-test were conducted. Findings informed that the model is valid and reliable. TSC could directly affect EE, DE, and RPA, as well as indirectly influence them mediated by TE. Besides, TE is also reported to have significant relationships with EE, DE, and RPA. No significant differences in terms of age and teaching experiences emerge, except for EE.
This study was conducted to investigate the perspectives of sports science students on factors affecting distance learning in the setting of Indonesian higher education institutions (HEIs). This study proposed an extended technology acceptance model (TAM) with eight variables; experience, enjoyment, self-efficacy, perceived ease of use, perceived usefulness, attitude, intention to use, and actual use. An online survey was used to collect data from 1291 respondents. The structural model was examined through the partial least square structural equation modeling (PLS-SEM). The multi-group analysis (MGA) was conducted to understand the role of geographical areas in moderating all hypothetical relationships. The findings show that the respondents were not excited about online learning due to weak means (below 3) for most items of five variables; enjoyment, perceived ease of use, perceived usefulness, attitude, and intention to use. All relationships were supported except the relationship between experience and perceived usefulness. The strongest significant relationship emerged between intention to use and actual use. Meanwhile, the least significant relationship was found between self-efficacy and perceived usefulness. Three out of 12 hypotheses were confirmed regarding the differences of geographical areas (rural and urban) regarding all relationship paths. The findings add to a deeper understanding of the acceptability of distance learning during pandemics like COVID-19.