Income and happiness in teaching: Understanding teachers’ well-being using regression model and K-means clustering

Abstract

The happiness of a teacher depends on some factors in the workplace including income and other benefits. This research paper examines the relationship between income inequality and happiness among college teachers. The study also aims to identify distinct clusters based on net income and happiness levels and explore their economic implications. The analysis involved secondary data from a current published study which were gathered through an adapted questionnaire from literature involving 101 college teachers. The gathered data were computed through statistical measures, regression analysis, and the K-means clustering method to make descriptions and draw conclusions. The results showed that, on average, faculty members are "happy" and with income relatively “low” based on Philippine standards. The regression analysis revealed that income and happiness are directly related but not significant association. Plus, the K-means clustering findings highlight the interconnections of income and happiness, with variations across clusters. Based on the significant Silhouette score of 0.631, the optimal number of clusters via K-means is 3. The three clusters represent the low, medium, and high levels of teachers' income and happiness. Cluster 1 represents few faculty with economically and emotionally well-off individuals, Cluster 2 depicts dominant faculty with lower income with high levels of happiness, and Cluster 3 faces challenges with lower income and happiness. Conclusively, income does not always influence the happiness of a college teacher. Hence, the research article strongly suggests that to improve the well-being of college teachers which is vital in quality teaching, the school heads must focus on professional development opportunities and incentives that compensate their efforts.