Determinants of Adult Education and Training Participation in the United States: A Machine Learning Approach

Abstract

In response to recent shifts in the global economy, there has been a growing academic interest in adult education and training (AET), enabling adults to meet the ever-changing demands of the workforce. However, empirical findings offer nuanced evidence on the most influential factors among various aspects. This study aims to reexamine the previously highlighted determinants of job-related AET participation using the random forest classifiers technique. The data is drawn from the 2017 U.S. Program for the International Assessment of Adult Competencies, where we selected 1,334 respondents with work experience in the last 12 months. Our findings suggest that age and skills use at work were found to be the most important factors for formal AET, whereas skills use at work and organization size were the most significant factors for nonformal AET. Our results emphasize the critical role of skills utilization and organizational support in working adults’ participation in AET.