There are low participation rates and low literacy and numeracy gains for students in federally funded adult education programs, resulting in students not gaining the academic skills they need to improve their workforce employability. The purpose of this nonexperimental quantitative correlational study was to determine if U.S. jurisdiction…

Higher education institutions need to be responsible for understanding the characteristics and qualities of learners who decide to take courses with them; online vs. on-campus and what it takes to keep them learning at an institution. Taking heed and modifying structures, communications, and services will help learners and institutions in this…

Effective personalization of education requires knowing how each student will perform under certain conditions, given their specific characteristics. Thus, the demand for interpretable and precise estimation of heterogeneous treatment effects is ever-present. This paper outlines a new approach to this problem based on the Leave-One-Out Potential…

Purpose: This study aimed to use enrollment information including demographic, family background and financial status, which can be gathered before the first semester starts, to construct early prediction models (EPMs) and extract crucial factors associated with first-year student dropout probability. Design/methodology/approach: The real-world…

This paper combines a theoretical-based model with a data-driven approach to develop an Early Warning System that detects students who are more likely to dropout. The model uses innovative multilevel statistical and machine learning methods. The paper demonstrates the validity of the approach by applying it to administrative data from a leading…