EXPLORING THE DETERMINANTS OF HIGHER EDUCATION DEGREE PRODUCTIVITY IN MACHINE LEARNING

Abstract

Studying the measures and determinants of institutional productivity is a critical field for policymakers and institutional leaders to identify an improvement strategy on how to allocate properly limited resources for higher productivity. Among them, degree completion is not only an ultimate outcome for students who are seeking a degree program, but also one of the essential measures that evaluate student success. Studies show that achieving higher degree productivity is identified as the most common concern for postsecondary institutions. This study reveals cost-related determinants play significant impacts on degree productivity by adopting a machine learning approach. The results suggest how these determinants worked in different scenarios which further explains the previous studies in degree productivity. With more online education being forcefully enforced with the lifestyle adaptation with COVID-19 pandemic, this explanation in degree productivity plays an important role to provide visions on how to allocate resources in an online learning environment.