Deep Learning or Deeper Learning (DL) theory has gained traction as a helpful framework for designing higher education curricula in face-to-face (F2F), hybrid, and online settings. Although many research studies have been published testing DL methods in higher education, it is difficult to apply the results without an overview. This review applies a scientifically-informed search approach to select a sample of 127 peer-reviewed articles (representing 176 experimental groups) published from 1999 through 2019 on the topic of DL in higher education, classifies and extracts data from them, and presents a descriptive analysis of the findings.