Dr. Ocumpaugh has been publishing in the field of learning analytics for over a decade where her work focuses on using data to improve student engagement and learning outcomes. Her work spans efforts across a range of learning environments, including intelligent tutoring systems for math, online learning games for science, and even mobile computer assisted learning systems for language acquisition. Dr. Ocumpaugh is perhaps best-known for formalizing the Baker Rodrigo Ocumpaugh Monitoring Method, which has been used to develop machine-learned sensor-free affect detection. BROMP-based models have been used in dozens of publications (see review in Baker et al., 2020). This work, which is at the intersection of learning analytics and human computer interaction (HCI) has continued to evolve, as research demonstrates the need for more qualitative data in order to make sense of student learning patterns and to develop new interventions.