Jaclyn Ocumpaugh, Associate Director, Penn Center for Learning Analytics
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 [https://learninganalytics.upenn.edu/ryanbaker/bromp.html], 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 [https://learninganalytics.upenn.edu/ryanbaker/BROMPbookchapter.pdf]). 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. Currently, she is leading efforts to develop new protocols for in situ interviews, triggered by an app developed by the PCLA, which works to signal the interviewer when a particular event (or aIffective experience) is detected within the learning software.
Dr. Ocumpaugh’s early training was as a sociolinguist, and she is very interested in how individual-level characteristics interact with group-level variables to influence students behavior and other learning experiences. She has extensive teaching experience across topics that require a wide range of student skills and will be teaching a course on Dashboards for the new online Learning Analytics MA degree starting in the Fall of 2023.
