Dr. Pardos is an Assistant Professor at UC Berkeley in a joint position between the Graduate School of Education and School of Information. His focal areas of study are educational data mining and learning analytics concentrating on measurement of learning phenomena in digital environments. He earned his PhD in Computer Science at Worcester Polytechnic Institute in the Tutor Research Group in 2012. Funded by a National Science Foundation Fellowship (GK-12) he spent extensive time on the front lines of K-12 education working with teachers and students to integrate educational technology into the curriculum as a formative assessment tool. He was program co-chair of the 2014 conference on Educational Data Mining, on the organizing committee for the 2014 Learning Analytics and Knowledge conference, and serves on the executive committee for the Artificial Intelligence in Education Society. He has received numerous academic awards and honors for work on predictive models of learning including a top prize applying his educational analytics in the 2010 KDD Cup, an international big data competition on predicting student performance within an intelligent tutoring system. Pardos comes to UC Berkeley after a post-doc at MIT studying Massive Open Online Courses. At UC Berkeley he directs the Computational Approaches to Human Learning (CAHL) research lab and teaches courses on Data Mining and Analytics, Digital Learning Environments, and Machine Learning in Education.
Research Expertise and Interest
knowledge representation, Learning Analytics, Big Data in Education, Computational Psychometrics, Digital Learning Environments, Cognitive Modeling, Bayesian Knowledge Tracing, Formative Assessment, machine learning