Associate Vice Provost for Educational Innovation and Learning Analytics, Director, Eberly Center for Teaching Excellence & Educational Innovation, Co-coordinator of The Simon Initiative, Professor of Psychology (Teaching)
Areas of Expertise
Cognitive Science, Learning Science
BioIn my research, I study how learning works (mostly in college-level courses) and then find ways to improve it. I have done this in several disciplines, including physics, matrix algebra, programming, statistics, and engineering. I use various methodologies in my work, including computational modeling, protocol analysis, laboratory experiments, and classroom studies. As a result, I have developed several innovative, educational technologies to promote student learning and metacognition, including StatTutor (an intelligent tutoring system for statistics) and the Learning Dashboard (a learning analytics system that promotes adaptive teaching and learning in online instruction).
Besides my appointment in the Psychology Department, I am Director of the Eberly Center for Teaching Excellence and Educational Innovation. At the Eberly Center, I apply theoretical and empirical principles from cognitive psychology to help CMU faculty improve their teaching. Combining my research and Eberly Center work, I co-authored the book, How Learning Works: 7 Research-Based Principles for Smart Teaching, that distills the research on how students learn into a set of fundamental principles that instructors can use to guide their teaching.
Lovett, M.C. (2013). Make exams worth more than the grade: Using exam wrappers to promote metacognition. In M. Kaplan, D. LaVaque-Manty, D. Meizlish, & N. Silver (Eds.) Reflection and Metacognition in College Teaching. New York: Stylus Publishing.
Ambrose, S. A., Bridges, M. W., DiPietro, M., Lovett, M. C., & Norman, M. K. (2010). How Learning Works: Seven Research-Based Principles for Smart Teaching. San Francisco, CA: Jossey-Bass.
Lovett, M. C., Meyer, O., & Thille, C. (2010). In search of the perfect blend between an instructor and an online course for teaching introductory statistics. Proceedings of the Eighth International Conference on the Teaching of Statistics.
Rosenberg-Lee, M., Lovett, M. C., & Anderson, J. R. (2009). Neural correlates of arithmetic calculation strategies. Cognitive, Affective, & Behavioral Neuroscience, 9, 270-285.
Lovett, M. C., Meyer, O., & Thille, C. (2008). Open Learning Initiative: Testing the accelerated learning hypothesis in Statistics. Journal of Interactive Media in Education. [special issue printing top papers from the OpenLearn Conference 2008]
DiPietro, M., Norman, M., Lovett, M., et al. (2008). Defeating the Developers Dilemma: An Online Tool for Individual Consultations. To Improve the Academy, 27, 183-198.
Complete List of Publications