I teach the MOOC Big Data and Education on EdX.
I am co-Director of the MOOC Replication Framework (MORF) project.
I proposed the Baker Learning Analytics Prizes
and co-authored the report High-Leverage Opportunities
for Learning Engineering.
My research involves the use of Educational Data Mining/Learning Analytics to study learners and learning.
I develop and use methods for mining the data that comes out of the interactions between students and educational software, in order to better understand how students respond to educational software, and how these responses impact their outcomes.
I study these issues within intelligent tutors, simulations, MOOCs/online courses, and educational games.
I study these issues in the context of K-12 formal and informal learning, higher education, the military, and lifelong learning.
In recent years, my colleagues and I have developed automated detectors that make inferences in real-time about students' affect and motivational and
meta-cognitive behavior, using data from students' actions within educational software (no sensor, video, or audio data). We have in particular studied
gaming the system, off-task behavior, carelessness, "WTF behavior", boredom, frustration/confrustion, engaged concentration, and the appropriate use of help and feedback.
We use these models to study the conditions under which these behaviors or affective states arise, and their impacts.
Many of these models are developed using data collected through the
Baker Rodrigo Ocumpaugh Monitoring Protocol (BROMP), and the HART Android app.
I have made some tools for EDM research available here.
My daughter and I created a card game, Academic Squabble
My kids and I also write children's stories for fun.
Please check out my publications web page for recent papers.
Follow my research group on Twitter or Facebook.
Educational Data Monkey (art courtesy of Maria Baker)