Educational Data Mining Intelligent Tutoring Systems The Learning Sciences Gaming the System
Ryan Baker ( Ryan Shaun Joazeiro de Baker )              


I am Associate Professor of Cognitive Studies in Education in the Department of Human Development at at Teachers College Columbia University.

I am also Program Coordinator of TC's Masters in Learning Analytics.

I also have an affiliate appointment at Worcester Polytechnic Institute, in the Department of Social Science and Policy Studies.I am also a member of LearnLab.

I am President of the International Educational Data Mining Society. I am also Associate Editor of the Journal of Educational Data Mining.

My research is at the intersection of Educational Data Mining and Human-Computer Interaction. 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 learning. I study these issues within intelligent tutors and educational games.

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, engaged concentration, and appropriate use of help and feedback. We use these models to make basic discoveries about human learning and learners. 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.

Selected Current and Upcoming Projects

  • Predicting STEM Career Choice from Computational Indicators of Student Engagement within Middle School Mathematics Classes (funded by NSF ITEST)
  • Classroom Environment, Allocation of Attention, and Learning Outcomes in K-4 Students (funded by IES)
  • Understanding the Differences Between Rational and Machine-Learned Models of Gaming the System (funded by NSF-SLC PSLC)
  • Modeling Relationship Between Affect and Robust Learning (funded by NSF-SLC PSLC)
  • Detectors of Affect in Educational Software (funded by NSF-SLC PSLC and Gates Foundation)
  • Studying Relationship Between Affect, Learning, and Persistence (funded by Gates Foundation)
  • Detecting, Studying, and Adapting to Affect in Military Training (cooperative agreement with Army Research Laboratory)
  • Creating Design Patterns for More Engaging Educational Software, Based on Evidence from EDM (funded by NSF REAL)
  • Studying Social Factors that Impact Community Participation After Use of MOOCs (funded by NSF DIRITL)
  • Studying Participation in Online Courses By Students From Underrepresented Groups (funded by Gates Foundation)
  • Student Behavior in Educational Software Across Cultures

Please check out my publications web page for recent papers.

I organize the Learning Analytics Seminar Series at Teachers College.

Teachers College now offers a Masters in Learning Analytics.

Teachers College also offers a Focus in Learning Analytics, within the Masters program in Cognitive Studies in Education.

I will be teaching the MOOC Big Data and Education on EdX, starting in June 2015.

I have written a MOOT (Massive Online Open Textbook), Big Data and Education. This MOOT is based on a course taught on the Coursera platform in Fall 2013.

Follow my research group on Twitter or Facebook.

Quantitative Field Observation Affective Computing Human-Computer Interaction Psychometric Machine-Learned Models