Ryan Shaun Joazeiro de Baker
Professional Background
Educational Background
2005. Advisors: Kenneth R. Koedinger, Albert T. Corbett
M.S. Human-Computer Interaction. Carnegie Mellon University. Conferred August 9, 2005.
ScB. Computer Science. Brown University. Graduated with Honors in Computer Science, May
2000.
Scholarly Interests
Student Modeling (Disengagement, Affect, Robust Learning, Knowledge, Strategic Behavior,
Meta-Cognition), Intelligent Tutoring Systems, Serious Games/Educational Games, Science
Microworlds, Off-Task Behavior, Cultural Factors
Selected Publications
active professional organizations
Conference Chair. Third International Conference on Educational Data Mining. Pittsburgh, PA,
USA. June 11-13 2010.
Mining, Montreal, Canada, June 20-21, 2008.
Steering Committee. Learning Analytics and Knowledge Conference / Society for Learning
Analytics Research, 2011-present.
biographical information
grants
Bill and Melinda Gates Foundation, US Program, Vital Behaviors and Skills Associated with Engagement Derived from Learning Analytics Topic. Towards an Engagement Pedometer for Everyone: Unobtrusive Assessment of Engagement and Disengagement. Baker, R.S.J.d. (PI).
National Science Foundation, Software and Hardware Foundations (SHF). SHF: Small: User Studies to Improve Novice Programming. Fisler, K. (PI), Baker, R.S.J.d. (Co-PI).
U.S. Department of Education, Institute of Education Sciences. Classroom Environment, Allocation of Attention, and Learning Outcomes in K-4 Students. Fisher, A. (PI), Baker, R.S.J.d. (Co-PI).
National Science Foundation, Innovative Technology Experiences for Students and Teachers (ITEST). Research: Predicting STEM Career Choice from Computational Indicators of Student Engagement within Middle School Mathematics Classes. Baker, R.S.J.d. (PI), Heffernan, N.T. (Co-PI).
National Science Foundation, Research and Evaluation on Education in Science and Engineering (REESE). Empirical Research: Emerging Research: Using Automated Detectors to Examine the Relationships Between Learner Attributes and Behaviors During Inquiry in Science Microworlds. Gobert, J.G. (PI), Baker, R.S.J.d. (Co-PI).
National Science Foundation, Research and Evaluation on Education in Science and Engineering (REESE). Empirical Research: Emerging Research: Robust and Efficient Learning: Modeling and Remediating Students’ Domain Knowledge. Corbett, A.T. (PI), Baker, R.S.J.d. (Co-PI).
U.S. Department of Education, Institute of Education Sciences. Promoting Robust Understanding of Genetics with a Cognitive Tutor that Integrates Conceptual Learning with Problem Solving. Corbett, A.T. (PI), Baker, R.S.J.d. (Co-PI).
National Science Foundation, Science of Learning Centers. Toward a Decade of PSLC Research: Investigating Instructional, Social, and Learner Factors in Robust Learning through Data-Driven Analysis and Modeling. Koedinger, K.R. (PI). Baker, R.S.J.d. (Senior Personnel).
honors and awards
principal publications
Whether Student Learning is Shallow. Proceedings of the International Conference on Intelligent
Tutoring Systems, 444-453. [Won Best Paper Award]
Models of Systematic Inquiry, Even with Less Information. Proceedings of the 20th International
Conference on User Modeling, Adaptation and Personalization (UMAP 2012), 249-260. [Won
James Chen Best Student Paper Award]
Collection Inquiry Skills across Physical Science Microworlds. Paper presented at the American
Educational Research Association Conference. [Won Best Student Paper Award, AERA SIGATL]
Proceedings of 15th International Conference on Artificial Intelligence in Education, 23-30.
[Finalist for Best Paper Award]
Mitchell, A.P., Giguere, S. (2010) Contextual Slip and Prediction of Student Performance After
Use of an Intelligent Tutor. Proceedings of the 18th Annual Conference on User Modeling,
Adaptation, and Personalization, 52-63. [Finalist for Best Paper Award]
Proceedings of the 10th Annual Conference on Intelligent Tutoring Systems, 25-34. [People’s
Choice Award for Best Oral Presentation] [Finalist for Best Paper Award]
than Bored: The Incidence, Persistence, and Impact of Learners' Cognitive-Affective States
during Interactions with Three Different Computer-Based Learning Environments. International
Journal of Human-Computer Studies, 68 (4), 223-241.
A Data Repository for the EDM commuity: The PSLC DataShop. In Romero, C., Ventura, S.,
Pechenizkiy, M., Baker, R.S.J.d. (Eds.) Handbook of Educational Data Mining. Boca Raton, FL:
CRC Press, pp. 43-56.
(2009) Educational Software Features that Encourage and Discourage “Gaming the System”.
Proceedings of the 14th International Conference on Artificial Intelligence in Education, 475-482.
[Honorable Mention for Best Paper Award]
Future Visions. Journal of Educational Data Mining, 1 (1), 3-17.
Detector of When Students Game the System. User Modeling and User-Adapted Interaction, 18
(3), 287-314.
Why Students Engage in “Gaming the System” Behavior in Interactive Learning Environments.
Journal of Interactive Learning Research, 19 (2), 185-224.
Contextual Estimation of Slip and Guess Probabilities in Bayesian Knowledge Tracing.
Proceedings of the 9th International Conference on Intelligent Tutoring Systems, 406-415.
Tutoring Systems. Proceedings of ACM CHI 2007: Computer-Human Interaction, 1059-1068.
[Honorable Mention for Best Paper Award]
Raspat, J., Baker, D.J., Beck, J. (2006) Adapting to When Students Game an Intelligent Tutoring
System. Proceedings of the 8th International Conference on Intelligent Tutoring Systems, 392-
401. [Won Best Paper Award]
the System Across a Tutoring Curriculum. Proceedings of the 8th International Conference on
Intelligent Tutoring Systems, 402-411. [Finalist for Best Paper Award]
to Game the System? Proceedings of the International Conference on Artificial Intelligence and
Education (AIED2005), 57-64. [Finalist for Best Paper Award]
Sensor-Based Estimates in Human Computer Interaction. Proceedings of Graphics Interface
(GI 2005), 129-136.
Tutoring Systems. Proceedings of the 7th International Conference on Intelligent Tutoring
Systems, 531-540.
Cognitive Tutor Classroom: When Students "Game The System". Proceedings of ACM CHI
2004: Computer-Human Interaction, 383-390.
Visualizers for Teaching Data Structures. 30th ACM SIGCSE Technical Symposium on Computer
Science Education, 261-265.




