Roger Azevedo, Ph.D.

Professor and Lead Scientist

Learning Sciences and Educational Research; UCF Learning Sciences Cluster

Office: ED 322C

Phone: 823-5349


Roger Azevedo is a Professor in the Department of Learning Sciences & Educational Research at the University of Central Florida. He is the Lead Scientist for UCF’s Learning Sciences Faculty Cluster Initiative. He received his doctorate from McGill University (1998) and completed his postdoctoral training in cognitive psychology at Carnegie Mellon University. His main research area includes examining the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies (e.g., intelligent tutoring systems, hypermedia, multimedia, simulations, serious games, immersive virtual learning environments). More specifically, his overarching research goal is to understand the complex interactions between humans and intelligent learning systems by using interdisciplinary methods to measure cognitive, metacognitive, emotional, and motivational processes and their impact on learning, performance, and transfer. To accomplish this goal, he conducts laboratory, classroom, and in-situ (e.g., medical simulator) studies and collects multi-channel data to develop models of human-computer interaction; examines the nature of temporally unfolding self- and other-regulatory processes (e.g., human-human and human-artificial agents); and, designs intelligent learning and training systems to detect, track, model, and foster learners, teachers, and trainers’ self-regulatory processes. He has published over 200 peer-reviewed papers, chapters, and refereed conference proceedings in the areas of educational, learning, cognitive, educational, and computational sciences. He is the editor of the Metacognition and Learning journal and also serves on the editorial board of several top-tiered learning and cognitive sciences journals (e.g., International Journal of AI in Education, European Journal of Psychological Assessment). His research is funded by the National Science Foundation, Institute of Education Sciences, and the Social Sciences and the Humanities Research Council of Canada. He is a fellow of the American Psychological Association and the recipient of the prestigious Early Faculty Career Award from the National Science Foundation.


PhD. Educational Psychology
McGill University

Areas of Expertise

  • Metacognition and Self-Regulated Learning
  • Human-Machine Interactions
  • Multimodal Multichannel Human Data

Research Interests

  • Advanced Learning Technologies
  • Learning, Reasoning, Problem Solving, and Performance
  • Analyses of Complex Human-Machine Interactions

Recent Honors and Awards

  • Barry J. Zimmerman Award for Outstanding Contributions to the fields of Studying and Self-Regulated Learning Research, from the American Educational Research Association’s (AERA) Studying and Self-Regulated Learning (SSRL) Special Interest Group (SIG), 2018
  • Outstanding International Research Collaboration Award sponsored by the Technology, Instruction, Cognition, and Learning SIG of the American Educational Research Association (AERA), 2017
  • Endowed Senior Canada Research Chair (Tier 1), Canada Research Chairs Program, 2011
  • Fellow, American Psychological Association (Division 15), 2009
  • Early Career Award, National Science Foundation, 2001

Recent Publications

Azevedo, R., Mudrick, N. V., Taub, M., & Bradbury, A. (in press). Self-regulation in computer-assisted learning systems. In J. Dunlosky & K. Rawson (Eds.), Handbook of cognition and education. Cambridge, MA: Cambridge University Press.

Azevedo, R., Taub, M., & Mudrick, N.V. (2018). Using multi-channel trace data to infer and foster self-regulated learning between humans and advanced learning technologies. In D. Schunk & Greene, J.A (Eds.), Handbook of self-regulation of learning and performance (2nd ed., pp. 254-270). New York, NY: Routledge.

Harley, J. M., Taub, M., Azevedo, R., & Bouchet, F. (in press). “Let’s set up some subgoals”: Understanding human-pedagogical agent collaborations and their implications for learning and prompt and feedback compliance. IEEE Transactions on Learning Technologies.

Mudrick, N.V., Azevedo, R., & Taub, M. (in press). Integrating metacognitive judgements and eye movements using sequential pattern mining to understand processes underlying successful multimedia learning. Computers in Human Behavior

Taub, M., Azevedo, R., Bradbury, A. E., Millar, G. C., & Lester. J. (in press). Using sequence mining to reveal the efficiency in scientific reasoning during STEM learning with a game-based learning environment. Learning and Instruction.

Funded Projects

Recommended: Co-Principal Investigator, Supporting Student Planning with Open Learner Models in Middle Grades Science—National Science Foundation. PI James Lester (NCSU). $1,499,183.

2017-present: Principal Investigator, Convergence HTF: Collaborative: Workshop on Interdisciplinary Research about Multimodal Human Learning Data during Human-Machine InteractionsNational Science Foundation. Co-PI Gautam Biswas (Vanderbilt University). $100,000.

2017-present: Co-Principal Investigator, Diagnostic Inventories of Cognition in EducationInstitute of Education Sciences (Goal 5). PI Laine Bradshaw (University of Georgia) and Co-PI Holylynne Lee (NCSU), Jessica Masters and Lisa Famularo (Research Matters) $1,399,999.

2017-present: Principal Investigator, Using Real-Time Multichannel Self-Regulated Learning Data to Enhance Student Learning and Teachers’ Decision-Making with MetaDashNational Science Foundation. Co-PIs Min Chi and Soonhye Park (North Carolina State University). $1,499,792.

2017-present: Co-Principal Investigator, REFLECT: Improving Science Problem Solving with Adaptive Game-Based Reflection ToolsNational Science Foundation. PI James Lester (North Carolina State University). $1,499,498.

2015-present: Collaborator, L2eLearn—Learning to eLearnEuropean Union Program for Lifelong Learning. PI Jose Carlos Nunez-Perez (University of Oviedo, Spain) and collaborators Mathias Gruenke (University of Cologne, Germany), Ioannis Agaliotis (University of Macedonia, Greece), Pedro Rosario (University of Minho, Portugal), and Daijela Milosevic (University of Kragujevac, Serbia). 505,001 €.

2014–present: Principal Investigator, CORE: The Effectiveness of Intelligent Virtual Humans in Facilitating Self-Regulated Learning in STEM with MetaTutorNational Science Foundation. Co-PI James Lester (North Carolina State University). $1,350,535.

2013–present: Co-Principal Investigator, NeuroLabCanadian Foundation for Innovation. PI is Julien Mercier (Universite de Montréal) and Co-PIs are Patrick Charland, Dave Saint-Amour, Philip Abrami, Armando Bertone, Isabelle Gauvin, Roland Grabner, Catherine Herba, Susanne Lajoie, Line Laplante, Pierre-Majorique Léger, Françoise Maheu, Steve Masson, Hélène Poissant, Patrice Potvin, Martin Riopel, Rushen Shi, Isabelle Soulières, and Sylvain Sénécal. $830,308.

2013–present: Principal Investigator, Transforming Teacher Training and Improving Students’ Academic Achievement with Advanced Digital TechnologiesPartnership Development Grant—Social Sciences and Humanities Research Council of Canada (SSHRC). Co-PIs Susanne Lajoie and Anila Asghar (McGill University), Vivek Venkatesh (Concordia University), and collaborators Elizabeth Charles (Dawson College), Françoys Labonté, and Claude Chapdelaine (Centre de recherche informatique de Montréal), Renne Marqui (EXO U), Philip Winne (Simon Fraser University), and Thérèse Laferrière (Université de Laval). $190,123.

Professional Organizations

  • American Educational Research Association (AERA)
  • American Psychological Association (APA)
  • American Society of Civil Engineers (ASCE)
  • Association for the Advancement of Affective Computing (AACI)
  • European Association for Research on Learning and Instruction (EARLI)
  • International Artificial Intelligence in Education Society (AI-ED)
  • Society for Learning Analytics Research (SOLAR)