Laboratory for the Study of Metacognition and Advanced Learning Technologies (SMART Lab)

The main objective of our research lab is to examine the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies (e.g., intelligent tutoring systems, hypermedia, simulations). More specifically, we aim to understand the complex interactions between humans and intelligent learning systems by using interdisciplinary methods to measure cognitive, metacognitive, affective, and motivational processes and their impact on learning and transfer. To accomplish this goal, we conduct laboratory, classroom, and in-situ (e.g., medical simulator) studies and collect traditional data (e.g., learning outcomes, self-reports) as well as rich, multi-channel trace data (e.g., eye tracking, facial expressions of emotions, physiological arousal, log files) to develop models of human-computer interaction; examine the nature of temporally unfolding self- and other-regulatory processes (e.g., human-human and human-artificial agents); and, design intelligent learning and training systems to detect, track, model, and foster humans' self-regulatory processes.


People

Roger Azevedo

Roger Azevedo
Professor

Michelle Taub
Ph.D. Candidate

Nicholas V. Mudrick
Ph.D. Student


Garrett C. Millar
Ph.D. Student

Amanda E. Bradbury
Ph.D. Student

Megan J. Price
Research Assistant


Click here for a list of past SMART Lab members.


Recent Publications

Journal Articles

  • Harley, J.M., Carter, C.K., Papaionnou, N., Bouchet, F., Azevedo, R., Landis, R. L., & Karabachian, L. (2016). Examining the predictive relationship between personality and emotion traits and students’ agent-directed emotions: Towards emotionally-adaptive agent-based learning environments. User Modeling and User-Adapted Interaction, 26, 177-219.
  • Trevors, G., Feyzi-Behnagh, R., Azevedo, R., & Bouchet, F. (2016). Self-regulated learning processes vary as a function of epistemic beliefs and contexts: Evidence from eye tracking and concurrent and retrospective reports. Learning and Instruction, 42, 31-46.
  • Azevedo, R. (2015). Defining and measuring engagement and learning in science: Conceptual, theoretical, methodological, and analytical issues. Educational Psychologist, 50, 84-94.
  • Duffy, M., & Azevedo, R. (2015). Motivation matters: Interactions between achievement goals and agent scaffolding for self-regulated learning within an intelligent tutoring system. Computers in Human Behavior, 52, 338-348.
  • Duffy, M., Azevedo, R., Sun, N.-Z., Griscom, S., Stead, V., Dhillon, I., Crelinsten, L., Wiseman, J., Maniatis, T., & Lachapelle, K. (2015). Team regulation in a simulated medical emergency: An in-depth analysis of the cognitive, metacognitive, and affective processes. Instructional Science, 43, 401-426.
  • Harley, J. M., Bouchet, F., Hussain, S., Azevedo, R., & Calvo, R. (2015). A multi-componential analysis of emotions during complex learning with an intelligent multi-agent system. Computers in Human Behavior, 48, 615-625.
  • Muis, K. R., Pekrun, R., Azevedo, R., Sinatra, G. M., Trevors, G., Meier, E., & Heddy, B. (2015). The curious case of climate change: Testing a theoretical model of epistemic beliefs, epistemic emotions, and complex learning. Learning and Instruction, 39, 168-183.

Book Chapters

  • Taub, M., Martin, S. A., Azevedo, R., & Mudrick, N. V. (2016). The role of pedagogical agents on learning: Issues and trends. In F. Neto, R. Souza, & A. Gomes (Eds.), Handbook of research on 3-D virtual environments and hypermedia for ubiquitous learning (pp. 362-386). Hershey, PA: IGI Global.
  • Azevedo, R., Taub, M., Mudrick, N., Farnsworth, J., & Martin, S. A. (2016). Interdisciplinary research methods used to investigate emotions with advanced learning technologies. In M. Zembylas & P. Schutz (Eds.), Methodological advances in research on emotion and education (pp. 231-243). Amsterdam, The Netherlands: Springer.
  • Azevedo, R. (2015). An interview with Roger Azevedo. In H. Bembenutty (Ed.), Contemporary pioneers in educational psychology: Theory, research, and applications (pp. 103-120). Charlotte, NC: Information Age Publishing.
  • Azevedo, R., Taub, M., & Mudrick, N. (2015a). Technologies supporting self-regulated learning. In M. Spector, C. Kim, T. Johnson, W. Savenye, D. Ifenthaler, & G. Del Rio (Eds.), The SAGE Encyclopedia of educational technology (pp. 731-734). Thousand Oaks, CA: SAGE.
  • Azevedo, R., Taub, M., & Mudrick, N. (2015b). Think-aloud protocol analysis. In M. Spector, C. Kim, T. Johnson, W. Savenye, D. Ifenthaler, & G. Del Rio (Eds.), The SAGE Encyclopedia of educational technology (pp. 763-766). Thousand Oaks, CA: SAGE.

Refereed Conference Proceedings

  • Lallé, S., Mudrick, N. V., Taub, M., Grafsgaard, J. F., Conati, C. & Azevedo, R. (2016). Impact of individual differences on affective reactions to pedagogical agents scaffolding. In D. Traum et al. (Eds.), Proceedings of the 16th International Conference on Intelligent Virtual Agents—Lecture Notes in Computer Science 10011 (pp. 269-282). The Netherlands: Springer.
    [Winner of the Best Conference Paper Award]
  • Azevedo, R., Martin, S. A., Taub, M., Mudrick, N. V., Millar, G. C., & Grafsgaard, J. F. (2016). Are pedagogical agents’ external regulation effective in fostering learning with intelligent tutoring systems? In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Proceedings of the 13th International Conference on Intelligent Tutoring Systems—Lecture Notes in Computer Science 9684 (pp. 197-207). The Netherlands: Springer.
    [Winner of the Best Conference Paper Award]
  • Bouchet, F., Harley, J., & Azevedo, R. (2016). Can adaptive pedagogical agents’ prompting strategies improve students’ learning and self-regulation? In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Proceedings of the 13th International Conference on Intelligent Tutoring Systems—Lecture Notes in Computer Science 9684 (pp. 368-374). The Netherlands: Springer.
  • Martin, S. A., Azevedo, R., Taub, M., Mudrick, N., Millar, G., & Grafsgaard, J. (2016). Are there benefits of using multiple pedagogical agents to support and foster self-regulated learning in an intelligent tutoring system? In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Proceedings of the 13th International Conference on Intelligent Tutoring Systems—Lecture Notes in Computer Science 9684 (pp. 273-279). The Netherlands: Springer.
  • Taub, M., & Azevedo, R. (2016). Using eye-tracking to determine the impact of prior knowledge on self-regulated learning with an adaptive hypermedia- learning environment? In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Proceedings of the 13th International Conference on Intelligent Tutoring Systems—Lecture Notes in Computer Science 9684 (pp. 34-47). The Netherlands: Springer.
  • Taub, M., Mudrick, N., Azevedo, R., Millar, G. Rowe, J., & Lester, J. (2016).Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with Crystal Island. In A. Micarelli, J. Stamper, & K. Panourgia (Eds.), Proceedings of the 13th International Conference on Intelligent Tutoring Systems—Lecture Notes in Computer Science 9684 (pp. 240-246). The Netherlands: Springer.
  • Azevedo, R., Johnson, A., & Burkett, C. (2015). Does training of cognitive and metacognitive regulatory processes enhance learning and deployment of cognitive and metacognitive processes with hypermedia? In D. C. Noelle, R. Dale, A. S., Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp.136-141). Austin, TX: Cognitive Science Society.
  • Mudrick, M., Azevedo, R., Taub, M., & Bouchet, F. (2015). Does the frequency of pedagogical agent intervention relate to learners’ self-reported boredom while using multiagent intelligent tutoring systems? In D. C. Noelle, R. Dale, A. S., Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp.1661-1666). Austin, TX: Cognitive Science Society.
  • Taub, M., Farnsworth, J., & Azevedo, R. (2015). Does prior knowledge reveal cognitive and metacognitive processes during learning with a hypermedia-learning system based on eye-tracking data? In D. C. Noelle, R. Dale, A. S., Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp. 2999). Austin, TX: Cognitive Science Society.
  • Harley, J. M., Carter, C.K., Papaionnou, N., Bouchet, F., Landis, R. L., Azevedo, R., & Karabachian, L.R. (2015). Examining the predictive relationship between personality and emotion traits and learners’ agent-directed emotions. In C. Conati, N. Heffernan, A. Mitrovic, & M. F. Verdejo (Eds.), Proceedings of the 17th International Conference on Artificial Intelligence in Education (pp. 145-154). Amsterdam, The Netherlands: Springer.

Conference Presentations

  • Azevedo, R., Taub, M., Mudrick, N., Martin, S. A., & Grafsgaard, J. (2016, August). Measuring and supporting the dynamic interplay between self- and externally-regulated learning with advanced learning technologies. Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Azevedo, R., Taub, M., Mudrick, N., Martin, S. A., & Grafsgaard, J. (2016, August). Using adaptive scaffolding by animated pedagogical agents to improve self-regulation during complex learning: Evidence from multi-modal trace data. Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Martin, S. A., Mudrick, N., Taub, M., & Azevedo, R. (2016, August). The importance of regulatory flexibility in learning with advanced learning technologies. Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Mudrick, N., Taub, M., & Azevedo, R. (2016, August). Multimedia discrepancies and their influence on metacomprehension during multimedia learning. Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Mudrick, N., Taub, M., & Azevedo, R. (2016, August). Using eye-movements to understand metacomprehension during learning with multimedia discrepancies. Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Taub, M., Mudrick, N., & Azevedo, R. (2016, August). Using multi-level models to predict how metacognitive monitoring predicts performance assessment with MetaTutor. Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Wortha, F., Azevedo, R., Taub, M., Mudrick, N., Martin, S. A., & Millar, G. C., & Narciss, S. (2016, August). Judgements of learning during learning with hypermedia: How do they affect study time allocation and study behaviors? Paper to be presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI) Metacognition SIG, Nijmegen, The Netherlands.
  • Azevedo, R., Martin, S. A., Taub, M., Mudrick, N., Millar, G., & Grafsgaard, J. (2016, June). Are pedagogical agents’ external regulation effective in fostering learning with intelligent tutoring systems? Paper presented at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Azevedo. R., Mudrick, N. V., Taub, M., Martin, S., Wortha, F., & Millar, G. (2016, June). The coupling between metacognition and emotions during STEM learning with advanced learning technologies: A critical analysis and implications for future research. Paper presented at the 2nd International Workshop on Affect, Meta-Affect, Data and Learning (AMADL 2016) at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Bouchet, F., Harley, J., & Azevedo, R. (2016, June). Can adaptive pedagogical agents’ prompting strategies improve students’ learning and self-regulation? Paper presented at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Martin, S. A., Azevedo, R., Taub, M., Mudrick, N., Millar, G., & Grafsgaard, J. (2016, June). Are there benefits of using multiple pedagogical agents to support and foster self-regulated learning in an intelligent tutoring system? Paper presented at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Martin, S., Grafsgaard, J., Mudrick, N. V., Taub, M., & Azevedo. R. (2016, June). On the feasibility of providing real-time adaptive support for motivation and emotion in intelligent tutoring systems. Paper presented at the 2nd International Workshop on Affect, Meta-Affect, Data and Learning (AMADL 2016) at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Taub, M., & Azevedo, R. (2016, June). Using eye-tracking to determine the impact of prior knowledge on self-regulated learning with an adaptive hypermedia- learning environment? Paper presented at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Taub, M., Mudrick, N., Azevedo, R., Millar, G. Rowe, J., & Lester, J. (2016, June). Using multi-level modeling with eye-tracking data to predict metacognitive monitoring and self-regulated learning with Crystal Island. Paper presented at the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), Zagreb, Croatia.
  • Azevedo, R., (2016, April). Multimodal data tracking, alignment, and analyses of Metacognitive processes: Measurement issues and challenges in learner modeling. Paper presented at the annual Learning Environments Across Disciplines (LEADS) workshop, Washington, DC.
  • Taub, M., Azevedo, R., Martin, S. A., Millar, G. C., & Wortha, F. (2016, April). Aligning log-file and facial expression data to validate assumptions linking SRL, metacognitive monitoring, and emotions during learning with a multi-agent hypermedia-learning environment. Structured poster presented at the annual meeting of the American Educational Research Association, Washington, DC.
  • Taub, M., Mudrick, N. V., Azevedo, R., Markhelyuk, M., & Powell, G. S. (2016, April). Assessing middle school students' use of a metacognitive monitoring tool during learning with SimSelf. Paper presented at the annual meeting of the American Educational Research Association, Washington, DC.
  • Feyzi-Behnagh, R, Azevedo, R., Bouchet, F, & Tian, Y. (2016, April). The role of an open learner model and immediate feedback on metacognitive calibration in MetaTutor. Paper presented at the annual meeting of the American Educational Research Association, Washington, DC.
  • Wortha, F., Azevedo, R., Taub, M., Mudrick, N. V., Martin, S. A., Millar, G. C., & Narciss, S. (2016, April). Emotion profiles: The importance of emotions during learning with a multi-agent hypermedia-learning environment. Paper presented at the annual meeting of the American Educational Research Association, Washington, DC.
  • Azevedo, R. (2015, October). Understanding and reasoning about real-time cognitive, affective, and metacognitive processes to foster self-regulation with advanced learning technologies. Invited talk presented at the Université du Quebéc à Montréal, Quebéc, Canada.
  • Azevedo, R. (2015, August). Using process data to examine self-regulation with advanced learning technologies: Issues and challenges. Paper presented at an invited session of the biennial meeting of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.
  • Azevedo, R., Mudrick, N., Taub, M., & Martin, S. A., (2015, August). Issues in capturing, analyzing, and inferring self-regulatory processes from multi-channel data. Paper presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.
  • Azevedo, R., Taub, M., Mudrick, N., & Martin, S. A. (2015, August). Monitoring and regulating emotions between humans and pedagogical agents during learning with MetaTutor. Paper presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.
  • Lebeau, I., Baetan, S., Azevedo, R., & Crauwels, M. (2015, August). Does students’ SRL-training in an authentic learning environment improve their performance? Paper presented at an invited session of the biennial meeting of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.
  • Taub, M., Azevedo, R., Mudrick, N., & Martin, S. A. (2015, August). Using process data to examine self-regulatory processes during learning with MetaTutor. Paper presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.
  • Taub, M., Azevedo, R., Lisk, S., Kabat, G., Martin, S. A., & Smith, T. (2015, August). Product vs process: PA influence on time and use of SRL processes on relevant pages with MetaTutor. Paper presented at the biennial meeting of the European Association for Research on Learning and Instruction (EARLI), Limassol, Cyprus.