| Can the use of cognitive and metacognitive self-regulated learning strategies be predicted by learners’ levels of prior knowledge in hypermedia-learning environments? M Taub, R Azevedo, F Bouchet, B Khosravifar Computers in Human Behavior 39, 356-367, 2014 | 100 | 2014 |
| The effectiveness of pedagogical agents’ prompting and feedback in facilitating co-adapted learning with MetaTutor R Azevedo, RS Landis, R Feyzi-Behnagh, M Duffy, G Trevors, JM Harley, ... International conference on intelligent tutoring systems, 212-221, 2012 | 55 | 2012 |
| Understanding and reasoning about real-time cognitive, affective, and metacognitive processes to foster self-regulation with advanced learning technologies R Azevedo, M Taub, NV Mudrick, SA Martin, JF Grafsgaard Handbook of self-regulation of learning and performance, 254-270, 2018 | 31 | 2018 |
| Are pedagogical agents’ external regulation effective in fostering learning with intelligent tutoring systems? R Azevedo, SA Martin, M Taub, NV Mudrick, GC Millar, JF Grafsgaard international conference on intelligent tutoring systems, 197-207, 2016 | 30 | 2016 |
| Using data visualizations to foster emotion regulation during self-regulated learning with advanced learning technologies R Azevedo, M Taub, NV Mudrick, GC Millar, AE Bradbury, MJ Price Informational environments, 225-247, 2017 | 28 | 2017 |
| Using multi-channel data with multi-level modeling to assess in-game performance during gameplay with Crystal Island M Taub, NV Mudrick, R Azevedo, GC Millar, J Rowe, J Lester Computers in Human Behavior 76, 641-655, 2017 | 27 | 2017 |
| Using sequence mining to reveal the efficiency in scientific reasoning during STEM learning with a game-based learning environment M Taub, R Azevedo, AE Bradbury, GC Millar, J Lester Learning and instruction 54, 93-103, 2018 | 26 | 2018 |
| Using multi-channel trace data to infer and foster self-regulated learning between humans and advanced learning technologies R Azevedo, M Taub, NV Mudrick, SA Martin, J Grafsgaard Handbook of self-regulation of learning and performance 2, 2017 | 23 | 2017 |
| Let's Set Up Some Subgoals: Understanding Human-Pedagogical Agent Collaborations and Their Implications for Learning and Prompt and Feedback Compliance JM Harley, M Taub, R Azevedo, F Bouchet IEEE Transactions on Learning Technologies 11 (1), 54-66, 2017 | 15 | 2017 |
| Interdisciplinary research methods used to investigate emotions with advanced learning technologies R Azevedo, M Taub, N Mudrick, J Farnsworth, SA Martin Methodological advances in research on emotion and education, 231-243, 2016 | 11 | 2016 |
| Technologies supporting self-regulated learning R Azevedo, M Taub, N Mudrick The SAGE Encyclopedia of educational technology, 731-734, 2015 | 11 | 2015 |
| The impact of student individual differences and visual attention to pedagogical agents during learning with MetaTutor S Lallé, M Taub, NV Mudrick, C Conati, R Azevedo International Conference on Artificial Intelligence in Education, 149-161, 2017 | 10 | 2017 |
| Transitioning self-regulated learning profiles in hypermedia-learning environments C Lau, J Sinclair, M Taub, R Azevedo, EE Jang Proceedings of the Seventh International Learning Analytics & Knowledge …, 2017 | 9 | 2017 |
| How Does Prior Knowledge Influence Eye Fixations and Sequences of Cognitive and Metacognitive SRL Processes during Learning with an Intelligent Tutoring System? M Taub, R Azevedo International Journal of Artificial Intelligence in Education 29 (1), 1-28, 2019 | 8 | 2019 |
| Impact of individual differences on affective reactions to pedagogical agents scaffolding S Lallé, NV Mudrick, M Taub, JF Grafsgaard, C Conati, R Azevedo International Conference on Intelligent Virtual Agents, 269-282, 2016 | 8 | 2016 |
| Coupling between Metacognition and Emotions during STEM Learning with Advanced Learning Technologies: A Critical Analysis, Implications for Future Research, and Design of … R Azevedo, N Mudrick, M Taub, F Wortha Teachers College Record 119 (13), n13, 2017 | 7 | 2017 |
| Using Multi-level Modeling with Eye-Tracking Data to Predict Metacognitive Monitoring and Self-regulated Learning with Crystal Island M Taub, NV Mudrick, R Azevedo, GC Millar, J Rowe, J Lester International Conference on Intelligent Tutoring Systems, 240-246, 2016 | 7 | 2016 |
| Using eye-tracking to determine the impact of prior knowledge on self-regulated learning with an adaptive hypermedia-learning environment M Taub, R Azevedo International Conference on Intelligent Tutoring Systems, 34-47, 2016 | 7 | 2016 |
| CSCL and learning analytics: Opportunities to support social interaction, self-regulation and socially shared regulation AF Wise, R Azevedo, K Stegmann, J Malmberg, CP Rosé, N Mudrick, ... International Society of the Learning Sciences, Inc.[ISLS]., 2015 | 7 | 2015 |
| A framework to understand the nature of co-regulated learning in human-pedagogical agent interactions J Harley, M Taub, F Bouchet, R Azevedo 11th International Conference on Intelligent Tutoring Systems, Crete, 2012 | 7 | 2012 |
