| Affective states and state tests: Investigating how affect and engagement during the school year predict end-of-year learning outcomes. ZA Pardos, RSJD Baker, MOCZ San Pedro, SM Gowda, SM Gowda Journal of learning Analytics 1 (1), 107-128, 2014 | 235 | 2014 |
| Affective states and state tests: Investigating how affect throughout the school year predicts end of year learning outcomes ZA Pardos, RSJD Baker, MOCZ San Pedro, SM Gowda, SM Gowda Proceedings of the third international conference on learning analytics and …, 2013 | 213 | 2013 |
| Predicting college enrollment from student interaction with an intelligent tutoring system in middle school MO Pedro, R Baker, A Bowers, N Heffernan Educational Data Mining 2013, 2013 | 181 | 2013 |
| The effects of an interactive software agent on student affective dynamics while using; an intelligent tutoring system MMT Rodrigo, RSJ Baker, J Agapito, J Nabos, MC Repalam, SS Reyes, ... IEEE Transactions on Affective Computing 3 (2), 224-236, 2012 | 90 | 2012 |
| Detecting carelessness through contextual estimation of slip probabilities among students using an intelligent tutor for mathematics MOCZ San Pedro, RSJ Baker, MMT Rodrigo Artificial Intelligence in Education: 15th International Conference, AIED …, 2011 | 59 | 2011 |
| Towards an understanding of affect and knowledge from student interaction with an intelligent tutoring system MOZ San Pedro, RSJ Baker, SM Gowda, NT Heffernan Artificial Intelligence in Education: 16th International Conference, AIED …, 2013 | 58 | 2013 |
| Carelessness and affect in an intelligent tutoring system for mathematics MOZ San Pedro, RSJ Baker, MMT Rodrigo International Journal of Artificial Intelligence in Education 24, 189-210, 2014 | 57 | 2014 |
| Middle school engagement with mathematics software and later interest and self-efficacy for STEM careers J Ocumpaugh, MO San Pedro, H Lai, RS Baker, F Borgen Journal of Science Education and Technology 25, 877-887, 2016 | 55 | 2016 |
| Predicting STEM and non-STEM college major enrollment from middle school interaction with mathematics educational software MO Pedro, J Ocumpaugh, R Baker, N Heffernan Educational Data Mining 2014, 2014 | 52 | 2014 |
| An integrated look at middle school engagement and learning in digital environments as precursors to college attendance MOZ San Pedro, RS Baker, NT Heffernan Technology, Knowledge and Learning 22, 243-270, 2017 | 37 | 2017 |
| NCLEX-RN readiness: HESI Exit Exam validity and nursing program policies M Shah, B Fuller, C Gouveia, CL Mee, RS Baker, MOZ San Pedro Journal of Professional Nursing 39, 131-138, 2022 | 31 | 2022 |
| Beyond cognitive ability S Joksimovic, G Siemens, YE Wang, MOZ San Pedro, J Way Journal of Learning Analytics 7 (1), 1–4-1–4, 2020 | 25 | 2020 |
| Comparing expert and metric-based assessments of association rule interestingness DL Bazaldua, R Baker, MO Pedro Educational Data Mining 2014, 2014 | 24 | 2014 |
| The relationship between carelessness and affect in a Cognitive Tutor MOCZ San Pedro, MMT Rodrigo, RSJ Baker Affective Computing and Intelligent Interaction: 4th International …, 2011 | 22 | 2011 |
| Exploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test Achievement. MOZ San Pedro, EL Snow, RS Baker, DS McNamara, NT Heffernan International Educational Data Mining Society, 2015 | 20 | 2015 |
| Exploring college major choice and middle school student behavior, affect and learning: What happens to students who game the system? MOZ San Pedro, RS Baker, NT Heffernan, JL Ocumpaugh Proceedings of the fifth international conference on learning analytics and …, 2015 | 20 | 2015 |
| Investigating Test Prep Impact on Score Gains Using Quasi-Experimental Propensity Score Matching. ACT Working Paper 2018-6. R Moore, E Sanchez, MO San Pedro ACT, Inc., 2018 | 15 | 2018 |
| Guidance counselor reports of the ASSISTments college prediction model (ACPM) J Ocumpaugh, RS Baker, MOCZ San Pedro, MA Hawn, C Heffernan, ... Proceedings of the Seventh International Learning Analytics & Knowledge …, 2017 | 14 | 2017 |
| Learning, moment-by-moment and over the long term Y Jiang, RS Baker, L Paquette, MS Pedro, NT Heffernan Artificial Intelligence in Education: 17th International Conference, AIED …, 2015 | 12 | 2015 |
| Adaptive learning MOZ San Pedro, RS Baker The Cambridge guide to blended learning for language technologies, 234-247, 2016 | 7 | 2016 |
Ryan BakerUniversity of PennsylvaniaVerified email at upenn.edu
