Ryan Baker

Research Interests

Learning analytics Learning Sciences Learning, motivation and emotion Machine learning

Prof Ryan Baker

Professor of AI in Education

School of Education

College of Education, Behavioural and Social Science

Additional webpage with list of publications, past courses taught, and resourceshttps://learninganalytics.upenn.edu/ryanbaker/index.html

Date Position Institution name
2025 - ongoing Professor of Artificial Intelligence and Education University of South Australia
2025 - ongoing Adjunct Professor University of Pennsylvania

Date Institution name Country Title
2000 - 2005 Carnegie Mellon University United States PhD
2000 - 2005 Carnegie Mellon University United States MS
1996 - 2000 Brown University United States ScB

Date Title Institution Country
2016 - 2016 Innovation and Entrepreneurship Columbia University United States

Year Citation
2025 Kaliisa, R., Baker, R. S., Wasson, B., & Prinsloo, P. (2025). Coming but Uneven Storm. Journal of Learning Analytics, 12(2), 1-18.
DOI
2025 Baker, R. S., Cloude, E., Andres, J. M. A. L., & Wei, Z. (2025). Confrustion Constellation: a New Way of Looking at Confusion and Frustration. Cognitive Science, 49(1, article no. e70035), 1-30.
DOI
2025 Liu, X., Zambrano, A. F., Baker, R. S., Barany, A., Ocumpaugh, J., Zhang, J., . . . Wei, Z. (2025). Qualitative Coding with GPT-4: where it Works Better. Journal Of Learning Analytics, 12(1), 169-185.
DOI
2024 Tao, Y., Viberg, O., Baker, R. S., & Kizilcec, R. F. (2024). Cultural bias and cultural alignment of large language models. Pnas Nexus, 3(9, article no. 346), 1-9.
DOI
2024 Ocumpaugh, J., Roscoe, R. D., Baker, R. S., Hutt, S., & Aguilar, S. J. (2024). Toward Asset-based Instruction and Assessment in Artificial Intelligence in Education. International Journal Of Artificial Intelligence In Education, 34(4), 1559-1598.
DOI
2023 Ruiperez-Valiente, J. A., Kim, Y. J., Baker, R. S., Martinez, P. A., & Lin, G. C. (2023). The Affordances of Multivariate Elo-Based Learner Modeling in Game-Based Assessment. IEEE Transactions on Learning Technologies, 16(2), 152-165.
DOI Scopus10 WoS9
2023 Zhang, Y., Paquette, L., Baker, R. S., Bosch, N., Ocumpaugh, J., & Biswas, G. (2023). How are feelings of difficulty and familiarity linked to learning behaviors and gains in a complex science learning task?. European Journal Of Psychology Of Education, 38(2), 777-800.
DOI
2023 Scruggs, R., Baker, R. S., Pavlik Jr, P. I., McLaren, B. M., & Liu, Z. (2023). How well do contemporary knowledge tracing algorithms predict the knowledge carried out of a digital learning game?. Etrandd-Educational Technology Research And Development, 71(3), 901-918.
DOI
2022 Hutt, S., Baker, R. S., Ashenafi, M. M., Andres Bray, J. M., & Brooks, C. (2022). Controlled outputs, full data: a privacy-protecting infrastructure for MOOC data. British Journal Of Educational Technology, 53(4), 756-775.
DOI
2022 Baker, R. S., & Hawn, A. (2022). Algorithmic bias in education. International Journal Of Artificial Intelligence In Education, 32(4), 1052-1092.
DOI
2021 Zhang, Y., Paquette, L., Baker, R. S., Ocumpaugh, J., Bosch, N., Biswas, G., & Munshi, A. (2021). Can strategic behaviour facilitate confusion resolution? The interplay between confusion and metacognitive strategies in Betty's brain. Journal of Learning Analytics, 8(3), 28-44.
DOI
2021 Baker, R. S., Boser, U., & Snow, E. L. (2021). Learning engineering: a view on where the field is at, where it's going, and the research needed. Technology, Mind, And Behavior, 3(1), 1-23.
DOI
2021 Godwin, K. E., Seltman, H., Almeda, M., Davis Skerbetz, M., Kai, S., Baker, R. S., & Fisher, A. V. (2021). The elusive relationship between time on-task and learning: not simply an issue of measurement. Educational Psychology, 41(4), 502-519.
DOI
2021 Baker, R. S., Gaševic, D., & Karumbaiah, S. (2021). Four paradigms in learning analytics: why paradigm convergence matters. Computers and Education Artificial Intelligence, 2(100021), 1-9.
DOI
2017 Slater, S., Joksimovic, S., Kovanovic, V., Baker, R. S., & Gasevic, D. (2017). Tools for educational data mining: a review. Journal of educational and behavioral statistics, 42(1), 85-106.
DOI Scopus175 WoS111

Year Citation
2025 Deho, O. B., Joksimovic, S., Vieira, M., & Baker, R. (2025). Beyond Predictive Accuracy: Fairness and Bias in Predicting Test Anxiety. In A. I. Cristea (Ed.), Event/exhibition information: 26th International Conference, AIED 2025, Italy, 22/07/2025-26/07/2025
Source details - Title: Artificial Intelligence in Education (pp. 247-262). Switzerland: Springer.
DOI
2025 Rodrigues, L., Zambrano, A. F., Pankiewicz, M., Barany, A., & Baker, R. (2025). Usage patterns and performance gains in gamified online judges: a data-driven analysis informed by cognitive psychology in CS1. In A. I. Cristea (Ed.), Event/exhibition information: 26th International Conference, AIED 2025, Palermo, Italy, 22/07/2025-26/07/2025
Source details - Title: Artificial Intelligence in Education: 26th International Conference, AIED 2025 (pp. 99-106). US: Springer.
DOI
2025 Kizilcec, R. F., Baker, R. S., Brooks, C., Geathers, J., Hicke, Y., Moore, S., & Wu, B. (2025). Applications of generative AI to support teaching and learning in higher education: a half-day workshop. In A. I. Cristea (Ed.), Event/exhibition information: 26th International Conference, AIED 2025, Palermo, Italy, 22/07/2025-26/07/2025
Source details - Title: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED (pp. 267-274). Switzerland: Springer.
DOI
2025 Ocumpaugh, J., Paquette, L., Barany, A., & Baker, R. (2025). Full-day tutorial: conducting in-the-moment Data-Driven Classroom Interviews (DDCI) during digital learning using Quick Red Fox (QRF). In A. I. Cristea (Ed.), Event/exhibition information: 26th International Conference, AIED 2025, Palermo, Italy, Palermo, Italy, 22/07/2025-26/07/2025
Source details - Title: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium, Blue Sky, and WideAIED (pp. 278-283). Switzerland: Springer.
DOI
2025 Belitz, C., Lee, H. J., Nasiar, N., Fancsali, S. E., Stinar, F., Almoubayyed, H., . . . Bosch, N. (2025). Exploring student identity in adaptive learning systems through qualitative data. In A. I. Cristea (Ed.), Event/exhibition information: 26th International Conference, AIED 2025, Palermo, Italy, 22/07/2025-26/07/2025
Source details - Title: Artificial Intelligence in Education: 26th International Conference, AIED 2025 (pp. 356-363). Switzerland: Springer.
DOI
2024 Liu, X., Gurung, A., Baker, R. S., & Barany, A. (2024). Understanding the impact of observer effects on student affect. In A. Kim (Ed.), Event/exhibition information: 6th International Conference, ICQE 2024, Philadelphia, US, 03/11/2024-07/11/2024
Source details - Title: Advances in Quantitative Ethnography (pp. 79-94). US: Springer.
DOI
2024 Pankiewicz, M., Zambrano, A. F., Barany, A., & Baker, R. S. (2024). How we code code: leveraging GPT and ordered networks for understanding introductory programming education. In Y. J. Kim (Ed.), Event/exhibition information: 6th International Conference, ICQE 2024, Philadelphia, US, 03/11/2024-07/11/2024
Source details - Title: Advances in Quantitative Ethnography (pp. 225-240). US: Springer.
DOI
2024 Liu, X., Zambrano, A., Barany, A., Ocumpaugh, J., Ginger, J., Gadbury, M., . . . Baker, R. S. (2024). Investigating learner interest and observation patterns in a minecraft virtual astronomy environment. In Y. J. Kim (Ed.), Event/exhibition information: 6th International Conference, ICQE 2024, Philadelphia, US, 03/11/2024-07/11/2024
Source details - Title: Advances in Quantitative Ethnography (pp. 19-34). US: Springer.
DOI
2023 van Stee, E. G., Heath, T., Baker, R. S., Andres, J. M. A. L., & Ocumpaugh, J. (2023). Help seekers vs. Help accepters: understanding student engagement with a mentor agent. In N. Wang (Ed.), Event/exhibition information: 24th International Conference on Artificial Intelligence in Education (AIED), Tokyo, Japan, 03/07/2023-07/07/2023
Source details - Title: Artificial Intelligence In Education, Aied 2023 (Vol. 13916, pp. 139-150). US: Springer.
DOI
2023 Scianna, J., Liu, X., Slater, S., & Baker, R. S. (2023). A case for (Inter)Action: the role of log eata in QE. In G. Irgens (Ed.), Event/exhibition information: 5th International Conference, ICQE 2023, Melbourne, Australia, 08/10/2023-12/10/2023
Source details - Title: Advances in Quantitative Ethnography (pp. 395-408). US: Springer.
DOI
2023 Liu, X., Hussein, B., Barany, A., Baker, R. S., & Chen, B. (2023). Decoding player behavior: analyzing reasons for player quitting using log data from puzzle game Baba is you. In G. Irgens (Ed.), Event/exhibition information: 5th International Conference, ICQE 2023, Melbourne, Australia, 08/10/2023-12/10/2023
Source details - Title: Advances in Quantitative Ethnography (pp. 34-48). US: Springer.
DOI
2022 Wang, K., Ma, Z., Baker, R. S., & Li, Y. (2022). Iterative Refinement of an AIS Rewards System. In R. A. Sottilare (Ed.), Event/exhibition information: 4th International Conference on Adaptive Instructional Systems Held as Part of the 24th International Conference on Human-Computer Interaction (HCII), online, 26/06/2022 -01 /06/2022
Source details - Title: Adaptive Instructional Systems, Ais 2022 (pp. 113-125). US: Springer.
DOI
2021 Richey, J. E., Zhang, J., Das, R., Andres Bray, J. M., Scruggs, R., Mogessie, M., . . . McLaren, B. M. (2021). Gaming and confrustion explain learning advantages for a math digital learning game. In I. Roll (Ed.), Event/exhibition information: 22nd International Conference on Artificial Intelligence in Education (AIED) - Mind the Gap - AIED for Equity and Inclusion, online, 14/06/2021-18/06/2021
Source details - Title: Artificial Intelligence In Education (aied 2021), Pt I (pp. 342-355). US: Springer.
DOI
2020 Wang, Y., Kai, S., & Baker, R. S. (2020). Early detection of wheel-spinning in ASSISTments. In I. I. Bittencourt (Ed.), Event/exhibition information: 21st International Conference on Artificial Intelligence in Education (AIED), online, 06/07/2020-10/07/2020
Source details - Title: Artificial Intelligence In Education (aied 2020), Pt I (pp. 574-585). US: Springer.
DOI
2019 Richey, J. E., McLaren, B. M., Andres Bray, M., Mogessie, M., Scruggs, R., Baker, R., & Star, J. (2019). Confrustion in learning from erroneous examples: does type of prompted self-explanation make a difference?. In S. Isotani (Ed.), Event/exhibition information: 20th International Conference on Artificial Intelligence in Education (AIED), Chicago, Il, 25/06/2019-29/06/2019
Source details - Title: Artificial Intelligence In Education (aied 2019), Pt I (pp. 445-457). US: Springer.
DOI

Year Citation
2025 Karimov, A., Saarela, M., Aliyev, S., & Baker, R. S. (2025). Ethical Considerations and Student Perceptions of Engagement Data in Learning Analytics. In T. X. Bui (Ed.), Proceedings of the Annual Hawaii International Conference on System Sciences (pp. 4757-4766). HI: HICSS.
DOI Scopus4 WoS1
2025 Liu, X., Wei, Z., Baker, R. S., Metcalf, S. J., Zhang, J., Barany, A., . . . Gagnon, D. J. (2025). Integrating large language models and machine learning to detect struggle in educational games. In A. I. Cristea (Ed.), Artificial Intelligence in Education (pp. 398-405). US: Springer.
DOI
2025 Scarlatos, A., Baker, R. S., & Lan, A. (2025). Exploring Knowledge Tracing in Tutor-Student Dialogues using LLMs. In Fifteenth International Conference On Learning Analytics and Knowledge, Lak 2025 (pp. 249-259). US: ACM.
DOI
2025 Mehta, S., Srivastava, N., Liu, X., Vanacore, K., & Baker, R. S. (2025). Do MOOC conversations matter? investigating the role of social presence and course-relevant discussion in career advancement. In L@s 2025 Proceedings of the 12th ACM Conference on Learning @ Scale (pp. 236-240). US: ACM.
DOI
2025 Dai, Y., Vanacore, K., Baker, R., & Slater, S. (2025). Understanding MOOC stopout patterns: course and assessment-level insights. In L@s 2025 Proceedings of the 12th ACM Conference on Learning @ Scale (pp. 300-304). US: ACM.
DOI
2025 Shah, M., Pankiewicz, M., Baker, R. S., Chi, J., Xin, Y., Shah, H., & Fonseca, D. (2025). Students' use of an LLM-Powered virtual teaching assistant for recommending educational applications of games. In J. L. Plass (Ed.), Serious Games, Jcsg 2024 (pp. 19-24). US: Springer.
DOI
2025 Liu, X., Slater, S., Swanson, L., Metcalf, S. J., Gagnon, D. J., & Baker, R. S. (2025). Identifying When and Why Students Choose to Quit Jobs in a Science Exploration Game. In J. L. Plass (Ed.), Serious Games, Jcsg 2024 Vol. 15259 (pp. 56-69). US: Springer.
DOI
2025 Baker, R., Mills, C., & Choi, J. (2025). Difficulty of Achieving High Precision with Low Base Rates for High-Stakes Intervention. In Fifteenth International Conference On Learning Analytics and Knowledge, Lak 2025 (pp. 790-796). US: ACM.
DOI
2025 Baker, R., & Hutt, S. (2025). MORF: a Post-Mortem. In Fifteenth International Conference On Learning Analytics and Knowledge, Lak 2025 (pp. 797-802). US: ACM.
DOI
2025 Borchers, C., & Baker, R. S. (2025). ABROCA Distributions For Algorithmic Bias Assessment: considerations Around Interpretation. In Fifteenth International Conference On Learning Analytics and Knowledge, Lak 2025 (pp. 837-843). US: ACM.
DOI
2024 Cloude, E. B., Zhang, J., Baker, R. S., & Fouh, E. (2024). Procrastination vs. active delay: how students prepare to code in introductory programming. In Proceedings Of The 55th Acm Technical Symposium On Computer Science Education, Sigcse 2024, Vol. 1 (pp. 214-220). US: ACM.
DOI
2024 Pankiewicz, M., & Baker, R. S. (2024). Navigating compiler errors with AI assistance - a study of GPT hints in an introductory programming course. In Proceedings Of The 2024 Conference Innovation And Technology In Computer Science Education, Vol 1, Iticse 2024 (pp. 94-100). US: ACM.
DOI
2024 Svabensky, V., Pankiewicz, M., Zhang, J., Cloude, E. B., Baker, R. S., & Fouh, E. (2024). Comparison of three programming error measures for explaining variability in CS1 grades. In Proceedings Of The 2024 Conference Innovation And Technology In Computer Science Education, Vol 1, Iticse 2024 (pp. 87-93). US: ACM.
DOI
2024 Zambrano, A. F., Baker, R. S., Mehta, S., & Barany, A. (2024). Epistemic association rule networks: incorporating association rule mining into the quantitative ethnography toolbox. In Y. J. Kim (Ed.), Advances in Quantitative Ethnography (pp. 3-17). US: Springer.
DOI
2024 Liu, X., Zhang, J., Barany, A., Pankiewicz, M., & Baker, R. S. (2024). Assessing the potential and limits of large language models in qualitative coding. In Y. J. Kim (Ed.), Advances in Quantitative Ethnography (pp. 80-103). US: Springer.
DOI
2024 Borchers, C., Zhang, J., Baker, R. S., & Aleven, V. (2024). Using think-aloud data to understand relations between self-regulation cycle characteristics and student performance in intelligent tutoring systems. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 529-539). US: ACM.
DOI
2024 Cloude, E. B., Kumar, P., Baker, R. S., & Fouh, E. (2024). Novice programmers inaccurately monitor the quality of their work and their peers′ work in an introductory computer science course. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 35-45). US: ACM.
DOI
2024 Zambrano, A. F., & Baker, R. S. (2024). Long-term prediction from topic-level knowledge and engagement in mathematics learning. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 66-77). US: ACM.
DOI
2024 Zambrano, A. F., Zhang, J., & Baker, R. S. (2024). Investigating algorithmic bias on bayesian knowledge tracing and carelessness detectors. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 349-359). US: ACM.
DOI
2024 Belitz, C., Lee, H. J., Nasiar, N., Fancsali, S. E., Ritter, S., Almoubayyed, H., . . . Bosch, N. (2024). Hierarchical dependencies in classroom settings influence algorithmic bias metrics. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 210-218). US: ACM.
DOI
2024 Hutt, S., Depiro, A., Wang, J., Rhodes, S., Baker, R. S., Hieb, G., . . . Mills, C. (2024). Feedback on Feedback: comparing Classic Natural Language Processing and Generative AI to Evaluate Peer Feedback. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 55-65). US: ACM.
DOI
2024 Cloude, E. B., Munshi, A., Andres, J. M. A., Ocumpaugh, J., Baker, R. S., & Biswas, G. (2024). Exploring confusion and frustration as non-linear dynamical systems. In Fourteenth International Conference On Learning Analytics and Knowledge, Lak 2024 (pp. 241-252). US: ACM.
DOI
2024 Zambrano, A. F., Pankiewicz, M., Barany, A., & Baker, R. S. (2024). Ordered network analysis in CS education: unveiling patterns of success and struggle in automated programming assessment. In Proceedings Of The 2024 Conference Innovation And Technology In Computer Science Education, Vol 1, Iticse 2024 (pp. 443-449). US: ACM.
DOI
2024 Lee, F. M., Baker, R. S., Tomar, P. S., Kumari, K., Liang, Q., & Wei, Z. (2024). Videos for Parents and Child Performance. In Proceedings Of The Eleventh Acm Conference On Learning@scale, L@s 2024 (pp. 265-268). US: ACM.
DOI
2024 Shah, M., Baker, R. S., Granville, P., & Sharp, K. (2024). Examining student engagement in online learning platforms for promoting exam readiness and success in undergraduate nursing education. In Proceedings Of The Eleventh Acm Conference On Learning@scale, L@s 2024 (pp. 443-445). US: ACM.
DOI
2023 Liu, X., Slater, S., Andres, J. M. A. L., Swanson, L., Scianna, J., Gagnon, D., & Baker, R. S. (2023). Struggling to Detect Struggle in Students Playing a Science Exploration Game. In Chi Play 2023 Companion Proceedings of the Annual Symposium on Computer Human Interaction in Play (pp. 83-88). US: ACM.
DOI
2023 Wong, A. Y., Bryck, R. L., Baker, R. S., Hutt, S., & Mills, C. (2023). Using a webcam based eye-tracker to understand students' thought patterns and reading behaviors in neurodivergent classrooms. In Thirteenth International Conference On Learning Analytics and Knowledge, Lak2023 (pp. 453-463). ACM: US.
DOI
2023 Cloude, E. B., Baker, R. S., & Fouh, E. (2023). Online help-seeking occurring in multiple computer-mediated conversations affects grades in an introductory programming course. In Thirteenth International Conference On Learning Analytics and Knowledge, Lak2023 (pp. 378-387). US: ACM.
DOI
2023 Zhang, J., Baker, R. S., & Farmer, T. (2023). No benefit for high-dosage time management interventions in online courses. In Proceedings Of The Tenth Acm Conference On Learning @ Scale, L@s 2023 (pp. 302-305). US: ACM.
DOI
2023 Andres Bray, J. M., Hutt, S., & Baker, R. S. (2023). Exploring cross-country prediction model generalizability in MOOCs. In Proceedings Of The Tenth Acm Conference On Learning @ Scale, L@s 2023 (pp. 183-193). US: ACM.
DOI
2015 Kovanović, V., Gašević, D., Dawson, S., Joksimović, S., Baker, R. S., & Hatala, M. (2015). Penetrating the black box of time-on-task estimation. In ACM International Conference Proceeding Series Vol. 16-20-March-2015 (pp. 184-193). US: ACM.
DOI Scopus90

  • EdPsych FY25 UoSA - University of Minnesota, I-University of Minnesota, 30/04/2025 - 31/01/2027

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