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Faculty Anthony Botelho

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Anthony Botelho 

Assistant Professor

Anthony Botelho

Phone

352-273-4214

Email

abotelho@coe.ufl.edu

Address

PO Box 117048
Gainesville, FL 32611

Connect

LinkedIn

About

Anthony Botelho, Ph.D., is Assistant Professor of Educational Technology and CS Education in the School of Teaching and Learning at UF and Director of the VIABLE Lab (Versatile Innovations in Affect, Behavior, and Learning Engineering). His research advances the science and responsible application of artificial intelligence to improve how students learn across educational contexts. He develops and deploys human-centered AI systems that both generate new insight into learning processes and meaningfully augment instructional practice. Dr. Botelho’s work integrates theory, methodology, and application across education, cognitive psychology, artificial intelligence, and computer science. He leverages advanced quantitative approaches including learning analytics, machine learning, natural language processing, multimodal modeling, and causal inference to examine cognitive, behavioral, and affective dimensions of learning across education contexts.

Supported by multiple federal and philanthropic agencies, his scholarship contributes to research and training initiatives in data science and AI for education while helping shape international research standards in the field. Through interdisciplinary collaboration with educators, researchers, and institutional leaders, he designs and refines human-in-the-loop systems that promote impactful uses of AI. Dr. Botelho works to advance scalable innovations that bridge science with real-world educational transformation.

Affiliations

  • School of Teaching and Learning
  • Institute for Advanced Learning Technologies

Research Interests

Assessment and Evaluation, Behavior, Causal Inference, Cognition, Collaboration and Teaming, Design and Development of Educational Technology Interventions, Dropout Prevention, Educational / Instructional Design, Emerging Technologies, Emotion, Experimental and Quasi-Experimental Design and Analysis, Language, Learning Culture and Technology, Longitudinal Data Analysis, Mathematical Modeling, Mathematics Education, Mixed Methods, Motivation, Multilevel Model, Quantitative Research, Stealth Assessment, Theoretical Perspectives

Education

  • Ph.D. in Learning Science and Technologies, 2019- Worcester Polytechnic Institute
  • M.S. in Computer Science, 2015- Worcester Polytechnic Institute
  • B.A. in Interactive Media and Game Development, 2013- Becker College

Professional Appointments

  • Assistant Professor, School of Teaching and Learning, University of Florida, 2021–Present.
  • Program Co-Chair, Elected Leadership Role for the International Conference on Educational Data Mining (EDM), 2026.
  • Senior Program Committee Member, Editorial-Level Review and Meta-Review Leadership Role for the Learning Analytics & Knowledge (LAK) Conference, 2024-Present.
  • Senior Program Committee Member, Editorial-Level Review and Meta-Review Leadership Role for the Artificial Intelligence in Education (AIED) Conference, 2025-Present.
  • Senior Program Committee Member, Editorial-Level Review and Meta-Review Leadership Role for the Educational Data Mining (EDM) Conference, 2022-Present.
  • Affiliate Faculty, Institute for Advanced Learning Technologies, University of Florida.
  • Affiliate Faculty, Lastinger Center for Learning, University of Florida.
  • Affiliate Faculty, CS Everyone Center, University of Florida.
  • Affiliate Faculty, Warren B. Nelms Institute for the Connected World, University of Florida.

Activities and Honors

  • Best Student Paper Award, American Educational Research Association (AERA) Annual Meeting, 2026.
  • Best Student Paper Award Nomination, American Educational Research Association (AERA) Annual Meeting, 2026.
  • Catalyst Prize, Learning Engineering Tools Competition (CHECKPOINT), 2025.
  • Emerging Learning Technology Award, Association for Educational Communications and Technology (AECT), Division of Emerging Learning Technologies (DELT), 2025.
  • Best Poster Nominee, 26th International Conference on Artificial Intelligence in Education (AIED), 2025.
  • OpenAI Research Catalyst Award, InterLearn: Advancing Fair and Adaptive Educational Technologies, 2024.
  • Best Paper Nomination, 32nd International Conference on Computers in Education (ICCE), 2024.
  • Best Short Paper Nomination, 16th International Conference on Educational Data Mining (EDM), 2023.
  • Best Paper Nomination, 14th International Conference on Educational Data Mining (EDM), 2021.
  • Best Paper Nomination, 11th International Conference on Learning Analytics & Knowledge (LAK), 2021.
  • Best Student Paper Award, 11th International Conference on Educational Data Mining (EDM), 2018.

Selected Grants

CHECKPOINT: Misconception-Focused Assessment Generation

Role
  • PI
Funding Agency
  • Learning Engineering Tools Competition
Project Period
  • 2025-2026
Award Amount
  • $50,000

ALTER-Math: AI-Augmented Learning by Teaching to Enhance and Renovate Math Learning

Role
  • Co-PI
Funding Agency
  • Learning Engineering Virtual Institute
Project Period
  • 2023-2027
Award Amount
  • $9,999,996

EAGER: Orchestrating Productive Collaboration Among Students in Mathematics with Multimodal Machine Learning

Role
  • PI
Funding Agency
  • National Science Foundation (NSF)
Project Period
  • 2023-2025
Award Amount
  • $299,623

Data Science Methods for Digital Learning Platforms Training Program

Role
  • Co-PI
Funding Agency
  • Institute of Education Sciences (IES)
Project Period
  • 2023-2026
Award Amount
  • $795,312

Tech-Enabled Teacher Supports: Teachley

Role
  • Co-PI
Funding Agency
  • Gates Foundation
Project Period
  • 2024-2026
Award Amount
  • $1,000,000

PRODUCTIVE: AI Math Problem-Solving Platform for Productive Failure

Role
  • Co-PI
Funding Agency
  • Gates Foundation
Project Period
  • 2024-2025
Award Amount
  • $451,563

Cyberlearning & Future of Learning Technologies: Putting Teachers in the Driver\'s Seat Using Machine Learning to Personalize Interactions with Students (DRIVER-SEAT)

Role
  • PI
Funding Agency
  • National Science Foundation (NSF)
Project Period
  • 2018-2021
Award Amount
  • $764,317

Collaborative Research: Frameworks: Cyber Infrastructure for Shared Algorithmic and Experimental Research in Online Learning

Role
  • Co-PI
Funding Agency
  • National Science Foundation
Project Period
  • 2019-2024
Award Amount
  • $1,891,611

USE EHR: Improving Undergraduate Algorithms Instructing with Online Feedback: ADVISOR

Role
  • Co-PI
Funding Agency
  • National Science Foundation
Project Period
  • 2019-2022
Award Amount
  • $299,059

DIBBs: PD: Enhancing and Personalizing Educational Resources through Tools for Experimentation

Role
  • Co-PI
Funding Agency
  • National Science Foundation
Project Period
  • 2017-2020
Award Amount
  • $544,644

Selected Publications

Books / Book Chapters
  • Baral, S., Cheng, L., Botelho, A.F., & Heffernan, N.T. (2026). Advancing automated assessment for open-ended questions in mathematics. In E. Geraniou, C. Crisan, & M. Mavrikis (Eds.), Digital Technology and Artificial Intelligence in Mathematics Education Assessment. Routledge. ISBN 9781032876528.
  • Cheng, L., Prihar, E., Baral, S., Gurung, A., Botelho, A. F., Haim, A., Heffernan, C., Patikorn, T., Sales, A., & Heffernan, N. T. (2023). Authoring Tools for Crowdsourcing from Teachers to Enhance Intelligent Tutoring Systems. In Design Recommendations for Intelligent Tutoring Systems: Volume 11 – Intelligent Tutoring System Applications for Professional Career Education. (pp. 115-125). ISBN 978-0-9977258-5-8.
  • Botelho, A. F. & Heffernan, N. T. (2019). Crowdsourcing Feedback to Support Teachers and Students. In Sinatra, A.M., Graesser, A.C., Hu, X., Brawner, K., and Rus, V. (Eds.). (2019). Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Self-Improving Systems. Orlando, FL: U.S. Army Research Laboratory. (pp. 101-108). ISBN 978-0-9977257-7-3. Available at: https://gifttutoring.org/documents/.
Articles
  • Lee, S. M., Baral, S., Li, H., Cheng, L., Zhang, S., Thorp, C. S., St. John, J., Thompson, T., Heffernan, N. T., & Botelho, A. F (2025). Developing a Feedback Taxonomy for Math: A Synergy of Perspectives through Data Mining Methods. Journal of Educational Data Mining, 17(1), 337-360.
  • Closser, A. H., Sales, A., & Botelho, A. F. (2024) Should We Account for Classrooms? Analyzing Online Experimental Data with Student-level Randomization. Journal of Educational Technology Research and Development, 1-30. doi: https://doi.org/10.1007/s11423-023-10325-x
  • Botelho, A. F., Baral, S., Erickson, J. A., Benachamardi, P., & Heffernan, N. T. (2023). Leveraging Natural Language Processing to Support Automated Assessment and Feedback for Student Open Responses in Mathematics. Journal of Computer Assisted Learning, 39, 823-840. doi: https://doi.org/10.1111/jcal.12793
  • Gurung, A., Botelho, A.F., Thompson, R., Sales, A.C., Baral, S., & Heffernan, N.T. (2022). Considerate, Unfair, or Just Fatigued? Examining Factors that Impact Teacher Grading. In Proceedings of the 30th International Conference on Computers in Education, 197-206.
  • Botelho, A.F., Prihar, E., & Heffernan, N.T. (2022. Deep Learning or Deep Ignorance? Comparing Untrained Recurrent Models in Educational Contexts. In Proceedings of the 23rd International Conference on Artificial Intelligence in Education, 281-293. Springer, Cham.
Presentations
  • Newell, B., Wang, X., Ritzhaupt, A., Botelho, A., Wusylko, C., Ganapathy Prasad, P., Cisternas-Garcia, L., Kohnen, A., & Cen, K. (2026). Mapping the dimensions of AI literacy self-efficacy among middle schoolers: An exploratory factor analysis. In the American Educational Research Association (AERA) Annual Meeting 2026 , Los Angeles, CA, United States.
  • Lee, S., Zhang, S., Li, H., & Botelho, A. (2026). Designing for procedural flexibility with collaborative digital whiteboards: A case study of middle school algebra. In the American Educational Research Association (AERA) Annual Meeting 2026 , Los Angeles, CA, United States.
  • Li, H., Zhang, S., Lee, S., Trexler, M., & Botelho, A. F. (2025). LOGEN AI: Implementing a Transparent Human-AI Collaborative Tool for Enhanced Instructional Design. In the Association for Educational Communications and Technology (AECT) International Convention 2025, Las Vegas, NV, USA.
  • Lee, S., Li, H., Zhang, S., Zhong, Z., Lee, J. E., & Botelho, A. F. (2025). So What Now? AI-Augmented Sense-Making in Action: An Interactive Dashboard for Collaborative Mathematics Learning. In the 26th International Conference on Artificial Intelligence in Education (AIED 2025) Interactive Events Track, Palermo, Italy.
Other Publications
  • Zhang, S., Li, H., Lee, S. M., Schroeder, N. L., & Botelho, A. F. (2025). VETTING AI for Deeper Learning: Constraining LLMs to Encourage Student Inquiry. In International Conference on Artificial Intelligence in Education, 266-273.
  • Rahimi, S., Ercan, D., Gao, R., Esmaeiligoujar, S., Babaee, M., Li, H., Zhang, S., Lee, S., Closser, A.H., & Botelho, A.F. (2025). ProductiveMath: A Generative-AI-Powered App to Support Productive Failure Teaching. In Proceedings of the 26th International Conference on Artificial Intelligence in Education, 344-351.
  • Zhang, S., Li, H., Li, H., Botelho, A.F., & Israel, M. (2024). Investigating the Dynamic Change of Pre- and In-service Teachers\' Experiences, Attitudes, and Perceptions through CS Autobiography Using Topic Modeling. Proceedings of the 17th International Conference on Educational Data Mining, 921-926. https://doi.org/10.5281/zenodo.12729999
  • Botelho, A. F. & Heffernan, N. T. (2019). Crowdsourcing Feedback to Support Teachers and Students. In Sinatra, A.M., Graesser, A.C., Hu, X., Brawner, K., and Rus, V. (Eds.). Design Recommendations for Intelligent Tutoring Systems: Volume 7 - Self-Improving Systems. Orlando, FL: U.S. Army Research Laboratory. Pages 101-108. ISBN 978-0-9977257-7-3
  • Erickson, J., Botelho, A. F., McAteer, S., Varatharaj, A., & Heffernan, N. T. (2020, March). The Automated Grading of Student Open Responses in Mathematics. In Proceedings of the 10th International Conference on Learning Analytics and Knowledge, 615-624. ACM.
  • Botelho, A. F., Varatharaj, A., Patikorn, T., Doherty, D., Adjei, S. A., Beck, J. E. (2019). Developing Early Detectors of Student Attrition and Wheel Spinning Using Deep Learning. Journal of IEEE Transactions on Learning Technologies. Volume 12(2), pp. 158-170. doi: 10.1109/TLT.2019.2912162
  • Botelho, A. F., Varatharaj, A., VanInwegen, E., & Heffernan, N. T. (2019, March). Refusing to Try: Characterizing Early Stopout on Student Assignments. In Proceedings of the 9th International Conference on Learning Analytics and Knowledge, 391-400. ACM.
  • Botelho, A. F., Baker, R. S., Ocumpaugh, J., & Heffernan, N. T. (2018, July). Studying Affect Dynamics and Chronometry Using Sensor-Free Detectors. In Proceedings of the 11th International Conference on Educational Data Mining, 157-166.
  • Sales, A., Botelho, A. F., Patikorn, T., & Heffernan, N. T. (2018, July). Using Big Data to Sharpen Design-Based Inference in A/B Tests. In Proceedings of the Eleventh International Conference on Educational Data Mining, 479-485.
  • Botelho, A. F., Baker, R. S., & Heffernan, N. T. (2017, June). Improving Sensor-Free Affect Detection Using Deep Learning. In Proceedings of the 18th International Conference on Artificial Intelligence in Education, 40-51. Springer, Cham.

Selected Links