Publications

Journal Publications

  • 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
[pdf] [journal page]

Full-Paper Publications

Peer Reviewed Conference Proceedings

  • Varatharaj, A., Botelho, A. F., Lu, X., Alphonsus, A. G., & Heffernan, N. T. (2020, July). Supporting Teacher Assessment in Chinese Language Learning Using Textual and Tonal Features. In Proceedings of the 21st International Conference on Artificial Intelligence in Education, (accepted)
[pdf pending]
  • 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.
[pdf]
  • 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.
[pdf]
  • Karumbaiah, S, Andres, J.M.A, Botelho, A. F., Baker, R. S., & Ocumpaugh, J. (2018, November). The Implications of a Subtle Difference in the Calculation of Affect Dynamics. In Proceedings of the 26th International Conference on Computers in Education, 29-38.
[Nominated for Best Paper Award] [pdf]
  • 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.
[16% Acceptance Rate] [Won Best Student Paper Award] [Nominated for Best Paper Award] [pdf]
  • Botelho, A. F., Baker, R. S., & Heffernan, N. T. (2017, June). Improving Sensor-Free Affect Detection Using Deep Learning. In International Conference on Artificial Intelligence in Education, 40-51. Springer, Cham.
[pdf]
  • Botelho, A., Wan, H., & Heffernan, N. (2015, March). The prediction of student first response using prerequisite skills. In Proceedings of the Second (2015) ACM Conference on Learning @ Scale, 39-45. ACM. (acceptance rate 25%)
[pdf]

Short-Paper Publications

Peer Reviewed Conference Proceedings

  • 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.
[pdf]
  • Adjei, S. A., Botelho, A. F., & Heffernan, N. T. (2017, March). Sequencing Content in an Adaptive Testing System: The Role of Choice. In Proceedings of the Seventh International Conference on Learning Analytics and Knowledge. (10.1145/3027385.3027412)
[pdf]
  • Adjei, S. A., Botelho, A. F., & Heffernan, N. T. (2016, April). Predicting student performance on post-requisite skills using prerequisite skill data: an alternative method for refining prerequisite skill structures. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, 469-473. ACM.
[pdf]
  • Botelho, A. F., Adjei, S. A., & Heffernan, N. T. (2016, June). Modeling Interactions Across Skills: A Method to Construct and Compare Models Predicting the Existence of Skill Relationships. In Proceedings of the Ninth International Conference on Educational Data Mining, 292-297. ACM
[pdf]

Book Chapters

Peer Reviewed and Invited Book Chapters

  • 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. Pages 101-108. ISBN 978-0-9977257-7-3. Available at: https://gifttutoring.org/documents/ .
[pdf]

Dissertation

Ph.D. Dissertation, Learning Science & Technologies, Worcester Polytechnic Institute

  • Botelho, A. (2019). Characterizing Productive Perseverance Using Sensor-Free Detectors of Student Knowledge, Behavior, and Affect. Retrieved from https://digitalcommons.wpi.edu/etd-dissertations/523
[pdf]

Poster Publications

Peer Reviewed Conference Proceedings

  • Lan, A. S., Botelho, A. F., Karumbaiah, S., Baker, R. S., & Heffernan, N. T. (2020, March). Accurate and Interpretable Sensor-free Affect Detectors via Monotonic Neural Networks. In Proceedings of the 10th International Conference on Learning Analytics and Knowledge. ACM
[pdf]
  • Varatharaj, A., Botelho, A. F., Lu, X., & Heffernan, N. T. (2019, July) Hao Fayin: Developing Automated Audio Assessment Tools for a Chinese Language Course. In Proceedings of the Twelfth International Conference on Educational Data Mining, 663-666.
[pdf]
  • Botelho, A. F., Baker, R. S., & Heffernan, N. T. (2019, July). Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Student Behavior and Affect. In Proceedings of the Twelfth International Conference on Educational Data Mining, 508-511.
[pdf]
  • Hulse, T., Harrison, A., Ostrow, K. S., Botelho, A. F., & Heffernan, N. T. (2018, July). Starters and Finishers: Predicting Next Assignment Completion From Student Behavior During Math Problem Solving. In Proceedings of the Eleventh International Conference on Educational Data Mining, 525-528.
[pdf]
  • Harrison, A, Wixon, N., Botelho, A. F., Arroyo, I. (2018, July). Sensor-Free Predictive Models of Affect in an Online Learning Environment. In Proceedings of the Eleventh International Conference on Educational Data Mining, 634-637.
[pdf]
  • Yin, B., Botelho, A. F., Patikorn, T., Heffernan, N. T., & Zou, J. (2017, June). Causal Forest vs. Naïve Causal Forest in Detecting Personalization: An Empirical Study in ASSISTments. In Proceedings of the Tenth International Conference on Educational Data Mining, 388-389.
[pdf]
  • Zhang, L., Xiong, X., Zhao, S., Botelho, A., & Heffernan, N. T. (2017, April). Incorporating Rich Features into Deep Knowledge Tracing. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale, 169-172. ACM.
[pdf]
  • Yin, B., Patikorn, T., Botelho, A. F., & Heffernan, N. T. (2017, April). Observing Personalizations in Learning: Identifying Heterogeneous Treatment Effects Using Causal Trees. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale, 299-302. ACM.
[pdf]
  • Zhao, S., Zhang, Y., Xiong, X., Botelho, A., & Heffernan, N. (2017, April). A Memory-Augmented Neural Model for Automated Grading. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale, 189-192. ACM.
[pdf] [extended pdf]
  • Patikorn, T., Selent, D., Heffernan, N. T., Yin, B., Botelho, A. (2016, October) ASSISTments Dataset for a Data Mining Competition to Improve Personalized Learning. In The Conference on Digital Experimentation (CODE) 2016, MIT, Cambridge, MA
[pdf] [conference page] [conference program]
  • Williams, J. J., Botelho, A., Sales, A., Heffernan, N., & Lang, C. (2016, June). Discovering ‘Tough Love’ Interventions Despite Dropout. In Proceedings of the Ninth International Conference on Educational Data Mining, 650-651. ACM
[pdf]
  • Botelho, A. F., Adjei, S. A., Wan, H., & Heffernan, N. T. (2015, June). Predicting Student Aptitude Using Performance History. In Proceedings of the Eighth International Conference on Educational Data Mining, 622-623. ACM
[pdf]

Conference Presentations and Workshops

Less-Strictly Peer Reviewed or Non-Archival

  • Botelho, A. F., Sales, A. C., Patikorn, T., & Heffernan, N.T. (2019, April). The ASSISTments TestBed: Opportunities and Challenges of Experimentation in Online Learning Platforms. In the 9th International Conference on Learning Analytics and Knowledge (LAK) Workshop on Learning Analytic Services to Support Personalized Learning and Assessment at Scale, Tempe, AZ.
[abstract] [link] [slides]
  • Sales, A. Botelho, A. F., Wu, E., Gagnon-Bartsch, J., Miratrix, L., Patikorn, T., & Heffernan, N. T. (2018, October). Combining Residualization Methods to Better Estimate Treatment Effects in Randomized Controlled Trials. In The Conference on Digital Experimentation (CODE) 2018, MIT, Cambridge, MA
[abstract] [link]
  • Botelho, A. F. (2018, July). Observing Persistence and Mental Effort in the Presence of Failure. In the 11th International Conference on Educational Data Mining, Buffalo, NY
[doctoral consortium paper]
  • Sales, A., Botelho, A. F., Patikorn, T., & Heffernan, N. T. (2018, May). Deep Learning, Auxiliary Data, and Randomization: Analyzing Experiments Run Within a Computerized Math Tutor. In The 2018 Atlantic Causal Inference Conference, Pittsburgh, PA.
[abstract] [link]
  • Adjei, S. A., Botelho, A. F., Patikorn, T., Yin, B., & Beck, J. E. (2017, June). Using "Snapshots" of Student Performance to Model Wheel Spinning. In the Tenth International Conference on Educational Data Mining, Wuhan, Hubei, China.
[workshop paper]
  • Botelho, A. F. & Heffernan, N. T. (2016, May). Sharing Data Across Experiments. In The 2016 Atlantic Causal Inference Conference, New York City, NY
[link]