Selent, D. (2017). Creating Systems and Applying Large-Scale Methods to Improve Student Remediation in Online Tutoring Systems in Real-time and at Scale. (Dissertation) [PDF]
Patikorn, T., Selent, D., Beck, J., Heffernan, N., & Zhou, J. (2017, January). Using a single model trained across multiple experiments to improve the detection of treatment effects. In 10th International Conference on Educational Data Mining. [PDF]
Dommeti, V., Selent, D. (2017). Applying and Exploring Bayesian Hypothesis Testing for Large Scale Experimentation in Online Learning Systems. In Proceedings of the Fourth ACM Conference on Learning@Scale. [PDF]
Patikorn, T., Selent, D., Heffernan, N. T., Yin, B., Botelho, A. (2016) ASSISTments Dataset for a Data Mining Competition to Improve Personalized Learning. Poster at the Conference on Digital Experimentation at MIT 2016. [PDF]
Selent, D., Patikorn, T., & Heffernan, N. (2016, April). ASSISTments Dataset from Multiple Randomized Controlled Experiments. In Proceedings of the Third (2016) ACM Conference on Learning@ Scale (pp. 181-184). ACM. [PDF]
Ostrow, K., Selent, D., Wang, Y., Van Inwegen, E., Heffernan, N., & Williams, J.J. Assessment of Learning Infrastructure (ALI): The Theory, Practice, and Scalability of Automated Assessment. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. ACM, 2016. [PDF]
Heffernan, N.T., Ostrow, K.S., Kelly, K., Selent, D., Van Inwegen, E.G., Xiong, X., & Williams, J.J. (2016). The Future of Adaptive Learning: Does the Crowd Hold the Key? International Journal of Artificial Intelligence in Education. Springer New York. DOI: 10.1007/s40593-016-0094-z. [PDF]
Selent, D., & Heffernan, N. (2015, June). When More Intelligent Tutoring in the Form of Buggy Messages Does not Help. In Artificial Intelligence in Education (pp. 768-771). Springer International Publishing. [PDF]
Adjei, S., Selent, D., Heffernan, N., Pardos, Z., Broaddus, A., & Kingston, N. (2014, July). Refining Learning Maps with Data Fitting Techniques: Searching for Better Fitting Learning Maps. In Educational Data Mining 2014. [PDF]
Selent, D., & Heffernan, N. (2014, January). Reducing Student Hint Use by Creating Buggy Messages from Machine Learned Incorrect Processes. In Intelligent Tutoring Systems (pp. 674-675). Springer International Publishing. [PDF]
Selent, D. (2011). Clue Computer Game. Rivier Academic Journal, 7(2). [PDF]
Selent, D. (2011). The design and complexity analysis of the light-up puzzle program: faculty poster. Journal of Computing Sciences in Colleges, 26(6), 187-189. [PDF]
Selent, D. (2010). Advanced encryption standard. Rivier Academic Journal, 6(2). [PDF]