| Mathbert: A pre-trained language model for general nlp tasks in mathematics education JT Shen, M Yamashita, E Prihar, N Heffernan, X Wu, B Graff, D Lee arXiv preprint arXiv:2106.07340, 2021 | 78 | 2021 |
| Classifying math knowledge components via task-adaptive pre-trained BERT JT Shen, M Yamashita, E Prihar, N Heffernan, X Wu, S McGrew, D Lee Artificial Intelligence in Education: 22nd International Conference, AIED …, 2021 | 28 | 2021 |
| Toward personalizing students' education with crowdsourced tutoring E Prihar, T Patikorn, A Botelho, A Sales, N Heffernan Proceedings of the Eighth ACM Conference on Learning@ Scale, 37-45, 2021 | 27 | 2021 |
| Comparing different approaches to generating mathematics explanations using large language models E Prihar, M Lee, M Hopman, AT Kalai, S Vempala, A Wang, G Wickline, ... International Conference on Artificial Intelligence in Education, 290-295, 2023 | 22 | 2023 |
| Exploring common trends in online educational experiments E Prihar, M Syed, K Ostrow, S Shaw, A Sales, N Heffernan Proceedings of the 15th International Conference on Educational Data Mining, 2022 | 19 | 2022 |
| Automatic interpretable personalized learning E Prihar, A Haim, A Sales, N Heffernan Proceedings of the Ninth ACM Conference on Learning@ Scale, 1-11, 2022 | 13 | 2022 |
| Extending engine gas path analysis using full flight data L Tang, AJ Volponi, E Prihar Turbo Expo: Power for Land, Sea, and Air 58677, V006T05A004, 2019 | 12 | 2019 |
| The Effect of an Intelligent Tutor on Performance on Specific Posttest Problems. A Sales, E Prihar, N Heffernan, JF Pane International Educational Data Mining Society, 2021 | 11 | 2021 |
| Cyther: a human-playable, self-tuning robotic zither. S Barton, E Prihar, P Carvalho NIME, 319-324, 2017 | 8 | 2017 |
| Toward improving effectiveness of crowdsourced, on-demand assistance from educators in online learning platforms A Haim, E Prihar, NT Heffernan International Conference on Artificial Intelligence in Education, 29-34, 2022 | 6 | 2022 |
| Using Auxiliary Data to Boost Precision in the Analysis of A/B Tests on an Online Educational Platform: New Data and New Results AC Sales, EB Prihar, JA Gagnon-Bartsch, NT Heffernan arXiv preprint arXiv:2306.06273, 2023 | 5 | 2023 |
| A Bandit You Can Trust E Prihar, A Sales, N Heffernan Proceedings of the 31st ACM Conference on User Modeling, Adaptation and …, 2023 | 3 | 2023 |
| More powerful a/b testing using auxiliary data and deep learning AC Sales, E Prihar, J Gagnon-Bartsch, A Gurung, NT Heffernan International Conference on Artificial Intelligence in Education, 524-527, 2022 | 3 | 2022 |
| Identifying struggling students by comparing online tutor clickstreams E Prihar, A Moore, N Heffernan International Conference on Artificial Intelligence in Education, 290-295, 2021 | 3 | 2021 |
| Assessing the ability of Large Language Models in Generating Mathematics Explanations A Wang, E Prihar, N Heffernan Learning@ Scale (L@ S’23), July 20–22, 2023, Copenhagen, Denmark., 2023 | 2 | 2023 |
| Identifying explanations within student-tutor chat logs E Prihar, A Moore, N Heffernan Proceedings of the 15th International Conference on Educational Data Mining, 773, 2022 | 2 | 2022 |
| Can Large Language Models Generate Middle School Mathematics Explanations Better Than Human Teachers? A Wang, E Prihar, A Haim, N Heffernan International Conference on Artificial Intelligence in Education, 242-250, 2024 | 1 | 2024 |
| Effective Evaluation of Online Learning Interventions with Surrogate Measures E Prihar In The Proceedings of the 16th International Conference on Educational Data …, 2023 | 1 | 2023 |
| The great challenges and opportunities of the next 20 years MMT Rodrigo, J Vassileva, HC Lane, P Brusilovsky, S Sosnovsky, ... Handbook of Artificial Intelligence in Education, 606-649, 2023 | 1 | 2023 |
| Deep Learning or Deep Ignorance? Comparing Untrained Recurrent Models in Educational Contexts AF Botelho, E Prihar, NT Heffernan International Conference on Artificial Intelligence in Education, 281-293, 2022 | 1 | 2022 |
