Publications

Conference Full Papers

Gurung, A., Lee, M. P., Baral, S., Vanacore, K. P., McReynolds, A. A., Kreisberg, H., Heffernan, C., Haim, A., Smearsoll, N., Sales, A. C., & Heffernan, N. T. (2022, July 22). How Common are Common Wrong Answers? Crowdsourcing Remediation at Scale. In Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23). Association for Computing Machinery, New York, NY, USA, 70–80. https://doi.org/10.1145/3573051.3593390

Authors

Ashish Gurung

Morgan P. Lee

Sami Baral

Kirk P. Vanacore

Andrew A. McReynolds

Hilary Kreisberg

Christina Heffernan

Aaron Haim (me)

Nathan Smearsoll

Adam C. Sales

Neil T. Heffernan

Prihar, E., Haim, A., Shen, T., Sales, A. C., Lee, D., Wu, X., & Heffernan, N.. (2023, July 22). Investigating the Impact of Skill-Related Videos on Online Learning. In Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23). Association for Computing Machinery, New York, NY, USA, 4–13. https://doi.org/10.1145/3573051.3593376

Associated Links

OSF Project: https://doi.org/10.17605/osf.io/cxkzf

Haim, A., Gyurcsan, R., Baxter, C., Shaw, S. T., & Heffernan, N. T., III. (2023, July 21). How to Open Science: Analyzing the Open Science Statement Compliance of the Learning @ Scale Conference. In Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23). Association for Computing Machinery, New York, NY, USA, 174–182. https://doi.org/10.1145/3573051.3596166

Associated Links

OSF Project: https://doi.org/10.17605/osf.io/pj3te

Authors

Aaron Haim (me)

Robert Gyurcsan

Chris Baxter

Stacy T. Shaw

Neil T. Heffernan

Haim, A., Gyurcsan, R., Baxter, C., Shaw, S. T., & Heffernan, N. T., III. (2023, July 11). How to Open Science: Debugging Reproducibility within the Educational Data Mining Conference. Proceedings of the 16th International Conference on Educational Data Mining (EDM ‘23), 114–124, July 11-14, 2023, Indian Institute of Science Campus, Bengalaru, India. https://doi.org/10.5281/zenodo.8115651

Associated Links

OSF Project: https://doi.org/10.17605/osf.io/unhyp

Authors

Aaron Haim (me)

Robert Gyurcsan

Chris Baxter

Stacy T. Shaw

Neil T. Heffernan

Haim, A., Shaw, S. T., & Heffernan, N. T., III. (2023, March 16). How to Open Science: A Principle and Reproducibility Review of the Learning Analytics and Knowledge Conference. In Proceedings of the 13th International Learning Analytics and Knowledge Conference (LAK ‘23), March 13-17, 2023, Arlington, Texas, USA. https://doi.org/10.1145/3576050.3576071

Awards and Honors

Best Full Paper Nominee

Honorable Mention

Authors

Aaron Haim (me)

Stacy T. Shaw

Neil T. Heffernan

Prihar, E., Haim, A., Sales, A. C., & Heffernan, N. (2022, June). Automatic Interpretable Personalized Learning. In Proceedings of the Ninth ACM Conference on Learning @ Scale (L@S ’22), June 1–3, 2022, New York City, NY, USA. 1-11. https://doi.org/10.1145/3491140.3528267

Awards and Honors

Best Paper Nominee

Best Dataset

Associated Links

OSF Project: https://doi.org/10.17605/osf.io/9pgv5

Poster Papers

Haim A., & Heffernan, N. (2022, July). Student Perception on the Effectiveness of On-Demand Assistance in Online Learning Platforms. Proceedings of the 15th International Conference on Educational Data Mining (EDM '22), July 24-27, 2022, Durham, England, UK. 734–737. https://doi.org/10.5281/zenodo.6853053

Associated Links

OSF Project: https://doi.org/10.17605/osf.io/f8w9p

Authors

Aaron Haim (me)

Neil T. Heffernan

Workshops and Tutorials

Haim, A., Shaw, S. T., & Heffernan, N. T., III. (2023, July 20). How to Open Science: Promoting Principles and Reproducibility Practices within the Learning @ Scale Community. In Proceedings of the Tenth ACM Conference on Learning @ Scale (L@S '23). Association for Computing Machinery, New York, NY, USA, 248–250. https://doi.org/10.1145/3573051.3593398

Authors

Aaron Haim (me)

Stacy T. Shaw

Neil T. Heffernan

Haim, A., Shaw, S. T., & Heffernan, N. T., III. (2023, July 14). How to Open Science: Promoting Principles and Reproducibility Practices within the Educational Data Mining Community. Presented at the 16th International Conference on Educational Data Mining (EDM ‘23), 582–584, July 11-14, 2023, Indian Institute of Science Campus, Bengalaru, India. https://doi.org/10.5281/zenodo.8115776

Authors

Aaron Haim (me)

Stacy T. Shaw

Neil T. Heffernan

Haim, A., Shaw, S. T., & Heffernan, N. T., III. (2023, July 3). How to Open Science: Promoting Principles and Reproducibility Practices Within the Artificial Intelligence in Education Community. In: Wang, N., Rebolledo-Mendez, G., Dimitrova, V., Matsuda, N., Santos, O.C. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2023. Communications in Computer and Information Science, vol 1831. Springer, Cham. https://doi.org/10.1007/978-3-031-36336-8_11

Authors

Aaron Haim (me)

Stacy T. Shaw

Neil T. Heffernan

Haim, A., Shaw, S. T., & Heffernan, N. T., III. (2023, March 13-14). How to Open Science: Promoting Principles and Reproducibility Practices within the Learning Analytics Community. Presented at the 13th International Learning Analytics and Knowledge Conference (LAK '23), March 13-17, 2023, Arlington, Texas, USA. https://lak2023-tutorial.howtoopenscience.com. Accessible at https://doi.org/10.17605/osf.io/kyxba.

Authors

Aaron Haim (me)

Stacy T. Shaw

Neil T. Heffernan

Haim, A., Shaw, S. T., & Heffernan, N. T., III. (2023, March 10). Understanding Licenses, Terms of Use/Service, and Private Policies. Presented at the Unconference 2023: Open Scholarship Practices in Education Research (Unconference ‘23), March 9-10, 2023. Accessible at https://osf.io/f784k/

Authors

Aaron Haim (me)

Stacy T. Shaw

Neil T. Heffernan

Extended Abstracts

Haim, A., Prihar, E., Shaw, S. T., Sales, A. C., & Heffernan, N. T., III. (2022, October 20). Expansion on Exploring Common Trends in Online Educational Experiments. Presented at the 2022 Conference on Digital Experimentation @ MIT (CODE@MIT '22), October 20-21, 2022, Boston, MA, US. Accessible at https://doi.org/10.17605/osf.io/m2jqe

Doctoral Consortiums

Haim, A., Prihar, E., Heffernan, N.T. (2022, July). Toward Improving Effectiveness of Crowdsourced, On-Demand Assistance from Educators in Online Learning Platforms. In: Rodrigo, M.M., Matsuda, N., Cristea, A.I., Dimitrova, V. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium. AIED 2022. Lecture Notes in Computer Science, vol 13356. Springer, Cham. https://doi.org/10.1007/978-3-031-11647-6_5

Authors

Aaron Haim (me)

Ethan Prihar

Neil T. Heffernan