Platform-based Adaptive Experimental Research in Education
Adaptive Experimentation is one of the most promising approaches to support complex decision-making in learning experience design and delivery. This paper reports on our experience with a real-world, multi-experimental evaluation of an adaptive experimentation platform within the XPRIZE Digital Learning Challenge framework, and summarizes data-driven lessons learned and best practices for Adaptive Experimentation in education. We outline key scenarios of the applicability of platform-supported experiments and reflect on lessons learned from this two-year project, focusing on implications relevant to platform developers, researchers, practitioners, and policy stakeholders to integrate Adaptive Experiments in real-world courses.
Authors
- Steven Moore (ORCID: https://orcid.org/0000-0002-5256-0339)
- Haochen Song (ORCID: https://orcid.org/0009-0006-7825-4993)
- Michael Liut (ORCID: https://orcid.org/0000-0003-2965-5302)
- Ilya Musabirov (ORCID: https://orcid.org/0000-0003-2246-0094)
- Mohi Reza (ORCID: https://orcid.org/0000-0001-9668-3384)
- Anna N. Rafferty
- Harsh Kumar (ORCID: https://orcid.org/0000-0003-2878-3986)
- John Stamper (ORCID: https://orcid.org/0000-0002-2291-1468)
- Thomas Price (ORCID: https://orcid.org/0000-0001-9375-2292)
- Joseph Jay Williams (ORCID: https://orcid.org/0000-0002-9122-5242)
- Audrey Durand (ORCID: https://orcid.org/0000-0001-9290-8603)
- Nina Deliu (ORCID: https://orcid.org/0000-0003-2501-8795)
- Tong Li (ORCID: https://orcid.org/0000-0003-1345-6675)
- Norman Bier (ORCID: https://orcid.org/0009-0003-3666-3973)
- Pan Chen (ORCID: https://orcid.org/0000-0001-7569-9504)
Institutions
- North Carolina State University (US)
- University of Toronto (CA)
- Carleton College (US)
- Université Laval (CA)
- Carnegie Mellon University (US)
- Sapienza University of Rome (IT)
Publication Details
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1145/3706468.3706471
- Citations
- 1
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 4.17