Stacey Alicea and Meghan McCormick argue that traditional randomized controlled trials move too slowly to evaluate fast-evolving AI education tools. They propose an ‘implementation research and development’ approach emphasizing rapid testing, feedback, and refinement to build evidence before large-scale adoption. The authors recommend building evidence in stages, examining how tools function before measuring outcomes, and letting research questions—not convention—determine methodology.
