GenAI Insights Hub

Contributing Authors: Melanie Kurimchak, Learning Data Insights | Aaron Wong, University of Minnesota | Maggie Beiting-Parish, CUNY Graduate Center/EdAIfy | Kristen DiCerbo, Khan Academy | John Whitmer, Learning Data Insights AI Disclosure: NotebookLM was used in the initial drafting of this post, human editing and review conducted throughout.  We are documenting our work building an evidence hub for AI in educational assessment. All content CC BY-SA. Read the welcome post .

Contributing Authors: Melanie Kurimchak  | John Whitmer AI Disclosure: Claude Sonnet v4.5 was used in the initial drafting of this post, human editing and review conducted throughout. Welcome to the GenAI Evidence Insights Hub. In this blog, we will openly document the complex, imperfect, and often challenging work of building a robust evidence base for Generative AI (GenAI) in education assessment. We are doing this work in public because we believe that GenAI has tremendous promise for these applications. The flexibility of this new technology and speed at which innovations can be created calls for increased measurement – to make sure that learners & teachers have high-quality materials and to distinguish research-backed results from “AI slop.” There is a proliferation of research being conducted to help us to use methods that work and identify new areas of practice. What This Blog Is This blog is the behind the scenes record of the GenAI Evidence Hub for Educational Assessm...