In a world where information is abundant, and generative AI can produce polished answers almost instantly, the value of historical education cannot simply be the acquisition of more information. History is training in judgment. Students learn to ask good questions, evaluate incomplete and competing evidence, distinguish what can be known from what must be inferred, revise interpretations when the evidence demands it, and communicate responsible arguments of their own. I want students to leave my courses with greater intellectual agency: more capable of investigating questions for themselves, deciding what they believe and why, recognizing the limits of their knowledge, and navigating a world saturated with claims and information.
My emerging scholarship of teaching and learning grows from the same question that shapes my classroom: What capacities should the study of history give a person? I am particularly interested in historical thinking, source-centered assessment, experiential and place-based learning, and the future of history education in the age of generative AI.
My courses require students to actually practice history. In class, they encounter and grapple with primary sources, interpretation, argumentation, uncertainty, revision, and communication. I design assignments that ask students to make their reasoning visible. I want to know: What evidence brought you there? Why does that evidence matter? What can this source tell us, and what can’t it tell us? What might complicate your interpretation? Rather than rewarding students primarily for reproducing historical information, I want to reward the intellectual work historians actually perform. In my classroom, uncertainty is part of the discipline. Historians rarely possess perfect evidence, and learning to make careful judgments under imperfect conditions is one of the most transferable skills historical study can provide.
I am currently developing a History Lab course where students encounter the different environments where historical knowledge is created, preserved, interpreted, and contested. Archives, museums, historic sites, cemeteries, monuments, oral history interviews, and the built environment become laboratories for practicing particular historical skills. Students should come to understand that history does not simply exist in a textbook waiting to be learned. Someone asked a question, found evidence, decided what counted as evidence, confronted gaps and contradictions, constructed an interpretation, and communicated it to someone else. Then they learn to do the same.
Generative AI has revealed a longstanding problem in education that has now become impossible to ignore: an assignment can produce a polished product without necessarily producing meaningful learning.
I am therefore increasingly interested in assessment that centers process rather than performance alone. My response to AI is not to attempt to recreate a classroom in which these technologies do not exist. Instead, I ask what kinds of historical work remain educationally valuable precisely because they require judgment, context, interpretation, interaction with particular evidence, and the ability to explain one’s reasoning.
This includes source-centered analysis, iterative argumentation, place-based research, oral work, reflection, and assignments in which students must demonstrate how their thinking developed.
Rather than assume the miserable job of policing AI use, I believe it is more useful to ask: What intellectual work do I actually want a student to do, and how can I design an assessment that makes that work matter?