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| This fall I have redesigned my W101 to experiment with new methods of assessment given that many students will use AI to write their essays. Because the quality of a written artifact is no longer necessarily a sign of student learning or a reflection of their ideas, I have shifted some of my assessment criteria to focus on evidence of student learning. I am also using class time to ensure that students perform some tasks without the aid of AI.
My first essay assignment is an example. Students will write the first draft of each essay in an 80-minute class period. They then revise that draft outside of class. I have a liberal AI policy (see syllabus) that allows students to use AI in any way they wish as long as they are honest about their use. Students submit a portfolio of documents: the in-class draft, the final essay, transcripts of all AI conversations, and a notebook that they use in class to take notes. My rubric for the essay assesses the typical components of an academic essay, but I have included two new categories: “voice” and “independent thinking.” If students choose to use AI, they are still required to refine the output to reflect their unique voice and there needs to be evidence that they have engaged in independent thinking. To assess those two categories, I look at how the final essay grows out of their class notes and the in-class draft. And I look for signs of independent thinking and refinement in their conversations with AI. A student who submits AI conversations that suggest they mostly copied and pasted AI output to compose their essay will receive lower scores for voice and independent thinking. Students whose AI conversations demonstrate an attempt to use AI to learn rather than offload cognitive labor will receive higher scores. All of this takes place in a context in which I devote class time to helping students better understand what they gain and, more likely, lose when they over-use AI to offload cognitive labor. |