Spencer Smith

The advent of generative Artificial Intelligence (GenAI) has forced educators to contend with its presence in schools, classrooms, and student work. In this paper, I investigate the epistemic consequences of using GenAI in literacy learning. Using the concept of formative epistemic injustice, I argue a wrong is done to students when instructors encourage students to farm out learning tasks to GenAI; specifically, formative epistemic injustice is done to students when they are told to use GenAI. Using the example of writing studies, I show how many of the tasks students and educators are most likely to assign to GenAI when writing are some of the most educative, resulting in formative epistemic injustice when GenAI is used. Recognizing the staying power of GenAI in education and schooling, I sketch out ways to mitigate the mal-formative effects of the use of GenAI in writing classrooms.

Most studies of No-Excuses charter schools are distributive in nature. They answer a question of distributive justice: do these schools adequately close the academic achievement gap that exists in America between white and Black or Hispanic students? When discussion of No-Excuses schools is limited to their distributive worth, critics of No-Excuses schools are trapped. Are they really against high academic achievement, supporters of No-Excuses schools might say. This analysis seeks to escape this trap by proposing and doing an analysis of No-Excuses schools using relational justice. A turn to relational justice recognizes other educational goods schools might deliver to their students. By focusing on relational justice, the author moves the debate over No-Excuses schools into a register in which both their supporters and their opponents can work toward common aims. The author uses Anthony Laden’s relational justice to analyze No-Excuses discourse and practice and then offers recommendations to both No-Excuses schools and education theorists.