Generative AI (GenAI) tools are increasingly pervasive, pushing instructors to redesign how students use GenAI tools in coursework. We conceptualize this work as emergency pedagogical design: reactive, indirect efforts by instructors to shape student-AI interactions without control over commercial interfaces. To understand practices of lead users conducting emergency pedagogical design, we conducted interviews (n=13) and a survey (n=169) of computing instructors. These instructors repeatedly encountered five barriers: fragmented buy-in for revising courses; policy crosswinds from non-prescriptive institutional guidance; implementation challenges as instructors attempt interventions; assessment misfit as student-AI interactions are only partially visible to instructors; and lack of resources, including time, staffing, and paid tool access. We use these findings to present emergency pedagogical design as a distinct design setting for HCI and outline recommendations for HCI researchers, academic institutions, and organizations to effectively support instructors in adapting courses to GenAI.

A recent paper by David Lechner stated that for many long-lived systems, it is more efficient to reengineer portions of systems than to continually repair them. That paper made an implicit assumption about the ability of software engineers to determine precisely which software should be reengineered. We report the results of a study that addresses the readiness of graduates, who will soon be beginning software engineers, to make such an assessment, based on comprehension of reusable vs. reengineered software. We address this comprehension in the context of software engineering education.