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.

The rapid adoption of generative AI across the tech industry demands a corresponding evolution in educational practices. By proactively incorporating generative AI, educational institutions can ensure their programs remain relevant and continue to provide students with the skills necessary for career success. This work presents an intro Software Engineering course, Software Development Studio (SDS), designed and implemented by Google in collaboration with faculty, to ensure students acquire industry-relevant skills. The course focuses on integrating generative AI tools into software engineering practices, mirroring the evolving methodologies used by professionals in the field. The curriculum emphasizes practical, real-world projects, providing early undergraduate computer science students hands-on experience using generative AI tools. Data collected during the Spring 2024 semester from students and faculty reveals a positive experience and enhancement of software engineering learning through the integration of generative AI.

Generative AI tools are rapidly evolving and impacting many domains, including programming. Computer Science (CS) instructors must address student access to these tools. While some advocate to ban the tools entirely, others suggest embracing them so that students develop the skills for utilizing the tools safely and responsibly. Studies indicate positive impacts, as well as cautions, on student outcomes when these tools are integrated into courses. We studied the impact of incorporating instruction on industry-standard generative AI tools into a mid-level software development course with students from 16 Minority Serving Institutions. 89% of student participants used generative AI tools prior to the course without any formal instruction. After formal instruction, students most frequently used generative AI tools for explaining concepts and learning new things. Students generally reported positive viewpoints on their ability to learn to program and learn problem-solving skills while using generative AI tools. Finally, we found that students: reported to understand their code when they work with generative AI tools, are critical about the outputs that generative AI tools provide, and check outputs of generative AI tools to ensure accuracy.