TY - CHAP A1 - Prather, James A1 - Leinonen, Juho A1 - Kiesler, Natalie A1 - Benario, Jamie Gorson A1 - Lau, Sam A1 - MacNeil, Stephen A1 - Norouzi, Narges A1 - Opel, Simone A1 - Pettit, Virginia A1 - Porter, Leo A1 - Reeves, Brent N. A1 - Savelka, Jaromir A1 - Smith, David H. A1 - Strickroth, Sven A1 - Zingaro, Daniel T1 - How Instructors Incorporate Generative AI into Teaching Computing T2 - Proceedings of the 2024 on Innovation and Technology in Computer Science Education Vol. 2 N2 - Generative AI (GenAI) has seen great advancements in the past two years and the conversation around adoption is increasing. Widely available GenAI tools are disrupting classroom practices as they can write and explain code with minimal student prompting. While most acknowledge that there is no way to stop students from using such tools, a consensus has yet to form on how students should use them if they choose to do so. At the same time, researchers have begun to introduce new pedagogical tools that integrate GenAI into computing curricula. These new tools offer students personalized help or attempt to teach prompting skills without undercutting code comprehension. This working group aims to detail the current landscape of education-focused GenAI tools and teaching approaches, present gaps where new tools or approaches could appear, identify good practice-examples, and provide a guide for instructors to utilize GenAI as they continue to adapt to this new era. Y1 - 2024 U6 - https://doi.org/10.1145/3649405.3659534 SP - 771 EP - 772 PB - ACM CY - New York, NY, USA ER - TY - CHAP A1 - MacNeil, Stephen A1 - Leinonen, Juho A1 - Denny, Paul A1 - Kiesler, Natalie A1 - Hellas, Arto A1 - Prather, James A1 - Becker, Brett A. A1 - Wermelinger, Michel A1 - Reid, Karen T1 - Discussing the Changing Landscape of Generative AI in Computing Education T2 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2 N2 - In a previous Birds of a Feather discussion, we delved into the nascent applications of generative AI, contemplating its potential and speculating on future trajectories. Since then, the landscape has continued to evolve revealing the capabilities and limitations of these models. Despite this progress, the computing education research community still faces uncertainty around pivotal aspects such as (1) academic integrity and assessments, (2) curricular adaptations, (3) pedagogical strategies, and (4) the competencies students require to instill responsible use of these tools. The goal of this Birds of a Feather discussion is to unravel these pressing and persistent issues with computing educators and researchers, fostering a collaborative exploration of strategies to navigate the educational implications of advancing generative AI technologies. Aligned with this goal of building an inclusive learning community, our BoF is led by globally distributed leaders to facilitate multiple coordinated discussions that can lead to a broader conversation about the role of LLMs in CS education. KW - academic integrity; assessment; computing education; curriculum; large language models; pedagogy Y1 - 2024 SN - 979-8-4007-0424-6 U6 - https://doi.org/10.1145/3626253.3635369 PB - ACM CY - New York, NY, USA ER -