The widespread adoption of Generative AI (GenAI) tools by students across different educational levels highlights the need for them to develop robust GenAI literacy, including a working understanding of these systems' fundamental concepts, their limitations, and implications for responsible use. However, misconceptions about GenAI, such as perceiving these systems as mere search engines or database lookup systems, are commonly observed among students, while the availability of teaching resources remains fragmented, and learning objectives lack alignment. This Working Group aims to design pedagogical resources for computing science instructors, enabling them to develop students' GenAI literacy. To achieve this, the Working Group will first identify a concise set of GenAI literacy learning objectives informed by instructor experience, research literature, and community input, and subsequently design pedagogical resources aligned with these objectives.

The ever-increasing spread of AI-assistance tools into programming workflow presents a pedagogical challenge: assessing whether students possess genuine understanding of code they may not have written themselves. This paper proposes integrating video 'vivas' into programming assessments as a mechanism for validating code comprehension. In this approach, students submit code and recorded explanations in which they discuss their design choices and the logical flow of their code. Although this mechanism cannot fully eliminate misconduct, it reduces the feasibility of submitting AI-generated solutions without engaging with the code. We discuss implementation considerations, marking rubric development aspects, and consider the broader implications of this approach.

The subject of discrete mathematics is fundamental to software engineering. Yet, when learners first encounter it, many perceive it as too abstract and disconnected from their chosen field of study. Additionally, traditional discrete mathematics assessments often use small, isolated, and abstract scenarios that do not reflect real-world software development, potentially further alienating these learners. This paper presents an authentic assessment developed for first-year applied software engineering students that grounds discrete mathematics in realistic, industry-relevant problem context.

GenAI is playing an increasingly important role in computing courses at all levels, offering new opportunities to support teaching and learning. However, using GenAI effectively raises important concerns regarding trust, academic integrity, and broader social and ethical dimensions. This Working Group was formed to report on the current state of the art in using GenAI in upper-level computing courses to aid educators. The working group will undertake a methodological review of published work and solicit input from the computing educational community as part of the report.