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Item Teaching Game Programming in an Upper-level Computing Course Through the Development of a C++ Framework and Middleware(The Eurographics Association, 2024) Hooper, Steffan; Wünsche, Burkhard C.; Denny, Paul; Luxton-Reilly, Andrew; Sousa Santos, Beatriz; Anderson, EikeThe game development industry has a programming skills shortage, with industry surveys often ranking game programming as the top skill-in-demand across small, mid-sized, and large triple-A (AAA) game studios. C++ programming skills are desired, however, educators can perceive C++ as too difficult to teach due to its size and complexity. We address the challenges of teaching C++ in an upper-level Game Programming course and demonstrate how learners are up-skilled in C++ game programming, providing insights and reflections on the course. We show how through careful educational-design choices, combined with scaffolding a C++ framework and contemporary middleware, it is possible to transition learners to C++ for game programming.Item Can GPT-4 Trace Rays(The Eurographics Association, 2024) Feng, Tony Haoran; Wünsche, Burkhard C.; Denny, Paul; Luxton-Reilly, Andrew; Hooper, Steffan; Sousa Santos, Beatriz; Anderson, EikeRay Tracing is a fundamental concept often taught in introductory Computer Graphics courses, and Ray-Object Intersection questions are frequently used as practice for students, as they leverage various skills essential to learning Ray Tracing or Computer Graphics in general, such as geometry and spatial reasoning. Although these questions are useful in teaching practices, they may take some time and effort to produce, as the production procedure can be quite complex and requires careful verification and review. From the recent advancements in Artificial Intelligence, the possibility of automated or assisted exercise generation has emerged. Such applications are unexplored in Ray Tracing education, and if such applications are viable in this area, then it may significantly improve the productivity and efficiency of Computer Graphics instructors. Additionally, Ray Tracing is quite different to the mostly text-based tasks that LLMs have been observed to perform well on, hence it is unclear whether they can cope with these added complexities of Ray Tracing questions, such as visual processing and 3D geometry. Hence we ran some experiments to evaluate the usefulness of leveraging GPT-4 for assistance when creating exercises related to Ray Tracing, more specifically Ray-Object Intersection questions, and we found that an impressive 67% of its generated questions can be used in assessments verbatim, but only 42% of generated model solutions were correct.