Exploring AI tools for Content Generation in Programming Courses Science Academic Year 2023 Rejected Computer Science This project explores the usage of AI tools in teaching and learning settings. We focus our attention on core courses related to computer programming. We consider content generation the process of making course-related material (e.g., examples, notes, homework assignments, programming projects, quizzes, and exams). Given the nature of existing AI tools (e.g., ChatGPT, Copilot, Codeium, Tabnine, Replit, and Tensain), we will classify them according to their features, capabilities, and limitations. As our understanding of these tools increases, we will generate course content using them and evaluate their output correctness. Furthermore, we will explore how to use AI tools adequately for an impactful student learning experience. The results of this project will be of immediate application in selected courses in Computer Science. Andres Mauricio M Bejarano Posada Andres Mauricio M Bejarano Posada The selected students are expected to conduct independent work every week. That includes consulting material (e.g., research papers, websites, textbooks, tutorials), proposing ideas, implementing solutions, and thorough testing. There will be instances for the students to present material to diverse audiences (e.g., fellow group members, teaching assistants, professors, and general audience). By the end of the project, each student should have contributed to the thorough exploration process of at least one AI tool. Having passed a course in Data Structures and Algorithms (CS251 or ECE 368) is required. Having passed CS381 is preferred but not required. Knowledge of Java, C/C++, and Python is preferred. 3 6 (estimated)

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