The recent advent of highly accurate and scalable large language models (LLMs) has taken the world by storm. From art to essays to computer code, LLMs are producing novel content that until recently was thought only humans could produce. Recent work in computing education has sought to understand the capabilities of LLMs for solving tasks such as writing code, explaining code, * Randomly-ordered Co-leaders Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Competency-based learning has been a successful pedagogical approach for centuries, but only recently has it gained traction within computing. Competencies, as defined in Computing Curricula 2020, comprise knowledge, skills, and professional dispositions. Building on recent developments in competency and computing education, this working group examined relevant pedagogical theories, investigates various skill frameworks, reviewed competencies and standard practices in other professional disciplines such as medicine and law. It also investigated the integrative nature of content knowledge, skills, and professional dispositions in defining professional competencies in computing education. In addition, the group explored appropriate pedagogies and competency assessment approaches. It also developed guidelines for evaluating student achievement against relevant professional competency frameworks and explores partnering with employers to offer students genuine professional experience. Finally, possible challenges and opportunities in moving from traditional knowledge-based to competency-based education were also examined. This report makes recommendations to inspire * Working Group Leader † Working Group Co-Leader

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