This article analyzes the impact of Communities of Practice (CoP) in the context of professional growth and pedagogical development in higher education in the wake of Generative Artificial Intelligence (GAI) technology. Based on the INOV-NORTE initiative and concentrating on CAP “Generative Artificial Intelligence and Higher Education: First Steps”, the research addresses the problem of how faculty can be supported through peer organization to critically and creatively apply GAI into teaching through structured, unlockable teaching frameworks. Using qualitative case study methodology, the article captures participants’ engagements with AI through ethical, technological, and pedagogical lenses, analysis, and policy curation, collaborative debates, practical workshops, and teamwork that occurred both synchronously and asynchronously. Results underscore the CoP’s contribution to fostering interdisciplinary engagement, including informed ethical thinking, innovation, and proactive curricular change, along with other barriers to participating in digitally enabled governance and institutional responsiveness. The research validates the integration of CoP as professional learning frameworks that invite multiple perspectives and scales responsive to various contexts, illustrating the urgent need for institutions to strategically adapt their policies to remain relevant in the rapidly evolving educational landscape shaped by AI technology.

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Communities of Practice and Generative Artificial Intelligence in Higher Education: Pedagogical Innovation, Professional Development, and Reflective Engagement

  • Mário Cruz,
  • Ricardo Queirós,
  • Daniela Mascarenhas,
  • Erika Ribeiro

摘要

This article analyzes the impact of Communities of Practice (CoP) in the context of professional growth and pedagogical development in higher education in the wake of Generative Artificial Intelligence (GAI) technology. Based on the INOV-NORTE initiative and concentrating on CAP “Generative Artificial Intelligence and Higher Education: First Steps”, the research addresses the problem of how faculty can be supported through peer organization to critically and creatively apply GAI into teaching through structured, unlockable teaching frameworks. Using qualitative case study methodology, the article captures participants’ engagements with AI through ethical, technological, and pedagogical lenses, analysis, and policy curation, collaborative debates, practical workshops, and teamwork that occurred both synchronously and asynchronously. Results underscore the CoP’s contribution to fostering interdisciplinary engagement, including informed ethical thinking, innovation, and proactive curricular change, along with other barriers to participating in digitally enabled governance and institutional responsiveness. The research validates the integration of CoP as professional learning frameworks that invite multiple perspectives and scales responsive to various contexts, illustrating the urgent need for institutions to strategically adapt their policies to remain relevant in the rapidly evolving educational landscape shaped by AI technology.