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AI Competencies for Teaching: From Conceptual Frameworks to Enacted Practices

Authors

  • Teresa Ober ETS Research Institute Author
  • Caitlin Tenison ETS Research Institute Author
  • Geoffrey Phelps ETS Research Institute Author
  • Erin Renfrow-Symon ETS Research Institute Author
  • Jamie Mikeska ETS Research Institute Author
  • Vincent Dean ETS Praxis Author

DOI:

https://doi.org/10.64634/z5j3ts49

Keywords:

artificial intelligence, AI, assessment, educational technology, teacher preparation, teacher professional learning, teaching competencies

Abstract

As artificial intelligence (AI) becomes increasingly embedded in educational systems, teachers face new expectations for engaging AI as part of their instructional work and professional responsibilities. This paper argues that clarifying AI competencies for teaching requires more than listing skills: it requires a coherent account of (1) what these competencies involve, (2) how they are enacted in practice, and (3) what evidence can support teacher learning and professional judgment over time. We conceptualize these integrated capacities as AI competencies for teaching and distinguish them from broader notions of AI literacy by emphasizing application, professional judgment, and context sensitivity. Drawing on trends in how AI is reshaping teaching, we introduce a framing of AI’s roles in education (as tool, content, and context) to specify the instructional demands to which our current understanding of teaching competencies must respond. We then summarize features of existing competency frameworks to surface shared foundations and key tensions related to ethics, technical depth, professional agency, and domain specificity. We describe six interrelated domains of AI competencies for teaching, spanning AI content knowledge, AI technologies, pedagogical integration, ethical awareness, professional judgment and agency, and openness to continuous learning. To illustrate what these competencies look like in use, we present a scenario that makes teachers’ instructional decision-making visible when AI is present. Finally, we discuss progress-oriented, evidence-centered approaches, including implications for assessment, that can support teachers’ development of these competencies. This work ultimately positions AI competencies for teaching as central to sustaining ethically grounded, responsible, and professionally empowering teaching in AI-mediated educational environments.

Suggested citation: Ober, T. M., Tenison, C., Phelps, G., Renfrow-Symon, E., Mikeska, J., & Dean, V. J. (in press). AI competencies for teaching: From conceptual frameworks to enacted practices. ETS Research Report Series. https://doi.org/10.64634/z5j3ts49

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Published

2026-07-02

Issue

Section

Reports