AI Readiness and Responsibility: Organizational Assessment for Teacher Education Programs

Outline

0–10 minutes: Framing the Challenge (Facilitator: Jody Britten)
 • Content: Overview of why organizational assessment matters in preparing teacher candidates for AI-integrated classrooms. Introduction to key concepts: AI literacy, institutional readiness, and alignment with UNESCO and ISTE frameworks.
 • Engagement: Interactive polling question (“Where is your program today on AI readiness?”) and word cloud activity to visualize participants’ current contexts and challenges.
 • Process: Participants engage using devices or QR code to contribute anonymously. This anchors the conversation in participants’ lived experience.

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10–25 minutes: Frameworks and Indicators (Facilitator: James Basham)
 • Content: Deep dive into implementation science, Universal Design for Learning (UDL), and organizational change models that support sustainable AI integration. Presentation of sample indicators across curriculum, pedagogy, policy, and ethics.
 • Engagement: Participants complete a short interactive self-rating using an excerpt from the AI Readiness Rubric (digital or printed version). They discuss findings with a peer to surface shared challenges and innovations.
 • Process: Facilitated peer-to-peer dialogue in small clusters or table groups, encouraging perspective exchange across institutions.

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25–45 minutes: Tools for Action (Facilitator: Cheryl Lemke)
 • Content: Introduction to planning templates and resource toolkit. Demonstration of how to translate assessment results into actionable steps. Examples from real institutions will illustrate how to move from assessment to implementation.
 • Engagement: Participants complete one section of the Action Plan Outline, identifying one immediate next step and one long-term institutional goal.
 • Process: Guided reflection prompts and real-time resource sharing (via QR code). Participants can upload notes to a shared Padlet or digital wall for post-session access.

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45–60 minutes: Reflection and Commitments (All Presenters)
 • Content: Group synthesis—connecting organizational assessment to educator agency and ethical AI integration.
 • Engagement: “Lightning share” where volunteers highlight one takeaway or commitment. Facilitators summarize emerging themes and link them to global AI and education frameworks.
 • Process: Brief verbal share-outs, digital reflection card submission, and optional sign-up for continued collaboration via resource link or community network.

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Engagement Frequency and Tactics
 • Audience engagement occurs every 5–7 minutes through polls, peer discussions, digital prompts, or self-assessments.
 • Multiple modes of participation (digital, verbal, written) are used to model UDL-aligned facilitation.
 • Resource access and continued dialogue are supported through a shared link hub provided at the session’s end.

Outcomes

Attendees will leave with a personalized action plan outline and curated resources to guide organizational self-assessment and planning. These materials will help participants evaluate their current readiness, identify next steps for integrating AI literacy, and access frameworks and tools to continue the work beyond the session.

Supporting research

**Primary / Field-Specific Sources**

1. The AI and Education Studio (Jody Britten) — Toolkit, frameworks, guides, and curated resources focused on inclusive AI integration in learning.
URL: https://jodybritten.com/the-ai-and-education-studio/
2. Framework for Responsible AI Integration in PreK-20 Education (CIDDL) — Foundational framework for institutional-level AI readiness across policy, pedagogy, equity, and ethics.
URL: https://ciddl.org/framework-for-responsible-ai-in-prek-20-education/
3. Navigating the AI State Guidance in Education — Analysis of emerging state-level AI guidance in K–12, themes, gaps, and implications for teacher preparation.
URL: https://ciddl.org/navigating-the-ai-state-guidance-in-education/
4. Beyond Performance: AI Integration for Meaningful Learning (CIDDL blog) — Argument that effective AI integration must support deeper learning, not just performance.
URL: https://ciddl.org/beyond-performance-ai-integration-for-meaningful-learning/
5. Integrating AI Without Promoting Dependency (CIDDL blog) — Best practices for balancing AI scaffolding with independent student thinking; useful for designing assignments and policy signals.
URL: https://ciddl.org/integrating-ai-without-promoting-dependency/
6. “Empowering Education Leaders: A Toolkit for Safe, Ethical, and Equitable AI Integration” — U.S. Department of Education–sponsored guidance, with CIDDL/J. Basham involvement documenting guardrails, accessibility, equity, and governance.

**Complementary / Theoretical Works**

1. Mutlu Cukurova, The Interplay of Learning, Analytics, and Artificial Intelligence in Education: A Vision for Hybrid Intelligence (arXiv preprint) — Presents a conceptual grounding for human–AI hybrid intelligence and a broader lens for AI beyond tool adoption.
URL: https://arxiv.org/abs/2403.16081
2. Lixiang Yan, Lele Sha, et al., Practical and Ethical Challenges of Large Language Models in Education: A Systematic Scoping Review — Identifies major practical, ethical, and methodological issues of applying LLMs in educational settings.
URL: https://arxiv.org/abs/2303.13379
3. Cecilia Ka Yuk Chan & Louisa H. Y. Tsi, The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education? — Explores the dynamic tension between augmentation and replacement of educators, and the role of AI literacy.
URL: https://arxiv.org/abs/2305.01185
4. Ethan Mollick & Lilach Mollick, Assigning AI: Seven Approaches for Students, with Prompts — Proposes modes (e.g. AI-coach, AI-tool, AI-teammate) to frame assignment design so that student thinking remains central.
URL: https://arxiv.org/abs/2306.10052