The Learning Lab experience is supported by both asynchronous and synchronous components. Each Learning Lab sequence includes a set of resources, an asynchronous discussion, and an interactive live session, all of which culminate in the development of a project or application to apply learning to local and specific contexts in support of the learning objectives.
Schedule
Part 1: AI Integration in Open Educational Resources: Enhancing Accessibility, Personalization, and Innovation
September 3, 2025, 12:00–1:30 p.m. ET
In this session, you’ll explore how AI can enhance the way you create, curate, and personalize OER to support more dynamic, inclusive, and adaptive learning experiences. We’ll start with a look at what AI can do in education today—like generating content, translating and localizing materials, and creating multimedia resources. You’ll also dig into how AI can help you improve and update OER, make it more accessible, and personalize learning through adaptive technologies that respond to individual student needs
Learning Objectives
- Identify and analyze the most promising applications of generative AI for enhancing OER..
- Explore how AI can expand accessibility, personalization, and innovation within educational resources..
- Discover real-world case studies showcasing successful AI-OER integration.
Part 2: Ethical and Legal Challenges of AI Integration in Open Educational Resources
September 8, 2025, 12:00–1:30 p.m. ET
In Part 2, you’ll take a critical look at the risks and challenges of using AI in OER, with a focus on ethical, legal, and educational concerns. We’ll explore issues like bias, representation, and transparency—how AI can reinforce stereotypes or miss the mark on cultural sensitivity—and discuss ways to spot and reduce those risks. You’ll also dive into legal questions around copyright, attribution, and how AI-generated content fits within OER licenses. Finally, we’ll tackle equity and access challenges, including the digital divide, and begin identifying strategies you can use to navigate these complexities in your own work.
Learning Objectives
- Critically assess the ethical, legal, and practical challenges of using AI in OER.
- Explore issues like bias in AI, intellectual property concerns, and the implications of AI-generated content for teaching and learning.
- Examine the potential negative impact of AI on equity, authorship, and academic integrity in the context of OER.
Part 3: Strategies for Responsible AI Integration in Open Educational Resources Development
September 10, 2025, 12:00–1:30 p.m. ET
During Part 3, you’ll build on earlier insights to develop practical, context-specific strategies for integrating AI into OER responsibly. Together, we’ll explore how to balance innovation with ethical considerations while working within your institution’s frameworks. You’ll dive into quality assurance, stakeholder engagement, and ethical oversight, then collaborate with others to design sustainable models for AI-OER development—complete with feedback loops, educator–AI expert partnerships, and plans for continuous improvement.
Learning Objectives
- Synthesize the first two sessions to create a balanced and informed approach to integrating AI in OER.
- Develop strategies that leverage the potential of AI while addressing its risks.
- Identify key principles and practices for ensuring ethical, equitable, and effective use of AI in OER creation and implementation.
Part 4: Finalizing AI-Open Educational Resources Integration Plans: Practical Strategies for Implementation
September 17, 2025, 12:00–1:30 p.m. ET
In this final session, you’ll pull together everything you’ve learned to craft a clear, actionable plan for integrating AI into OER at your institution. We’ll start with a quick recap of key takeaways—highlighting both the promise and pitfalls of AI—then dive into guided activities to refine your strategy. You’ll tackle real-world challenges like gaining support, finding resources, and addressing resistance to change. We’ll also explore how to measure impact by identifying metrics and tools for assessing success. To wrap up, you’ll share your plan, get peer feedback, and commit to your next steps.
Learning Objectives
- Reflect on and consolidate the key takeaways from the previous sessions.
- Develop a clear and actionable plan to bring AI-OER initiatives to their own campuses.
- Identify future steps for continuous development and professional growth in the AI and OER
Lab Implementation Project
You will develop an action plan for integrating AI-enhanced Open Educational Resources (OER) within your specific institutional context. This project will evolve over the course of the four sessions, allowing you to apply your learning in real-time and receive feedback from peers and facilitators.
This project will include the following components:
- Institutional Analysis: Assess your institution's current OER landscape, technological capabilities, and readiness for AI integration.
- Opportunity Identification: Identify 2-3 high-potential areas where AI could significantly enhance OER at your institution (e.g., content creation, personalization, accessibility).
- Risk Assessment and Mitigation: Conduct an analysis of potential ethical, legal, and pedagogical risks specific to your chosen AI-OER applications. Develop strategies to address these challenges.
- Implementation Strategy: Outline a step-by-step plan for introducing and scaling AI-OER initiatives at your institution. Include timelines, resource requirements, and key stakeholders to engage.
- Collaboration and Community Engagement Plan: Describe how you will foster collaboration among educators, AI experts, and other stakeholders. Include strategies for building a community of practice around AI-OER.
- Evaluation and Continuous Improvement: Develop a framework for measuring the success and impact of your AI-OER initiatives, including key metrics and assessment tools.
Throughout the learning lab, you will have opportunities to share your progress, receive feedback, and refine your plans.