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
March 12, 2025, 12:00–1:30 p.m. ET
Participants will explore and apply ways of integrating AI technologies with OER. The focus will be on exploring how AI can enhance the creation, curation, and personalization of OER, offering new opportunities for dynamic, adaptive, and inclusive educational materials. Part 1 will begin with an overview of AI’s current capabilities in education, followed by an in-depth look at AI-driven content generation, automated translation and localization, and multimodal content creation (e.g., text, video, and images).
Participants will also examine AI’s role in improving OER, particularly in the areas of editing, updating, and making OER more accessible. The session will include an exploration of AI-powered adaptive learning, where participants will learn how AI can adjust content based on learner performance and create personalized learning pathways.
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
March 17, 2025, 12:00–1:30 p.m. ET
Participants will critically examine the potential risks and challenges associated with integrating AI into OER. The focus will be on understanding the ethical, legal, and educational concerns that arise when AI is used to create, curate, and personalize educational content.
Some of the ethical issues to be discussed include bias, representation, and transparency. Participants will explore how AI systems may reinforce biases or create content that lacks cultural sensitivity and inclusivity, and they will discuss strategies for identifying and mitigating these risks.
We’ll also cover legal complexities, particularly those related to copyright and attribution. Participants will explore the challenges of properly attributing AI-generated content and potential conflicts with existing OER licenses, examining recent legal developments and precedents.
Additionally, participants will discuss the equity and access issues that AI can exacerbate, such as the digital divide and unequal access to AI resources, and they will begin exploring strategies to mitigate these challenges in their own contexts.
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
March 20, 2025, 12:00–1:30 p.m. ET
This session will guide participants in developing actionable, context-specific strategies for the responsible integration of AI into Open Educational Resources (OER). Building on the insights from the first two sessions, participants will balance innovation with caution as they create pathways for leveraging AI while addressing the associated ethical and practical challenges.
The session will explore how to work within existing institutional frameworks to support AI-OER integration, emphasizing the importance of quality assurance, ethical oversight, and stakeholder engagement.
Participants will work collaboratively to design models for ongoing AI-OER development. This will include establishing feedback loops for continuous improvement, creating partnerships between educators and AI experts, and ensuring sustainability in AI-driven initiatives.
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
March 26, 2025, 12:00–1:30 p.m. ET
Participants will synthesize the insights gained from previous sessions and work collaboratively to develop actionable AI-OER integration strategies that are tailored to their specific institutional contexts. This session focuses on refining and finalizing the action plans created in earlier sessions, ensuring that they are both practical and sustainable.
The session will begin with a recap of key takeaways from the workshop, emphasizing the balance between the possibilities of AI and the perils it can present. Participants will then engage in guided exercises to finalize their AI-OER integration plans, addressing common implementation challenges such as gaining institutional support, securing resources, and overcoming resistance to change.
The session will also focus on strategies for measuring the success and impact of AI-enhanced OER initiatives. Participants will identify metrics and assessment tools to evaluate the effectiveness of their projects, ensuring continuous improvement and long-term sustainability.
The workshop will conclude with participants sharing their finalized action plans, receiving peer feedback, and committing to 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
Participants will develop an action plan for integrating AI-enhanced Open Educational Resources (OER) within their specific institutional context. This project will evolve over the course of the four sessions, allowing participants to apply their 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 workshop, participants will have opportunities to share their progress, receive feedback, and refine their plans.