Using AI to Create Resources and Strengthen the Implementation of Open Educational Resources

Overview

Educators need access to adaptable, high-quality instructional materials to meet the diverse needs of their students. Open Educational Resources (OER), when combined with generative AI tools, offer a powerful solution to create customized supports and innovative learning experiences, particularly because OER can be freely used and reused at no cost without permission. Depending on the license, OER may even be revised (e.g., translated to another language) and/or combined with other materials to create something new (learn more about OER). The accessible nature of OER makes these resources easy to integrate with other tools – such as a learning management system or by embedding OER curricula into other curricular materials. Additionally, generative AI can be used with OER to develop resources that strengthen the implementation.

Example From the School Teams AI Collaborative

One example of using AI to develop resources to strengthen the implementation of OERs comes from DSST Public Schools, a school system that participated in the School Teams AI Collaborative. DSST uses the OER Illustrative Mathematics (IM) as its math curriculum, which offers curricular materials including lesson plans, digital activities, accelerated content, and more for grades K-12. IM partners with AI tools, including Playlab, which enables educators to build their own AI-enabled tools, allowing schools to build additional resources and supports for their own curriculum. In the partnership between IM and Playlab, the IM curriculum was uploaded as a reference document so that generative AI would review and build off of the curriculum. DSST’s process included the following steps:

1. Convening a Working Group: DSST brought together accomplished math educators and curriculum specialists for a “hackathon” to generate ideas. Schools can replicate this by organizing workshops or planning sessions with instructional leaders, teachers, and edtech specialists.

2. Defining Specific Needs: DSST identified specific areas where they could strengthen the implementation of the IM curriculum, such as engagement strategies for novice teachers and creating end-of-unit projects.

3. Prototyping and Testing Solutions: Promising ideas from the hackathon were developed into functional chatbots and tools. Educators used these tools and tested them in real classroom settings, gathering feedback from teachers and students about the process.

4. Iterating and Improving: Educators are using the tools, and the chatbots continue to be refined based on direct feedback to make them more effective.

Some examples of resources the chatbots developed include:

• Engagement Strategies for Novice Teachers: This tool provides teachers with ways to incorporate movement, voice, and participation and engagement strategies into their lessons. Teachers select which lesson in IM they are teaching, and guidance is provided tailored to that lesson.

• End-of-Unit Projects: One resource the IM curriculum does not provide is end-of-unit projects. These opportunities present strong avenues for students to apply their learnings to a unit with real-world applications. This tool creates projects based on the Common Core standards the class is covering.

Apply This Strategy in Your Context

1. Identify and Leverage Existing Resource Tools: Some AI tools have libraries of chatbots for educators to use from the get-go. Educators can explore chatbots developed by the Playlab community and use or modify them to be more tailored to their needs. TeachingLab partnered with IM to create a library of chatbots – including ones that modify an activity for English language learners and for specific learning needs. This library has been reviewed by the team at TeachingLab, providing an additional layer of vetting.

2. Focus on Specific Areas of Development: Schools should identify particular challenges their teachers and students face – using data from assessments, teacher feedback, or classroom observations.

3. Create Your Own Resources Using Generative AI Platforms: Generative AI tools like ChatGPT and Gemini allow users to upload materials that the tool can then reference when creating outputs. This can look like attaching files or copying and pasting the text (note: verify text you input is allowed to be used in this way). Users can instruct the tool to refer to specific documents in their prompts. For example, teachers can upload a math lesson plan and prompt the generative AI tool to take on the persona of a math teacher (note: input grade level and content for more precise results), review the uploaded math lesson plan, and perform a task (e.g., provide modifications for multi-language learners, provide an extension activity for students who have demonstrated mastery).

4. Engage Experts in Your Context: Identify experts like content specialists, teachers, and instructional coaches to develop resources using generative AI and to review these resources to ensure they meet the needs of your students, staff, and community – and are further aligned to your school or system’s instructional vision and curriculum.

5. Test Solutions and Iterate: Try out the resources in your school and get feedback from teachers and students about the usefulness of the resources. Then, refine these tools based on the feedback you’ve collected to make them stronger.

As seen in DSST Public Schools' approach, AI tools can help educators develop tailored supports and resources. By combining the flexibility of OER with the power of generative AI, schools can create customized, high-quality materials that enhance student learning and engagement.

This AI-enabled strategy was developed by a member of the School Teams AI Collaborative — a partnership between Leading Educators and The Learning Accelerator (TLA). The Collaborative was developed to bring together innovative educators from schools across the country to share ideas and discover effective ways to use AI in the classroom.