High textbook costs can limit or prevent student access to needed instructional materials, complicating student learning and potentially leading to lower student success. Rich repositories of open educational resources (OER) play a crucial role in broadening student access to high-quality learning materials, and ancillary materials are particularly important among these resources as they supplement and enrich student learning experiences. However, compared to OER textbooks, ancillary materials are less readily available. With the content generation capabilities offered by Generative AI, what new opportunities exist for creating OER ancillaries, and which areas require special consideration? In this session, we will explore these questions, compare the quality of peer-reviewed ancillaries with AI-generated materials, and provide hands-on activities both during the session and for participants to complete at home.
Attendees of this session will be able to:- Identify specific opportunities where Generative AI can be leveraged to develop OER ancillary materials, thereby expanding educational content for students.
- Articulate key considerations and challenges in employing GenAI for the creation of OER materials, ensuring they are aware of both the potential and the limitations of these technologies.
- Compare and assess the quality of AI-generated ancillaries against traditional peer-reviewed OER materials to enable informed decisions on their integration into teaching and learning.
- Use GenAI tools hands-on to create and evaluate ancillary materials, thereby gaining practical experience and insights on integrating these tools into curriculum development.
- Contribute to the discourse on the future of OER material creation using GenAI, providing feedback and insights that could shape the direction of future research and development in this field.
