GAIDE: A Framework for Using Generative AI to Assist in Course Content Development

Contribution: This research-to-practice full paper presents “GAIDE: Generative AI for Instructional Development and Education,” introducing a pragmatic and systematic framework for employing Generative AI (GenAI) in the development of educational content. Unlike existing frameworks, GAIDE emphasizes practical applicability for educators, facilitating the creation of diverse, engaging, and academically sound materials. The novel aspect of our approach lies in its detailed methodology for integrating GenAI into curriculum design processes, thereby reducing instructors' workload and improving the quality of educational materials. Through GAIDE, we contribute a distinct, adaptable model for leveraging technological advancements in education, providing a foundational step towards more efficient and effective instructional material development. Background: The motivation for our study emerges from the increasing demand for innovative and engaging educational content, coupled with the notable rise in Generative AI (GenAI) utilization among students for academic tasks. Our investigations reveal that nearly half of students engage with GenAI tools for completing homework assignments, highlighting a significant shift in study behaviors and the potential for technology to shape educational practices. This scenario presents a dual challenge for educators: to adapt to and incorporate these emerging technologies into their teaching methodologies, not merely to keep pace with technological advancements but to leverage them in fostering a more dynamic and inclusive learning environment. This research addresses these challenges by offering a concrete, adaptable solution, aiming to reshape the landscape of educational content creation and its application across diverse learning settings. Intended Outcomes: The primary objectives of introducing GAIDE are to: 1) Streamline the course content development process for educators, 2) Foster the creation of dynamic, engaging, and varied educational materials, and 3) Demonstrate the practical utility of GenAI in enhancing instructional design, potentially setting a precedent for its adoption in diverse educational contexts. Application Design: GAIDE was conceived out of a necessity to efficiently harness GenAI's potential in education. The application design is rooted in constructivist learning theory and TPCK, emphasizing the importance of integrating technology in a manner that complements pedagogical goals and content knowledge. Our Outcomes-Based Course Design approach aids educators in crafting effective GenAI prompts and guides them through interactions with GenAI tools, both of which are critical for generating high-quality, contextually appropriate content. Findings: Preliminary evaluation of GAIDE indicates its effectiveness in mitigating the instructional challenges associated with content creation. Educators reported a significant reduction in the time and effort required to develop course materials, without compromising on the breadth or depth of the content. Moreover, the use of GenAI has shown promise in deterring conventional cheating methods, suggesting a positive impact on academic integrity and student engagement.