4. AI as a Course Design Partner
Resources/AI Statement
Tools
Microsoft. (2026). Copilot [large language model]. https://copilot.microsoft.com
Anthropic. (2026). Claude 3.5 Sonnet [Large language model]. https://claude.ai
Google. (2026). Gemini [Large language model]. https://gemini.google.com
OpenAI. (2026). ChatGPT [Large language model]. https://chat.openai.com
Readings
Choi, G. W., Kim, S. H., Lee, D., & Moon, J. (2024). Utilizing generative AI for instructional design: Exploring strengths, weaknesses, opportunities, and threats. TechTrends, 68(4), 832–844.
Erdogan, N. (2026). AI-supported reflective practice: Redesigning teacher education courses for critical AI integration. Essays in Education, 32(1), Article 7.
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474.
Gagich, M. E. (2026). AI week: Redesigning assignments and assessments for an age of AI. Cleveland State University.
Green, M. (2025, November 5). GenAI use and ethics framework: A pedagogical model for responsible AI integration in K-12 and higher education. OLC Insights. https://onlinelearningconsortium.org/olc-insights/2025/11/genai-use-and-ethics-framework/
Huff, C. (2024, October 1). The promise and perils of using AI for research and writing.
American Psychological Association. https://www.apa.org/topics/artificial-intelligence-machine-learning/ai-research-writing
IBM. (2026). Building AI agents and agentic workflows specialization. Coursera. https://www.coursera.org/specializations/ai-agents
Ilieva, G., Yankova, T., Ruseva, M., & Kabaivanov, S. (2025). A framework for generative AI-driven assessment in higher education. Information, 16(6), 472. https://doi.org/10.3390/info16060472
Khalifa, M., & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, Article 100145. https://doi.org/10.1016/j.cmpbup.2024.100145
Kibar, P., & Ilgaz, H. (2026). The intersection of artificial intelligence and instructional design practice: A systematic review. Educational Technology Research and Development. https://doi.org/10.1007/s11423-026-10624-z
Kiyan Tsunami, C., et al. (2024, October 22). Guidelines for integrating actionable A-SMART learning outcomes into the backward design process. MedEdPublish, 14, Article 242. https://doi.org/10.12688/mep.20606.1
Lelis, C. (2026). Devil’s advocates wear AI: Exploring the assistive role of AI in assessment, in a meaningful way. In K. Tammets, S. Sosnovsky, R. Ferreira Mello, G. Pishtari, & T.
Nazaretsky (Eds.), Two decades of TEL: From lessons learnt to challenges ahead (Lecture Notes in Computer Science, Vol. 16064). Springer. https://doi.org/10.1007/978-3-032-03873-9_21
Mittal, V. (2025). Designing with agents: How agentic AI elevates instructional design. LinkedIn. https://www.linkedin.com/pulse/designing-agents-how-agentic-ai-elevates-design-vishakha-mittal-gy6xc
Nyabuto, G., Mosora, G., & Nyabuto, P. (2026). Artificial intelligence as a research assistant: A framework for ethical use among university students. International Journal of Progressive Research in Engineering Management and Science, 6, 1678–1687. https://doi.org/10.58257/IJPREMS54009
O’Sullivan, J., Lowry, C., Woods, R., & Conlon, T. (2025). Generative AI in higher education teaching & learning: AI-resilient assessment practices. Higher Education Authority. https://doi.org/10.82110/Z7MD-RM66
Sikka, M. (2025, November 30). Why the human-in-the-loop model is key to ethical AI in K-12 education. Defined Learning Blog. https://blog.definedlearning.com/why-the-human-in-the-loop-model-is-key-to-ethical-ai-in-k-12-education/
Suresh, D., et al. (2025). Generative AI in learning design practice: Building an online course for biomedical sciences research programs. International Journal of Designs for Learning, 16(2), 244–265. https://doi.org/10.14434/ijdl.v16i2.41995
University of Cincinnati Online. (n.d.). How instructional designers use AI to optimize workflow and the learning experience. https://www.online.uc.edu/blog/how-instructional-designers-use-ai.html
Van der Burg, V., et al. (2026). Reflective AI: A slow technology approach for design education. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’26). Association for Computing Machinery. https://doi.org/10.1145/3772318.3791691
Wang, J., Xiao, R., Hou, X., & Stamper, J. (2025). Enabling multi-agent systems as learning designers: Applying learning sciences to AI instructional design. arXiv. https://arxiv.org/html/2508.16659
White, J. (2026). AI agent developer specialization. Coursera.
Zhai, X. (2022). ChatGPT user experience: Implications for education. SSRN.
AI Disclosure Statement
During the preparation of this chapter, each of the four authors independently used one or more large language model (LLM) based AI tools as research and writing aids. These tools were used to facilitate brainstorming, clarify complex ideas, explore perspectives, develop outlines, suggest organizational structures, and provide formative feedback on draft materials.
The authors did not rely on AI systems to author the chapter’s content. All substantive writing, analysis, interpretation, pedagogical recommendations, and conclusions were created, evaluated, and revised by the authors. Any AI-generated suggestions were critically reviewed for accuracy, relevance, bias, and alignment with the chapter’s goals before being incorporated into the final work.
Several portions of the chapter intentionally illustrate the use of LLMs within educational and professional workflows. In these instances, prompts, outputs, and step-by-step examples are presented as part of the instructional content and should be understood as demonstrations of practice rather than evidence of AI authorship.
The authors accept full responsibility for the final content of this chapter.