Creating a successful professional development course involves collaboration among experts in instructional design, artificial intelligence, ethics, and teaching practices. To ground the minicourse, Ethical Integration of AI Tools for Instructors’ Professional Development, in solid subject-matter expertise, I will include scholarly, practitioner, and expert resources that directly support the course modules, learning activities, and assessments.
1) Instructional Designer (Zeenat Giwa)- As the main SME, I offer direct insights into the instructional challenges instructors encounter and ensure that course content stays relevant, practical, and applicable to real teaching scenarios and environments.
2) Floridi et al. (2018) – AI Ethics Principles Framework
Floridi and colleagues outline key ethical principles for AI, including beneficence, non-maleficence, autonomy, justice, and explicability (Floridi et al., 2018). These principles will form the foundation for Module 1: Ethical Foundations of AI in Education, where learners will examine transparency, equity, privacy, and academic integrity in instructional settings. Concepts from this framework will inform lecture content, references to ethical principles, and scenario analyses aligned with CLO 1, aiding instructors in understanding the ethical philosophy behind responsible AI use.
3) UNESCO (2023) – Guidance for Generative AI in Education and Research
UNESCO’s guidelines provide internationally accepted standards for ethical AI use in education, addressing data protection, transparency, equity, and responsible governance (UNESCO, 2023). This resource supports Module 3: Evaluating AI Tools Responsibly, particularly the AI ethical evaluation activity and rubric aligned with CLO 6. Learners will use UNESCO’s recommendations to analyze AI tools for privacy concerns, bias, and fairness issues.
4) EDUCAUSE Review and EDUCAUSE AI Community Resources
EDUCAUSE offers practitioner-focused articles, case studies, and policy discussions on AI in higher education. These resources support Module 2: Ethical Decision-Making in AI Practice, where learners examine real-world instructional scenarios involving AI. The EDUCAUSE case studies will be incorporated into scenario-based discussions and ethical decision-making exercises that align with CLO 1 and CLO 4, connecting ethical theory to real teaching challenges.
5) Institutional AI Teaching Guides and Responsible AI Use Policies (including OpenAI documentation)
Guidelines from higher education institutions and OpenAI provide practical examples of responsible AI implementation in teaching settings. These resources support Module 4: Designing Ethical AI-Integrated Instruction, in which participants develop AI-infused course elements such as syllabus policies and learning activities. They help learners create transparent AI policies and ethical instructional designs that align with CLO 3.
6) Subject Matter Expert (SME): Instructional Technologist or Faculty Member Using AI in Teaching
To improve course authenticity, I will seek input from a faculty member or instructional technologist experienced in AI integration. The SME might participate through a brief interview, guest lecture, or case study highlighting real classroom uses of AI. This cooperation will enhance activities in Modules 2 and 4 by offering practical insights into the ethical use of AI and supporting the development of realistic instructional scenarios and tasks.
This combination of scholarly research, policy guidance, practitioner resources, and SME input ensures that the course content remains academically rigorous and relevant to professionals, supporting instructors in developing ethical and responsible AI integration practices.
REFERENCES
Anderson, L. W., & Krathwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. Longman.
EDUCAUSE. (2023). Artificial intelligence resources for higher education. https://www.educause.edu
Floridi, L., Cowls, J., Beltrametti, M., et al. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023- 018-9482-5
OpenAI. (2024). Using AI responsibly in education. https://www.openai.com
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO Publishing.
University of Maryland Global Campus. (n.d.). Subject matter experts (SMEs).
https://leocontent.umgc.edu/content/umuc/tgs/ldtc/ldtc605/2262/unit-7/subject-matter- experts-- smes-.html?ou=1378426