By Cub Kahn, OSU Center for Teaching and Learning and Ecampus
The growing popularity of generative AI (GenAI) tools since ChatGPT’s 2022 release has simultaneously sparked enthusiasm and deep concern across higher education. This post provides a brief introduction to one aspect of GenAI’s potential by focusing on how AI tools may support inclusivity in teaching and learning. It outlines benefits, challenges, risks, and practical strategies for using GenAI to create more inclusive learning environments, while also acknowledging that such outcomes are far from assured. Fulfilling the promise of greater inclusivity linked to the use of GenAI tools requires thoughtful reflection and sustained commitment.
Inclusive teaching at a glance
Inclusive teaching encompasses pedagogical practices that deliberately support the success of all students, especially learners historically underrepresented in higher education. Hogan and Sathy (2022) describe inclusive teaching as both a mindset and a collection of strategies that promote equity, belonging, and student agency. These strategies involve attention to course design, structure, representation, accessibility, and the interaction of learners with their peers and their instructors. Use of active learning and collaboration, formative assessments, and the principles of Universal Design for Learning (UDL) are among the widely cited means of supporting all students (Souther, 2005).
Generative AI’s potential
There is growing interest in the use of GenAI to support inclusive teaching and learning, for instance, by more readily adapting content to diverse learners’ needs, offering more support for multilingual learners, or providing better individualized feedback to students. Let’s take a closer look:
- Personalized learning: With expert human guidance from teaching faculty, AI can be used to tailor content to the needs and pace of individual students. An exhaustive review (including 75 empirical studies and 52 review papers) of research on AI-enabled adaptive learning platforms “demonstrates that adapting instruction to students’ unique learning profiles enhances performance, motivation, and engagement” (Tan et al., 2025). The recent introduction of platforms such as ChatGPT study mode, tailored to help students learn without “giving away” answers, represents a promising direction for AI tools to provide individual support.
- Language and accessibility: AI tools can translate, simplify or reframe content, with particular benefits for multilingual learners and for students with disabilities. A meta-analysis of 40 empirical studies of English language learning found that students who integrated AI in their learning processes achieved substantially better than those who learned in traditional ways (Xu & Wang, 2024). GenAI can also support inclusion by generating content in multiple formats to support the needs of diverse learners (Stefaniak & Moore, 2024). Of course, the accuracy and alignment of such content need to be thoughtfully reviewed.
- Consistent feedback: Timely, specific feedback is instrumental to learning and student success. GenAI can potentially provide rapid feedback, aiding students who might otherwise not receive timely feedback. Though there are major concerns about the efficacy and ethics of AI-generated feedback when compared to human feedback, research shows that “GenAI’s capacity to deliver instant, accessible, and consistent feedback is particularly valued in fostering learner autonomy and enhancing learning outcomes” (Noroozzi et al., 2024, p. 381).
- AI–powered tutoring: AI tutoring can offer just-in-time individual assistance to learners across the curriculum. This tutoring may come from free or paid versions of the popular AI chatbots, as well as dedicated tutoring systems such as Khanmigo. Benefits of AI tutoring include its 24/7 availability, multilingual capabilities, multimodal features (speech, text, visuals, interactives), and scalability. Recent research suggests strong potential for AI tutoring, in one case outperforming in-class active learning (Kestin et al., 2025).
Risks and challenges
While GenAI holds significant promise to support inclusive teaching, its use requires mindful application of human oversight to avoid unintentional reinforcement of existing inequities, and to navigate troubling issues such as bias, data privacy, barriers to access, copyright, environmental impacts, and inaccuracy of information (“7 Things,” 2023). Key issues include:
- Bias and homogenization: AI models are trained on large datasets that reflect dominant cultural norms. This can lead to outputs that misrepresent or diminish historically marginalized perspectives.
- Digital divide: As with educational technology in general, the cost of more advanced AI tools is a recipe for unequal access for college students. For example, subscriptions to three popular AI systems, ChatGPT Plus, Google Gemini Pro and Claude Pro are each $17 to $20 per month. These paid versions provide significantly upgraded feature sets compared to the corresponding free versions.
- Overreliance on AI: Faculty and students themselves express concerns that if learners routinely defer too much to AI, their critical thinking skills and capacity to practice original expression may remain underdeveloped (Underhill et al., 2025).
- Privacy and data security: Use of GenAI tools by faculty and students may routinely involve sharing of confidential student data, especially when they use tools not vetted for security. Oregon State University provides commercial data protection for students and employees using Copilot with their OSU login credentials. Nonetheless, students still face challenges in comprehending security and privacy policies of various AI platforms they use.
Each of these issues potentially undercuts the goals of inclusive teaching. Taken together, they point to the importance of purposeful integration of GenAI guided by pedagogical values that prioritize the success of all students.
Practical strategies
The path forward lies not in total resistance to AI nor in unrestricted adoption, but in thoughtful integration supported by explicit instruction. As illustrated in a recent Oregon State University study, educators who provide this strategic guidance can help ensure these technologies enhance student creativity while preserving the full range of creative expression (Bushnell & Harrison, 2025, p. 17).
Instructors can proactively take steps to increase the probability that Gen AI enhances learning as well as supports inclusion:
- Co-design with students: Engage students in setting norms and expectations for AI use in your course. This approach can build trust and a sense of ownership around academic integrity (Hommel, 2025).
- Transparent policies: Clearly communicate when and how AI tools can be used in your course. This communication begins at the outset of the course with a concise statement in the syllabus, then is reinforced in announcements and in individual assignments.
- AI literacy: Start to educate your students about GenAI prior to its application in your course. Encourage them to benefit from resources and programming of the new OSU AI Literacy Center.
- Scaffolding assignments: Stage assignments so that students repeatedly reflect on, critique, revise and synthesize AI-generated draft content. Developing these skills as college students is a rapidly emerging part of career preparation.
- Professional development: Participate in workshops and webinars, and join faculty learning communities, book clubs, or other groups within or beyond your academic unit to explore inclusive teaching with AI.
Collectively, these strategies can strengthen inclusive teaching by making the use of GenAI more transparent while helping to clarify its expanding role in teaching and learning.
Looking forward
We stand on the cusp of an era when AI changes how we educate—empowering teachers and students and reshaping the learning experience . . . the only question now is whether we steer this shift in a way that lives up to the ideals of expanding opportunity for everyone (Mollick, 2024, p. 81).
As previously noted, inclusive teaching involves course design and pedagogical practices as well as a mindset centered around establishing and maintaining learning environments in which all students can succeed. Creating a more inclusive teaching and learning culture that is enhanced through careful use of GenAI requires commitment. This includes developing AI literacy among both students and faculty, fostering interdisciplinary collaboration, and the assistance of faculty and student support units.
Generative AI comprises a growing and varied collection of powerful tools that can be applied to support inclusive teaching and learning. The links between use of GenAI, inclusive teaching and student success are just beginning to be understood. Far more research and innovation is needed to establish the true educational utility of GenAI. By approaching AI with a mix of curiosity, caution, and commitment to inclusive teaching, faculty can play a central role in shaping future educational environments that offer more personalization, more learner engagement, and more student success.
References
Bushnell, J. T., & Harrison, W. (2025). A new muse: How guided AI use impacts creativity in online creative writing courses. [White Paper]. Oregon State University Ecampus Research Unit.
Hogan, K.A., & Sathy, V. (2022). Inclusive teaching: Strategies for promoting equity in the college classroom. West Virginia University Press.
Hommel, D. (2025, August 13). AI in the classroom: Panic, possibility, and the pedagogy in between. Faculty Focus. https://www.facultyfocus.com/articles/teaching-with-technology-articles/ai-in-the-classroom-panic-possibility-and-the-pedagogy-in-between/
Kestin, G., Miller, K., Klales, A., Milbourne, T., & Ponti, G. (2025). AI tutoring outperforms in-class active learning: An RCT introducing a novel research-based design in an authentic educational setting. Scientific Reports, 15(1), 17458. https://doi.org/10.1038/s41598-025-97652-6
Mollick, E. (2024). Co-intelligence: Living and working with AI. Penguin.
Noroozi, O., Soleimani, S., Farrokhnia, M., & Banihashem, S.K. (2024). Generative AI in education: Pedagogical, theoretical, and methodological perspectives. (2024). International Journal of Technology in Education, 7(3), 373-385. https://doi.org/10.46328/ijte.845
7 things you should know about generative AI. (2023, December 6). EDUCAUSE Review. https://er.educause.edu/articles/2023/12/7-things-you-should-know-about-generative-ai
Souther, S.S. (2025, March 20). The power of belonging: Enhancing student success through inclusive teaching strategies. The Scholarly Teacher. https://www.scholarlyteacher.com/post/the-power-of-belonging-enhancing-student-success-through-inclusive-teaching-strategies
Stefaniak, J.E., & Moore, S.L. (2024) The use of generative AI to support inclusivity and design
deliberation for online instruction. Online Learning, Volume 28(3), (181-205). https://doi.org/10.24059/olj.v28i3.4458
Tan, L. Y., Hu, S., Yeo, D. J., & Cheong, K. H. (2025, December). Artificial intelligence-enabled adaptive learning platforms: A review. Computers and Education: Artificial Intelligence, 9. https://doi.org/10.1016/j.caeai.2025.100429
Underhill, G. R., Dello Stritto, M. E., Aguiar, N. R. (2025). “If we rely on AI to do this for us, what’s left?”: Online students’ concerns about generative AI throughout their education and their lives. Oregon State University Ecampus Research Unit. https://ecampus.oregonstate.edu/research/study/ai-survey/results.htm
Xu, T., & Wang, H. (2024). The effectiveness of artificial intelligence on English language learning achievement. System, 125, 103428. https://doi.org/10.1016/j.system.2024.103428
Looking for guidance around AI and teaching? Explore the AI resources of the Center for Teaching and Learning, Ecampus, OSU Libraries, and the new OSU AI Literacy Center.
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