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Center for Teaching, Learning, and Assessment
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Generative AI and Teaching and Learning

Generative AI and Teaching and Learning

Generative AI and Teaching and Learning

The Center for Teaching, Learning, and Assessment supports the principled implementation and integration of Generative Artificial Intelligence (GenAI) inhigher education when and where it promotes

  • student achievement of stated learning outcomes in a course or across a curriculum;
  • support for faculty by increasing effectiveness and efficiency in the performance of instructional and administrative tasks; 
  • our collective ability to leverage technology-rich contexts to build community and human connection; and 
  • the facilitation of personalized learning, tutoring and other customized assistance for teaching and learning tasks.

This position is grounded on the following six principles:

1. AI is here to stay. 

Far from being merely a gimmick or a flash-in-the-pan, AI has increasingly infiltrated professional work and many people’s daily lives. We believe that these technologies present fundamental changes to writing, multimodal creating, and professional workflows. Students graduating with understanding of and competence in disciplinary application of AI will be better prepared for future professional and personal aspirations. 

2. Like any technology, AI has affordances and limitations. 

Because we see AI as transformative for and increasingly a fundamental aspect of education and work, it is our goal to maximize the affordances and mitigate its limitations. We are committed to nurturing conversations and offering resources to aid you in that endeavor. 

3. AI will require us as educators to update our approaches inside and outside the classroom. 

We believe that now more than ever, ongoing pedagogical development is necessary. Many concerns educators have regarding the implications of AI, and particularly students’ use of it, relate to pedagogical approaches that predate AI. Good pedagogical practice accounts for the broader context in which teaching occurs. If the context has changed because of AI tools, then we need to continue to reflect on and develop our pedagogy and practices in light of those changes.

4. Sound, evidence-based Scholarship of Teaching and Learning (SoTL) can be adapted to and supportive of sound pedagogical practice with AI. 

While the rising influence of AI on professional and academic contexts may require us to update our pedagogical practices, we recognize that SoTL can provide valuable resources for evidence-based research that may inform our responses to AI tools. CTLA is dedicated to familiarizing you with the best research and scholarship related to teaching and learning in the context of AI. 

5. Empowering AI literacy requires at least two components: effective practices and ethical considerations and contexts for critical use. 

We recognize that practitioners (faculty, staff, students, and others) need to know how to engineer prompts, select particular AI applications, understand the affordances and limitations of different platforms, and so forth. However, real agency with AI requires that we understand the ethical contexts both narrowly, in terms of our ethical practices with AI, and broadly, in terms of larger ethical concerns, such as inherent biases embedded in programming or training, exploitation of human trainers of LLMs, and power consumption of servers. 

6. A one-size-fits-all approach to AI in higher education is counter-productive. 

We recognize that faculty, staff, and students are concerned about the implications of AI for higher education, and that everyone wants to ensure they are doing the right thing regarding these tools. These concerns may provoke a desire for an institutional response that clearly defines how and when AI should be used at the university. However, we believe positions regarding AI use are better developed within specific contexts by the stakeholders most closely engaged with those domains.

Just as what constitutes “good writing” varies from discipline to discipline, what constitutes “good AI use” may vary as well. Our mission is to provide you with training and resources for pedagogical development to support you in the process of developing effective policies, course design, and pedagogical implementations. However, as the expert in your context, you will be central in adapting your practices and materials to respond effectively to innovative technologies such as AI tools.

Join the Conversation

Instructors can participate in the development of resources on this technology.

  • Upcoming Events

    Workshops, sessions and panels on Generative AI can be found on the Programs and Events page. CTLA staff and Faculty Learning Community facilitators are available to present on Generative AI and Teaching and Learning or to assist departments and teaching teams in developing programming on the topic. 

    Programs and Events

  • Share Teaching Tips

    Instructors are invited to submit a teaching tip (written or multimedia) sharing how they are approaching this new technology. We'll use these tips to further develop this website with OHIO case studies.

    Submit Sample Assignments, Teaching Approaches

Sample OHIO AI Policies and Assignments

CTLA highly recommends all courses have a policy established on the use of Generative AI. These three examples, as well as a recommended policy used by the College of Business, can be adapted to best meet an instructor's needs given their discipline and course level.

The following are additional examples of course policies and assignments developed during the spring semester 2023 ChatGPT and AI Faculty Learning Community.

CTLA Recommended Resources

Because this list will be updated frequently, we recommend contacting the staff at the Libraries should you need access to any of the content.

Conceptualizing AI Use

Establish your predisposition to AI trends

Reflect on your own personal biases preconceptions about AI and consider where those feelings originate. Stay open-minded and consider that AI is a tool, not a replacement for instructors or student engagement.

Investigate different tools (generative and detection tools) in a balanced way

Explore tools like AI-driven content generators, plagiarism detectors, predictive analytics, etc., and come to understand the limitations and strengths of each tool.

Explore the broader context of AI use

  • In Your Field: How is AI reshaping research methodologies, findings, or pedagogies?
  • Inside Academia: Are there leading universities or faculty pioneering AI-driven approaches?
  • In the Private Sector: How are businesses using AI for tasks related to your discipline?
  • In Everyday Use: Familiarize with general AI applications, like smart assistants, to understand its pervasiveness.

Further explore its uses in your discipline and in your courses

As noted above, the implications of AI differ for various disciplines. Part of evaluating the value or challenge of a particular technology involves understanding how instructors and students might use it in the classroom or laboratory setting. How does generative AI differ from what is already available to students via the internet or in other support services and programs? How might it actually support your instruction?

Reflect on your current concerns related to teaching and learning and/or academic integrity

What worries or excites you about this new technology from a teaching and learning standpoint? It would be helpful to list the positive and negative implications of something like ChatGPT. If your greatest concern is around academic integrity, for example, you might want to examine your graded activities and assessments for susceptibility. If you are excited about how generative AI applications can be used to evaluate aspects of student writing so you don’t have to, how can you incorporate its use into an assignment?  

Identify current assignments and assessments where students might leverage AI

New technology that may affect how your students learn is worth considering in light of your currently planned activities, assignments and assessments. Think hard about a balanced approach between mitigation and integration of AI in your pedagogy. Develop a policy for AI use in your course based on your firsthand experience investigating AI tools. Think about assignments that might fruitfully integrate AI or that become less impactful as a result of AI.

  • Are the questions you pose in a discussion board easily answered by generative AU? Are they worth keeping if so?
  • Can generative AI or another program take multiple choice questions with great accuracy? If so, are you asking for memorization of an essential and scaffolded knowledge set? And if that is the case, how should you best test for that?
  • Do you teach coding? How might generative AI impact particular assignments?

Finally, consider how AI might aid your development of some course materials/activities.

Be strategic and transparent in adjustments you choose to make

The more transparent you are in developing assignments, exams or other graded activities, the more students engage with those activities. CTLA recommends Transparency in Learning and Teaching (TILT) frameworks to support students’ meaningful engagement with instructional activities and most effective use of technology.

Consider the needs of your students

Are students equipped with the literacies (information literacy, technical literacy, ethical literacy) to engage with AI tools? How might AI change the job landscape for your students? Do they have the skills to adapt?

Consider how you might productively and academically contribute to your students' various literacies related to AI use.

Engage students in the conversation and course design around new technologies

Ask your students about their use of AI in learning. How does it help them learn? How does it hinder their learning? How are they and their colleagues using ChatGPT? Do they have concerns about ethical use or academic integrity? Students may be the best resource for feedback on how to adjust or refine instructional strategies to support their learning.

Stay updated and collaborate

The field of AI is rapidly evolving, so pay attention to new stories about it. Engage with AI communities, attend conferences or join interdisciplinary teams. Collaborate with colleagues to share findings, approaches, and resources and talk about your experiences and developing pedagogy regarding AI.

Develop ethical best practices regarding AI

Be aware of the ethical implications of AI, especially in data collection, biases, and accessibility, and help students develop their ethical points of view regarding AI use at the university and on the job. Discuss these implications in your courses to foster critical thinking.

Assess the effectiveness of new policies and instructional practices

If you make a significant change to an instructional strategy or assignment, consider how you will assess its effectiveness. To gather student feedback on their experiences or a course policy change, a short survey or question at the end of the assignment might provide valuable information. Maybe students perform differently on an essay assignment or a set of test questions. CTLA is always here to help you strategize on how to best assess the impact of instructional change on student learning.

Recognize that ChatGPT and AI detection is challenging at best

Current applications that support detection of AI-generated text are not highly reliable. The best detection is to avoid having to detect use of generative AI.

Think short-term, mid-term, long-term on pedagogical development

  • Short-term: Investigate AI tools. Experiment. Brainstorm. Attend workshops, courses, or webinars on AI basics. Develop a course policy.
  • Midterm: Integrate AI tools in one or two courses and gather feedback. Develop activities.
  • Long-term: Consider a holistic shift in pedagogical approach. How might you revise curricula in relation to what you've learned about AI?