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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

What is Generative AI?

Generative Artificial Intelligence (AI) refers to a type of technology designed to create new content, data, or information. Unlike traditional AI systems that are task-specific and rely on predefined rules or patterns, generative AI has the ability to produce content that is not explicitly programmed.

Generative AI is based on deep learning models trained on large datasets from which the system learns to generate content by predicting the most likely next element in a sequence based on usage patterns.

The release and rapid development of ChatGPT, the most familiar Generative AI in higher ed, faculty, instructors and staff throughout higher ed considering its role in and out of the classroom given the (relative) quality of its responses and potential misuse regarding academic integrity.

Generative AI applications can create articles, stories and code; generate images, art or designs; produce speech for voiceovers or synthetic voices; compose music or generate melodies; create video content, special effects and animations; augment datasets or generate data samples; summarize long texts or articles; and power chatbots (OpenAI. (n.d.). What is Generative AI?). 

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

  • CTLA Summer AI Redesign Institute

    faculty who are interested in exploring the ways generative Artificial Intelligence (AI) can be infused into a course -- topically, as an instructional strategy or as a significant support for student achievement of course learning outcomes -- are invited to apply to be part of the Center for Teaching, Learning, and Assessment’s Summer 2024 AI-enhanced Course Redesign Institute. 

    Learn More and Apply

  • 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

  • CTLA Seeks AI Faculty Fellow

    CTLA is currently accepting applications for an AI in Teaching and Learning Faculty Fellow. The AI Faculty Fellow will work closely with the CTLA leadership team on a projects ranging from the scaling of an AI Redesign Institute to further development of robust AI and teaching and learning digital resources, including case studies and model assignments and assessments. The fellow will also promote, facilitate, and elevate conversations on AI and teaching and learning.

    Read More and Apply

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?