Generative artificial intelligence (Generative AI) uses technology to draw information from various sources and create text or image-based outputs like those created by humans. Examples of this technology are ChatGPT, Claude, Copilot, and Gemini. Recent developments and dissemination of Generative AI tools have led to both concerns and enthusiasm about possible uses among academics.
According to the Cornell University Center for Teaching Innovation, “Generative artificial intelligence is a subset of AI that utilizes machine learning models to create new, original content, such as images, text, or music, based on patterns and structures learned from existing data. A prominent model type used by generative AI is the large language model (LLM).” Generative Artificial Intelligence
The Barnard College Center for Engaged Pedagogy explains that “Generative AI is a type of artificial intelligence that creates new content, based on what it has learned from existing content. The process of learning from existing content is called ‘training,’ and results in the creation of a statistical model. When given a prompt, generative AI uses this statistical model to predict what an expected response might be – and thus generate new content.” Generative AI & the College Classroom.
According to the Yale University Poorvu Center for Teaching and Learning, “AI uses data and algorithms that enable technological tools and applications to learn, act, and perform functions usually associated with human-like intelligence. Generative AI refers to a type of application, such as ChatGPT(link is external), designed to use a variety of machine learning algorithms to create new content—such as text, images, and music—that mimic human creation. Generative AI applications operate on programs called large language models (LLM), which are trained by being fed large bodies of text (e.g., the entire internet) to predict the most relevant sequence of original content in response to a prompt.” AI Guidance
Two points have been made repeatedly about using Generative AI in teaching. The first is that instructors must become familiar with the various tools, which entails not only learning about the different platforms, but also trying them out and discovering what they can do. For example, Yale University’s Poorvu Center for Teaching and Learning recommends that the best way to learn about AI tools is to try them by signing up for accounts on several platforms and using them to do tasks an instructor might do. They suggested a few prompts to try:
- “Ask the program to write a response to one of the assignments from your class.
- Prompt the tool for help with a task you’re working on like writing an email or choosing the next step toward completing a project.
- Choose an assignment one of your students has submitted to your class and prompt the AI tool to produce a response that is as close as possible to the student’s, entering follow-up prompts as necessary to bring the text closer to the student’s.
- Ask the tool to teach you about a subject and then quiz you at the end.”
On a broader level, instructors need to consider the following questions when thinking about the use of Generative AI in their courses:
- “How can this help me prepare course materials or handle administrative aspects of instruction?
- How, if at all, can they help students master my course outcomes?
- Where, if at all, in my course should I be explicitly teaching how to use the tool?
- Where, if at all, is it appropriate in my course for students to use the tool independent of goals one and two?”
Additionally, instructors need to be aware of possible pitfalls and dangers:
- “How might use of the tool negatively impact students’ learning in the course?
- What equity and access issues does the existence of the tool raised for my course?
- How will I address concerns with data privacy breaches, intellectual property protection, algorithmic biases, and ‘hallucinations’, situations where generative AI provides false information?”
Generative AI for Teaching and Learning
A second frequently made point is that instructors should discuss with students both the role of Generative AI in academics and the permissible use of Generative AI in their course. Before holding these discussions, it may be useful to conduct an anonymous survey on students’ knowledge and behavior regarding Generative AI. Possible topics include (a) students’ use of AI for schoolwork, (b) students’ beliefs about AI tools that should or should not be allowed for academic assignments; (c) students’ beliefs about their need to learn about using AI to be prepared for future work; (d) students’ beliefs about uses they would consider cheating or plagiarism; and (e) students’ comfort with level of AI use by other students in the class.
Navigating the AI Conversation
The results of the survey can be used as a basis for general discussions on the use of Generative AI in academics, with the goal of creating an open dialogue about its benefits and limitations. Discussions might include specific topics such as privacy, misinformation, environmental impact, bias, inaccuracy, and academic integrity. These discussions can help students make thoughtful decisions about their own behavior. In facilitating these discussions, instructors should be transparent about their own knowledge and expectations and model critical thinking, curiosity, and reflection. “If students see that you are being inquisitive, careful, and ethical in your approach to AI use, they are more likely to engage in a similar manner.” AI Teaching Strategies: Having Conversations with Students
One crucial set of discussion topics involves the benefits of students doing their own work. These include (a) thinking about how assignments help students to achieve the goals of the course; (b) connecting students to the value and meaning of what they are learning (e.g., how why they are learning will benefit them, including its relevance for their professions, personal growth, future academic work, or communities; and (c) discussing AI and academic integrity (e.g., why academic integrity is important and which possible uses are and are not ethical). The goal of these discussions is to build students’ investment in their learning and increase their motivation to use Generative AI appropriately; they should foster critical thinking as well as self-reflection. “Discussions about AI use are an opportunity to remind students of their roles in building a strong academic culture and community and to ensure students are familiar with the University’s academic integrity policy.” Navigating the AI Conversation
In its 2024 Global AI Student Survey, the Digital Education Council found that the majority of students (86%) reported they use artificial intelligence regularly in their studies. The survey included 3,839 responses from bachelor, masters, and doctorate students across 16 countries in multiple fields of study. Common uses included searching for information (69%), check grammar (42%), summarizing documents (33%), paraphrasing a document (28%), and creating a first draft (24%). Survey Results
Given this widespread use, instructors must go beyond general discussions and adopt policies about the appropriate use of Generative AI in their classes. In doing so, they should seek student input but also be clear and transparent about their own expectations. To this end, it is important to achieve clarity and transparency not only about policies concerning Generative AI use but also about the reasons the course and each of the assignments are structured as they are. Students should know what skills an instructor wants them to learn as well as what knowledge they will gain by completing assignments. This means making sure that students understand the learning objectives on which their assignments and learning activities are based, so they can better evaluate whether using a Generative AI tool would interfere with or assist them in attaining these objectives.
Discussions with students should occur at the beginning in the term, and policies should be disseminated early and often. The rules must be communicated explicitly because interpretations may vary among individuals. Two places where they can be included are in the syllabus – as part of a syllabus statement on use of Generative AI in the course – and in a codification of a Community Agreement on appropriate behavior. The syllabus statement should comprise not only a clarification of appropriate uses, but also a discussion of possible consequences of violations. This section should also include information on detection tools the instructor plans to use (including their limits); school, college, or university policies; and process for dealing with noncompliance (including at the school, college, and university levels). Discussions about Generative AI use should be continued throughout the term. Specifically, time to discuss Generative AI could be scheduled during the first week of the term, and students can be reminded briefly before each written assignment.
Additionally, it is important for instructors to understand students’ motivations for using Generative AI in violation of course and university policies. Do they arise from stress about the writing and research process? Time management problems on big projects? Competition with other students? Experimentation and curiosity about using AI? Grade and/or other pressures and/or burnout? To avoid or mitigate this problem, it is important to cultivate a course environment in which students feel comfortable approaching the instructor if they need more support from them, their peers, or a campus resource to successfully complete an assessment. Generative AI & the College Classroom
None of these precautions mean that instructors should ignore Generative AI or discourage students from becoming familiar with it and using it. In fact, it is crucial for students to know how Generative AI is being used in their field; therefore, instructors should discuss with students how professionals are applying this technology in their work and demonstrate example of their use.
Sources
University of Kansas Center for Teaching Excellence
Adapting your course to artificial intelligence
University of Kansas Center for Teaching Excellence
An instructor guide to easing into generative AI
Carnegie Mellon University Eberly Center for Teaching Excellence & Educational Innovation
Generative AI Tools FAQ
Cornell University Center for Teaching Innovation
Generative Artificial Intelligence
Ohio State University Teaching & Learning Resource Center
AI Teaching Strategies: Having Conversations with Students
University of California/Irvine Division of Teaching Excellence and Innovation
Generative AI for Teaching and Learning
University of Chicago Academic Technology Solutions
Navigating the AI Conversation
Northwestern University
Use of Generative AI in Courses
Williams College Rice Center for Teaching
Managing the Use of Generative AI
Yale University Poorvu Center for Teaching and Learning
AI Guidance
University of Maryland Teaching & Learning Transformation Center
Artificial Intelligence
Barnard College Center for Engaged Pedagogy
Generative AI & the College Classroom
University of Western Michigan WMUx
Helping Students Develop a Critical Approach to Using Generative AI
Temple University Center for the Advancement of Teaching
Talking to Your Students about AI and Learning
University of Virginia Center for Teaching Excellence
Generative AI in Teaching and Learning
University of Illinois/Champagne-Urbana Center for Innovation in Teaching & Learning
Generative Artificial Intelligence
University of North Carolina/Chapel Hill Provost’s AI Committee
Student Guide to Using Generative AI Appropriately
Campus Technology
Survey Results
Mollick, E., and Mollick, L. (2023)
Wharton Interactive Crash Course: Practical AI for Instructors and Students
Darby, F. (2023)
Why You Should Rethink Your Resistance to ChatGPT