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Center for Excellence in Learning and Teaching

AI and college teaching

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Center for Excellence in Learning and Teaching

Overview

The release of ChatGPT on November 22, 2022 and the subsequent continuing rapid development of generative AI tools have provided students and faculty with services that, drawing from a training database that contains a massive collection of human knowledge can generate generate writtem, audio, image, and video response to queries. These tools have the potential to dramatically change the way we work and live. They also provide some substantial benefits and challenges to how we engage in educational processes.

A primary benefit resulting from the widespread availability of AI tools is that it provides students with personalized support that is available 24 hours a day. Students arrive at college with diverse educational backgrounds and substantial differences in preparation for college-level coursework. AI tools can be used to level the playing field, allowing students to get the specific support they need when they need it.

One of the challenges facing educators, though, is that generative AI tools can provide relatively high quality responses to virtuallyh all types of traditional online assessments and there is no definitive way of distinguishing material created by AI tools and humans, despite the claims of the creators of a growing number of AI detection services. 

The initial reaction of educators top the use of AI tools was to attempt to ban any use of AI in their classes. AI tools, though, are already being widely adopted in virtually all of the occupations to which college students aspire. 

The challenge facing educators is to prepare students to be able to thrive in a world in which AI tools are ubuiquitous. Our graduates must be prepared to use AI tools ethically and productively if they wish to be employable. They also, though, must develop the knowledge and analytical skills to be able to use these tools effectively.

Course design and AI

AI course policies

There is no single course policy that is appropriate for all courses or for all disciplines. In determining what types of student AI usage is appropriate for your class, you should reflect on the learning objectives of your class, the ways in which AI tools are being used (or are likely to be used in the near future) in your discipline, and the level of skills that your students bring into your class. Consider ways in which AI usage might support student learning and ways in which this usage could harm student learning and skill acquisition and construct policies that are most conducive to supporting learning. The level and types of appropriate AI usage may vary from assignment to assignment.

Every course should contain a syllabus statement addressing what ways in which AI usage is (or is not) allowed in the course. To help ensure student buy-in, it can be useful to co-create an AI policy with your students at the start of the semester. One useful strategy for this is to have students construct possible AI policies in small groups and then build a policy following a whole class discussion.

Students do not always remember everything written in their course syllabus, so we striongly recommend that each assignment include a statement of ways in which AI tools may (or may not) be used in completing assignments (more on this below). 

Examples of course policies and syllabus statements

Assessment and academic integrity

Academic integrity issues are more common when students are faced with high-stakes assessment activities that do not seem seem to have intrinsic value in terms of the development of skills and knowledge that will be needed in future educational and career plans. Among the strategies can be used to support academic integrity are:

  • authentic assessment techniques
  • low-stakes assessments
  • alternative assessment approaches

Authentic assessment

Academic integrity concerns can be reduced by using authentic assessment activities that are recognized as being relevant to the students goals. Faculty are encouraged to use the Transparency in Learning and Teaching (TILT) approach developed by Mary-Ann Winklemes to provide transparent connections between assessments and course learning outcomes. When using the TILT approach, faculty include with every assessment a brief description of:

  • the purpose of the assessment,
  • a clear description of the task (including a rubric and/or exemplars of high-quality work), and
  • the criteria used to evaluate the work (possibly including a rubric).

Useful resources on TILT:

Low-stakes assessment

The use of low-stakes assessment, particularly when students have the option of multiple assessment attempts without penalty, reduces the pressure on students to achieve high grades on initial assessment attempts, thereby reducing the incentive to engage in academic dishonesty.

Alternative assessment approaches

Students have been exposed to high-stakes assessments throughout their K-12 education and their ability to progress successfully has been linked to the grades they receive,m rather than to their learning. Alternative assessment approaches are designed to shift the focus from maximizing grades to maximizing learning. Among the mnost commonly used alternative assessment strategies are:

  • standards-based assessment
  • specifications grading
  • contract grading
  • labor-based grading
  • ungrading

AI and teaching resources

Books

  • Bowen, J. A., & Watson, C. E. (2024). Teaching with AI: A practical guide to a new era of human learning. JHU Press.
  • Levy, D. and Angela Pérez Albertos (2024). Teaching Effectively with ChatGPT: A practical guide to creating better learning experiences for your students in less time. LSC Communications
  • Mollick, E. (2024). Co-Intelligence. Random House UK.
  • Skrabut, Stan (2023). 80 Ways to Use ChatGPT in the Classroom. Stan Skrabut.

Blogs

Local workshop video recordings

Tea for Teaching podcast episodes focused on AI

People to follow on social media

Other resources: