How Will Generative AI Change My Course (GenAI Checklist)?

With the growing prevalence of generative AI applications like ChatGPT and the ongoing discussions surrounding their integration in higher education, it can be overwhelming to contemplate their impact on your courses, learning materials, and field. As we navigate these new technologies, it is crucial to reflect on how generative AI can either hinder or enhance your teaching methods. To support instructors in this endeavor, CATL created a video presentation and checklist designed to help you assess the extent to which generative AI will affect your courses and provide guidance on next steps for moving forward.

How Will ChatGPT Change My Course – CATL Presentation Slides (PDF)

Checklist for Assessing the Impact of Generative AI (ChatGPT, etc.) on your Course

View the Checklist for Assessing the Impact of Generative AI as a PDF.

Step One: Experiment with Generative AI

  • Experiment with ChatGPT or a similar application by inputting your own assignment prompts and assessing its performance in completing your assignments. Consider using a de-identified email account when doing so.
  • Research the potential benefits, use cases, limitations, and privacy concerns regarding generative AI to gain a sense of the potential applications and misuses of this technology.

Step Two: Review Your Learning Outcomes

  • Reflect on your course learning outcomes. Which outcomes lend themselves well to the use of generative AI and which skills go beyond the current limitations of AI? Keep this in mind as you move on to steps three and four, as the way students demonstrate achieved learning outcomes may need to be adjusted in course assignments/activities.

Step Three: Assess the Extent of AI Use in Class

  • Assess to what extent your course or discipline will be influenced by AI advancements. Are experts in your discipline already collaborating with tools like ChatGPT? Will current or future careers in your field work closely with these technologies?
  • Determine the extent of usage appropriate for your course. Will you allow students to use it all the time or not at all? If students can use it, is it appropriate for only certain assignments/activities with guidance and permission from the instructor? Be specific and clear with students and teach them how to cite ChatGPT.
  • Revisit your learning outcomes (step two). After assessing the impact of advancements in generative AI on your discipline and determining how the technology will be used (or not used) in your course, return to your learning outcomes and reassess if they align with course changes/additions you may have identified in this step.

Step Four: Review Your Assignments/Assessments

  • Review your assignments and evaluate whether revisions are needed to make them more resistant to generative AI or to incorporate generative AI collaboration. Which assignments are vulnerable to applications like ChatGPT and which ones can stay as is?
  • Provide an alternative for students who choose to opt-out of working with generative AI due to legitimate concerns regarding privacy and accessibility. This only applies if you choose to incorporate generative AI into an assignment.
  • View this CATL blog post on strategies for creating “generative AI-resistant” assessments for recommendations that focus on avoiding generative AI usage and view this resource on what aspects ChatGPT struggles to do.

Step Five: Update Your Syllabus

  • Add a syllabus statement outlining the guidelines you’ve determined pertaining to generative AI in your course. You can refer to our syllabus snippets for examples of ChatGPT-related syllabi statements.
  • Include your revised or new learning outcomes in your syllabus.

Step Six: Prepare to Address Misuse

  • Develop a plan for potential instances of suspected misuse. Your syllabus will be a valuable resource to communicate those expectations and boundaries to students.
  • Address and discuss your guidelines and expectations for generative AI usage with students on day one of class.

Step Seven: Seek Support and Resources

  • Engage with your colleagues to exchange experiences and best practices for incorporating or navigating generative AI.
  • Stay informed about advancements and applications of generative AI technology.

Need Help?

CATL is available to offer assistance and support at every step of the checklist presented above. Contact CATL for a consultation or by email at CATL@uwgb.edu if you have questions, concerns, or perhaps are apprehensive to go through this checklist.

Strategies for Creating “Generative AI-Resistant” Assessments

The use of generative-AI tools in education has recently garnered significant attention, placing educators in a unique position to consider their roles in higher education and how students engage with such tools. In a previous blog post, we introduced AI technologies and their endless capabilities, as well as potential implications for higher education. Additionally, we provided advice on considerations, precautions, and ethical concerns for using generative-AI in the classroom.

While some educators are excited about integrating AI collaboration into their teaching practices, others are apprehensive about its potential misuse by students. To address these concerns, this blog post presents assignment strategies that can be more “generative AI-resistant.” There are no “AI-proof” assessments, but these suggestions should serve as starting points for creating authentic assignments and/or ones that require demonstration of original and critical thinking.

Assessment Strategies

Be specific and personal

Consider creating assessments that involve tasks ChatGPT struggles to do such as referring to personal anecdotes or student reflections, referencing current events and recent field developments, or administering interviews or making references to specific course materials. Asking students to connect specific details from course materials (readings, lectures, experiments, etc.) to their personal lives or career paths can also help students see relevance in their course activities and engage with them on a deeper level.

Go beyond research papers

Instead of asking students to create a research paper that ChatGPT could do for them, ask students to create an annotated reference list that demonstrates their ability to apply proper research methods and analysis of resources collected. Alternatively, consider asking students to write a paper analyzing a case study that you’ve created yourself.

Mix up the medium

Incorporate assignments that make use of multimedia content such as creating, writing, recording, and producing a podcast episode relevant to course content and ideas.

Flip your classroom

Consider using in-class time for activities like classroom debates and/or peer-to-peer feedback on projects. Grade those efforts that are happening in real-time and under your observation (without generative AI). Note that a flipped classroom approach also allows students to practice higher order thinking and application of the content they’ve learned through homework.

Look at grading

Consider reviewing your course grading criteria and use growth-oriented rubrics that prioritize process over product.

Ask students to show their process

Consider adding assignment elements that ask students to think about the process of their work. This could be done by requiring students to submit notes they took on sources to prepare for their papers or presentations. You could also ask students to show their work in progress as they move toward a final draft (e.g., require submission of a project outline or proposal, annotated bibliography, and multiple drafts).

Allow for growth and resubmission

Consider adding in some flexibility when students fall short of an objective by allowing for revisions or resubmissions on certain assignments. This can reduce the “high stakes” nature of assessments and associated pressures.

Make adjustments to current assessments

Review your existing assignments to see if there are areas where you can have students demonstrate their holistic growth and development. For exams, you could add supplemental reflection questions or even consider adopting oral exams.

A Note on Academic Honesty

It can be easy or tempting to spend a lot of effort trying to catch instances of academic dishonesty using tools like ChatGPT. Although there are detection tools available, such as Turnitin, the effectiveness of AI detection reports remains uncertain due to insufficient data. Please review our blog on Considerations for Using Generative AI Tools to learn more and remember how important it is to communicate explicitly with students about if, when, and how they may use AI in your class.

Learn More

Explore even more CATL resources related to AI in education:

If you have questions, concerns, or ideas specific to generative AI tools in education and the classroom, please email us at catl@uwgb.edu or set up a consultation!

Considerations for Using Generative AI Tools

Staying updated on the rapidly evolving generative-AI tools can be challenging, and educators may hold divergent (and strong!) views about them. In a previous article, we introduced generative-AI technologies, their capabilities, and implications for higher education. While some educators are enthusiastic about incorporating AI into their teaching methodologies, others may harbor doubts, apprehensions, or simply lack interest in exploring these tools. Regardless of one’s stance, understanding the disruptive impact of these technologies is crucial as we grapple with their ethical and pedagogical implications as educators.

In this article, we will explore some considerations for using generative-AI tools in the classroom, including preliminary precautions and ethical concerns. The more we understand these technologies, the better we can adapt to maximize their potential benefits while minimizing their negative impact.

Things to Consider When Using AI-Powered Tools in your Courses

Understand the inevitability of advancing AI technology.

AI, like many other recent technologies (e.g., personal computers or the internet), will continue to advance and not go away. In fact, they will progress and become better than previous models. This is not something we can “outrun.”

Encourage dialogue on the impact of AI in education

Consider discussing AI technology and its implications with your department, colleagues, and students. In what ways will generative-AI tools change the nature of learning outcomes and even careers in your discipline? How are other instructors responding? In what ways can instructors support each other as they each grapple with these questions?

Provide clear communication with your students on expectations

Whichever camp or situation you may fall into, it is always important to provide students with clear expectations for their use of AI in the classroom. Be specific in your syllabi and assignment descriptions about where and when you will allow or prohibit the use of these tools. You should also make sure whatever guidance you provide is also consistent with UWS Chapter 14 and the communications from our Provost Office. For example statements, view our Syllabus Snippets related to generative-AI

Use generative-AI tools with caution

Exercise caution when using generative-AI tools because the information provided by them may not always be accurate. AI creators, like OpenAI, are upfront about the fact that ChatGPT’s answers aren’t always correct. Due to their ability to hallucinate facts and resources, it’s best to avoid using these tool as a primary source. Be sure to also watch out for potential bias that can appear in outputs by these tools as they are trained on human-generated data.

Offer alternatives for privacy-minded students

If you are asking students to complete an assignment using generative-AI technology, you will also want to provide an opt-out or alternative assignment because students may legitimately not want to provide personal information to sign-up and use certain AI technologies. Many tools openly state they will sell that information.

AI detection tools are not perfect

When using Turnitin’s AI writing detection indicator, it is important to note that there is currently insufficient data to validate its effectiveness. Therefore, results from such reports should be treated as signals that additional review may be necessary. If you suspect academic misconduct, be prepared to support the claim with additional information beyond the detection tool’s report.

Consider ethical and legal issues when using AI tools

As instructors, it is also important to consider the potential ethical, legal, and security risks of AI technologies. Many generative-AI tools are “trained” on the data we put into them, so we must exercise caution when providing prompts to the tools. For example, never put students’ personal information into an AI-powered tool, as this may violate FERPA. Asking students to submit their work (or doing it yourself) to get feedback from ChatGPT or a similar resource puts their intellectual property into the public domain. This should not be done without their explicit consent.

Prepare students to use AI effectively

If you assign tasks that require students to use AI technology, it is important to provide clear instructions about how to do so and not assume students already know. Consider incorporating a discussion on the benefits, limitations, cautions, and ethics of using generative-AI. This could be a valuable in-class activity.

Don’t get caught up in the smoke

Although the capabilities of generative-AI can be scary or worrying at this point, it is best to not get bogged down in the negatives of AI or focus on how to detect cheating through AI use. Are you worried about what AI tools mean for your course materials? Schedule a consultation with us. CATL is here to help!

Learn More

Explore even more CATL resources related to AI in education:

If you have questions, concerns, or ideas specific to generative AI tools in education and the classroom, please email us at catl@uwgb.edu or set up a consultation!

What is ChatGPT? Exploring AI Tools and Their Relationship with Education

Artificial Intelligence (AI) and machine-generated content have become prominent in educational discussions. Amidst technical jargon and concerns about the impact of traditional writing and learning, understanding these topics can be overwhelming. This toolbox guide simplifies the generative AI landscape, providing clear definitions and insights into some commonly used generative AI tools.

What is Generative AI?

To provide an introduction to generative AI, CATL has created an informative video presentation. This video, paired with interactive PowerPoints slides, serves as a valuable resource for understanding how generative AI tools work, their capabilities, and limitations.

Introduction to Generative AI – CATL Presentation Slides (PDF)

Common Generative AI Tools

One of the most popular AI-powered text generators is ChatGPT by OpenAI. Since its November 2022 release, various companies have developed their own generative AI applications based on or in direct competitive with OpenAI’s framework. Learn more about common generative AI tools below.

Note: For UWGB faculty, staff, and students, we recommend using Microsoft Copilot and other tools that do not require users to provide personal information in the sign-up process.

What Can Generative AI Tools Do?

The generative AI tools we’ve discussed so far are all trained on large datasets that produce outputs based on patterns in that dataset. User prompts and feedback can be used to improve their outputs and models, so these tools are constantly evolving. Explore below to learn about general use cases for generative AI tools and their limitations.

Generative AI tools can be used in a multitude of ways. Some common uses cases for text-based generative AI tools include: 

  • Language generation: Users can ask them to create essays, poems, or code snippets on a given topic.  
  • Information retrieval: Users can ask them to answer simple non-academic questions like “explain the rules of football to me” or “what is the correct way to use a semicolon?”  
  • Language translation: Users can ask them to translate words or phrases into different languages.  
  • Text summarization: Users can ask them to condense notes from a lecture and or long texts, including entire books, into shorter summaries. 
  • Idea generation & editorial assistance: Users can ask them to brainstorm and generate ideas for a story or a research outline or provide feedback on writing to make it more concise or formal.  

However, these tools also have some limitations, including but not limited to:  

  • Lack of real-world understanding: They do not understand the context and/or logic of the real world. They do not understand sarcasm, analogies, jokes, and satire. For example, an output created by the technology may be grammatically correct, but semantically is nonsensical or contradictory.  
  • Dependent upon the data it is trained on: They may produce outputs that are not accurate, relevant, or current because they rely on the data they are trained on. 
  • False results or hallucinated responses: They may produce outputs that are false, misleading, or plagiarized from other sources, and are unable to verify the accuracy of their outputs.  
  • Machine learning bias: They may produce outputs that are discriminatory or harmful due to bias in the data they are trained on.  

The possibilities of tools like ChatGPT seem to be almost endless — writing complete essays, creating poetry, summarizing books and large texts, creating games, and translating languages and data. ChatGPT and its contemporaries can understand text and spoken words similar to how human beings can. These tools have become more conversational and corrective with each update, making it difficult to discern between what is generated by an AI and what is produced by a human. In addition, the data and algorithms they draw from imitate the way humans learn and can gradually improve their accuracy the more you interact with it. As explored above, they offer large potential in their use cases, yet they still come with their own set of limitations to consider.

What Does This Mean for Educators?

The existence of this technology raises questions about which tasks will be completed all or in part by machines in the future and what that means for our learning outcomes and assessments. Some experts are also discussing to what extent it should become part of the educational enterprise to teach students how to write effective AI prompts and use tools like ChatGPT thoughtfully to produce work that balances quality with efficiency.

One way to approach the conversation surrounding AI technology is to consider these applications as tools that educators can choose either to work with or without in their classes. Some may also consider teaching their students how to use these tools most effectively and/or integrating lessons on AI ethics into their teaching. With any teaching tool we look to incorporate, we must provide proper thought, scaffolding, and framing around what it can do and where it falls short so that students can use the tool responsibly.

Learn More

Explore even more CATL resources related to AI in education:

If you have questions, concerns, or ideas specific to generative AI tools in education and the classroom, please email us at catl@uwgb.edu or set up a consultation!

Reading and Resources About AI in Education

To help you as you research and explore AI tools, we have provided a list of resources and additional readings on the topic of Generative AI technology below.

Additionally, CATL developed a GenAI checklist for instructors that will help you assess the extent to which generative AI will affect your courses and provide guidance on steps for moving forward.

Generative Artificial Intelligence In the Classroom

ChatGPT, built on the GPT-4 system, and other Generative AI platforms, offer unique opportunities for instructors and students to leverage the technology while still providing robust, comprehensive learning experiences. However, some instructors are apprehensive about its potential misuse by learning activities. Below you will find a variety of resources on how to use generative AI in classroom activities, with examples of activities that may not require any usage of AI.

Add a Generative AI Syllabus Statement

Incorporating Generative AI

Working Around Generative AI

Additional Resources on Assessment and Generative AI

Learning to Use AI Yourself

Playing Around with AI

Additional Commentary on AI (Articles, Podcast, etc.)

Other Center Resources

Learn More

Explore even more CATL resources related to AI in education:

If you have questions, concerns, or ideas specific to generative AI tools in education and the classroom, please email us at catl@uwgb.edu or set up a consultation!