Using AI
AI can be useful to educators and students alike. In fact, you may feel more confident in talking about AI with students if you practice using the tools across your own areas of work (research or teaching preparation). There’s a number of ways to begin experimenting and working with AI, depending on what you’re trying to accomplish. Text-based, analytics, and visualization AI tools can all assist you and your students depending on the desired activity.
AI tool by activity
See this list of AI tools grouped by activity:
| Task | Tool |
|---|---|
| Idea generation | LLMs such as ChatGPT, Gemini, Copilot, Perplexity , Claude, IdeaNote |
| Concept mapping & planning | Lucidchart |
| Time/project management | krisp, Goblin Tools, Trello, Asana |
| Research | Elicit, typeset.io, Rayyan, Explainpaper, Connectedpapers, Research Rabbit, Scite, Perplexity, Semantic Scholar |
| Summarizing | Chat PDF, Glasp, ChatGPT, Gemini, Bing, Claude, Smmry |
| Outlining & drafting | LLMs such as ChatGPT, Claude, Gemini, Copilot, Perplexity, Bing, Claude, Kickresume, textblaze.me, Scrivener |
| Collaborative writing | Overleaf, Authorea |
| Reference management | Zotero, Mendeley, EndNote, Citavi |
| Coding | hashnode.com/ai, Fronty, Tabnine, debugcode.ai, Stack Overflow |
| Data analysis & statistical analysis | GPT4,Tableau AI, Excel, Google Workspace (non-GU), Power.bi, Rstudio (tidyverse). These tools work with: SPSS, SAS, Stata, Python (pandas, NumPy) |
| Data visualization | D3.js, Plotly, Infogram, Datawrapper, Adobe Illustrator |
| Presentation tools | Gamma, SlidesGPT, Canva, Prezi |
Below, we explain how AI tools can help make your teaching preparation workflow more efficient, with the dual-goal of familiarizing yourself with AI tool capabilities. Then we share some insight into how students use these tools.
Back to top arrow_upwardUsing AI as faculty
AI can be used to support your original, authentic writing—work that you have produced, edited, and to which you have invested thought and emotion. The focus of using AI to support your teaching and research workflows should be on augmentation, not automation. AI tools have the capability to make many teaching tasks less labor-intensive while maintaining your original ideas and direction.
See below for some samples of the tasks for which you can use AI.
Prompting tips and examples
Administrative support
Try the following prompts in Claude, Gemini, Perplexity, or ChatGPT.
| Task | Prompt example |
|---|---|
| Scheduling help | Please provide faculty members with a listing of all the Tuesdays between August 21 and December 18. Please list them in the following format: Tuesday, September [Date]. If any US holidays happen between each Tuesday listed, please include the holiday and its date. Additionally, please include any religious holidays or special days for Christianity, Judaism, Islam, Hinduism, or other major religions. See sample response. |
| Data synthesis | Please synthesize these documents and create a spreadsheet tracking the details of various grant applications. Include detail categories such as the grantee, application due date, funding amount, and any other relevant details. Do not summarize or leave anything out. |
| Info/summary table | Can you please provide a 200-300 word summary for faculty and staff of how FERPA protects student privacy? Please also provide the same information in a table. |
| Outline | Please organize these notes in this document into an outline for a scholarly paper. Be sure to retain the citations for references that the notes indicate. Be sure to identify clear themes and possibilities for future work . |
Creating quick assessments
It’s also possible to use a more elaborate prompt which asks an AI tool to play a particular role. This approach will result in the LLM drawing on ‘knowledge’ or data that is tightly linked to the context and audience. Of course after seeing what AI generates, edit the content as needed for your learning goals and course.
| Task | Prompt example |
|---|---|
| Multiple choice prompt | “You are a quiz creator of highly diagnostic quizzes. You will look up how to develop low-stakes tests and diagnostics. You will construct several multiple-choice questions to quiz the audience on the topic of [storytelling]. The questions should be highly relevant and go beyond just facts. Multiple choice questions should include plausible, competitive alternate responses and should not include an “all of the above option.” At the end of the quiz, you will provide an answer key and explain the right answer. See sample response (requires login). |
| Simulation or personalized feedback generator | “I want to practice my knowledge of [CONCEPT]. You’ll play [ROLE]. Create a scenario in which I can practice. Give me dilemmas or problems [SCENARIO]. After 4 interactions, set up a consequential choice for me to make. Then wrap up by telling me how I performed in [SCENARIO] as [MY ROLE] and what I can do better next time. Do not play my role. Only play the role of [AI’S ROLE]. [OTHER CONSTRAINTS] Wait for me to respond before proceeding.” See sample interaction. |
| Rubric generator | “Could you create a rubric for a college-level final project presentation? I’d like the rubric to include the following criteria: content knowledge, clarity of presentation, visual aids, and engagement with the audience. Please set up four levels of achievement (Excellent, Good, Satisfactory, Needs Improvement) and describe what each level entails for all criteria. Assign point values out of 25, with each level differentiated by 5 points.” |
Considerations
A note on detection tools
Though Turnitin initially enabled its AI detection in Canvas assignments for Georgetown University, it has been disabled primarily because the tool has been reported to identify sentence-level false positives at a rate of 4% or higher, and has proven to falsely identify AI-written text at much higher rates in many other discrete instances (D’Agostino, 2023; Chechitelli, 2023). As Turnitin’s Chief Product Officer noted in a blog post, the detection tool has been designed to provide a “flag report,” serving as an “indicator” rather than a confirmation that language in an assignment may have been written by AI (Chechitelli, 2023). As LLMs become increasingly sophisticated, the accuracy and precision of detection software decreases (Sadasivan et al., 2023).
Additionally, “instances of false accusations of AI usage being leveled against students at other universities have been widely reported over the past few months, including multiple instances that involved Turnitin (Fowler, 2023; Klee, 2023).” One of the harmful side effects of the detection software’s inaccuracy has been impacting non-native English speakers (Sample, 2023; Myers 2023; Liang et al, 2023). Other universities—see Vanderbilt University and the University of Pittsburgh—have also disabled Turnitin’s AI detector. The Center for New Designs in Learning and Scholarship advises against relying on an AI detector to assess student work, and set forth clear expectations about how AI tools can or cannot be used in assessments/assignments.
Bias and inclusivity
We all bring biases with us into the classroom (Banaji & Greenwald 2013); and so do AI tools, maybe even more so. See the resources below which expand on the ways AI tools may amplify biases, and how to address and mitigate these biases to whatever extent possible:
- Berkeley HAAS Centre for Equity, Gender and Leadership (2023). Bias in AI: Examples Tracker. [Google Sheets]
- D’Ignazio, C. and Klein, L. (2020). Data feminism. MIT Press.
- Gross, N. (2023). What ChatGPT Tells Us about Gender: A Cautionary Tale about Performativity and Gender Biases in AI. Social Sciences, 12(8), 435.
- Henneborn, J. (2023). Designing Generative AI to Work for People with Disabilities. Harvard Business Review.
- Sharma, Kriti. (2019). How to keep human bias out of AI [Video]. YouTube.
- Weerts, H., Dudík, M., Edgar, R., Jalali A., Lutz, R., and Madaio, M. (2023). Fairlearn: Assessing and Improving Fairness of AI Systems.
- Zhou, X. and Schofield, L. (2023).Towards an inclusive approach to using AI in learning and teaching. Wonkhe.
Data and privacy
Among the many complications surrounding data and privacy in generative and detection (see below) AI tools, one issue prominently arises: “when plagiarism detection services archive student work… student privacy rights may be violated,” (Brinkman 2013). Do not upload any student work to AI tools (generators or detectors) without their permission. It’s important to “consider whether the information about students shared with or stored in an AI-enabled system is subject to federal or state privacy laws, such as FERPA,” (Department of Education 2023).
As you talk with your students about data and privacy implications, you may want to review the privacy policies you (and students) are agreeing to by engaging with the tools. For example, in teaching with Chat GPT, read over the porous privacy policy with students and discourage them from sharing personal information on the platform. Note that:
- The company may access any information fed into or created by its technology.
- They use log-in data, tracking, and other analytics.
- Their technology does not respond to “Do Not Track.”
Allow students to opt out if they don’t feel comfortable having their data collected. See Open AI’s full policy here and these FAQs on how the company may use information shared with it.
Back to top arrow_upwardUsing AI as a student
When it comes to final touches or formatting help, AI is useful to students in a variety of school-related tasks.
- Copyediting and revision: Students may use the grammar and spell-checking capabilities of AI tools like Grammarly and ChatGPT to copyedit their writing, even if the original body of work was completely self-written.
- Finding academic sources and literature reviews: Text-based tools like Elicit and Perplexity provide a starting place for students to search and analyze academic research papers, given a topic or research question.
- Presentations and powerpoints: Tools like SlidesGPT and Gamma create visuals and slide decks that students may use as starting points for their presentations.
- Professional and career development: AI tools are popular resources for career development outside of the classroom, including resume and cover letter writing and even interview preparation. These include tools like Kickresume and Huntr.