Artificial Intelligence

Recent advances in artificial intelligence (AI) for writing (including CoPilot and ChatGPT) can quickly create coherent, cohesive prose and paragraphs on a seemingly limitless set of topics. The potential for abuse in academic integrity is clear, and our students are likely using these tools already. There are similar AI tools for creating images, computer code, and many other domains. Here’s an overview video (33 minutes) of what AI actually is and how it impacts teaching and learning.

Most of this guide concerns generative AI (GenAI) such as large-language models (LLMs) that function as word-predictors and can generate text and entire essays. As AI represents a permanent addition to society and students’ tools, we need to permanently re-envision how we assign college writing and other projects. As such, FCTL has assembled this set of ideas to consider.

Category 1: Lean into the Software’s Abilities

Re-envision writing as editing/revising. Assign students to create an AI essay with a given prompt, and then heavily edit the AI output using Track Changes and margin comments. Such an assignment refocuses the work of writing away from composition and toward revision, which may be more common in an AI-rich future workplace. Generative AI (GenAI, such at Copilot or ChatGPT) is spectacular at providing summaries, but they lack details and specifics, which could be what the students are tasked to do. Other examples include better connecting examples to claims, and revising overall paragraph structure in service of a larger argument. Here are some example assignments using GenAI as part of the writing prompt.
Re-envision writing as first and third stage human work, with AI performing the middle. Instead of asking students to generate the initials drafts (i.e., “writing as composition”), imagine the student work instead focusing on creating effective prompts for the AI, as well editing the AI output.
Focus student learning on creative thesis writing by editing AI-created theses. The controlling statement for most AI essays can be characterized as summary in nature, rather than analytical. Students can be challenged to transform AI output into more creative, analytical theses.
Refine editing skills via grading. Assign students to create an AI essay and grade it, providing specific feedback justifying each of the scores on the rubric. This assignment might be paired with asking students to create their own essay responding to the same prompt.
Write rebuttals. Ask the AI to produce a custom output you’ve intentionally designed, then assign students to write a rebuttal of the AI output.
Create counterarguments. Provide the AI with your main argument and ask it to create counterarguments, which can be incorporated – then overcome – in the main essay.
Evaluate AI writing for bias. Because the software is only as good as information it finds and ingests (remember the principle of GIGO: garbage in, garbage out), it may well create prose that mimics structural bias and racism that is present in its source material. AI writing might also reveal assumptions about the “cultural war” separating political parties in the United States.
Teach information literacy through AI. Many students over-trust information they find on websites; use AI software to fuel a conversation about when to trust, when to verify, and when to use information found online.
Give only open-book exams (especially online). Assume that students can and will use the Internet and any available AI to assist them.
Assign essays, projects, and tests that aim for “application” and above in Bloom’s taxonomy. Since students can look up knowledge/information answers and facts, it’s better to avoid testing them on such domains, especially online.
Teach debate and critical thinking skills. Ask the AI to produce a stance, then using the tools of your discipline evaluate and find flaws/holes in its position or statements.
Ask the AI to role play as a character or historical figure. Since GenAI is conversation-based, holding a conversation with an in-character personality yields insights.
Overcome writer’s block. The AI output could provide a starting point for an essay outline, a thesis statement, or even ideas for paragraphs. Even if none of the paragraphs (or even sentences) are used, asking the AI can be useful for ideation to be put into one’s own words.
Treat it like a Spellchecker. Ask your students to visit GenAI, type “suggest grammar and syntax fixes:” and then paste their pre-written essay to gain ideas before submission. (Note: for classes where writing ability is a main learning outcome, it might be advisable to require that students disclose any such assistance).
Make the AI your teaching assistant. When preparing a course, ask the AI to explain why commonly-wrong answers are incorrect. Then, use the Canvas feedback options on quiz/homework questions to paste the AI output for each question.
Teach sentence diagramming and parts of speech. Since AI can quickly generate text with variety in sentence structures, use the AI output to teach grammar and help students how better to construct sophisticated sentences.
Engage creativity and multiple modes of representation to foster better recall. Studies show that student recall increases when they use words to describe a picture, or draw a picture to capture information in words. Using AI output as the base, ask students to create artwork (or performances) that capture the same essence.
Teach AI prompt strategies as a discreet subject related to your field. AI-created content is sure to be a constant in the workplace of the future. Our alumni will need to be versed in crafting specific and sophisticated inputs to obtain best AI outputs.
Create sample test questions to study for your test. Given appropriate prompts, AI can generate college-level multiple choice test questions on virtually any subject, and provide the right answer. Students can use such questions as modern-day flash cards and test practice.
View more ideas in this free e-book written by FCTL: “60+ Ideas for ChatGPT Assignments,” which is housed in the UCF Library’s STARS system. Even though the ebook mentions ChatGPT in its title, the assignment prompts work for most GenAI, including CoPilot, our official university LLM.

Category 2: Use the software to make your teaching/faculty life easier

Create grading rubrics for major assignments. Give specifics about the assignment when asking the software to create a rubric in table format. Optionally, give it the desired sub-grades of the rubric.
Write simple or mechanical correspondence for you. GenAI is fairly good at writing letters and formulaic emails. The more specific the inputs are, the better the output is. However, always keep in mind the ethics of using AI-generated writing wholesale, representing the writing as your own words–particularly if you are evaluating or recommending anything. AI output should not be used, for instance, in submitting peer reviews.
Adjust, simplify, shorten, or enhance your formal writing. The software could be asked to shorten (or lengthen) any professional writing you are composing, or to suggest grammar and syntax fixes (particularly useful for non-native speakers of English!) In short, you could treat it like Spellchecker before you submit it. However, again consider the ethics of using AI content wholesale–journals and granting agencies are still deciding how (or whether) to accept AI-assisted submissions, and some have banned it.
Summarize one-minute papers. If you ask students for feedback, or to prove they understand a concept via one-minute papers, you can submit these en masse and ask the AI to provide a summary.
Generate study guides for your students. If you input your lecture notes and ask for a summary, this can be given to students as a study guide.
Create clinical case studies for students to analyze. You can generate different versions of a case with a similar prompt.
Evaluate qualitative data. Provide the AI with raw data and ask it to identify patterns, not only in repeated words but in similar concepts.
What about AI and research? It’s best to be cautious, if not outright paranoid, about privacy, legality, ethics, and many related concerns, when thinking about exposing your primary research to any AI platform–especially anything novel that could lead to patent and commercialization. Consult the IT department and the Office of Research before taking any action.
Create test questions and banks. The AI can create nearly limitless multiple-choice questions (with correct answers identified) on many topics and sub-topics. Obviously, these need to be proof-read and verified before using with a student audience.

Category 3: Teach Ethics, Integrity, and Career-Related Skills

Discuss the ethical and career implications of AI-writing with your students. Early in the semester (or at least when assigning a writing prompt), have a frank discussion with your students about the existence of AI writing. Point out to them the surface-level ethical problem with mis-representing their work if they choose to attempt it, as well as the deeper problem of “cheating themselves” by entering the workforce without adequate preparation for writing skills, a quality that employers highly prize.
Create and prioritize an honor code in your class. Submitting AI-created work as one’s own is, fundamentally, dishonest. As professionals, we consider it among our top priorities to graduate individuals of character who can perform admirably in their chosen discipline, all of which requires a set of core beliefs rooted in honor. Make this chain of logic explicit to students (repeatedly if necessary) in an effort to convince them to adopt a similar alignment toward personal honesty. A class-specific honor code can aid this effort, particularly if invoked or attested to when submitting major assignments and tests.
Reduce course-related workload to disincentivize cheating. Many instances of student cheating, including the use of AI-writing, is borne out of desperation and a lack of time. Consider how realistic the workload you expect of students is

Category 4: Attempt to neutralize the software

Faculty looking to continue assigning take-home writing and essays may be interested in this list of ideas to customize their assignments so that students do not benefit from generative AI. However, this approach will likely fail in time, as the technology is improving rapidly, and automated detection methods are already unreliable (at UCF, in fact, the office of Student Conduct and Academic Integrity will not pursue administrative cases against students where the only evidence is from AI detectors). Artificial intelligence is simply a fact of life in modern society, and its use will only become more widespread.

Possible Syllabus Statements

Faculty looking for syllabus language may consider one of these options:

Use of AI prohibited. Only some Artificial Intelligence (AI) tools, such as spell-check or Grammarly, are acceptable for use in this class. Use of other AI tools via website, app, or any other access, is not permitted in this class. Representing work created by AI as your own is plagiarism and will be prosecuted as such. Check with your instructor to be sure of acceptable use if you have any questions.
Use of AI only with explicit permission. This class will make use of Artificial Intelligence (AI) in various ways. You are permitted to use AI only in the manner and means described in the assignments. Any other use of AI requires explicit permission from the instructor. Any attempt to represent AI output inappropriately as your own work will be treated as plagiarism.
Use of AI only with acknowledgement. Students are allowed to use Artificial Intelligence (AI) tools on assignments if the usage is properly documented and credited. For example, text generated from Copilot should include a citation such as: “Copilot. Accessed 2023-12-03. Prompt: ‘Summarize the Geneva Convention in 50 words.’ Generated using http://bing.com/chat.”
Use of AI is freely permitted with no acknowledgement. Students are allowed to use Artificial Intelligence (AI) tools in all assignments in this course, with no need to cite, document, or acknowledge any support received from AI tools.
Use of AI will be required. In this course, various assignments require you to complete tasks with the aid of Copilot, while logged in with your NID. When logged in this way, Copilot is safe, private, and free.

If you write longer announcements or policies for students, try to aim for a level-headed tone that neither overly demonizes AI nor overly idolizes it. Students who are worried about artificial intelligence and/or privacy will be reassured by a steady, business-like tone.

AI Detection and Unauthorized Student Use

AI detectors are not reliable and relatively easy for students to beat, so UCF does not have a current contract with any detector. If you use third-party detectors, you should keep in mind that both false positives and false negatives can occur, and student use of Grammarly can return a result of “written by AI.”

FCTL recommends that you NOT use AI detectors.

Because the detectors don’t work, independent verification is required. If you have other examples of this student’s writing that does not match, that might be reason enough to take action. Evidence of a hallucinated citation is even stronger.

A confession of using AI by the student is, of course, the gold standard for taking action.
One approach might be to call the student to a private (virtual?) conference and explain why you suspect the student used AI and ask them how they would account for these facts.
Another option is to inform them of your intention to fail the paper, but offer them the chance to perform proctored, in-person writing on a similar prompt to prove they can write at this level.

The S tudent Conduct and Academic Integrity office will not “prosecute” a case where the only evidence comes from an AI detector, due to the possibility of false positives and false negatives. A hallucinated citation does constitute evidence.

They do still encourage you to file a report in any event and can offer suggestions on how to proceed.
Existing university-level policies ban students from representing work that they did not create as their own, so it’s not always necessary to have a specific AI policy in your syllabus – but it IS a best practice to have such a policy for transparency to students and to communicate your expectations. After all, the lived experience of students is that different faculty have different expectations regarding AI, and extreme clarity is always best.

At the end of the day, the final say about grading remains with the instructor. We recognize that in marginal cases, it might come down to a “gut feeling.” Every instructor has a spectrum of response available to them, from “F” for the term, an “F” or zero for the assignment, a grade penalty (10%? 20%?) applied to the assigned grade, a chance to rewrite the assignment (with or without a grade penalty), taking no grade action but warning the student not to do it again, or to simply letting it go without even approaching the student.

Be aware that students have the right to appeal academic grades. For that reason, it may be advisable to check with your supervisor about how to proceed in specific cases.

Because of all of these uncertainties, FCTL suggests that faculty consider replacing essay writing with another deliverable that AI cannot today generate (examples include narrated PowerPoint, narrated Prezi, selfie video presentation WITHOUT reading from a script, digital poster, flowcharts, etc.) An alternative is to include AI-generated output as part of the assignment prompt, and then require the students to “do something” with the output, such as analyze or evaluate it.

AI at UCF

The Faculty Center recommends that UCF faculty work with Copilot (formerly Bing Chat Enterprise) over other large-language model AI tools. The term Copilot is also used by Microsoft to refer to embedded AI in MS Office products, but the web-based chat tool is separate.

Copilot with Commercial Protection is NOT the same thing as “Copilot.” The latter is the public model of Microsoft’s LLM, also available on the web. Copilot with Commercial Protection (if logged in with a UCF NID) is a “walled garden” for UCF that offers several benefits:

It searches the current Internet and is not limited to a fixed point in time when it was trained
It uses GPT-4 (faster, better) without having to pay a premium
It uses DALL-E 3.0 to generate images (right there inside CoPilot rather than on a different site)
It provides a live Internet link to verify the information and confirm there was no hallucination
It does not store history by user; each logout or new session wipes the memory. In fact, each query is a new blank slate even within the same session, so it’s not possible to have a “conversation” with Copilot (like you can with ChatGPT)
Faculty and students log in with their NID
Data stays local and is NOT uploaded to Microsoft or the public model version of Copilot. Inputs into Copilot with Commercial Protection are NOT added to the system’s memory, database, or future answers

The safe version of UCF’s Copilot is accessed via this procedure:

Start at the Copilot greeting page.
- If the site doesn’t recognize your UCF email, switch to the Edge browser.
Click “sign in” at the top-right
Select “work or school” for the type of account
Type your full UCF email (including @ucf.edu) and click NEXT
Log in with your NID and NID password. (Note: you may need to alter your SafeSearch settings away from “Strict”)
You may not always see on-screen verification that you are in “data protection” mode, but if you’re logged in with the steps above, it will be protected.

AI Fluency

We recommend that faculty approach the AI revolution with the recognition that AI is here to stay and will represent a needed skill in the workplace of the future (or even the present!) As such, both faculty and students need to develop AI Fluency skills, which we define as:

Understanding how AI works – knowing how LLMs operate will help users calibrate how much they should (mis)trust the output.
Deciding when to use AI (and when not to) – AI is just another tool. In some circumstances users will get better results than a web-based search engine, but in other circumstances the reverse may be true. There are also moments when it may be unethical to use AI without disclosing the help.
Valuing AI – a dispositional change such as this one is often overshadowed by outcomes favored by faculty on the cognitive side, yet true fluency with AI – especially the AI of the future – will require a favorable disposition to using AI. Thus, we owe it to students to recognize AI’s value.
Applying effective prompt engineering methods – as the phrase goes, “garbage in, garbage out” applies when it comes to the kind of output AI creates. Good prompts give better results than lazy or ineffective prompts. Writing effective prompts is likely to remain a tool-specific skill, with different AI interfaces needing to be learned separately.
Evaluating AI output – even today’s advanced AI tools can create hallucinations or contain factual mistakes. Employees in the workplace of the future – and thus our students today – need expertise in order to know how trustworthy the output is, and they need practice in fixing/finalizing the output, as this is surely how workplaces will use AI.
Adding human value – things that can be automated by AI will, in fact, eventually become fully automated. But there will always be a need for human involvement for elements such as judgment, creativity, or emotional intelligence. Our students need to hone the skill of constantly seeking how humans add value to AI output. This includes sensing where (or when) the output could use human input, extrapolation, or interpretation, and then creating effective examples of them. Since this will be context-dependent, it’s not a single skill needed so much as a set of tools that enable our alumni to flourish alongside AI.
Displaying digital adaptability – today’s AI tools will evolve, or may be replaced by completely different AI tools. Students and faculty need to be prepared for a lifetime of changing AI landscapes. They will need the mental dexterity and agility to accept these changes as inevitable, and the disposition to not fight against these tidal forces. The learning about AI, in other words, should be expected to last a lifetime.

“60+ ChatGPT Assignments to Use in Your Classroom Today”

The Faculty Center staff assembled this open-source book to give you ideas about how to actually use AI in your assignments. It is free for anyone to use, and may be shared with others both inside and outside of UCF.

“50+ AI Hacks for Educators”

The Faculty Center staff wrote this second open-source book that provides ideas on how to use AI in your own life as a faculty member, including research and productivity. It is free for anyone to use, and may be shared with others both inside and outside of UCF.

“Teach with AI” Conference

UCF’s Faculty Center and Center for Distributed Learning are co-hosts of the “Teach with AI” annual conference. This is a national sharing conference that uses short-format presentations and open forums to focus on the sharing of classroom practices by front-line faculty and administrators, rather than research about AI. Although this conference is not free for UCF faculty and staff, we hold separate internal events about AI that are free for UCF stakeholders.

AI Fundamentals for Educators Course

Interested in diving deeper in using AI, not just for teaching but also in your own research? Join the Faculty Center for this 6-week course! Held face to face on the Orlando campus, this course includes topics such as:

LLM models (explore the differences in ChatGPT, Bard/Genesis, CoPilot, and Claude), the art of prompt engineering, and how to incorporate these tools into lesson planning, assignments, and assessments.
Image, audio, and video generation tools and how to create interactive audio and video experiences using various GenAI tools while meeting digital accessibility requirements.
Assignment and assessment alterations to include—or combat—the use of GenAI tools in student work.
Interactive teaching tools for face-to-face AND online courses.
AI tools that assist students—and faculty—with discipline-specific academic papers and research.
Teaching AI fluency and ethics to students.

Registration details are on our “AI Fundamentals page.”

Asynchronous Training Module on AI

Looking for a deeper dive into using AI in your teaching and research, but need a self-paced online option? We’ve got that too! Click on this website to self-enroll in this training Webcourse.

Repository of AI Tools

There are several repositories that attempt to catalog all AI tools (futurepedia.io and theresanaiforthat stand out in particular), but we’ve been curating a smaller, more targeted list here.

AI Glossary

Canva – a “freemium” online image creating/editing tool that added AI-image generation in 2023
ChatGPT – the text-generating AI created by OpenAI
Claude – the text-generating AI created by Anthropic (ex-employees of OpenAI)
Copilot – a UCF-specific instance of Microsoft’s LLM, using UCF logins and keeping data local (note: confusingly, this name is ALSO used by Microsoft for AI embedded in Microsoft Office products, but UCF does not purchase this subscription).
DALL-E – the image-generating AI created by OpenAI
Gemini – an LLM from Google (formerly known as Bard)
Generative AI – a type of AI that “generates” an output, such as text or images. Large language models like ChatGPT are generative AI
Grok – the generative AI product launched by Elon Musk
Khanmigo – Khan Academy’s GPT-powered AI, which will be integrated into Canvas/Webcourses (timeline uncertain)
LLM (Large Language Model) – a type of software / generative AI that accesses large databases it’s been trained on to predict the next logical word in a sentence, given the task/question it’s been given. Advanced models have excellent “perplexity” (plausibility in the word choice) and “burstiness” (variation of the sentences).
Midjourney – an industry-leading text-to-AI solution (for profit)
OpenAI – the company that created ChatGPT and DALL-E
Sora – a text-to-video generative AI from OpenAI