(from Faculty Focus, October 29, 2025 by Sybil Prince Nelson, PhD)

Parents who grew up in the ’80s and ’90s know the feeling: you’re listening to your kid’s playlist, and suddenly a song hits you with a wave of uncanny familiarity. Despite the claims by your teen that it is the latest and greatest, you know that it is just a repackaging of one of your favorite tunes from the past. I am noticing a similar trend with generative AI. It is inherently regurgitative: reshaping and repackaging ideas and thoughts that are already out there. 

Fears abound as to the future of higher education due to the rise of generative AI. Articles from professors in many different fields predict that AI is going to destroy the college essay or even eliminate the need for professors altogether. Their fears are well founded. Seeing the advances that generative AI has made in just the past few months, I am constantly teetering between immense admiration and abject terror. My Chatbot does everything for me, from scheduling how to get my revise and resubmit done in three months to planning my wardrobe for the fall semester. I fear becoming too self-reliant on it. Am I losing myself? Am I turning my ChatGPT into a psychological crutch? And if I am having these thoughts, what effect is generative AI having on my students? 

Remix vs. Originality: Girl Talk or Beyonce

Grappling with the strengths and weaknesses of my own AI usage, I feel I have discovered what might be the saving grace of humanity (feel free to nominate me for the Nobel Peace Prize if you wish). As I hinted earlier, AI is more like a DJ remixing the greatest hits of society rather than an innovative game changer. My ChatGPT is more like Girl Talk (who you have probably never heard of. Just ask your AI) than Beyonce (who you most definitely have heard of). Not that there’s anything wrong with Girl Talk. Their mashups are amazing and require a special kind of talent. Just like navigating AI usage requires a certain balance of skills to create a usable final product. But no matter how many pieces of music from other artists you mash together, you will not eventually turn into a groundbreaking, innovative musician. Think Pat Boone vs. The Beatles, Sha Na Na vs. David Bowie, Milli Vanilli vs. Prince, MC Hammer vs. Lauryn Hill. 

What AI Gets Wrong in Writing

As a mathematician and a novelist, I see this glaring weakness in both of these very different disciplines. I’ll start with writing. ChatGPT is especially helpful in coming up with strange character or planet names for my science fiction novels. It will also help me create a disease or something else I need to drive the plot further. And, of course, it can help me find an errant comma or fix a fragmented sentence. But that is about it. If I ask it to write an entire chapter, for example, it will come up with the most boring, derivative, and bland excuse for prose I have ever seen. It will attempt my humor but fail miserably. It sometimes makes my stomach turn, it’s so bad.  

A study from the Wharton School found that ChatGPT reduces the diversity of ideas in a pool of ideas. Thus, it diminishes the diversity of the overall output, narrowing the scope of novel ideas. Beyond that, I find that when I use ChatGPT to brainstorm, I typically don’t use its suggestions. Those suggestions just spark new ideas and help me come up with something different and more me.  

For example, I asked ChatGPT to write a joke for its bad brainstorming practice of using the same core ideas over and over again. It said: 

Joke: That’s not brainstorming—it’s a lazy mime troupe echoing each other. 

That’s lame. I would never say that. But another joke it gave me sparked the music sampling analogy I opened this article with.  

In any case, because of generative AI’s inability to actually generate anything new, I have hope that the college essay, like the fiction novel, will not die. Over-reliance on AI may indeed debilitate the essay, perhaps causing it to go on life support forcing students and faculty to drag its lifeless body across the finish line of graduation. But there is still hope.  

I remember one of my favorite English teachers in middle school required that we keep a journal. Each day she asked us to write something, anything in our journal, even if it was only a paragraph or just a sentence. Something about putting pen to paper sparked my creativity. It also sparked a lifelong notebook addiction. And even though I consider myself somewhat of a techie and a huge AI enthusiast, to this day I still use notebooks for the first draft of my novels. 

It is clear to me that ChatGPT will never be able to write my novels in my voice. I don’t claim to be a great novelist. I just feel that some of my greatest work hasn’t been written yet. While ChatGPT may be able to write a poem about aardvarks in the style of Robert Frost or a ballad about Evariste Galois in the style of Carole King, it can’t write my next novel, because it doesn’t yet exist. And even when it tries to imitate my voice and my style, predicting what I will write next, it does a poor job. 

The Research Paper Dilemma: AI vs. Process

A research paper is inherently different from a creative work of fiction, however. ChatGPT does do a pretty good job of gathering information on a topic from several sources and synthesizing it into a coherent paper. You just have to make sure to check for the errant hallucinated reference. And honestly, when are our students ever going to be asked to write a 15-page research paper on Chaucer without any resources? And if they are, ChatGPT can probably produce that product better than an undergraduate student can. But the process, I would argue, is more important than the final product.   

In his Inside Higher Ed paper Writing the Research Paper Slowly, JT Torres recommends a scaffolding process to writing the research paper. This method focuses on the process of writing a paper, exploring and reading sources, taking notes, organizing those notes into a ‘scientific story’ and creating an outline. Teaching students the process of writing the paper instead of focusing on the end product results in students feeling more confident that they can not only complete the task required but transfer those skills to another subject. Recognizing these limitations pushed me to rethink how I design assignments. 

Using AI in the Classroom

Knowing that generative AI can do somethings (but not all things) better than a human has made me a more intentional professor. Now when I create assignments, I think: Can ChatGPT do this better than an undergraduate student? If so, then what am I really trying to teach? Here are a few strategies I use: 

Method #1: Assess Your Assessments with AI in Mind

When designing an assignment, ask yourself whether it is testing a skill that AI already performs well. If so, consider shifting your focus to why that skill matters, or how students can go beyond AI’s capabilities. 

Method #2: Use AI Where It Adds Value – Remove It Where It Does Not

In some cases, it makes sense to integrate AI directly into the assignment (e.g., generating code, automating data analysis). In others, the objective may be to build a human-only skill like personal expression or creative voice. I decide case by case whether AI should be a part of the process or explicitly excluded. 

Method #3: Clarify Whether You are Teaching Theory or Application

When I am teaching tests, I have to ask myself: Am I assessing whether students understand the theory behind the test or whether they can run one using software? If it’s the latter, using AI to generate code might be appropriate. But if it’s the former, I’ll require manual calculations or a written explanation. 

Method #4: Add a Reflection to any AI Supported Assignment

Any assignment where they are allowed to use AI, they also have to write a reflection about how they used AI and whether it was helpful or not. This encourages metacognition and reduces overreliance.  

Method #5: Require Students to Share Their Prompts and Revisions

Having students share the prompts they used in completing the assignment teaches them about transparency and the need for iteration in their interaction with an AI. Students should not just be cutting and pasting the first response from ChatGPT. They need to learn how to take a response, analyze it then refine their prompt to get a better result. This helps them develop prompt engineering skills and realize that ChatGPT is not just a magic answer machine. 

AI and the Limits of Innovation in Research

What about academic research in general? How is AI helping or hindering? Given that generative AI merely remixes the greatest hits of human history rather than creating anything new, I think its role in academic research is limited. Academic breakthroughs start with unasked questions. Generative AI works within the confines of existing data. It can’t sense the frontier because it doesn’t know there is a frontier. It can’t sample past answers of a question that hasn’t been asked yet. About a year ago, I was trying to get my AI to write a section of code for my research and it kept failing. I spent a week trying to get it to do what I wanted. I realized it was having such a difficult time because I was asking it to do something that hadn’t been done before. Finally, I gave up and wrote the piece of code myself, and it only took me about half an hour. Sure, the coding capabilities have gotten better over the past year, but the core principle remains the same. AI still struggles to innovate. It can’t do what hasn’t already been done. Also because of ‘creative flattery’ it wants to make you happy so it will try to do what you tell it to do even if it can’t. The product will be super convincing, but it can still be wrong. 

I recently asked AI to write a theoretical proof that shows polygonal numbers are Benford distributed (Spoiler: They are not). Then I had it help me write a convincing journal-ready article. The only problem is it also wrote me a theoretical proof that Polygonal numbers are NOT Benford distributed as well.  I submitted the former to a leading mathematics journal to see what would happen. Guess what, they caught it. A human was able to detect the ‘AI Slop’. This shows me, that (1) there will always be a need for human gatekeepers and (2) ‘creative flattery’ is extremely dangerous in a research setting and confirms the need for human review. The chatbot tries too hard to please, thus reinforcing what the user already thinks even if that means proving or disproving the exact same thing. Academic research thrives on novel questions and unpredictable answers, which AI is incapable of doing since it inherently just regurgitates what is already out there. 

Helping Students See AI’s Blind Spots

The Benford Polygonal Numbers experiment is an important example of how we need to educate our students about AI usage in an academic setting. The Time.com article Why A.I. is Getting Less Reliable, Not More states that despite its progress over the years, AI can still resemble sophisticated misinformation machines.  Students need to know how to navigate this.  

One of my favorite assignments in my Statistics course is what I call: 

Method #6: “Beat ChatGPT” – A Concept Mastery Challenge

Students must craft a statistics question that the chatbot gets wrong, explain why the chatbot got it wrong and then provide the correct answer. A tweak of this activity would be to take AI generated content and human written then compare and critique tone, clarity, or originality. 

Remixing isn’t Creation

AI-generated content is like a song built entirely from remixed samples. Sampling has its place in music (and in writing) but when everything starts to sound the same, our ears and brains begin to tune out. A great remix can breathe new life into a classic, but we still crave the shock of the new. This is why people lost their minds the first time they heard Beyonce’s Lemonade or Kendrick Lamar’s To Pimp a Butterfly – not because they followed a formula, but because they bent the rules and made something we’d never heard before. AI, for all its value, doesn’t break the rules. It follows them. That is the difference between innovation and imitation. It is also the reason why AI, in its current capacity, will not kill original thought. 

Sybil Prince Nelson, PhD, is an assistant professor of mathematics and data science at Washington and Lee University, where she also serves as the institution’s inaugural AI Fellow. She holds a PhD in Biostatistics and has over two decades of teaching experience at both the high school and college levels. She is also a published fiction author under the names Sybil Nelson and Leslie DuBois. 

References 

Hsu, Hua. 2025. “The End of the English Paper.” The New Yorker, July 7, 2025. https://www.newyorker.com/magazine/2025/07/07/the-end-of-the-english-paper. 

Warner, John. 2024. “Get Ready for Faculty Bot-ification.” Inside Higher Ed, December 11, 2024. https://www.insidehighered.com/opinion/columns/just-visiting/2024/12/11/great-ready-faculty-bot-ification. 

Meincke, Lea, Gideon Nave, and Christian Terwiesch. 2025. “ChatGPT Decreases Idea Diversity in Brainstorming.” Nature Human Behaviour 9: 1107–1109. https://doi.org/10.1038/s41562-025-02173-x. 

Torres, J. T. 2021. “Writing the Research Paper Slowly.” Inside Higher Ed, May 5, 2021. https://www.insidehighered.com/advice/2021/05/05/benefits-new-approach-student-research-papers-opinion. 

Sonnenfeld, Jeffrey, and Joanne Lipman. 2024. “Why A.I. Is Getting Less Reliable, Not More.” Time, June 20, 2024. https://time.com/7302830/why-ai-is-getting-less-reliable/. 

In recent weeks I’ve been focusing on the problem of students coming to class less prepared. When that happens, discussions fall flat and frustrations rise. How can you meaningfully teach anyone if they’re not doing much work in between classes? (Read more by Beth McMurtrie from The Chronicle of Higher Education).

Mary Shelley wrote Frankenstein in 1818 when she was just 18 years old. In doing so, she not only created a gothic masterpiece that continues to influence and inspire literature but also broke barriers as a woman writer, pioneered science fiction, and created a cautionary tale that is relevant for AI, STEM, and tech researchers today (keep reading this article by Erik Ofgang at Tech & Learning).

At Rogue Community College (RCC), recent initiatives have focused on identifying systemic barriers to industry engagement and implementing targeted strategies to enhance agility in workforce development. Over the past year, RCC has taken deliberate steps to cultivate stronger partnerships with industry stakeholders and to align curricular offerings more closely with labor market needs to increase responsiveness and relevance in service of both students and workforce partners (keep reading this article by Lisa Parks at League for Innovation).

As an educator with years of experience in community colleges, I have often reflected on what drives career success today. One moment that reshaped my perspective came at a conference, where I met a senior executive from a leading tech company. Given his work in artificial intelligence (AI) and digital innovation, I assumed he held advanced degrees in computer science or a related field. To my surprise, he shared that his background was in philosophy (keep reading this article by Dr. Muddassir Siddiqi at Community College Daily)

Rubrics are a valuable tool that supports student growth and facilitates instructor grading and feedback (Suskie, 2018). As instructors, we see this value; unfortunately, many of our students, especially first-year students, are unfamiliar with the concept. This presents an opportunity to raise their awareness of a tool that will benefit them as they master concepts and seek course success (keep reading this article by Dr. Sarah Forbes at Faculty Focus)

Scholar Maryellen Weimer noted in her work "It's a Myth: Nobody Knows What Makes Teaching Good" in Teaching College, Collected Readings for the New Instructor that the consistent elements of effective teaching include:

• personal enthusiasm (which she notes tends to be contagious to students),

• clarity of discourse and presentation,

• an ability to stimulate and arouse interest from listeners,

• knowledge (both competence with respect to the actual content of instruction and an evident love of the subject matter).

Weimer stressed that these characteristics emphasize "thorough, up-to-date knowledge of the subject matter; clearly defined instructional objectives; and a genuine commitment to teaching" (p. 43).

What are you thoughts? What do you think contributes to an excellent teacher?

(Adapted from New Faculty: A Practical Guide for Academic Beginners by Christopher J. Lucas and John W. Murry, Jr.)

Advice for New Faculty: Start with the Syllabus. Focusing on the syllabus at the front end helps the teacher focus his or her ideas and bring all of his or her learning philosophies together in one place (keep reading this article by Jennifer Patterson Lorenzetti).

Possible AI Syllabus Statements (from TBR AI Learning Collaborative): A continually updated document outlining various syllabi policies for AI generative tools, providing guidance. See more from the TBR AI Learning  Collaborative. Also refer to TBR Policy: 1.08.10.00 Use of Artificial Intelligence

Mindset GPS Syllabus Checklist: What is a Mindset GPS syllabus messaging checklist? This checklist is designed to help you evaluate and reflect on the messages conveyed in your course syllabus so you can embed motivationally-supportive language throughout it. We encourage you to review your syllabus, focusing each time on one of the three learning mindsets. 

AI Syllabus Statement Template: A customizable syllabus statement template to help instructors transparently communicate the role, use, and ethical considerations of AI technologies in their courses, from the TBR AI Learning Collaborative.

Bringing C.H.A.O.S. to Choas: Syllabi with an A.I. Usage Policy: It is no secret that Artificial Intelligence (AI) technology is transforming college classrooms. AI tools can easily and quickly assist students in various tasks such as essay writing, literature reviews, analyzing data, formulating code, solving equations, image generation, music composition, and so much more. With minimal or no effort, within minutes, students have most assignments, test questions, or discussion problems figured out and done…enter the chaos!  (continue reading the article)

Beyond Syllabus Week: Creative Strategies to Engage Students from Day One. 

Ever wonder why students don't read the syllabus, despite the time and effort we put into creating it? It serves as a contract . . . yet many students simply aren't motivated to read it (continue reading this article by Dr. Joanne Ricevuto).

Start-Up Anxiety: Professor Shares His Fears as a New Semester Begins. 

I have often said to my friends who don't teach that the week before fall classes begin is a tough time for me. The students are coming back and the campus is abuzz (continue reading this article by Dr. Peter Kakela).

Support GPS on the First Day. This activity provide example scenarios/activities, based on the article How to Teach a Good First Day of Class by James Lang, that you can implement during your first day of class that would support your students’ learning mindsets. For Sense of Belonging, actions include arriving 10 minutes early and asking students to introduce themselves in small groups. 

1st Day Student Survey: On the first day of the course, ask students key questions to learn more about them. Surveying your students was also suggested as an active learning technique to appreciate their current skill levels, but additional questions can be added to appreciate student issues around belongingness (e.g., What concerns or questions do you currently have about the course?). Here is an example used in one of our courses. Then once collected, reach out to students individually over email (or create a single class email summarizing and addressing the major concerns/questions raised). (Sense of Belonging, number 1). 

Mindset Supportive Welcome Message: A welcome message can be an initial strategy to promote a better Sense of Belonging, but you also can consider adding elements of Growth Mindset and Purpose & Relevance as well. This includes a sample template to adapt. 

Check out how Walters State prepped for Week 1 of the Fall 2025 semester!

Visit the extensive OER resources from Pellissippi State Community College which includes:

• Introduction to OER

• OER Handbook for Educators 1.0

• OER Collections

• from the Tennessee Board of Regents (TBR): Tennessee Open Education flyer

• from the Tennessee Higher Education Commission (THEC): Tennessee Open Education

Review this sample checklist from fellow faculty at Columbia State: Pre-term checklist 

Review these sample checklists below to construct your own: Start of Semester Checklist from ETSU 

The first day of class represents an opportunity to get your course off to a good start. Don't just tell students your name and hand out the syllabus (important document, though it is). Keep in mind that the opening session sets the tone for the entire semester. It should be a time to anticipate students' unspoken questions and to address them directly:

• Who's the teacher of the course and are they any good? Introduce yourself, briefly share information about yourself: credentials, degrees, professional background. But also include your areas of interest. Share something about yourself as an individual human being.

• Who else is taking this course with me? Take the time to have students introduce themselves to one another and, time permitting, to the class as a whole. No one should leave class without learning the names of at least 3 other students.

• What's this course about? Refer to the syllabus and share an overview of the class. Express your enthusiasm for your topic and show your students you're interested in the course and in their success. If you are not interested in your own course, do not expect your students to become involved either.

• Will I enjoy this class? Explain what you require of your students and the course objectives. Indicate when, where, and how students can get help when they need it.

• How do I get a good grade in this course? Explain in detail what evaluation procedures will be used. Explain the basis for your grading. Offer concrete, specific suggestions on studying, preparing for class, and reviewing the material. Include test-taking tips.

(Adapted from New Faculty: A Practical Guide for Academic Beginners by Christopher J. Lucas and John W. Murry, Jr.)

See below for Term Start activities to explore; click on activity titles below for more information.

Mindset GPS Syllabus Checklist: What is a Mindset GPS syllabus messaging checklist? This checklist is designed to help you evaluate and reflect on the messages conveyed in your course syllabus so you can embed motivationally-supportive language throughout it. We encourage you to review your syllabus, focusing each time on one of the three learning mindsets.

Mindset Supportive Welcome Message: A welcome message can be an initial strategy to promote a better Sense of Belonging, but you also can consider adding elements of Growth Mindset and Purpose & Relevance as well. This includes a sample template to adapt.

Support Mindset GPS on the First Day. This activity provide example scenarios/activities, based on the article How to Teach a Good First Day of Class by James Lang, that you can implement during your first day of class that would support your students’ learning mindsets. For Sense of Belonging, actions include arriving 10 minutes early and asking students to introduce themselves in small groups.

Current Confidence and Prior Experience Survey: At the start of a course or new unit, have students reflect on their current confidence and prior experience in the skills that they are about to learn. Check out an example used in one of our courses. Then, at the end of the course (or unit),  have students respond again to reflect on how their confidence and experience with those skills improved. As a variation on this activity, you also can have students reflect on what’s helped (or not helped) them learn similar skills in the past. (Growth Mindset, number 1). 

Student Interest Survey: At the start of the course, collect a survey to assess students' (a) interest and prior knowledge in your course topic, (b) interest in pursuing particular majors/minors, (c) interest in future careers, and/or (d) general interests and hobbies in life. (Purpose & Relevance, number 1).

1st Day Student Survey: On the first day of the course, ask students key questions to learn more about them. Surveying your students was also suggested as an active learning technique to appreciate their current skill levels, but additional questions can be added to appreciate student issues around belongingness (e.g., What concerns or questions do you currently have about the course?). Here is an example used in one of our courses. Then once collected, reach out to students individually over email (or create a single class email summarizing and addressing the major concerns/questions raised). (Sense of Belonging, number 1).

Value Writing Interventions: This is a writing exercise that students can complete one or more times during the semester. In this activity, students reflect on beliefs that help them stay motivated. Specifically, this activity asks students to focus on reasons for learning that go beyond the typical motives of making money or making family proud. 

Sense of Belonging Interventions. This is a writing exercise that students can complete during the semester. In this activity, students reflect on how their experiences in college may change over time. Specifically, this activity asks students to read example quotes from other college students and reflect on how their own feelings of belonging on campus may be similar to their peers.