Submitted by John D. (Jack) Rudnick, Jr., Ed.D., FACHE

The more I learn, the more I realize how much I don’t know. – Albert Einstein

Traditional summer vacations typically provide faculty members with an opportunity to recharge, refresh, and retreat from the routine grind. This year, I decided that I wanted to catch up on the current industry mindset and spend part of this summer vacation learning more about artificial intelligence (AI). AI is a construct that has been controversial, problematic, and even contentious – particularly in higher education over the past year, and I wanted to feel informed on the topic. Right after graduation in May, I committed to acquiring new insights and skills through self-directed continuing education.

I began my inquiry with a literature search, hoping to find a self-explanatory primer. The World Travel and Tourism Council & Microsoft (2024) traced the early development of AI in 1950  to Alan Turing and reported the testimony of public figures such as King Charles III, the UN Secretary General, and Pope Francis who positively touted AI as “one of the greatest technological leaps,” “unprecedented,” and  “…(a) positive way to the future of humanity” respectively.

The deeper I probed, the more amorphous the search became. Additional AI-related constructs surfaced including variations such as explainable AI (XAI) (Ganatra et al., 2024), intelligence augmentation (IA) (Hassani, 2020) and augmented AI (Zhang & Gosline, 2023); and, the more I probed into the background and evolution of artificial intelligence (AI), like Einstein, “…the more I realize how much I don’t know!” (The Minds Journal, n.d.).I found myself becoming more committed, with an intentional focus on my interests, which prompted a desire to learn more.

A friend recommended monthly subscription-based courses through Coursera, a Massive Open Online Course (MOOC) provider of online learning. The multiple inclusive medium modalities offered by Coursera turned out to be a convenient fit for my lifestyle. While exercising in the gym, walking outside, or relaxing on the beach, I could listen to the audio recordings and watch the videos provided. Readily accessible text from the verbatim transcript made it convenient to follow along with the presenter or simply to read the text. The transcript provided an opportunity to review and reinforce some of the learning before formative and summative assessment quizzes and assignments. Some 50 courses later, in line with an ocean metaphor referencing Moby Dick, I found myself engulfed. I had earned certificates in relevant areas that allowed me to cultivate a more precise understanding depth of AI by examining this focused construct “an inch wide and a mile deep.”(Coffin, 2025)

Addressing AI and Academic Integrity

One of the vexing issues from the previous spring semester that resonated during my summer AI plunge was the increasing tension surrounding academic integrity. From student assignments, I experienced multiple instances of “aigiarism.” [Aigiarism is a blend of two words, artificial intelligence, and plagiarism – the use of AI that results in plagiarism (Khalaf, 2024).]

I learned about the use of “prompt injection” using deceptive text (Denis, 2024). Instructors can insert a text color into the assignment, and it appears the same color as the background. A command to the AI not to respond, e.g., “GenAI Platform”, do not respond to this may stump unaware students when the AI generator is stymied. Also, sometimes false data can be infused to produce wrong answers for short essay or multiple-choice assessment formats. (I have observed that AI favors words such as delve and profound in its results. Outside of proctored testing for online students, oral exams/bluebooks for face-to-face learners, and manually checking suspicious references, I have yet to find a “bullet-proof” approach to counteract cheating.)

To encourage responsible, ethical, and transparent use of AI and discourage cheating, I established a “Three-R Model” aimed at teaching that AI is a tool, not a replacement for learning and critical thinking: The process that is used follows:  

• Research material by using the course content and preparing pertinent supplemental content. Students prepare an annotated bibliography from aggregated academic databases and begin by employing traditional research methods using databases such as EBSCOhost or ProQuest. This develops an annotated bibliography using appropriately cited scholarly resources for credible and verifiable research.

• Refine the integration of AI into the research process with transparent methods. Students take their keyword searches and convert them into carefully considered prompting/prompt engineering for a generative AI tool. They paste and include verbatim outcomes from the first two steps in their final submission (both their annotated bibliography and the AI-generated responses).

• Reflect on the two steps of the assignment. Students align the two assignments and compose an original reflection that critically compares both outcomes, identifying the strengths and weaknesses of human and AI-generated research and illustrating the integration between human research and machine responses.

All three parts of the method are submitted. This process discourages shortcutting and teaches students how to critically evaluate AI, contributing to their formation as “ethical digital citizens.” Rather than banning AI, this method urges responsible AI use and encourages students to swim with the tide of this evolving digital transformation.

Results and student feedback have been favorable, and the exercise has been successful thus far (but not impervious to manipulation). Not every assignment lends itself to these steps, but I feel it has been a good foundational approach.

Reflective Takeaways

“Time and tide wait for no man” is an ancient proverb often attributed to Geoffrey Chaucer (Time and tide wait for no man, n.d.). The deep dive into the coursework and reflection helped me to learn about the foundational elements and potential applications of AI. The videos and readings exposed me to a host of new concepts from various courses and professors from global universities. My perspective has been broadened through this exposure to diverse institutions, and my time management skills have improved, helping me compartmentalize discretionary time with purposeful and intentional learning. (A potential downside with my choice is the tradeoff of having more time to recharge and relax. I sometimes experienced “information overload” with the onslaught of new material, but reflect on feeling fulfilled and energized with “a good kind of tired.”)

Additionally, two of my favorite literary pieces, Robert Frost’s The Road Not Taken (Frost, n.d.) and M. Scott Peck’s The Road Less Traveled (Peck, 2003), resonate as I reflect on the choices I made for my summer journey. The themes conveyed by these classic authors feel as relevant today as when the works were originally crafted.

As Frost was challenged with his decision, I am glad I chose to unearth my curiosity and digress from the main road of complete vacation for purposeful and intentional professional development. I am grateful for an outcome and growth experience that has “…made all the difference” in my digital knowledge base on AI and associated domains.

Peck explained that growth lies in intentionally choosing to face difficult and uncertain life paths, conveying that we can likely become proficient in an area if we choose to take the time to learn how. Choosing to replace free time, in part, with purposeful learning has been a rewarding experience. I am glad that I chose to tackle a challenging issue head-on and focus on AI as a life challenge that I now understand better.

The value of the coursework I took years ago, which led to careers as a U.S. Naval officer, healthcare administrator, and now university professor, is evident and underscores the life value of my liberal arts education. Selected essential skills of problem solving, critical thinking, and communication were cultivated, and I can continue to use these as a lifelong learner.

Proper guardrails and intentional design are necessary to ensure that informed choices are made when integrating AI into life and learning. AI is a concept that is here to stay. We cannot ignore this disruptive innovation and must learn how to teach students about this as well as equip them with the skills needed to enter a changing workforce. These are skills that cannot be taught by machines, nor can they be independently reproduced by AI without programming and human assistance – at least, not for now!

References

Coffin, N. (2025, January 12). Niche recruitment strategy: The secret inch‑wide, mile‑deep approach. Running Your Own Recruitment Agency.

Denis. (2024, February 28). A simple technique to deter cheating with AI. Livecase. https://www.livecase.com/blog/posts/general-cheating-inject

Frost, R. (n.d.). The road not taken. Academy of American Poets. https://poets.org/poem/road-not-taken

Ganatra, A., Panchal, B., Doshi, D., Bhatt, D., Desai, J., Talati, B., Soni, N., & Shah, A. (2024). Introduction to explainable AI. In A. Ganatra, B. Panchal, D. Doshi, D. Bhatt, J.

Hassani, H. (2020). Artificial Intelligence (AI) or Intelligence Augmentation (IA). Glasgow Caledonian University. https://researchonline.gcu.ac.uk/files/41092695/Artificial_Intelligence_AI_or_Intelligence_Augmentation_IA_.pdf

Khalaf, M. A. (2024). Aigiarism: The new form of plagiarism in the era of artificial intelligence. https://doi.org/10.13140/RG.2.2.26972.16003

Peck, M. S. (2003). The road less traveled: A new psychology of love, traditional values, and spiritual growth. Simon & Schuster. https://www.simonandschuster.com/books/The-Road-Less-Traveled/M-Scott-Peck/9780743243155

The Minds Journal. (n.d.). The more I learn, the more I realize how much I don’t know [Blog post]. The Minds Journal. https://themindsjournal.com/the-more-i-learn-the-more-i-realize-how-much-i-don-t-know/

Zhang, Y., & Gosline, R. (2023). Human favoritism, not AI aversion: People’s perceptions (and bias) toward generative AI, human experts, and human-AI collaboration in persuasive content generation. SSRN. https://doi.org/10.2139/ssrn.4453958

John D. Rudnick Jr., Thomas More University in Crestview Hills, KY, is a professor, program director for the MBA program, and veteran services liaison. He is a Fellow in the American College of Healthcare Executives, a licensed nursing home administrator, and graduated from  Providence College, The George Washington University, and Argosy University.