Northeastern University Student Demands Tuition Fee Refund After Professor Caught Using ChatGPT to Prepare Lecture

The use of artificial intelligence tools in education has sparked both innovation and controversy, with a recent incident at Northeastern University becoming a lightning rod for this ongoing debate.

A student’s formal complaint and subsequent demand for a tuition fee refund have raised questions about transparency, academic integrity, and the evolving role of AI in classrooms.

At the center of this storm is Ella Stapleton, a recent graduate who discovered her professor’s reliance on AI-generated content, igniting a dispute that has drawn attention across the academic world.

Student Demands Tuition Fee Refund

Ella Stapleton, a student in the business program at Northeastern University, began to grow suspicious of her professor’s lecture material when she noticed inconsistencies and unusual details in the course notes.

Among the red flags were citations that directly mentioned “ChatGPT,” as well as odd images featuring anatomical inaccuracies—figures with extra limbs, a common glitch in AI-generated graphics. Such signs led her to conclude that artificial intelligence tools had been employed to create educational content, a practice that had not been disclosed to the students.

The realization prompted Stapleton to immediately reach out to a classmate. In a text message exchange, she shared her concerns, expressing disbelief at the discovery. “Did you see the notes he put on Canvas? He made it with ChatGPT,” she wrote.

Her friend responded with shock: “OMG Stop. What the hell?” This shared outrage catalyzed a more formal response. Stapleton felt that the quality of her education had been compromised, particularly in light of the high tuition costs and the university’s esteemed reputation.

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Acting on her concerns, Stapleton filed a formal complaint with Northeastern’s business school. She accused her professor of not only relying on artificial intelligence to prepare class materials but also doing so in contradiction to his own teachings, as he reportedly warned students against using AI in their own academic work.

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To Stapleton, this was not only hypocritical but also a violation of the trust and standards expected from an institution of higher learning. Her demand: a full refund of her tuition fee for the course, which amounted to just over Rs 6.8 lakh, or $8,000.

University response and professor’s admission

Northeastern University did not take the complaint lightly. A series of meetings were convened to investigate Stapleton’s claims, ultimately leading to the university’s decision to reject the tuition refund request. Despite the rejection, the incident opened a window into the internal discussions and policy challenges universities face in the wake of AI’s rapid advancement.

Professor Rick Arrowood, the faculty member accused of using AI tools, eventually acknowledged his use of several popular platforms. These included ChatGPT, the AI-powered search engine Perplexity AI, and Gamma, a tool used to generate presentations.

While Arrowood admitted that these tools had been instrumental in preparing his lectures, he also expressed regret over not reviewing the content more thoroughly before distributing it to students. “In hindsight…I wish I would have looked at it more closely. If my experience can be something people can learn from then, OK, that’s my happy spot,” he told the New York Times.

The university’s decision was likely influenced by its own AI policy, which states that both students and faculty must provide appropriate attribution when using AI-generated content in scholarly works or public materials. While the professor’s use of AI may not have directly violated this policy, his failure to adequately disclose it to his students stirred frustration and disappointment.

This situation has thrown into sharp relief the gray areas surrounding AI’s place in academia. Should professors be allowed to use AI for efficiency? How transparent must they be? And do students have a right to know when their education is being supplemented—or even replaced—by machine-generated content?

The broader implications of AI in education

The controversy at Northeastern University touches on broader and increasingly urgent questions about the integration of artificial intelligence in higher education. Since its public release in 2022, ChatGPT and other generative AI tools have become widely used by students and educators alike.

Initially, students were the most enthusiastic adopters, using AI to assist with writing, research, and brainstorming. However, concerns about plagiarism, loss of critical thinking skills, and academic dishonesty quickly prompted many institutions to ban or severely restrict the use of such tools.

Ironically, in this case, it was a professor—not a student—who leaned heavily on AI technology. This reversal has led to a crisis of confidence among some students, who feel they are held to higher standards than their instructors.

When educators who warn students against AI usage are discovered to be using the same tools behind closed doors, it raises serious ethical concerns. The hypocrisy perceived by students like Stapleton erodes the authority and credibility of the faculty.

Furthermore, the question of value for money looms large. With tuition fees at many U.S. universities running into tens of thousands of dollars, students expect personalized instruction, critical engagement, and academic rigor. AI-generated lectures, especially when flawed or impersonal, may not meet those expectations. The cost-benefit balance is upended when students feel they’re receiving what could be described as outsourced or automated education.

That said, AI is not inherently detrimental to the learning experience. When used responsibly and transparently, AI tools can enhance pedagogy, streamline administrative tasks, and provide supplemental resources for both students and faculty.

The challenge lies in establishing clear boundaries and guidelines. Universities must decide where to draw the line between innovation and negligence, and they must involve both students and faculty in that conversation.

For instance, transparency could become a key pillar of AI policy. Professors who use AI might be required to disclose this upfront, ensuring that students understand how their material is being curated or created. Additionally, academic institutions might consider offering training programs to help educators use AI more responsibly and effectively. This would mitigate risks like factual inaccuracies or odd imagery, which can undermine learning outcomes.

Stapleton’s case may not have resulted in a refund, but it has sparked a necessary and timely dialogue. It underscores the need for educational institutions to revisit their AI strategies, ensuring that they are not only fair and consistent but also grounded in the core values of education: trust, integrity, and quality.

As AI tools continue to evolve and become more sophisticated, so too must the frameworks that govern their use. Universities must grapple with the ethical dilemmas posed by these technologies, weighing their potential benefits against the risks of overreliance and lack of oversight. In doing so, they must also reaffirm their commitment to student welfare, ensuring that technological advancement does not come at the expense of human connection and educational excellence.

While Ella Stapleton’s claim may have been rejected, her protest has already left a mark. It is a signal to universities everywhere that in the age of AI, students are watching—and they expect accountability.