College Students Spot AI-Enhanced Writing That Feels Too Perfect

The Role of Generative AI in Shaping Student Identity

Generative AI has become an integral part of the academic journey for many Canadian students. While educational institutions are increasingly focused on addressing misconduct and detecting AI use, a more profound transformation is occurring—one that touches on the very essence of student identity.

According to a recent KPMG Canada report, 73% of students use generative AI for schoolwork, with nearly half stating it is their "first instinct." This widespread adoption raises important questions about how students perceive their own capabilities and the legitimacy of their work. Many express unease, fearing that their use of AI might be seen as cheating or that their assignments may not truly reflect their abilities.

The study was based on a survey of 684 university, college, vocational, and high school students, as part of a larger sample of 3,804 Canadians (aged 18+), exploring how people are adopting generative AI in their daily lives.

In my doctoral research on STEM education in Ontario colleges, I am examining how AI is reshaping not only how students write but also how they view their own voice, legitimacy, and sense of self. Academic policies often define what constitutes cheating, but they do not address a deeper concern: if AI helps write an assignment, will students still be seen as capable, and will their work represent who they are?

Writing as a Reflection of Identity

Writing is more than just a technical skill; it is one of the primary ways students structure and elaborate ideas, demonstrate competence, and position themselves as emerging professionals. This is especially true in STEM fields, where programs are closely tied to specific career paths. Students are expected to begin positioning themselves as future professionals through how they communicate and present knowledge.

However, despite its importance, writing is often treated as secondary in STEM disciplines, which are typically seen as technical or data-driven. Yet research shows that communication is central to scientific practice, shaping how knowledge is constructed, interpreted, and shared.

AI is now part of this process, influencing how students envision their future careers and engage with their studies. When science students write assignments, they are engaging in what social and cultural theorists describe as "identity work"—building narratives that help them explore how they might belong in particular professional fields.

The Challenge of “Voice” in AI-Generated Text

In my research, I have observed college STEM classes, taken field notes, and spoken with students over a two-year period about their experiences. One recurring concern I hear is that AI-generated drafts are technically strong but "do not sound like me." This reflects the idea that "voice" or "sound" in writing is a signal of legitimacy.

In collaborative work on cultivating student agency, I use the concept of "becoming alive within science education" to describe moments when students can bring more of themselves—their perspectives, ways of thinking, and experiences—into how they learn and express ideas. However, institutions often favor standardized forms of writing, and AI can intensify this by making a fluent, generic style instantly available.

For some students, this lowers barriers and supports access. For others, it feels like self-erasure. One student described it this way:

"It’s better writing, yeah, it sounds good and helps get a better grade. But it’s kinda generic. Like anyone could’ve written it, not just me."

This pattern points to a broader tension: phrasing, structure, and tone in writing carry traces of identity, and AI can smooth or erase these traces.

Policy and Practice in the Age of AI

Canadian post-secondary institutions are still figuring out how to approach AI. Many policies aim to balance flexibility with oversight, allowing limited AI use while emphasizing disclosure and addressing risks such as fabricated citations, bias, and privacy issues. Yet enforcement remains a challenge.

As policies evolve, uncertainty persists. Students must navigate what is permitted, what constitutes their work, and whether it truly reflects who they are.

In Canada, participation in STEM fields remains uneven across gender and other social dimensions, including race, Indigenous identity, socioeconomic status, and immigrant background. Many students already question whether they belong, making recognition deeply consequential.

If AI-generated writing becomes the implicit standard for "good work," students may begin to locate competence in the tool rather than in themselves. Those who rely on AI may question the authenticity of their success, while those who avoid it may feel at a disadvantage.

What Can Educators Do?

Rethinking learning design is crucial. Students should not have to guess what is acceptable. Assessments should focus on the process that makes students’ thinking visible, not just the product.

Significantly, writing in one’s own voice must be treated as a skill worth developing. In practice, this can be as simple as asking students to explain how they used AI in an assignment, or compare an AI-generated paragraph with their own and discuss what changed in tone, clarity, and reasoning.

Instructors might also ask students to revise AI-polished text so it reflects their own thinking, or to identify where their interpretation and uncertainty matter. These small shifts help foreground not only what students produce but also how they think and position themselves in their work.

AI is here to stay. The question is whether STEM classrooms will help students use these tools without losing their voice, their agency, and their sense of belonging.