Postplagiarism Perspectives: Comparative Insights from K-12 and Postsecondary Research

By Beatriz Antonieta Moya Figueroa

The rapid integration of Generative AI (GenAI) has moved education into a liminal space where students often adopt these tools faster than institutions can adapt. For academic integrity practitioners and researchers, this isn’t just a technological shift; it is a fundamental reimagining of how we teach, learn, and assess.

Two recent studies, presented in the CAIELI Speaker series and anchored in the concept of postplagiarism, provide a comprehensive look at these complexities across the learning continuum—from K–12 classrooms to the high-stakes world of professional accounting.

The K–12 Tension: Augmented Thinking and the “Vicious Cycle”

In a study involving 44 interviews across 21 Canadian schools in seven provinces, Myke Healy (Assistant Head – Teaching and Learning at Trinity College School) explored how administrators are navigating the ethical issues of human-AI collaboration. The research highlights a profound tension: the gap between the long-term, deep-thinking tasks of traditional curricula and the shorter, less cognitively engaging paths offered by generative AI.

Healy also recognizes a potential “vicious cycle” in which teachers use GenAI to generate assignments, students use it to complete them, teachers use AI assess the work, and then students dismiss the work for lack of meaning. In such a loop, the human element risks becoming a ghost. 

However, the study also reveals significant possibilities. In the hands of capable students, GenAI could turbocharge cognitive processes, allowing for augmented thinking. Conversely, for those lacking judgment, it could lead to slop cannons, characterized by the rapid production of low-quality, inaccurate content. Likewise, beyond the student desk, administrators are seeing the benefits of GenAI for:

• Consistency: Streamlining and improving report card comments.
• Inclusion: Translating parent-teacher communications for international families in their mother tongues.
• Differentiation: Tailoring complex material to a student’s specific interest or reading level.

While individual teachers often identify as early adopters, schools themselves often lag on the innovation curve, revealing a mismatch between practice and institutional policy.

The Professional Threshold: Moving Beyond Compliance in Accounting

As we move toward professional certification, the stakes of this mismatch become even higher. Naomi Paisley’s (Instructor at SAIT) research on CPA-accredited accounting programs suggests that current approaches to academic integrity may fail to prepare students for the professional world.

Accounting is built on public trust. A lack of integrity doesn’t just result in a poor grade; it can lead to financial scandals and lost livelihoods. Yet Paisley found that many programs focus almost exclusively on technical skills, often ignoring the ethical reasoning and professional judgment required to use AI responsibly.

Analysing courses through the lens of postplagiarism, several systemic gaps emerged:

• Accountability vs. Prohibition: Many institutional policies still frame GenAI primarily as a threat to be banned. This “policy of prohibition” treats academic integrity as a punitive compliance exercise rather than a proactive pedagogy of “how to make an ethical decision.”
• The Competence Gap: In a professional context, using AI without a framework for attribution or verification is no longer just an integrity issue; it is a professional competence issue.
• The “Gut” Instinct: Currently, many students are navigating AI use instinctively, relying on their “gut” because they lack a systematic framework for attributing and co-creating with these tools.

Bridging the Gap: The Postplagiarism Future

Both studies point to a critical “mismatch” between K–12 skills and postsecondary requirements. Bridging this gap requires moving past traditional frameworks of plagiarism and embracing postplagiarism.

As envisioned by Dr. Sarah Elaine Eaton, postplagiarism acknowledges that the boundaries between human and machine-generated content are now permanently blurred. For the researcher and practitioner, this means preparing students to work ethically with AI, focusing on transparency and hybrid writing rather than on detecting its presence. It also means that accountability cannot rest solely on the individual student. Institutions must take responsibility for providing the frameworks and policies that reflect the reality of modern professional life.

The advent of GenAI has not replaced the need for learning; it has heightened the need for human-centric education. By navigating these tensions today and creating well-designed educational opportunities with clear policies and training, we can ensure that the “turbocharged” possibilities of the future are built on a foundation of unshakeable integrity.