The impact of AI in education is multifaceted. On one hand, AI tools can significantly enhance efficiency by generating ideas, aiding in research, and assisting with revisions. When used ethically as a support tool, they can free up time for students to engage in deeper learning and creative problem-solving. However, the risks escalate when students rely on AI to complete assignments or exams, which are critical to their overall academic performance:

Academic Integrity and Fairness

The use of AI without proper acknowledgment can lead to plagiarism and academic dishonesty. Research indicates that a substantial proportion of students perceive such practices as cheating, which undermines the fairness of academic evaluations and may prompt universities to implement stricter policies or punitive measures. Over-reliance on AI can also result in superficial learning. When assignments or exams are completed by AI rather than through genuine effort, the grades awarded may not accurately reflect a student's true understanding or critical thinking abilities. This misalignment can lead to inflated grades that fail to represent a student's actual competencies. Furthermore, disparities in access to or proficiency with AI tools can create an uneven playing field. Academic rankings influenced by AI-assisted work may devalue genuine academic achievement, potentially leading employers and postgraduate programs to question the reliability of these grades. This could drive a broader shift in education toward assessments that prioritise originality, critical reflection, and in-person evaluations.

To address these challenges, educators can adopt several proactive strategies to detect and prevent the misuse of AI in assignments and online exams:

1. Utilize AI Detection Tools: Tools such as Turnitin’s AI detection software can identify content that appears machine-generated. While not infallible, these tools provide a valuable starting point for further investigation.

2. Analyze Writing Style and Consistency: Educators should look for abrupt changes in tone, vocabulary, or structure within a student’s work. AI-generated text often exhibits unusually formal phrasing or repetitive patterns that deviate from a student’s typical writing style.

3. Require Process Documentation: Asking students to submit drafts, outlines, or annotated versions of their work can help verify the progression of their ideas. This makes it easier to detect if a final submission is overly polished or inconsistent with earlier versions.

4. Incorporate In-Person Assessments: Oral exams, one-on-one discussions, or timed in-class assignments can reveal a student’s true understanding through spontaneous responses. Designing assignments that require multiple drafts, reflective commentaries, or in-class components can also minimise the benefits of AI-generated content by focusing on the process rather than just the final product.

5. Revise Assessment Design: Create tasks that demand personalised responses, critical thinking, and creativity—elements that are difficult for AI to replicate. For example, incorporating reflective writing or problem-solving steps that require iterative feedback can enhance the authenticity of student work.

6. Implement Randomised Assessments: Use assessments that vary between students or require dynamic, real-time problem-solving, such as oral exams, in-class assignments, or interactive projects. This approach reduces the likelihood of students relying on pre-generated AI responses.

By combining robust detection methods with thoughtful, integrity-promoting assessment designs, educators and administrators can better safeguard academic standards while preparing students to use emerging technologies responsibly. Providing ongoing training for teachers on the potential and limitations of AI tools is also essential. This includes instruction on using AI detection software, understanding its limitations, and adapting teaching strategies accordingly.

While AI tools offer undeniable benefits in terms of efficiency and support, their misuse in completing key assessments can undermine both academic integrity and the accurate measurement of student competence. This dual-edged effect is prompting universities to develop clearer policies and more innovative assessment strategies that protect learning outcomes while leveraging the potential of AI technology.