According to the OECD (2020), academic dishonesty, encompassing cheating and plagiarism, emerged as a prominent concern with the shift to online examinations. A systematic literature review by Newton and Essex (2023) found that (44.7%) of students self-reported cheating during online exams, with rates increasing from (29.9%) before COVID-19 to (54.7%) during the pandemic.
Holden et al. (2021) identified specific manifestations of online cheating, including unauthorized resource use, assisting others in cheating, identity fabrication, and misappropriation of another’s work (Şendağ et al., 2012, as cited in Holden et al., 2021). Dawson (2020) indicator to this technology enabled form of cheating as “E-Cheating” emphasizing that online platforms create increased opportunities for dishonest practices in examinations. Utilizing these tools, which grant certain students an inequitable advantage, fundamentally contravenes an ethical principle upheld by educational institutions (in Hua, 2023).
Advancements in digital technology initially transformed traditional methods of academic dishonesty, such as plagiarism and copying, by introducing new tools and resources. The internet, for example, became a readily available source for plagiarized content.
More recently, the rise of artificial intelligence (AI) has marked a significant shift, moving from basic internet searches to sophisticated AI tools capable of generating essays, solving complex equations, and even producing coding solutions.
The Role of AI in Enabling Cheating: Modern AI tools, including generative language models, allow students to produce written work that appears original, potentially bypassing traditional plagiarism detection software. Additionally, automated solution generators can tackle complex problems in fields like mathematics, engineering, and computer science, allowing students to circumvent the learning process.
This poses a significant challenge for educators, as AI-generated content often lacks identifiable markers of authorship, making detection difficult. Impact of AI on Academic Integrity and Learning Outcomes: The integration of AI into academic work raises ethical concerns, particularly regarding students’ understanding of academic honesty.
Heavy reliance on AI tools can hinder the development of critical thinking, writing, and problem-solving skills, which are essential for both academic and professional success. Over-dependence on AI not only compromises students’ learning but may also diminish their preparedness for the workforce and future educational opportunities. AI as a Tool for Detecting Cheating: While AI enables certain forms of academic dishonesty, it also offers potential solutions for detection.
Advanced algorithms can identify unusual writing patterns or detect similarities in code, though current systems have limitations in terms of accuracy and privacy. AI-powered tools can also aid educators in designing assessments that are more resilient to cheating, such as personalized or adaptive testing. Developing Ethical and Policy Responses: To address AI-assisted cheating, academic institutions must consider updates to their policies, including establishing clear guidelines on AI usage.
Encouraging a culture of integrity and promoting the value of academic honesty are essential for mitigating dishonest practices. Additionally, revising assessment methods—such as incorporating open-book exams, project-based assessments, and oral examinations—can reduce opportunities for cheating and encourage genuine learning.
The integration of digital and artificial intelligence (AI) technologies has transformed traditional methods of academic dishonesty, evolving from simple internet-based plagiarism to more complex forms of cheating using AI.
Advanced AI tools, such as generative language models and automated solution generators, enable students to produce original-appearing content and solve complex problems, often bypassing traditional plagiarism detection.
This shift presents significant challenges for educators in detecting AI-generated content and raises ethical concerns regarding students’ understanding of academic integrity. Over-reliance on AI can undermine students' development of essential skills, affecting their future readiness for professional and academic endeavors.
However, AI also offers potential as a detection tool, with algorithms that identify irregular writing patterns or detect code similarities, though such systems face limitations in accuracy and privacy.
To address AI-assisted cheating, educational institutions must update policies on AI usage, promote academic integrity, and consider alternative assessment methods, such as open-book exams, project-based assessments, and oral examinations, to foster genuine learning and reduce opportunities for dishonesty.
AI presents both challenges and solutions in addressing student cheating. As a challenge, AI tools—such as generative language models and automated solution generators—allow students to bypass traditional learning and produce work that appears original, making academic dishonesty easier and harder to detect.
This shift poses ethical concerns and complicates efforts to maintain academic integrity, as AI-generated content often lacks identifiable markers of plagiarism or authorship. However, AI also offers promising solutions. Detection algorithms can analyze writing patterns and code similarities, helping educators flag potential cases of academic dishonesty.
AI-powered tools can even assist in creating more resilient assessments, like adaptive or personalized exams, which are less susceptible to cheating. Given these dynamics, it is crucial for educational institutions to adapt practices and policies to keep pace with technological advances. By updating academic policies, promoting a culture of integrity, and exploring alternative assessment methods—such as open-book exams, projects, and oral exams—educators can safeguard academic integrity and encourage genuine learning in an AI-driven landscape.
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