Author

Vanzal Dhliwayo

Observed name: Dhliwayo, Vanzal

Institution: Eastern Illinois University

Observed institution: Eastern Illinois University

ORCID: 0009-0006-5620-2084

Observed ORCID: 0009-0006-5620-2084

OpenAlex ID: A5152186018

Beyond Cheating: Preparing Students and Institutions for Responsible Generative AI Use in Higher Education Author: Vanzal Dhliwayo Institution: Southeast New Mexico College Abstract The rapid adoption of generative artificial intelligence (GenAI) tools such as ChatGPT, CoPilot and many more has generated both excitement and concern across higher education. Much of the early institutional conversation centered on whether students would use systems such as ChatGPT to complete assignments, quizzes, examinations, and other academic work. Although these concerns are legitimate, framing generative AI primarily as a cheating problem overlooks its considerable educational potential. Research has shown that artificial intelligence technologies have the potential to revolutionize education than anything else (Harry, et al.,2023). There are many things these tools can do. Students can use them to clarify difficult concepts, generate practice questions, organize notes, receive formative feedback, brainstorm ideas, and examine alternative explanations. Educators can use it to develop examples, improve instructional materials, create formative assessments, differentiate explanations, prepare rubrics, and revise course materials. It has also been shown by recent research that the educational effects of generative AI depend less on the mere presence of the technology than on how instructors design learning experiences around it. One of the meta-analysis' research projects concluded that artificial intelligence tools have a positive effect on student's academic performance (Liu et al., 2025), while some other publications show a concern in continuing gaps in institutional guidance, professional development, automated online learning, and assessment strategy (Fan et al., 2026; Baggia et al., 2026). In this short paper I will present a practice-oriented review of research on artificial technology tools in higher education and propose a good framework for integrating those tools while protecting academic integrity. Throughout the paper I will pay more attention to AI literacy, assessment design, transparency, equity, privacy, human oversight, and syllabus development. In this paper I argue that universities and colleges need to move away from a simple binary of "AI allowed" versus "AI prohibited" and instead specify appropriate AI use according to the learning objectives of individual assignments. The proposed framework has five parts: Course outcomes first; Label AI permissions; Educate for AI literacy; Assess learning processes; and Review risks, equity, and policy. I also provided one adaptable syllabus template. My conclusion is that instead of just labeling generative AI as a cheating tool, institutions need to protect academic integrity by teaching students how to use AI responsibly, redesigning assessments to reveal students' thinking, and establishing clear expectations rather than relying predominantly on prohibition or automated AI detection. Keywords: generative artificial intelligence, ChatGPT, higher education, academic integrity, AI literacy, syllabus design, assessment, teaching and learning ________________________________________

2026 · Dhliwayo, Vanzal · Zenodo (CERN European Organization for Nuclear Research)

Detecting Cloud Security Configuration Drift Before Unauthorized Data Exposure Across Multi-account Enterprise Infrastructure Environments

2026 · Vanzal Dhliwayo · International Journal of Engineering Technology Research & Management

Beyond Cheating: Preparing Students and Institutions for Responsible Generative AI Use in Higher Education

2026 · Vanzal Dhliwayo · SSRN Electronic Journal

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