Table 1
Data inclusion/exclusion criteria.
| VARIABLE | INCLUSION CRITERIA | EXCLUSION CRITERIA |
|---|---|---|
| Database | Scopus | Other than Scopus. |
| Year span of publications | Publications within the year 2022–2024. | Publication beyond the year of 2022–2024. |
| Search terms | Availability of specified search terms in either of abstract, title, or keywords of publication. | Non-availability of specified search terms in either of abstract, title, or keywords of publication. |
| Language of publication | Published in the English language. | Published in a non-English language. |
Table 2
Cluster of broad-themes and relevant micro-themes.
| RQ | Accompanying broad-themes | Relevant micro-themes |
| RQ1 | Viability of academic integrity | Academic writing and publishing, academic integrity, academic dishonesty/academic misconduct |
| RQ2 | Plagiarism and cheating | Plagiarism, cheating |
| RQ3 | Curriculum and assessment | Pedagogy, assessment, detection |
| RQ4 | Individual, institutional, and technical concerns | Personalized learning, critical thinking, interactive learning environments, accessibility, equity, privacy and bias, risk/threat |
| RQ5 | Ethical and legitimacy concerns | Ethics, copyright, responsible use, legitimacy |
| RQ6 | GAI policy matters | Policy frameworks, policy guidelines, AI literacy |
Table 3
Comprehensive GAI guideline for GAI usage in higher education.
| INDIVIDUAL CONCERNS | INSTITUTIONAL CONCERNS | TECHNICAL CONCERNS |
|---|---|---|
| Personalized learning skills development | Specifying discipline-specific AI interventions | Enhanced accessibility, ensuring equity to AI access |
| Self-directed learning skills development | Change of existing curricula and assessment practices, development of a clear institutional GAI policy | Minimizing data biases, protecting the data privacy of the users |
| Critical thinking skills development | Student and staff training on GAI | Framing copyright protection law, use of AI tools for plagiarism detection |
| Student-teacher-AI integration in teaching and learning | Fostering AI inclusive learning environment | Clearing GAI legitimacy issues |
| Ethical/responsible use of AI | Promoting awareness of academic integrity | Spreading AI literacy among the stakeholders |