Network visualisation analysis of the transformative potential of generative AI tools in the education landscape
| dc.contributor.author | Govender, Rajendran | |
| dc.contributor.author | Harun, Ibrahim | |
| dc.contributor.author | Rzyankina, Ekaterina | |
| dc.date.accessioned | 2026-01-12T09:26:37Z | |
| dc.date.available | 2026-01-12T09:26:37Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | This research examines the transformative pathways of generative AI tools in the South African higher education landscape, directed by three research questions: (1) specific generative AI tools being utilised, and how are they applied across educational contexts? (2) What are the predominant AI techniques and software tools? (3) What education topics and issues are being addressed by these AI applications? Notwithstanding substantial potential, the acceptance of AI remains unpredictable, principally due to infrastructural insufficiencies, digital literacy gaps, and ethical concerns such as algorithmic bias. By means of the PRISMA methodology, this study conducts thematic and network visualisation analysis to map AI application pathways. Findings show that AI tools like ChatGPT and OpenAI GPT-3 are utililsed for automated grading → personalised learning → real-time feedback. Pathways show that these tools reform administrative responsibilities for educators (by reducing workload → refining teaching effectiveness) and support students through personalised learning experiences (adaptive tutoring → enhanced engagement → improved outcomes). Quantitative analysis reveals that AI tools like ChatGPT and OpenAI GPT-3 lead to a 20% reduction in educator workload, primarily through automated grading and content creation. Additionally, these tools contribute to a 15% improvement in student engagement, particularly through personalised learning pathways and real-time feedback. Key challenges are to develop robust ethical models to avert buttressing prevailing inequalities. This study aligns with the focus on knowledge management by highlighting how generative AI tools underscore the creation, distribution, and deployment of knowledge in educational settings, specifically through tailored learning and adaptive platforms. The study concludes that a custom-made and ethical amalgamation of AI is vital for leveraging its potential to develop educational outcome and equity in South African higher education. | |
| dc.identifier.citation | Govender, R., Rzyankina, E., Bayaga, A. and Harun, I., 2025. Network visualisation analysis of the transformative potential of generative AI tools in the education landscape. Discover Education, 4(1), p.426. | |
| dc.identifier.uri | https://doi.org/10.1007/s44217-025-00726-w | |
| dc.identifier.uri | https://hdl.handle.net/10566/21640 | |
| dc.language.iso | en | |
| dc.publisher | Discover | |
| dc.subject | Education landscape | |
| dc.subject | Generative AI | |
| dc.subject | Intelligent systems | |
| dc.subject | Network analysis | |
| dc.subject | AI-focused | |
| dc.title | Network visualisation analysis of the transformative potential of generative AI tools in the education landscape | |
| dc.type | Article |