Artificial Intelligence in Education: A Dual Perspective From Academics and Students on Its Transformative Potential
TL;DR
The findings show that AI is increasingly seen as a transformative academic tool, especially for research, language learning, writing support and problem‐solving, and despite widespread AI adoption, the study identifies significant gaps in institutional infrastructure and the absence of systematic training programmes.
Abstract
This study investigates the integration of artificial intelligence (AI) technologies in higher education institutions in Kazakhstan. It aims to explore students' and academics' perceptions, usage patterns, challenges, and training needs. The findings show that AI is increasingly seen as a transformative academic tool, especially for research, language learning, writing support and problem‐solving. Although many participants first encountered AI through media exposure or academic requirements, their engagement has shifted from initial scepticism to routine use, with many reporting daily reliance on AI tools. Participants highlighted AI's potential to create more personalised and interactive learning environments, particularly through applications like chatbots and adaptive learning systems. However, concerns were raised about over‐dependence on AI, which could weaken critical thinking and problem‐solving skills. These concerns align with previous research warning of passive learning behaviours in AI‐supported educational settings. Despite widespread AI adoption, the study identifies significant gaps in institutional infrastructure and the absence of systematic training programmes. Most participants developed their AI skills through informal, self‐guided learning rather than formal university instruction, underscoring the urgent need for structured AI literacy initiatives within higher education. Ethical issues, including algorithmic bias and data privacy, were also highlighted, emphasising the importance of responsible AI use and ethical governance in institutional policies and curricula. The results suggest that universities should invest in AI infrastructure, implement comprehensive AI literacy programmes and incorporate AI ethics education into academic curricula to prepare both students and faculty for effective and responsible AI use. This study contributes to the growing body of literature on AI adoption in higher education by providing empirical insights from the Kazakhstani context.