Volume 01, Issue 03

Research Article

Generative AI as a Catalyst for Educational Personalisation through Learning Analytics and Design Research

Dr. Shehzadhussein Ansari

Assistant Professor, School of Education , Sabarmati University, Ahmedabad, Gujarat

Submitted: 15-09-2025

Accepted: 20-10-2025

Published: 31-12-2025

Pages: 131-155

Generative AI Learning Analytics Higher Education AI Adoption AI Personalisation AI Ethics
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Abstract:

The adoption of Generative Artificial Intelligence (GenAI) and Learning analytics (LA) in education is quickly moving beyond experimental pilots to widespread use. This research explores the stages of awareness, use and perceived usefulness and challenges and uses of these technologies by the teachers and the students. Survey results showed that all respondents were aware of ChatGPT (100%) with lower rates of awareness regarding Gemini (43%) and Copilot (39%) combined with high active-use rates (67%) and universal exposure to LA dashboards at that institution. Comparing to past studies that found moderate or mixed awareness in faculty (Zawacki-Richter et al., 2019), these results indicate a paradigm shift, at least in relation to the traditional gap of awareness and the use that was observed in adoption literature (Papamitsiou & Economides, 2014; Ferguson & Clow, 2017), except that it is now smaller in scale. The paper also notes positive perceptions of service advantages, such as personalization (93%), efficiency (98%), engagement (100%) and GenAI-LA synergy (94%), that verify previous theoretical expectations of a closed-loop adaptivity (Daniel, 2017; Gaevinc et al., 2019), but go further to show that they have been achieved in practice. On the other hand, the obstacles remain similar to those in previous literature: infrastructural gateway (79%), shortcomings on training (100%) and the moral implications of plagiarism (100%) and privacy dangers (87%) reooplify the permanent limits observed in the past studies (Ifenthaler & Yau, 2020; Cotton et al., 2023). The study is both theoretical and practical in that less adoption barriers are demonstrated due to use of GenAI, coupled with heightened issues regarding ethics and integrity. It highlights the importance of capacity-building, institutional governance and ethical protection to make sure that AI educational promise can be met with a fair, sustainable and integrity-driven learning experience.