The Impact of Artificial Intelligence on Academic Environments: Integrity, Inequality, and Interdisciplinary Transformation in Georgian Higher Education
Year: 2025
Type: article
Abstract: : The rapid proliferation of generative artificial intelligence, particularly large language models like ChatGPT, has fundamentally transformed academic environments globally. This study examines the multifaceted impact of AI integration on Georgian higher education institutions, focusing on academic integrity challenges, digital inequality patterns, and interdisciplinary transformation processes. A mixed-methods approach was employed, combining quantitative survey data (n=173) from academic staff and students across seven institutions (four capital-based, three regional) with qualitative semi-structured interviews (n=9) of institutional decision-makers. Data collection occurred between November 2023 and January 2024. Statistical analysis included descriptive statistics and chi-square tests, while qualitative data underwent thematic content analysis. Findings reveal significant usage patterns with 82% of students employing AI tools academically, yet only 31% disclosing such usage. Substantial digital inequality emerged across institutional types (68% vs. 12% premium access in private vs. public universities) and disciplines (91% usage in computer science vs. 49% in medical education). Notably, interdisciplinary collaboration increased by 43%, with 78% of faculty reporting significant pedagogical adaptations. AI integration presents a dual paradigm of opportunity and challenge in post-Soviet educational contexts. While facilitating unprecedented interdisciplinary collaboration and pedagogical innovation, it simultaneously exacerbates existing inequalities and challenges traditional academic integrity frameworks. The study provides evidence-based recommendations for ethical AI integration, emphasizing the critical need for inclusive policies to prevent deepening educational disparities.
Author: Tamar Vepkhvadze*
Institution: Tbilisi State University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7095003299
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