| Rafail Rzayev, Elman Ibishov, Aliagha Gasimov, Arzu Safarova Artificial Intelligence and Higher Education Quality: Survey Evidence from UNEC |
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| Abstract. Artificial intelligence (AI) technologies are increasingly transforming higher education systems worldwide by influencing teaching practices, learning processes, assessment methods, and institutional governance. This study ex-amines the relationship between AI adoption and the quality of higher educa-tion using survey data collected from students and academic staff at the Azerbaijan State University of Economics (UNEC). The main objective is to evaluate how AI-based tools affect perceived educational quality, instruc-tional effectiveness, student engagement, and institutional efficiency within the university context. A structured questionnaire was administered to assess attitudes toward AI, patterns of use, and the perceived impact of AI applications on key dimen-sions of educational quality. Quantitative methods were applied to analyze the survey data. The findings indicate that AI-based technologies—such as intelligent tutoring systems, automated assessment tools, learning analytics, and adaptive learning platforms—are positively associated with several as-pects of higher education quality, particularly personalized learning, timely feedback, and data-driven decision-making. However, the study also identi-fies key challenges related to AI integration, including concerns about data privacy, academic integrity, algorithmic bias, and unequal access to digital resources. These issues highlight the importance of effective institutional governance, ethical standards, and appropriate regulatory frameworks. Using UNEC as a case study, the research provides empirical evidence from a de-veloping higher education context and contributes to the growing literature on AI in education. Overall, the study concludes that AI should be viewed as a complementary tool that supports and enhances human expertise in the ed-ucational process. |
| Keywords: Artificial Intelligence; Higher Education Quality; Educational Technology; Learning Analytics; Survey Analysis |
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| DOI: https://doi.org/10.54381/itta2026.2.10 |