The Effectiveness of Integrating Artificial Intelligence into Traditional Educational Management Methods to Enhance the Educational Process Quality
DOI:
https://doi.org/10.15503/jecs2024.2.533.547Keywords:
education management, management model, quality of education, artificial intelligence, chatbots, automated assessment, learning individualisationAbstract
Aim. The purpose of this article is to identify the features of AI’s impact on educational process management and its potential for enhancing education quality indicators.
Methods. The study utilises formative experiment as the primary methodology, supplemented by testing as auxiliary research instruments for gathering empirical data. The sample was formed from students of higher education institutions of Kyiv.
Results. Throughout the study, it was established that the incorporation of artificial intelligence into educational management processes yields a favourable impact on the education quality. An increase in the development of verbal and logical reasoning, the mnemonic domain, coupled with a reduction in students’ anxiety were documented. It was found that the motivation for success increases both in the context of utilising AI as well as while implementing traditional methods of education management. It was established that during the formative experiment, the indicators of students’ formal success did not change.
Conclusion. Furthermore, it was concluded that the most promising areas of implementing artificial intelligence in education management are individualisation of learning and automatic assessment of students’ achievement. The findings of this study can be used to optimise learning management processes in higher education institutions.
Originality. In particular, of notable significance are the statistics pertaining to alterations in the cognitive sphere as well as emotional strategies’ indicators. We perceive potential research prospects in exploring the ramifications of incorporating AI into alternative forms of education management, specifically with regards to resource allocation. Also, further research is expedient to reveal AI potential in forecasting students’ progress and achievements.
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