Methodological foundations for assessing the return on investment in educational technologies based on artificial intelligence

Abstract

The article is devoted to solving a current scientific and practical problem – the adaptation of classical methodological approaches to assessing return on investment (ROI) for the field of educational technologies (EdTech), especially for solutions based on artificial intelligence (AI). A simplified analysis of traditional ROI models, such as the Kirkpatrick-Phillips model, was conducted, revealing their limitations in relation to the evaluation of AI solutions, their adaptability, predictability, and ability to provide qualitatively new educational results. The authors propose a comprehensive, multi-level assessment model that integrates quantitative financial indicators with qualitative metrics reflecting the transformative effect of AI. The model includes assessments of operational efficiency, academic results, strategic assets, and intangible assets. Particular attention is paid to methodological challenges, such as distinguishing the contribution of AI from other factors, the ethical aspects of data collection, and the long-term nature of return on investment. The theoretical significance of the work lies in the development of a methodology for assessing the effectiveness of digital educational innovations. The practical value lies in providing educational institution leaders and EdTech developers with a structured tool for justifying and managing investments.