PHILOSOPHICAL AND METHODOLOGICAL FOUNDATIONS OF A THEORETICAL MODEL FOR THE INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO EDUCATIONAL RESEARCH

Abstract

DOI: https://doi.org/10.26565/2074-8922-2026-86-01

The purpose. This work aims to develop the philosophical and methodological foundations for integrating artificial intelligence (AI) into educational research, which includes: establishing the philosophical basis for integrating AI into the research process; defining the terminology; identifying the methodological principles that ensure the appropriate use of AI in research practices; justifying the role of AI as the researcher’s analytical partner.

Research methods. The study employed a range of methods tailored to its objectives: an analysis of previous fundamental works in philosophy and research methodology, as well as research on the integration of AI into education and scientific research; philosophical-ontological, conceptual and hermeneutic analysis, conceptual-categorical analysis, content analysis, systematisation, conceptualisation and classification, methodological analysis, as well as inductive, deductive, linguistic and cognitive-conceptual methods.

As a result, the study highlights the philosophical foundations of integrating AI into the research process, which include the following concepts and theories: the theory of knowledge (epistemology), concepts regarding the nature of being, social philosophy, ethical theories (theory of moral duty, virtue ethics), theory of technology adoption in education, phenomenology and theories of AI and general AI, as well as theoretical approaches to academic integrity. The integration of AI into educational research is based on the principles of ethics and academic integrity, human control (human-centredness), data privacy and security, avoidance of algorithmic bias, accountability and transparency. Based on a comprehensive analysis of scientific sources, regulatory documents, international standards and contemporary research publications describing the integration of AI into education, this study has developed a terminological framework for the integration of AI into educational research. It contains an overarching concept (“Integration of AI into the research process”), basic concepts, and concepts grouped into three categories: those describing mechanisms for ensuring the validity and verification of results obtained using AI; those describing the evaluation of the effectiveness of using various AI tools at different stages of research; and those presenting the procedure for the phased integration of AI at various levels of scientific activity. Methodological approaches have been identified that ensure the operationalisation of the terminological system in research practice (systemic, synergistic, phenomenological, personal, holistic), and methodological principles that ensure the correct use of AI in research practices (objectivity, determinism, development, unity of theory, experiment and practice, informativeness, cognitive). The role of AI as an analytical partner to the researcher, capable of enhancing cognitive processes and analytics whilst maintaining the leading role of humans in decision-making, is substantiated.

Conclusions. The philosophical and methodological foundations for integrating AI into educational research are based on a combination of fundamental philosophical categories (concepts, theories, approaches, principles) and contemporary methodological approaches and principles, ensuring a holistic approach and the ethical, evidence-based and conceptually sound use of AI in scientific inquiry.