Journal

Scientia Paedagogica Experimentalis 2026, Vol. 63-1

ISSN

0582-2351

e-ISSN

2953-1446

Title

A MULTI-LEVEL THEORY AND AI-SUPPORTEDPEDAGOGY OF CRITICAL THINKING:AN APPLICATION IN HISTORY EDUCATION

Author

Hasmik Hovhannisian, Khachatur Stepanyan and Hayk Stepanyan

                                                              

Pages

133-144

Keywords

Artificial intelligence in education, critical thinking, experimentalpedagogy, history education, levels of critical thinking, nationalidentity, source criticism, understanding.

Abstract

This article presents an integrated application of the research programme A Multi-Level Theory and AI-Supported Pedagogy of Cri- tical Thinking within the domain of history education. Developed through a sequence of interconnected theoretical, methodological, and experimental studies, the programme addresses persistent difficulties in teaching critical thinking while responding to contemporary challenges posed by digitalization, algorithmic mediation, and artificial intelligen- ce in education. The research programme A Multi-Level Theory and AI- Supported Pedagogy of Critical Thinking was elaborated and systema- tically developed through a series of joint publications by the author and Robert Djidjian, which constitute an essential part of the theoreti- cal foundation of the present study and are included in the reference list. At its theoretical core, the programme proposes a hierarchical mo- del of critical thinking that distinguishes five interrelated levels: the logical level (identification of deductive fallacies), the analytical level (adequate understanding of problems and information), the synthetic level (generation of alternative solutions), the level of conceptual criti- que (revealing implicit presuppositions), and the level of meta- argumentation (meta-theoretical evaluation of arguments and theories). Central to this framework is the epistemological role of understanding as the foundational cognitive component underlying all higher forms of critical thinking. 142 Hasmik Hovhannisian et al. The article demonstrates how this multi-level model can be ope- rationalized in history education, a discipline inherently grounded in interpretation, source criticism, and narrative construction. Artificial intelligence is introduced not as an epistemic authority, but as a sup- portive pedagogical tool that enables diagnostic assessment, individua- lized learning trajectories, and reflective engagement with AI- generated historical content. Particular attention is given to the formati- on of reflective national identity and the development of algorithmic skepticism in the context of post-truth dynamics.

DOI

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