Developing research reasoning through digital tools in PhD students’ methodological training

Abstract The paper examines how digital tools integrated into the course “Modern IT in Scientific Research” are associated with patterns of research reasoning among PhD students. The authors argue that the digital transformation of science affects not only the technical aspects of a researcher’s work but may also shape how research problems are formulated, arguments are constructed, and evidence is verified. Research reasoning was operationalized through three indicators: I1—problematization, I2—methodological justification of procedures, and I3—reflective evaluation of evidence. These indicators are linked to mechanisms of digital tool use: M1—external representations and structuring of the research field (knowledge maps, citation graphs, timelines); M2—heuristic generation of alternatives and preliminary modeling; and M3—organization and verification of evidence (screening of contradictory citations, verification of claims, source management). The study employs a qualitatively dominant mixed-methods design. It draws on student work, reflective essays, educator observations, and a descriptive survey. The qualitative evidence suggests patterns of movement from procedural use of digital services toward more methodologically informed research reasoning. These patterns are reflected in students’ attempts to refine research boundaries, justify methodological choices, critically evaluate findings, and detect errors produced by generative AI. At the same time, the study identifies common barriers, including technical difficulties, fragmented use of digital services without connection to research tasks, and limited reflection. A model for integrating digital tools into doctoral methodological training is proposed. The study contributes to understanding how digital technologies may be pedagogically integrated into the development of research reasoning in PhD programs.