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Application of Cyber-Constructive Triangulation in Qualitative Research: Simultaneous Analysis of Human, Machine, and Data Interactions

Authors
Mohammad Abbaszadeh 1 iD
Monika Piątkowska 3 iD
Vedran Zubović 4 iD
Affiliations
1Department of Social Sciences, University of Tabriz, Tabriz, Iran
2Department of Sport Management, Faculty of Physical Education and Sport Sciences, University of Tabriz, Tabriz, Iran
3Józef Piłsudski University of Physical Education, Warsaw, Poland
4Faculty of Tourism and Hospitality Management, University of Rijeka, 51410 Opatija, Croatia
Overview

Abstract

The refinement of artificial intelligence (AI) systems has significantly impacted the field of qualitative research. Within this space, the interaction of human researchers, algorithmic agents, and data architectures is complex and requires new methodological frameworks which are adaptive and responsive. This article presents a new mixed-method framework called Cyber-Constructive Triangulation (CCT) which seeks to provide solutions to the epistemic, ethical, and methodological dilemmas posed by the intersection of qualitative research and AI technologies in the age of big data. The framework aims to examine the simultaneous and critical interplay of three elements: humans (the researchers and the participants), machines (algorithms and automated systems), and data (the digital and social systems). Unlike other approaches which CCT as a qualitative methhod attributes meaning construction solely to human activity or technology, CCT illustrates that in digital research, meaning and knowledge emerge from interplay of distributed processes involving human and non-human actors. These are informed by three main theories which are Foucault power/knowledge theory, Castells’ network society theory, and Beck risk society theory. They assist in the examination of algorithmic power, digital agency, and ethical risks posed by modern technologies. The model comprises of three primary stages: design, creation of mixed data set and perform a three-tiered analysis composed of interpretive, algorithmic, and contextual layers. This enhances the level of analysis, promotes ethical sensitivity, and allows researchers to become more self-aware and responsible. This paper demonstrates through case studies the different applications of CCT in various disciplines as a general, reusable, and locally flexible instrument for qualitative data analysis. In this sense, CCT presents a new opportunity for qualitative researchers working in digital spaces to integrate precision, reasoning, and theoretical coherence.

Cyber-Constructive TriangulationQualitative MethodologyFoucault’s Power/KnowledgeCastells’ Network SocietyBeck’s Risk SocietyAI Ethics