Modelling information-communicative competence for AI-era designers

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Authors: Oleksandr O. Musiienko
Cited by: 2
References: 50

Abstract

The rapid diffusion of generative artificial intelligence (AI) in design practice is transforming the professional competencies required of designers, yet the theoretical foundations guiding educational responses remain underdeveloped. A recent scoping review found that 73.7% of studies on generative AI in design education are entirely atheoretical, while domain-specific competency constructs for the AI era remain scarce. This conceptual paper proposes an integrative theoretical framework that (1) operationalises information-communicative competence (ICC) as a four-component construct for designers in the context of AI-driven professional transformation; (2) adapts the TPACK model to account for AI tools and studio pedagogy; and (3) identifies gaps when mapping national design competency standards to ICC. The study employs a conceptual analysis approach combining theory synthesis with framework adaptation. Terminological differentiation situates ICC among adjacent constructs (digital competence, ICT competence, information literacy, media competence). The framework is developed through systematic integration of TPACK, studio pedagogy theory, and competency-based education. ICC is operationalised as a four-component model comprising information-analytical, communicative, technological, and reflective components, each incorporating AI-specific descriptors. An adapted TPACK model reconceptualises Technological Knowledge to encompass prompt engineering, AI tool selection, and critical evaluation of AI outputs. A gap analysis of the Ukrainian B2 Design standard against ICC reveals systematic omissions in AI-related competencies across all four components. The integrative framework synthesises these three pillars into a coherent theoretical foundation for curriculum transformation. The proposed framework addresses the dominant atheoretical trend in generative AI design education research by providing a domain-specific theoretical architecture that can guide curriculum redesign. Its three-pillar structure - what knowledge is needed (TPACK), how it is acquired (studio pedagogy), and what standards require (competency mapping) - offers a replicable model for other professional fields undergoing AI transformation.

Fields of Study & Subjects

Ethics and Social Impacts of AI Design Education and Practice Interdisciplinary Research and Collaboration

Publication details

Journal / source
CTE Workshop Proceedings
Publisher
Academy of Cognitive and Natural Sciences
Volume
13
Pages
58–75
Publication date
21 March 2026
Language
EN