A context-sensitive scale for assessing GenAI-contextualized acceptance in conservation-related architectural education: development and initial validation

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• Semantic Scholar2026-08-09 07:15:27
  A context-sensitive scale for assessing GenAI-contextualized acceptance in conservation-related architectural education: development and initial validation

  Generative artificial intelligence (GenAI) is increasingly shaping higher education in professional fields where AI-supported outputs must be evaluated against disciplinary, ethical, and evidentiary criteria. Conservation-related architectural education is one such context because technically convincing outputs still require assessment against authenticity, material knowledge, intervention ethics, and heritage standards. This study developed and initially validated the Scale for Generative AI Technology Acceptance in Conservation Education (SGATE-CE) to assess GenAI-contextualized acceptance among undergraduate architecture students receiving conservation- and restoration-related coursework. After expert review, a 35-item pool was reduced to 27 items and examined using principal axis factoring with direct oblimin rotation in an exploratory sample ( n  = 157). Following pre-confirmatory measurement-model finalization, a 17-item structure comprising Perceived Usefulness, Behavioral Intention, Applied Educational Engagement, and Perceived Conservation-Specific Utility was tested through confirmatory factor analysis in a separate validation sample ( n  = 201). Reliability, convergent validity, discriminant validity, and theoretically specified structural associations were also examined. The unmodified four-factor model showed acceptable fit: CMIN/df = 2.044, GFI = .880, CFI = .942, TLI = .930, RMSEA = .072, SRMR = .058, and RMR = .037. Alpha ranged from .797 to .896, omega from .804 to .897, composite reliability from .843 to .897, and AVE from .574 to .636. Structural modeling showed positive associations overall, although the PU-to-BI association was weaker and less stable under bootstrap sensitivity analysis. The findings provide initial psychometric support for the four perceived-acceptance dimensions in conservation-related architectural education. Because some retained items may evoke broader AI or digital technologies, SGATE-CE measures GenAI-contextualized acceptance rather than exclusive GenAI acceptance. It does not measure subject knowledge, ethical judgment, critical evaluation, responsible AI use, or disciplinary competence. The Turkish version was tested, whereas the English wording is an informational translation. Further validation in dedicated conservation and heritage programs is required.