Perceptual Invariance and Question Types in the Digital Age: An Integrated Epistemological, Theological, and AI-Supported Model

This study examines the determining role of question types in knowledge production along epistemological and theological axes, focusing on how meaning can be preserved amid the escalating flow of information in the digital age. The original contribution of this work lies in linking question types with the concept of perceptual invariance, demonstrating that knowledge is not merely produced but is also consistently preserved and reconstructed. According to Perceptual Invariance Theory (PIT; Demirkus, 2026a), semantic noise in educational materials is the primary cause of student failure, and materials designed with the 99% Precision Principle are essential to reduce this noise. Scientific and religious domains of knowledge were comparatively examined; quantitative analyses revealed statistically significant differences in perceptual invariance rates across different question types [F(4, 495) = 89.47, p < .001, η² = .417]. The EduCode Protocol experimental intervention achieved a 42% reduction in semantic noise in the experimental group (Cohen's d = 0.72, 95% CI = [0.38, 1.05]). The proposed Digital Wisdom Guide and PIF-Prompt Model offer pedagogically grounded frameworks for meaning-preserving AI integration in education.