Reconstruction of the Teaching Paradigm of Genetic Diseases Empowered by Artificial Intelligence: A Study of Cognitive Embodiment and the Structuring of Ethical Decision Making

Abstract

The education penetration of AI technology is catalyzing the dual reform of the biology teaching paradigm: it not only realizes the macroscopic visualization of microscopic mechanisms but also promotes the dialectical structuring of ethical cognition. On the basis of constructivist learning theory, this study innovatively proposes a three-dimensional teaching framework of "digital twin-intelligent deduction-value modeling". Through the development of a chromosome behavior dynamic rendering engine, a phenotype‒gene association map generation system and an ethical decision tree algorithm, the three major problems of "fragmented mechanism understanding", "linearized case analysis", and "extreme ethical judgment" in the teaching of genetic diseases were effectively solved. Empirical studies revealed that the experimental group was significantly better than the control group in terms of accuracy of genetic map analysis (82.3% vs. 64.1%, p<0.01) and completeness of multivariate pathogenic model construction (4.7 vs. 2.9, Cohen's d=1.21). This study provides a reproducible technology integration solution for the digital transformation of biology education under the framework of “China Education Modernization 2035”.