Competency in Working with Genai in Road Engineering Education

Abstract

This article develops a competency model for working with generative artificial intelligence (GenAI) for engineering education. GenAI is increasingly used by students to explain methods, prepare rough calculations, and develop arguments, but the engineering value of such support is determined by the student's ability to verify formulas, units of measurement, input data, coefficients, assumptions, and normative statements. Based on a targeted documentary review of international AI competency frameworks, engineering accreditation requirements, research on GenAI in engineering education, and the context of Uzbekistan, an operational framework is developed. It integrates engineering problem statement, prompt quality, independent recalculation, unit and source audit, verification of normative references, error classification, engineering interpretation, and transparent disclosure of AI use. The framework focuses on assignments in road hydrology, drainage, road reconstruction, and design disciplines.