Year: 2025
Type: article
Abstract: This paper proposes a Generative Artificial Intelligence (GenAI) Competence Framework for Engineering Curriculum Enhancement, designed to leverage GenAI’s potential to enrich teaching and learning, address challenges arising from misuse or unethical application of GenAI, and prepare graduates for AI-driven workplaces. Building upon the university’s AI literacy conceptual framework, this GenAI Competence Framework defines GenAI competence tiers, provides comprehensive strategies for integrating GenAI into engineering education, and offers practical implementation plans and impact assessment mechanisms that collectively form a sustainability roadmap. The framework's development was informed by extensive consultation with students, staff, and industry experts through surveys, focus groups, interviews, and program reviews, ensuring its practicality, adaptability, and alignment with real-world demands. By incorporating GenAI-empowered curriculum enhancements alongside supplementary extracurricular activities to bridge the digital divide, the framework aims to equip students with essential GenAI competencies while enriching their overall learning experience.
DOI: 10.53761/ited/1.2
Authors: Yue Chen, Kok Keong Chai, Vindya Wijeratnre, Usman Naeem, Jonathan Loo, Xue Zhou, Simon Lucas
Institutions: Queen Mary University of London, University of Leicester
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4413175658