Aligning Higher Education with Workforce Competency Requirements in Data Science and Electric Vehicles: A Systematic Literature Review

Abstract

Rapid digitalisation and decarbonisation are reshaping the relationship between higher education and work, creating pressure for curricula to respond to emerging workforce competency requirements without becoming narrowly tool-driven. This systematic literature review examines data science and electric vehicle (EV) industries as comparative high-tech sectors within the new economy, representing the digital and green transitions, respectively. Using a PRISMA-informed protocol, 40 peer-reviewed journal articles published between 2010 and 2025 were synthesised: 20 from data science and 20 from EV-related fields. The analysis was interpreted through graduate employability and university–industry collaboration perspectives to move beyond a simple inventory of technical skills. Six competency clusters were identified in each domain, together with six cross-cutting capabilities: systems thinking, digital fluency, communication, problem solving under uncertainty, responsibility, and lifelong learning. Four mechanisms for higher education–industry alignment were also identified: competency-based curriculum mapping, authentic and work-integrated learning, recurring employer participation, and flexible upskilling pathways. The comparison shows that both sectors challenge discipline-bound educational models because workplace performance increasingly depends on the integration of technical knowledge, judgement, communication, ethics, and adaptation. The study proposes a higher education–industry competency alignment framework and discusses implications for graduate employability, equitable access to applied learning, institutional governance, and workforce development in data science and the electric vehicle industry.