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Assessing AI Literacy at University Entry: A Mixed-Item Diagnostic Instrument

Year: 2026

Type: article

Abstract: This poster introduces a four-dimensional mixed-item AI literacy diagnostic instrument combining self-report and performance-based measures to assess calibration between perceived and demonstrated competence at university entry (N = 106). The results identify dimension-specific perception–performance gaps and provide a foundation for AI-integrated curriculum design within the KoVEKI project.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.19483986

Author: Iovine, Ivan

Institution: University of Applied Sciences Potsdam

Language: English

Topic: Digital literacy in education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W7152559841

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