Abstract
In the evolving landscape of artificial intelligence (AI), critical thinking (CT) has become essential for navigating its opportunities and challenges, particularly in strategic HRM decision-making. This study evaluates the effectiveness of a targeted AI-based training intervention in enhancing AI-specific CT skills among graduate students. Adopting a mixed-methods convergent design, it combines a quasi-experimental pre- and post-test approach with qualitative focus groups. The quantitative component measures changes in CT levels using a performance-based assessment grounded in the Watson–Glaser framework and the International Performance Assessment of Learning (iPAL). The qualitative phase analyses how the adoption of AI during the training impacted students’ learning experiences and CT outcomes. Findings are expected to demonstrate improvements in AI-specific CT and inform the design of AI-based training programmes for HRM students and practitioners. The ultimate aim is to strengthen critical engagement with AI tools and support fairer, more reflective decision-making in HRM.
Recommended Citation
Airaghi, Ludovica; Contiero, Rachele; Lazazzara, Alessandra; and Zannini, Lucia, "Enhancing AI-Specific Critical Thinking Skills through AI: A Quasi-Experimental Mixed-Methods Study in HRM Higher Education" (2025). ITAIS 2025 Proceedings. 40.
https://aisel.aisnet.org/itais2025/40
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