The Strategic Prompting Scale (SPS) for Measuring Metacognitive Regulation in Human-AI Interaction

The increasing use of Neural Language Models (NLMs) calls for strategic and metacognitive skills in prompt formulation, monitoring, and adaptation. This study presents the Strategic Prompting Scale (SPS), designed to measure the extent to which users apply planning, adaptation, and evaluation strategies during interactions with generative language models. After expert review and pilot testing, an exploratory factor analysis with 187 participants revealed a three-factor structure-Planning, Adaptation, and Evaluation-explaining 60.4% of the total variance. The final 15-item scale demonstrated good internal consistency. Confirmatory factor analysis with an independent sample of 406 participants supported the proposed factor structure. The SPS also showed theoretically expected associations with related constructs, including positive correlations with metacognition and critical thinking, and negative correlations with disengagement in AI interaction. Overall, the findings provide preliminary psychometric evidence for the SPS as a theory-driven instrument to assess metacognitive regulation and self-regulated behaviors in generative AI use, with potential applications in educational, professional, and research contexts.