aceUnderstanding critical thinking in generative artificial intelligence use: Development, validation, and correlates of the critical thinking in AI use scale
Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that users must critically evaluate AI outputs rather than accept them at face value. The present research conceptualises critical thinking in AI use as a dispositional tendency to verify the source and content of AI-generated information, to understand how models work and where they fail, and to reflect on the broader implications of relying on AI. Across six studies ( N =…
Higher critical thinking in AI use was associated with better detection of inaccurate information during a GPT-powered chatbot interaction, including use of more verification strategies.
Evidence
- Peer-reviewedComputers in Human Behavior Reports2026-05-01
How should this claim be treated?
Truvace Impact Record TRV-2026-0136, v1: “Understanding critical thinking in generative artificial intelligence use: Development, validation, and correlates of the critical thinking in AI use scale.” Truvace, 2026-07-13. /record/TRV-2026-0136 (accessed at citation time). sha256 09afeec4124589c3…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-0136 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.