Simulated self-assessment in large language models: A psychometric approach to AI self-efficacy
- DOI
- 10.1016/j.chbah.2026.100389
- Published
- 2026-08
- Container
- Computers in Human Behavior: Artificial Humans
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.chbah.2026.100389,
title = {Simulated self-assessment in large language models: A psychometric approach to AI self-efficacy},
author = {Daniel I. Jackson and Emma L. Jensen and Syed-Amad Hussain and Emre Sezgin},
year = {2026},
journal = {Computers in Human Behavior: Artificial Humans},
doi = {10.1016/j.chbah.2026.100389},
url = {https://doi.org/10.1016/j.chbah.2026.100389}
}RIS
TY - JOUR TI - Simulated self-assessment in large language models: A psychometric approach to AI self-efficacy AU - Daniel I. Jackson AU - Emma L. Jensen AU - Syed-Amad Hussain AU - Emre Sezgin PY - 2026 JO - Computers in Human Behavior: Artificial Humans DO - 10.1016/j.chbah.2026.100389 UR - https://doi.org/10.1016/j.chbah.2026.100389 ER -
APA
Jackson, D. I., Jensen, E. L., Hussain, S., & Sezgin, E. (2026). Simulated self-assessment in large language models: A psychometric approach to AI self-efficacy. Computers in Human Behavior: Artificial Humans. https://doi.org/10.1016/j.chbah.2026.100389
Source records
- crossref · retrieved 2026-09-25T13:27:16.377Z