7,348 responses from 668 respondents to 11 items.
| Description | Information self-efficacy with GenAI output: 11 items on confidence to evaluate and synthesise GenAI-generated information, rated 1-7 from strongly disagree to strongly agree. Survey of 668 higher-education users of generative AI tools in Singapore; the deposit has no respondent identifier or demographics. |
|---|---|
| Reference | Nguyen, T. M. C.; Lee, C. S. (2026). Fact-Checking Against Misinformation by Generative Artificial Intelligence Conversational Agents: the Role of Digital Literacy. Technology in Society. Data: Nguyen, T. M. C.; Lee, C. S. (2026). Fact-Check Misinformation by Generative Artificial Intelligence: The Roles of Digital Literacy, Information Processing, and Information Self-Efficacy. DR-NTU (Data). https://doi.org/10.21979/N9/P5WUGI |
| Licence | CC BY-NC 4.0 |
| Source data | https://doi.org/10.21979/N9/P5WUGI |
| Responses | 7,348 |
|---|---|
| Respondents | 668 |
| Items | 11 |
| Response categories | 7 |
| Responses per respondent | 11 |
| Responses per item | 668 |
| Density | 1 |
| Longitudinal | FALSE |
iditemresp
Licence: CC BY-NC 4.0 — non-commercial use only.
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("nguyen_2026_factcheck_info_self_efficacy")
# Python
pip install irw
import irw
df = irw.fetch("nguyen_2026_factcheck_info_self_efficacy")
@misc{https://doi.org/10.21979/n9/p5wugi,
doi = {10.21979/N9/P5WUGI},
url = {https://researchdata.ntu.edu.sg/citation?persistentId=doi:10.21979/N9/P5WUGI},
author = {Nguyen, Tran Mai Chi and Lee, Chei Sian},
keywords = {Computer and Information Science, Social Sciences, GenAI misinformation, Digital literacy, Information processing, Higher education, Fact-checking, Human-AI interaction},
title = {Fact-Check Misinformation by Generative Artificial Intelligence: The Roles of Digital Literacy, Information Processing, and Information Self-Efficacy},
publisher = {DR-NTU (Data)},
year = {2026}
}
| IRW version | v407 |
|---|---|
| Redivis dataset | item_response_warehouse v56.0 |
| Redivis dataset DOI | 10.57761/dz3k-mc81 |
| Manifest pin for this IRW version | v56.0 |
| Metadata source | irw_meta v24.0 |