The DOI matches its DataCite record.
Survey Dataset for Exploring Students' Trust and Verification Behavior in AI Chatbot Use
Abstract
This dataset contains anonymized survey data from 104 university students who use AI chatbots for academic activities. The questionnaire consists of 20 items measured on a five-point Likert scale covering four constructs: Perceived Ease of Use (PEOU), Trust in AI, Verification Behavior (VB), and Digital Literacy (DL). The dataset was collected using purposive sampling and supports the statistical analyses reported in the accompanying research paper, including descriptive statistics, reliability testing, Pearson correlation, linear regression, moderation analysis, and mediation analysis. All personally identifiable information has been removed to ensure participant confidentiality.
Overview
Integrity signals
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Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The dataset is publicly accessible and anonymised.”
From Critical Evaluation of AI-Generated Academic Information in Higher Education: Empirical Evidence on Trust, AI-Related Digital Literacy and Verification Behaviour (2026) · cites this paper as Farras, A. J., Lusiawati, D. A. & Simatupang, S. S. S. (2026)
In the citing paper
“The dataset contains 104 student-level observations.”
From Critical Evaluation of AI-Generated Academic Information in Higher Education: Empirical Evidence on Trust, AI-Related Digital Literacy and Verification Behaviour (2026) · cites this paper as Farras, A. J., Lusiawati, D. A. & Simatupang, S. S. S. (2026)
In the citing paper
“The original sampling procedure was purposive and the dataset contains 104 student-level observations.”
From Critical Evaluation of AI-Generated Academic Information in Higher Education: Empirical Evidence on Trust, AI-Related Digital Literacy and Verification Behaviour (2026) · cites this paper as Farras, A. J., Lusiawati, D. A. & Simatupang, S. S. S. (2026)
In the citing paper
“The dataset contains 20 five-point Likert-scale items covering four constructs: PEOU, Trust in AI, Verification Behaviour and Digital Literacy.”
From Critical Evaluation of AI-Generated Academic Information in Higher Education: Empirical Evidence on Trust, AI-Related Digital Literacy and Verification Behaviour (2026) · cites this paper as Farras, A. J., Lusiawati, D. A. & Simatupang, S. S. S. (2026)
Citations
Cited by
Kaur, D. K., & Pundir, P. P. S. (2026) · International Journal of Scientific Research in Modern Science and Technology · doi:10.59828/ijsrmst.v5i9.459
Metadata
- Authors
- Farras, A. J., Lusiawati, D. A., & Simatupang, S. S. S.
- Affiliations
- Binus University
- Venue
- Zenodo
- Publisher
- Zenodo
- Published
- 2026-07-02
- References
- 0
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Survey Dataset for Exploring Students' Trust and Verification Behavior in AI Chatbot Use. https://app.cochat.ai/papers/10.5281/zenodo.21135117
- The paper
- Farras, A. J., Lusiawati, D. A., & Simatupang, S. S. S. (2026). Survey Dataset for Exploring Students' Trust and Verification Behavior in AI Chatbot Use. Zenodo. https://doi.org/10.5281/zenodo.21135117
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.