College Adaptation Questionnaire Data: Psychometric Network Analysis of Student Adjustment

A 2026 study analyzed the College Adaptation Questionnaire (CAQ) using psychometric network methods on a sample of 240 first-year students at a UK university. The research identified four latent clusters related to satisfaction, social connection, adjustment, and motivation, and compared network structures between first-generation and non-first-generation students. The dataset, authored by Thomas V. Pollet and shared under a CC-BY-4.0 license, supports the argument for using the CAQ as a multidimensional instrument.

Use Cases

• Replicate psychometric network analysis based on the described four latent clusters (satisfaction, social connection, adjustment, motivation).
• Compare network structures between student subgroups based on first-generation status as described in the study.
• Validate the multidimensional structure of the College Adaptation Questionnaire (CAQ) suggested by the findings.

Strengths

• Dataset is based on a sample of 240 first-year students, providing a concrete scale for analysis.
• The study applies a specific, modern analytical method (psychometric network analysis) to a widely-used instrument.
• Clear license (CC-BY-4.0) facilitates open reuse and sharing.

Limitations

• Row count is unknown, which may limit suitability assessment for certain modeling tasks.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (5.5 KB), indicating limited scope and likely a summary or processed results rather than raw survey responses.

Provenance

Source

figshare

Collection Method

Psychometric network analysis applied to College Adaptation Questionnaire (CAQ) responses.

Freshness

Last updated 2026-05-12 17:43:19; freshness should be verified.

Geography

Data collected from a UK university.