Survey of Chinese University Students on AI-Assisted Language Learning and Communication

A dataset from a study of 1,362 non-English-major university students in China. The research investigates how AI-mediated informal digital learning of English influences willingness to communicate through three dimensions of foreign language enjoyment. The dataset was authored by Sisi Guo and last updated on figshare in May 2026.

Use Cases

• Analyzing the mediating role of personal enjoyment in AI-assisted learning and communicative engagement based on the described structural equation model.
• Comparing the differential effects of teacher appreciation and social enjoyment in classroom versus out-of-class contexts based on the study's findings.
• Investigating the relative impact of productive versus receptive AI-mediated learning activities on positive emotions based on the reported results.
• Building predictive models for language learners' willingness to communicate based on AI usage and emotional dimensions described in the study.

Strengths

• Includes data from a large-scale investigation of 1,362 participants.
• Analysis employs structural equation modeling with confirmatory factor analysis, suggesting a rigorous methodological approach.
• Explicitly examines three distinct dimensions of foreign language enjoyment (teacher appreciation, personal enjoyment, social enjoyment).

Limitations

• The dataset is small (100.7 KB), indicating limited scope or summary-level data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for certain analyses.

Provenance

Source

figshare

Collection Method

Likely contains survey data collected from a large-scale investigation of university students, analyzed using structural equation modeling.

Time Range

null

Freshness

Last updated 2026-05-04 04:18:10; freshness should be verified.

Geography

Data was collected from university students in China.