University Student Survey on Generative AI for Personalized English Learning

A survey of university students collected 386 valid questionnaires to analyze determinants of their intention to use generative AI tools for personalized English learning. The study employed structural equation modeling using SmartPLS 4.0 software. The dataset was uploaded by Li Wang on figshare and last updated on 2026-05-05.

Use Cases

• Modeling technology acceptance based on constructs like performance expectancy and effort expectancy.
• Investigating the mediating role of flow experience in learning technology adoption.
• Analyzing the moderating effect of personal innovativeness on hedonic motivation.
• Informing the design of educational AI tools based on student behavioral intentions.

Strengths

• Dataset includes 386 valid survey responses.
• Analysis was conducted using structural equation modeling with SmartPLS 4.0.
• The study extends the UTAUT2 model with flow experience and personal innovativeness.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect bias inherent to the convenience sampling method.

Provenance

Source

figshare

Collection Method

Survey conducted among university students using a convenience sampling method.

Freshness

Last updated 2026-05-05 05:29:00; freshness should be verified.