Structural Model Results and Hypothesis Testing for AI in Fashion Design Education

500 fashion design students from 18 Chinese universities participated in a study examining the structural relationships among teacher support, AI usage, creative capability, and learning outcomes. The dataset contains structural equation modeling results and hypothesis testing, authored by Zhiyi Zhang and last updated in May 2026. It is shared under a CC-BY-4.0 license as a 5.5 KB XLS file.

Use Cases

• Testing mediation models in educational technology adoption based on the described chain mediation structure.
• Analyzing differential associations between teacher support dimensions and technology usage based on the study's findings.
• Investigating the relationship between generative AI usage behavior and creative design capability as described.
• Validating structural pathways from environmental support to learning outcomes via behavioral and cognitive variables.

Strengths

• Dataset is based on a sample of 500 students, providing a substantial basis for analysis.
• Study design draws on established theoretical frameworks (Technology Acceptance Model and Social Cognitive Theory).
• Results include specific quantitative findings, such as a 62.3% mediation effect for technical support.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data reflects a specific geographic and educational context (Chinese fashion design universities), which may limit generalizability.

Provenance

Source

figshare

Collection Method

Data collected via survey from students across 18 Chinese universities, analyzed using structural equation modeling.

Time Range

null

Freshness

Last updated 2026-05-06 17:30:29; freshness should be verified.

Geography

China