Student Survey on AI-Supported Learning Intentions and Academic Interest

Survey data from undergraduate students in business analytics courses, collected to study perceptions of AI in learning. The dataset, 9.5 KB in size, was authored by Yang Cheng and last updated on June 4, 2026. It is shared under a CC-BY-4.0 license.

Use Cases

• Modeling the relationship between perceived AI 'coolness' and continued usage intentions based on survey constructs.
• Analyzing the mediating role of academic interest between AI usage intentions and career-choice intentions.
• Testing structural equation models linking perceived enhancement, interactivity, fun, and coolness to educational outcomes.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• The underlying study is grounded in established theories including post-adoption continuance research and Social Cognitive Career Theory.
• Data was analyzed using structural equation modeling, suggesting a structured analytical approach.

Limitations

• The dataset is very small at 9.5 KB, indicating limited scope.
• Row count and column-level documentation are unknown, requiring manual inspection after download.
• Data may reflect bias inherent to the specific student population and courses sampled.

Provenance

Source

figshare

Collection Method

Survey data collected from undergraduate students enrolled in business analytics courses.

Freshness

Last updated 2026-06-04 17:32:25.