AI-Directed XR User Behavior Logs from an Industrial Heritage Museum Study

A single-group deployment study with 37 participants at the santralistanbul Energy Museum in 2026. The dataset likely contains telemetry logs of user behavior, including movement, head orientation, and hand movements, used to classify interaction profiles and adapt an XR experience. It was created by Başak Çakmak and includes pre/post questionnaire results on heritage perception.

Use Cases

• Train user profile classification models based on real-time movement and orientation telemetry.
• Analyze correlations between user immersion, workload, and changes in heritage perception.
• Study the feasibility of curatorially constrained, rule-based expert systems for XR content adaptation.

Strengths

• Includes multimodal logging data from 37 participants in a real-world museum setting.
• Provides validation metrics for profile classification (e.g., tie-aware accuracy: 83.8%).
• Contains pre/post questionnaire results showing a statistically significant change in heritage perception (mean paired change = 1.35, p<.001).

Limitations

• Row count and column-level documentation are unknown, requiring manual inspection after download.
• The dataset is small (105.5 KB), indicating limited scope and sample size.
• Data is from a single museum deployment, which may limit generalizability.

Provenance

Source

figshare, authored by Başak Çakmak.

Collection Method

Collected via a multimodal logging system during a single-group deployment study of a four-scene XR experience on a standalone headset.

Time Range

Data collection likely occurred around the time of the study's implementation, but specific dates are not provided.

Freshness

Last updated 2026-06-02 04:21:12.

Geography

santralistanbul Energy Museum, Istanbul, Turkey.