Evaluating a Web Tool to Predict Visitor Density at Staatliches Naturkundemuseum Karlsruhe

For disabled people, visitor density at a museum is an access concern. However, although museums collect visitor numbers, data is often not processed for public information and cannot be used for visit planning. Here, digital tools that automatically process data and predict visitor density offer an opportunity to allow potential visitors to make better decisions about their day and time of visit.

This work is in collaboration with the Staatliches Naturkundemuseum Karlsruhe and aims to evaluate an existing web tool that predicts and visualizes visitor density. The thesis will take a two-step research approach: First, the general usability of the tool and the quality of the visualization will be assessed. Second, the thesis will engage in qualitative evaluation together with disabled and non-disabled visitors either remotely or on-site at Naturkundemuseum, seeking to understand their perspectives on the potential and limitations of the tool.

Overall, the thesis is expected to contribute to the understanding of accessibility in public spaces and to improve access to leisure for disabled people. It is part of the Real-World Lab Accessibility, also see http://www.accessibility.kit.edu.

Task Summary

1. Prototype Evaluation Qualitative exploration of the tool together with disabled persons to understand their perspectives on the potential and limitations.
2. Design Recommendations Summary of recommendations for the design of tools that predict visitor density to increase venue accessibility.
3. Revising the Prototype Applying the design recommendations to revise the prototype.

Required Skills

• HCI German/English Language
• Web development
• Qualitative Analysis
• Quantitative Analysis
• Participant Recruitment

Contact

Dmitry Alexandrovsky and Zeynep Yildiz