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Gleaning museum visitors’ behaviors by analyzing questions asked in a mobile app

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Abstract

This study explores the feasibility of forming detailed inferences about museum visitor behavior based on analysis of data collected via Dr. Discovery—a mobile question-and-answer app. We analyzed 5656 questions asked by 795 visitor groups recorded by Dr. Discovery across two museums in the American Southwest. Analysis of this data supported the act of intuiting visitor movement through museum exhibit halls without the use of costly tracking or location technology by leveraging question keyword content, knowledge of exhibit hall layout, and question timestamp information. Additionally, data on question topic frequency enabled us to infer visitor engagement levels with specific exhibit hall content. We conclude that analysis of seemingly limited app-based data carries implications for the practice of museum evaluation since evaluators can gain evidence-based insight into visitor behaviors as well as illustrate helpful and promising technology-supported alternatives for conducting affordable, dependable, and scalable evaluations.

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The data that support the findings of this study are available upon request from the corresponding author.

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Acknowledgements

The authors would like to acknowledge the staff at both of our partner museums.

Funding

This work was supported by the National Science Foundation [Grant Number 1438825].

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Authors and Affiliations

  1. University of Pittsburgh, Murdoch Building, 3420 Forbes Ave., Pittsburgh, PA, 15260, USA

    Luis E. Pérez Cortés

  2. University of California, Los Angeles, USA

    Jesse Ha

  3. Arizona State University, Tempe, USA

    Man Su, Brian Nelson, Catherine Bowman & Judd Bowman

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  1. Luis E. Pérez Cortés
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Correspondence to Luis E. Pérez Cortés.

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Pérez Cortés, L.E., Ha, J., Su, M. et al. Gleaning museum visitors’ behaviors by analyzing questions asked in a mobile app. Education Tech Research Dev 71, 1209–1231 (2023). https://doi.org/10.1007/s11423-023-10208-1

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