{"id":919,"date":"2024-12-05T18:13:25","date_gmt":"2024-12-05T18:13:25","guid":{"rendered":"https:\/\/labs.cs.queensu.ca\/istudio\/?post_type=qsc_member&p=919"},"modified":"2025-12-02T18:17:15","modified_gmt":"2025-12-02T18:17:15","slug":"flora-lin","status":"publish","type":"qsc_member","link":"https:\/\/labs.cs.queensu.ca\/istudio\/members\/flora-lin\/","title":{"rendered":"Flora Lin\u200b"},"content":{"rendered":"
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Flora Lin\u200b<\/h1><\/div>\n\t\t
Research Assistant<\/div>\n\t\t
School of Computing<\/div>\n\t\t
Queen’s University<\/div>\n\t\t
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Flora is an undergraduate in the Cognitive Science Bachelor program at the School of Computing in Queen\u2019s University. She did her capstone project at the iStudio where she helped design interactive products and conduct research study’s fieldwork with local community members. She is now working as a Product Design at TD Bank.<\/p>\n\n\n\n

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Publications<\/strong><\/strong><\/h2><\/div>\n\n\n\n

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Alaa Nousir, Lee Jones, Flora Lin, Tom Everrett, Sara Nabil<\/p>

MobileMuseum: Smart, Portable, and Borrowable Museum Displays to Explore Interaction Patterns and Public Engagement<\/a> Journal Article<\/span> <\/p>

In: <\/span>Proceedings of the ACM on Human-Computer Interaction (PACM HCI) Journal, <\/span>vol. 9, <\/span>iss. 8, <\/span>no. ISS016, <\/span>pp. 341 \u2013 370, <\/span>2025<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{10.1145\/3773073,
\r\ntitle = {MobileMuseum: Smart, Portable, and Borrowable Museum Displays to Explore Interaction Patterns and Public Engagement},
\r\nauthor = {Alaa Nousir and Lee Jones and Flora Lin and Tom Everrett and Sara Nabil},
\r\nurl = {https:\/\/doi.org\/10.1145\/3773073
\r\nhttps:\/\/labs.cs.queensu.ca\/istudio\/wp-content\/uploads\/sites\/12\/2025\/11\/MobileMuseum-3773073.pdf
\r\nhttps:\/\/www.youtube.com\/watch?v=Wzt41AC_-_Y},
\r\ndoi = {10.1145\/3773073},
\r\nyear  = {2025},
\r\ndate = {2025-11-13},
\r\nurldate = {2025-11-13},
\r\nbooktitle = {Proceedings of the ACM on Human-Computer Interaction (PACM HCI) Journal},
\r\njournal = {Proceedings of the ACM on Human-Computer Interaction (PACM HCI) Journal},
\r\nvolume = {9},
\r\nnumber = {ISS016},
\r\nissue = {8},
\r\npages = {341 \u2013 370},
\r\nabstract = {We explore how smart, portable, tangible, and borrowable museum displays can be used to expand museum outreach, and provide tools for measuring user engagement. Our prototype, MobileMuseum, is a portable museum display on wheels, housing digitally-fabricated replicas of artifacts from a national science and technology museum. To track interactions without cameras, we embedded photo and magnetic door sensors and RFID tags and antenna. Our deployment study was carried out for 2 months and included 4 different locations (2 recreational and 2 educational). Data collected from 6 sensors, 261 hours of field observations, 17 filled questionnaires, and 14 interviews helped us understand interaction patterns. Qualitative and quantitative findings revealed that self-monitored interactions encouraged deeper open-ended exploration. Social sharing increased among people in groups while lower foot traffic increased engagement duration. We present generalizable opportunities for self-monitored Interfaces that lends themselves to social circulation, \u2018honeybee-effect\u2019, \u2018order effect\u2019, and \u2018leftovers\u2019 from users.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/pre><\/div>
Close<\/a><\/p><\/div>
We explore how smart, portable, tangible, and borrowable museum displays can be used to expand museum outreach, and provide tools for measuring user engagement. Our prototype, MobileMuseum, is a portable museum display on wheels, housing digitally-fabricated replicas of artifacts from a national science and technology museum. To track interactions without cameras, we embedded photo and magnetic door sensors and RFID tags and antenna. Our deployment study was carried out for 2 months and included 4 different locations (2 recreational and 2 educational). Data collected from 6 sensors, 261 hours of field observations, 17 filled questionnaires, and 14 interviews helped us understand interaction patterns. Qualitative and quantitative findings revealed that self-monitored interactions encouraged deeper open-ended exploration. Social sharing increased among people in groups while lower foot traffic increased engagement duration. We present generalizable opportunities for self-monitored Interfaces that lends themselves to social circulation, \u2018honeybee-effect\u2019, \u2018order effect\u2019, and \u2018leftovers\u2019 from users.<\/div>
Close<\/a><\/p><\/div>