Using Personas to Model Museum Visitors

Almeshari, Moneerah; Dowell, J. D.; Nyhan, Julianne

doi:10.1145/3314183.3323867

Cited by 7 publications

(4 citation statements)

References 16 publications

(22 reference statements)

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“…The combination of responses to the two questions resulted in 6 clusters representing different persona groups that also correspond with visitors' self-assessed persona (figure 1). This result indicates that we can reliably identify visitor persona using two multiple choice questions about visit motivation and success criteria (Almeshari, Dowell, & Nyhan, 2019).…”

Section: Persona Identificationmentioning

confidence: 78%

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Museum Mobile Guide Preferences of Different Visitor Personas

Almeshari

Dowell

Nyhan

2020

J. Comput. Cult. Herit.

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Personalising museum mobile guides is widely acknowledged as being important for enhancing the visitor experience. Due to the lack of information about an individual visitor and the relatively limited time of his or her visit, adapting the user interface based on a museum visitor's type is a promising approach to personalisation. This approach first requires a mechanism to identify the visitor type (‘persona’) and, second, knowledge of the preferences and needs of different types to apply personalisation. In this article, we report a face-to-face questionnaire study carried out with 105 visitors to Scitech, a science and technology visitor centre. The study aims to investigate the main facts required to identify a visitor persona and to explore the preferences of different visitor personas for particular mobile guide features. We limited our concern to the user interface features of the guide (e.g., whether it provides recommendations for related items to view) rather than what content and services the guide provides (e.g., what related items are recommended). We found that we can reliably identify the visitor persona using two multiple choice questions about visit motivation and perceived success criteria. In addition, we found that visitors have significant preferences for particular features such as presentation media, venue navigation tool, object suggestions, details level, accessing external links, exhibit information retrieval method and social interaction features such as voice communication, instant messaging, group games and challenges. Some features were found to be preferred differently by different personas such as the challenges feature, some were found to be preferred by personas differently to the overall preference such as in presentation media, and some were found to be preferred by some personas with no particular preference for others such as a venue navigation tool. Instant messaging was found to be significantly not preferred by all personas. The results provide a basis for personalisation of museum guides and services using a personas approach, which is a solution where data about individual users may be limited and where the individual configuration of a user interface may not be practical or warranted.

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Section: Persona Identificationmentioning

confidence: 78%

“…Figure1: The relation of the visitor persona with the visit motivation and the perceived success criteria(Almeshari et al, 2019) …”

mentioning

confidence: 99%

Museum Mobile Guide Preferences of Different Visitor Personas

Almeshari

Dowell

Nyhan

2020

J. Comput. Cult. Herit.

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“…Recent research has continued to focus on issues such as user modelling and recommender systems (Almeshari et al, 2019;Castagnos et al, 2019;Dahroug et al, 2019;De Angelis et al, 2017;Deladiennee & Naudet, 2017;Fishwick, 2016;Katifori et al, 2019;Mauro, 2019;Mokatren et al, 2019;Sansonetti et al, 2019).…”

Section: Interpersonalizationmentioning

confidence: 99%

Interpersonalizing Intimate Museum Experiences

Ryding

Spence

Løvlie

et al. 2021

International Journal of Human–Computer Interaction

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We reflect on two museum visiting experiences that adopted the strategy of interpersonalization in which one visitor creates an experience for another. In the Gift app, visitors create personal mini-tours for specific others. In Never let me go , one visitor controls the experience of another by sending them remote instructions as they follow them around the museum. By reflecting on the design of these experiences and their deployment in museums we show how interpersonalization can deliver engaging social visits in which visitors make their own interpretations. We contrast the approach to previous research in customization and algorithmic personalization. We reveal how these experiences relied on intimacy between pairs of visitors but also between visitors and the museum. We propose that interpersonalization requires museums to step-back to make space for interpretation, but that this then raises the challenge of how to reintroduce the museum's own perspective. Finally, we articulate strategies and challenges for applying this approach.

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“…Given such a premise, the idea of building "knowledge packages" (paths of linked information) targeted to different kinds of users, has to be considered in relation to specific visitors "profiles". There is a huge literature on how setting visitors classes, generally in relation to their expertise, behavior, attitude, interests [36,37]. In our case, we had to set up a sufficiently simple model to allow forms of automated reasoning in support to the definition of the lessons' content, yet more complex than a merely knowledge-based "expert vs novice" or similar dichotomy [37], taking into account both personal expertise and interest to the matter, which are, as we have stated before, linked each other.…”

Section: User Modeling For a Personalized Experiencementioning

confidence: 99%

Fostering the Creation of Personalized Content for Cultural Visits

et al. 2021

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Among more dramatic effects, the COVID-19 scenario also raised the need for new online information and communication services, promoting the spread of software solutions whose usefulness will last well beyond the pandemic situation. Particularly in the cultural heritage domain, it has been unveiled the relevance of new AI-based approaches, able to dynamically aggregate information and making them available for a customized fruition aimed to the individual cultural growth. Here, we integrate machine learning techniques for the automatic generation of contents for an intelligent tutoring system grounded on automated planning techniques. We present a solution for semantic, intelligent creation of personalized cultural contents, born as a lesson-making assistant, but developed as to become a multi-function “cultural crossover”, useful in the frame of a wide range of planning, dissemination, and managing activities for cultural heritage contents.

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Using Personas to Model Museum Visitors

Cited by 7 publications

References 16 publications

Museum Mobile Guide Preferences of Different Visitor Personas

Museum Mobile Guide Preferences of Different Visitor Personas

Interpersonalizing Intimate Museum Experiences

Fostering the Creation of Personalized Content for Cultural Visits

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