UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

User Modelling with Personas and the Personalisation of a Museum Mobile Guide

Almeshari, Moneerah; (2024) User Modelling with Personas and the Personalisation of a Museum Mobile Guide. Doctoral thesis (Ph.D), UCL (University College London).

[thumbnail of User Modelling with Personas and the Personalisation of a Museum Mobile Guide.pdf] Text
User Modelling with Personas and the Personalisation of a Museum Mobile Guide.pdf - Accepted Version
Access restricted to UCL open access staff until 1 April 2026.

Download (54MB)

Abstract

Personalisation of museum mobile guides (MGs) has become a priority aim for enhancing visitors’ experiences of museums. Since users of an MG are typically first-time users and since their usage is for a relatively short session, personalisation should use initial interaction data to associate the user with a particular persona category and thereby infer other facts about the user’s preferences and needs. Using this approach 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. This thesis contributes to the categorisation approach to user modelling and to the application of that approach to digital MGs. Five studies were conducted to achieve this aim involving 878 participants. In study 1, a face-to-face questionnaire survey of 105 museum visitors investigated the main facts required to identify a visitor persona and explored the preferences of different visitor personas for particular MG features. It was found that visitor persona could be reliably identified using multiple choice questions concerning the two factors of visit motivation and perceived success criteria. Characteristic preferences for certain features could also be associated with particular personas. Studies 2 and 3 were field studies involving visitor interaction experiences with MG interfaces and both questionnaire and observational data were collected. Study 2 (N=60) found significant correlations between different personas and their preferences for particular features. Study 3 (N=118) examined the experience of visitors using a personalised MG and investigated whether their preference for one of three alternative MG interfaces matched their persona. Study 4 focused on users’ preferences for the design of content of the MG. The study was conducted using an online questionnaire (N=260) where participants were given a scenario and asked to imagine visiting a museum and using an MG. Study 5 (N=335) evaluated summatively the use of motivation and perceived visit success criterion questions to identify a visitor’s persona as well as primary preferences results from the prior research. It also investigated personas preferences of other MG features including presentation form, menu and venue navigation tools. The study paradigm attempted to realistically represent the experience of visiting a museum, including navigating between exhibits, choosing which exhibits to see and viewing several exhibits. The behaviour of people in exploring the exhibit and using the MG has been explored in the first four studies at different levels and found differences among personas. These studies taken together indicate that it is possible to identify a museum visitor’s persona using simple MCQs and to provide them with an interface variant they are likely to prefer according to their persona; they show that the experiences of different visitors using different variant interfaces are equally good.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: User Modelling with Personas and the Personalisation of a Museum Mobile Guide
Language: English
Additional information: Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10188674
Downloads since deposit
3Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item