Please use this identifier to cite or link to this item: https://zone.biblio.laurentian.ca/handle/10219/3972
Title: Gender human-computer interaction: investigating the perceived credibility of mobile applications from gendered perspective
Authors: Randhawa, Gulnaz Kaur
Keywords: Inclusive design;gender bias;user-experience;gender stereotypes
Issue Date: 4-Nov-2021
Abstract: Consumer market has witnessed remarkable shift from designer’s preferences to what actual users want. Not only has this led to hike in market profit but also resulted in products with enhanced User-Experience. In the field of HCI, designers have been working to make their end products usable to large group of users belonging to different ages, gender as well as techsavvy and non-computer literates. Considering ‘gender’, much research has been done and is still being conducted to explore its’ relevance to Human-Computer Interaction. This research addresses the researcher’s vision to identify gender differences in User-Experience received from using mobile applications. The idea isto experimentally prove whether there exists samegender or opposite gender credibility in rating the usability of mobile applications. If no statistically significant differences are noted in male and female respondents’ respective ratings of applications from male and female designer, then null hypothesis will be accepted. This would imply that UI designers did not target users of any particular gender during the design phase thereby producing gender-inclusive designs. On the contrary, if differences are found then alternate hypothesis shall be accepted which will be an indication of gender bias being propagated in designs. Data collected from 30 participants (15 males and 15 females) showed no statistically significant differences in the ratings of male and female designer’s interfaces. Future research has been proposed with greater sample size along with additional test variants such as virtual gendered avatars.
URI: https://zone.biblio.laurentian.ca/handle/10219/3972
Appears in Collections:Computational Sciences - Master's theses

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