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University of Ontario Institute of Technology

Vixen: a games user research tool for collection and interactive visualization of usertesting data

Abstract

dc:description.abstract

Visualization techniques can facilitate the understanding and exploration of relationships in usertesting data. For example, data from players' in-game movement can be combined with interview data or questionnaire results. However, the process of amalgamation is not straightforward, because the underlying data often exists in different formats. Another challenge is making these visualizations simple enough to provide a quick overview for producers, but also detailed enough to be usable and practical for gameplay programmers. Hence, there is a need for an interactive visualization tool that can adjust data representation based on the nature and detail level of data required from different members of a development team. This thesis reports development efforts on a tool that assists data collection and provides a dynamic and interactive representation of usertesting data. The thesis reports two studies to evaluate the effectiveness of the tool with game developers.

Degree

thesis:*
Name thesis:degree_name
Master of Science (MSc)
Discipline thesis:degree_discipline
Computer Science
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Drenikow, Brandon
Advisor dc:contributor.advisor
  • Mirza-Babaei, Pejman

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/829
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/829

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Drenikow, Brandon. Vixen: a games user research tool for collection and interactive visualization of usertesting data. University of Ontario Institute of Technology, 2017. https://hdl.handle.net/10155/829