Star Salvager: A Remote Games User Research Toolkit for Small Teams

As Games User Research (GUR) becomes a mature and essential pillar of game development, the challenges of performing rigorous qualitative and quantitative research in small teams are exacerbated by the disruption caused by the 2020 COVID-19 pandemic. Research methods such as heuristic evaluation, think-aloud usability testing, initial experience testing, playthrough observation, and post-launch data analysis are taught as industry-standard in GUR courses. And they yield important insights on game usability, balance, learnability, and accessibility. However, many of these GUR methods require resources, staff, and lab space beyond the reach of small game developers. Such teams may struggle to perform a useful spread of research activities due to limited timelines and funds, while ad hoc, casual playtests are more difficult to perform while working remotely.
The objective of this project is to create, test, and refine remote-friendly versions of three key GUR approaches: think-aloud usability testing, full playthrough observation, and game balance telemetry. Our research aims to assess the effectiveness of each method variant in yielding actionable insights, and to document the challenges encountered when deploying them under a triforce of unfavourable conditions: a small team conducting remote research with significant time and budgetary constraints.

Intern: 
Chu Li
Faculty Supervisor: 
Anthony Tang;Velian Pandeliev
Province: 
Ontario
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