Generating data proxies for playground play and visit duration for use in predictive modeling - BC-398
Preferred Disciplines: Primary: Data science / Predictive modeling / Data visualization; Secondary: Child-computer interaction / Urban planning (Masters, PhD or Post-Doc)
Project length: 8-12 months (2 units)
Approx. start date: As soon as possible
Location: Vancouver, BC
No. of Positions: 3
Preferences: SFU or UBC
In our mission to get today’s screen-savvy kids back outdoors and active, we have created a suite of mobile games that are specifically designed to work with the equipment found in your neighbourhood playground. Our research shows that kids in a Biba-powered playground will play longer, harder and much more often! Our secondary mission: our Biba-powered games help provide communities with critical data about how their playground spaces are used as to make them better for the families who enjoy them. Working with PlayPower Inc – the world’s leading manufacturer of playgrounds and recreational equipment – more than 2500 Biba playgrounds are already active in cities across North America and beyond.
Summary of Project:
The Challenge: Currently, our company tracks playground play and park visitation through a suite of mobile games used by families in playgrounds. However, we only know what play looks like through the lens of these games—we currently have no comparative empirical data that can tell us how gameplay in our mobile games actually reticulates to a family’s total profile of on-site activity.
The Approach: Our aim is to conduct on-site, event-driven, observational research of key Biba sites in cities across North America to learn more about how families are using playgrounds on-the-ground by leveraging a variant of the SOPARC data collection instrument. This will help us learn about playground usage through a filter of time of day, on-site visitation and so forth.
The Objective: Collection of this type allows us to perform a comparative analysis that works towards the generation of reliable operational heuristics and approximations around location activity where Biba games are played. This lets us inform a generative, predictive model that can speak to the ostensible activity taking place in parks all over the world, be it Biba enabled or not.
- To be determined
SOPARC Research Instrument: SOPARC is a validated direct observation tool for assessing park and recreation areas, including park users’ physical activity levels, gender, activity modes/types, and estimated age and ethnicity groupings. It also collects information on park activity area characteristics (e.g., accessibility, usability, supervision, and organization)
Expertise and Skills Needed:
- Data analysis
- Predictive modeling
For more info or to apply to this applied research position, please