This project examines exergame enjoyment in order to find clusters of exergames that produce similar enjoyment. First, the team developed a classification system to group exergames together. Following that, data was gathered through experimentation, where participants played exergames and had values of their enjoyment recorded for each exergame played. The strongest relationship between classifications, according to a resulting relationship network, was between Control-Adventure and Control-Action, and so both classifications produced similar measured enjoyment. Finally, the gathered data was put to use in a functioning recommender system that recommended users exergames that they have not played. This developed recommender system returned accurate recommendations 83% of the time.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Bearce, Christopher Everett
• Scuzzarella, Brad Thomas
• Qin, Antony Erdong

Subject

• Culture
• Health

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-032318-155833

Palavra-chave

• Video games
• Public health

Advisor

• Agu, Emmanuel O.
• Claypool, Mark L.

Year

• 2018

Date created

• 2018-03-23

Localização

• Worcester

Resource type

• Interactive Qualifying Project

Rights statement

• In Copyright