Turning Difficult Scientific Problems into Easy Games: Crowdsourcing Solutions via Gamification
The aim of the research is to exploit, on a large scale, the idea introducing game elements in a non-game context (gamification) and make use of a large population of non-expert users to solve scientific problems (crowdsourcing). The proposed research follows the increasingly popular concept of splitting a large, complex task into small easily digestible tasks that lend themselves to division, distribution and game representation.
This research will begin by taking advantage of the University of Essex’s expertise in the field of Natural Language Engineering. Multiple games will be created to attempt to encourage people to participate in training natural language models. This will be achieved by splitting these tasks into smaller problems that can be represented as games, and easily solved by players that could not easily be solved computationally. Alongside this, the success of different gamification methods and game design choices will be evaluated to determine their effect on the information gathered and the accuracy achieved. This evaluation will be used to guide the development of future games in the research with a view to producing better quality models for solving natural language problems, and improving gamification.
Prior to starting my PhD with IGGI I completed a BSc in Computer Science and MSc in Advanced Computer Science. During both of those I took multiple computer game and AI courses in addition to text analytics and natural language engineering courses. During my BSc I was fortunate to work at Signal Media as an intern on text analytics related problems. Before starting my BSc I worked as a software developer for 5 years, primarily in web application development. I’ve had a passion for games from a very young age and continue to play on PC, mobile and consoles today.
Home institution: Queen Mary
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