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Generation of educational content through gameplay

Language learning games require large quantities of content to be educational. This paper presents a boot-strapping method to generate game content using a combination of existing digital resources and the human computation of game players themselves. It describes a baseline method for hint generation to be used in a two-player game in which players select hints to assist each other. It then shows that the data gathered from player actions contains significant agreement in evaluation of automatically generated content. The quality of this data is verified against data from tasked-based crowdsourcing. Results demonstrate that this type of data may be used to extend and improve the hint generation method.