Big Data Reduction: Lessons Learned from Analyzing One Billion Dota 2 Matches

The availability of large datasets of player choices in popular online computer games presents an opportunity to identify sudden changes in choice patterns and explore what factors may contribute to such changes. However, the size and scope of large datasets raises big data reduction problems. This study uses a large dataset of over one billion games played in the online computer game Dota 2 as a starting point to examine possible solutions applicable to individual researchers with limited computational resources

Revitalizing an Indigenous Language: I Have an App For That!

This study examined the effect of using two apps to teach the Secwepemctsin language to a group of elementary school children (N =90). Children from K-7 were divided into two conditions: (a) learning vocabulary related to clothing with the language teacher and (b) learning the same content by playing with apps designed for the purposes of this study. Over a period of two weeks, each group had the opportunity to be taught by the teacher or the app during 15-20 minutes two times on different days. At the end of the lesson on the second day, children were tested on their learning using a multiple-choice vocabulary test. To identify further learning, all participants were tested a second time a couple of days later. The main purpose of this study was to identify whether using digital technology such as apps can enhance Indigenous language learning. Currently there are less than 1000 fluent speakers of Secwepemctsin; therefore, insights form this study will make a valuable contribution to the community efforts to revitalize the language