Clustering on Player Types of Students in Health Science - Trial and Data Analyses.

Abstract

Gamification has many positive effects, such as increased motivation, engagement, and well-being of users. For this purpose, a wide field of game mechanics is already available that can be used in teaching. For the development of gamified teaching methods, it's important to adapt the mechanics used to the students. There are different models that divide target groups of games and gamification into player types to understand what motivates the respective users. This paper describes a study of player types among students of health-related disciplines and analyses the data by a K-Means clustering procedure. The player types Socializer, Player and Achiever are found, and game elements for this groups are suggested. Thus, in the field of health education, game mechanics can be used, which are suitable for students of this domain.