Detecting playfulness in educational gamification through behavior patterns

4 Games are not a new concept in learning. Game-based 5 learning, simulations, and serious games are known pedagogical 6 methods used to build on the inherent playfulness of learners. 7 Technological advances and the popularity of learning 8 management systems are making it easier to implement 9 gamification, analyze the resulting engagement and playfulness, 10 and modify the implementation if needed. However, knowledge 11 is often missing about how different combinations of game 12 mechanics and dynamics create playfulness. We discuss the 13 concept of gamification behavior patterns, which are sequences 14 of actions performed by a user that can be attributed to the 15 application of a gamification design pattern. A preliminary 16 experiment was conducted in an academic course where perceived 17 playfulness was analyzed with respect to three different sets of 18 independent variables: personality, perceived enjoyment from 19 game mechanics, and gamification behavior patterns. Results 20 show that it is practical to measure gamification behavior patterns 21 and that they have a significant predictive power. We propose 22 the development of an open-source, cloud-based gamification 23 behaviors database that will collect specific gamification 24 engagement events from systems worldwide, along with metadata 25 about each implementation. With such a database, Big Data, 26 machine-learning, and recommender-system algorithms can be 27 applied to increase knowledge regarding steering user behaviors 28 through gamification.