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Planning Gamification Strategies Based on User Characteristics and DM: A Gender-Based Case Study

Authors :
Toda, Armando M.
Oliveira, Wilk
Shi, Lei
Bittencourt, Ig Ibert
Isotani, Seiji
Cristea, Alexandra
Source :
International Educational Data Mining Society. 2019.
Publication Year :
2019

Abstract

Gamification frameworks can aid in gamification planning for education. Most frameworks, however, do not provide ways to select, relate or recommend how to use game elements, to gamify a certain educational task. Instead, most provide a "one-size-fits-all" approach covering all learners, without considering different user characteristics, such as gender. Therefore, this work aims to adopt a data-driven approach to provide a set of game element recommendations, based on user preferences, that could be used by teachers and instructors to gamify learning activities. We analysed data from a novel survey of 733 people (male=569 and female=164), collecting information about user preferences regarding game elements. Our results suggest that the most important rules were based on four (out of nineteen) types of game elements: Objectives, Levels, Progress and Choice. From the perspective of user gender, for the female sample, the most interesting rule associated Objectives with Progress, Badges and Information (confidence=0.97), whilst the most interesting rule for the male sample associated also Objectives with Progress, Renovation and Choice (confidence=0.94). These rules and our descriptive analysis provides recommendations on how game elements can be used in educational scenarios. [For the full proceedings, see ED599096.]

Details

Language :
English
Database :
ERIC
Journal :
International Educational Data Mining Society
Publication Type :
Conference
Accession number :
ED599208
Document Type :
Speeches/Meeting Papers<br />Reports - Research