SAGE: A dataset for Smart Adaptive Gamified Education

Abstract

Gamification design in education is the process of planning gamification strategies aligned with educational needs. However, the literature states that generating those strategies is not trivial, and it requires a lot of effort from gamification designers and educators due to the large number of game elements, especially since some of these elements are defined in confusing or misleading ways, context specificities in the teaching-learning processes, and the interaction between them. Based on this premise, this paper presents the design and data collection of a dataset composed of 1929 items (line entries in the dataset). This dataset was made through a survey data that went through a data filtering process and can be used to support tailored gamified tools or AI-based tools (e.g., recommendation systems) for educational environments, based on students’ profiles and favorite game elements.