Um estudo sobre a tipologia de usuários Hexad e sua relação com os elementos de jogos de uma plataforma de gamificação baseada em jogos RPG

Abstract

In recent years, several studies have emerged related to the use of games and gamification in education, due to the potential to increase student motivation and engagement in disciplines. However, each individual is motivated differently and has preferences when it comes to using game elements. Therefore, it is important to identify the user types in games and gamified systems, so that it is possible to provide the most suitable elements for each profile and improve the experience within the environment in question. In the literature, there are some typologies that divide the profiles by classes and point out which elements are preferred by each type of user. One of these typologies is the Hexad model, which covers six types: philanthropists, free spirits, players, disruptors, socializers and achievers. This master's thesis has as its main objective to evaluate the game elements most used by the types of users within the CodePlay gamification platform, which is incorporated into the CodeBench online judge; evaluate the feasibility of automatic profile identification based on platform interaction data; and, evaluate the profile change over time. The research methodology addressed is the multimethod, as different quantitative analyzes of an exploratory nature were carried out to investigate aspects related to gamification and types of player. Some results were: i) some differences were found in relation to the preference of player types according to the literature, for example, the player was not so interested in extrinsic rewards and the achiever was interested in elements of competition; ii) new findings were found regarding the change of profile over time, which are in line with recent studies in the area, such as the predominance of the achiever, free spirit and philanthropist types, in addition, new studies that indicate that the achiever type tends to change to the philanthropist type and the main changes happened after the first contact with gamification; and, iii) low accuracy was found in the machine learning models, which may have been influenced by the profile change factor over time, bringing a new perspective on the automatic identification of profiles based on taxonomies such as Hexad. The studies carried out open space for new research possibilities within the area of user personalization.