Gamification has been widely used to design better educational systems aiming to increase students’ concentration, motivation, engagement, flow experience, and others positive experiences. With advances in research on gamification in education, over the past few years, many studies have highlighted the need to tailor the gamification design properties to match individual students’ needs, characteristics and preferences. Thus, different studies have been conducted to personalize the gamification in education. However, the results are still contradictory and need to be better understood to advance this field. To provide a complete understanding of this research domain, we conducted a systematic literature review to summarize the results and discussions on studies that cover the field of tailored gamified education. Following a systematic process, we analysed 2108 studies and identified 19 studies to answer our research questions. The results indicate that most of the studies only consider students’ gamer types to tailor the systems, and most of the experiments do not provide sufficient statistical evidence, especially regarding learning performance using tailored gamified systems. Based on the results, we also provided an agenda with different challenges, opportunities, and research directions to improve the literature on tailored gamification in education. Our study contributes to the field of gamification design in education.

Gamification refers to the attempt to transform different kinds of systems to be able to better invoke positive experiences such as the flow state. However, the ability of such intervention to invoke flow state is commonly believed to depend on several moderating factors including the user’s traits. Currently, there is a dearth of research on the effect of user traits on the results of gamification. Gamer types (personality traits related to gaming styles and preferences) are considered some of the most relevant factors affecting the individual’s susceptibility to gamification. Therefore, in this study we investigate how gamer types from the BrainHex taxonomy (achiever, conqueror, daredevil, mastermind, seeker, socializer and survivor) moderate the effects of personalized/non-personalized gamification on users’ flow experience (challenge-skill balance, merging of action and awareness, clear goals, feedback, concentration, control, loss of self-consciousness andautotelicexperience), enjoyment, perception of gamification and motivation. We conducted a mixed factorial within-subject experiment involving 121 elementary school students comparing a personalized version against a non-personalized version of a gamified education system. There were no main effects between personalization and students’ flow experience, perception of gamification and motivation, and enjoyment. Our results also indicate patterns of characteristics that can lead students to the high flow experience (e.g., those who prefer to play multiplayer have a high flow experience in both personalized and non-personalized versions). Based on our results, we provided recommendations to advance the design of gamifed educational systems.

Gamification has been discussed as a standout approach to improve user experience, with different studies showing that users can have different preferences over game elements according to their user types. However, relatively less is known how different kinds of users may react to different types of gamification. Therefore, in this study ( $$N=331$$N = 331 ) we investigate how user orientation (Achiever, Disruptor, Free Spirit, Philanthropist, Player, and Socializer) is associated with the preference for and perceived sense of accomplishment from different gamification designs. Beyond singular associations between the user orientation and the gamification designs, the findings indicate no comprehensive and consistent patterns of associations. From the six user orientations, five presented significant associations: Socializer orientation was positively associated with Social, Fictional, and Personal designs, while negatively associated with Performance design; Player orientation was positively associated with Social (Accomplishment), Personal, and Ecological designs, while negatively associated with the Social design (Preference); Disruptor orientation was positively associated with Social design; Achiever orientation was positively associated with Performance and Social designs; and Free Spirit orientation was negatively associated with Social design. Based on the results, we provide recommendations on how to personalize gamified systems and set further research trajectories on personalized gamification.

Personalized gamification explores user models to tailor gamification designs to mitigate cases wherein the one-size-fits-all approach ineffectively improves learning outcomes. The tailoring process should simultaneously consider user and contextual characteristics (e.g., activity to be done and geographic location), which leads to several combinations to tailor. Consequently, tools for automating gamification personalization are needed. However, which of those characteristics are relevant and how to do such tailoring are open questions. Furthermore, the required automating tools are lacking. We tackled these problems in two steps. First, we conducted an exploratory study, collecting participants' opinions on the game elements they consider the most useful for different learning activity types (LAT) via survey. Then, we modeled opinions through Conditional Decision Trees to address the aforementioned tailoring process. Second, as a product of the first step, we implemented a recommender system that suggests personalized gamification designs (which game elements to use), addressing the problem of automating gamification personalization. Our findings present empirical evidence that LAT, geographic locations, and other user characteristics affect users' preferences, enable defining gamification designs tailored to user and contextual features simultaneously, and provide technological aid for those interested in designing personalized gamification. The main implications are that demographics, game-related characteristics, geographic location, and LAT to be done, as well as the interaction between different kinds of information (user and contextual characteristics), should be considered in defining gamification designs and that personalizing gamification designs can be improved with aid from our recommender system.

Flow Theory has been increasingly applied to Computers and Education to address several topics within this field (e.g., motivation, engagement, learning performance and so on). At the same time, in comparison with other recent theories related to Computers and Education, (e.g., Self-Determination Theory, S-Curve Theory, Intrinsic motivation, etc.), is a young topic, with different open research questions. Additionally, the Computers and Education community still lacks a comprehensive understanding of how Flow Theory is used in the area. Thus, this paper presents a Systematic Literature Review aiming to identify how students' flow state are measured during learning activities, how such activities are designed, which are the flow models used in Computers and Education and which are the main benefits of being in the flow state for the students. The main findings of this work are: (1) there is positive evidence about the benefits of applying Flow Theory in Computers and Education, especially, for increasing students’ learning, to generate students’ satisfaction, and to enable exploratory behavior; (2) the majority of studies use questionnaires to manual identify students’ flow state; (3) a great diversity of flow state scales have been used; (4) the majority of studies are not designing activities for leading students to the flow state, and (5) the Csikszentmihalyi’ flow model is more used. Finally, we conclude this work by showing some promising and interesting research opportunities that are underexplored in current research and practice.

Recent research has shown that using gamification can prone to impact negatively on the motivation of students in educational systems. One of the reasons is that people are motivated or demotivated by different gamification elements according to their "gamer type". Thus, one of the main challenges in this field is to tailor gamified educational systems based on the students' "gamer type" and investigate if this kind of system presents better results than the counter-tailored gamified educational systems. This paper aims to investigate the effects of a tailored gamified educational system based on gamer type in terms of students' flow experience. We conducted an experiment with 121 Brazilian elementary school students comparing a tailored version against a counter-tailored version of a gamified educational system in terms of students' flow experience. The main results indicate that there is no significant difference in terms of students' flow experience, surprising and contradicting recent important studies in this field.