Identifying Player Types to Tailor Game-Based Learning Design to Learners: Cross-sectional Survey using Q Methodology

Abstract

Background Game-based learning appears to be a promising instructional method because of its engaging properties and positive effects on motivation and learning. There are numerous options to design game-based learning; however, there is little data-informed knowledge to guide the choice of the most effective game-based learning design for a given educational context. The effectiveness of game-based learning appears to be dependent on the degree to which players like the game. Hence, individual differences in game preferences should be taken into account when selecting a specific game-based learning design. Objective We aimed to identify patterns in students’ perceptions of play and games—player types and their most important characteristics. Methods We used Q methodology to identify patterns in opinions on game preferences. We recruited undergraduate medical and dental students to participate in our study and asked participants to sort and rank 49 statements on game preferences. These statements were derived from a prior focus group study and literature on game preferences. We used by-person factor analysis and varimax rotation to identify common viewpoints. Both factors and participants’ comments were used to interpret and describe patterns in game preferences. Results From participants’ (n=102) responses, we identified 5 distinct patterns in game preferences: the social achiever, the explorer, the socializer, the competitor, and the troll. These patterns revolved around 2 salient themes: sociability and achievement. The 5 patterns differed regarding cheating, playing alone, story-telling, and the complexity of winning. Conclusions The patterns were clearly interpretable, distinct, and showed that medical and dental students ranged widely in how they perceive play. Such patterns may suggest that it is important to take students’ game preferences into account when designing game-based learning and demonstrate that not every game-based learning-strategy fits all students. To the best of our knowledge, this study is the first to use a scientifically sound approach to identify player types. This can help future researchers and educators select effective game-based learning game elements purposefully and in a student-centered way.

Student Player Types in Higher Education—Trial and Clustering Analyses

“…The consequence of this is the need to create educational games that dynamically adapt to the lecture content. It should also be noted that a game should be adapted to player types in order to achieve a positive effect [11].…”

“…Based on Bartle's model, Gaalen et al [11] conducted a study among medical and dental students using the Q-methodology. Participants were asked to sort 49 statements about gaming preferences based on their level of agreement.…”

The Effect of Game-based Learning on Student’s Conceptual Change in Bioaccumulation and Biomagnification

“…GBL is a kind of gameplay that has explicit learning objectives (Plass et al, 2015). The potential of GBL as an effective instructional method is promising due to its ability to captivate learners and positively impact their motivation and learning outcomes (Budasi et al, 2020;Loderer et al, 2019;Steinkuehler and Squire, 2014;Van Gaalen et al, 2022). Plass et al (2015) suggested a theoretical basis for incorporating games into the learning process that involved motivational, cognitive, affective, and sociocultural foundations.…”

A Systematic Mapping on Player’s Profiles: Motivations, Behavior, and Personality Characteristics

“…As recent research indicates, the effectiveness of serious games appears to be correlated to the degree to which play ers like the game (Van Gaalen et al, 2022). Hence, using a player classification in the games user research can help game designers to identify more clearly interpretable patterns and show how players perceive play to design more com pelling games.…”

“…Some re searchers have even searched for typological classifications in other areas, such as Psychology, Anthropology, and Soci ology, that can be used to understand the players' profiles (Paulin, 2013). More recently, researchers have started in vestigating scientifically sound approaches to identify player types, demonstrating that game effectiveness may be corre lated to player types (Van Gaalen et al, 2022).…”