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

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.

Gamification of health professions education: a systematic review.

Gamification refers to using game attributes in a non-gaming context. Health professions educators increasingly turn to gamification to optimize students' learning outcomes. However, little is known about the concept of gamification and its possible working mechanisms. This review focused on empirical evidence for the effectiveness of gamification approaches and theoretical rationales for applying the chosen game attributes. We systematically searched multiple databases, and included all empirical studies evaluating the use of game attributes in health professions education. Of 5044 articles initially identified, 44 met the inclusion criteria. Negative outcomes for using gamification were not reported. Almost all studies included assessment attributes (n = 40), mostly in combination with conflict/challenge attributes (n = 27). Eight studies revealed that this specific combination had increased the use of the learning material, sometimes leading to improved learning outcomes. A relatively small number of studies was performed to explain mechanisms underlying the use of game attributes (n = 7). Our findings suggest that it is possible to improve learning outcomes in health professions education by using gamification, especially when employing game attributes that improve learning behaviours and attitudes towards learning. However, most studies lacked well-defined control groups and did not apply and/or report theory to understand underlying processes. Future research should clarify mechanisms underlying gamified educational interventions and explore theories that could explain the effects of these interventions on learning outcomes, using well-defined control groups, in a longitudinal way. In doing so, we can build on existing theories and gain a practical and comprehensive understanding of how to select the right game elements for the right educational context and the right type of student.

[Assessing the quality of the medical learning environment, comparison of two validated Dutch questionnaires]. / Meten van de kwaliteit van de medische leeromgeving.

- Assessing the quality of the medical learning environment is an important part of the quality cycle of postgraduate medical education programmes.- The quality of the medical learning environment is primarily assessed by systematically documenting the experiences of doctors-in-training (residents).- For this purpose, several questionnaires have been developed, two of which have been specifically developed for use in the Dutch clinical learning environment.- D-RECT is a commonly-used, 50-item questionnaire (11 subscales), developed from qualitative research on the optimal learning environment for ObGyn residents.- SPEED ('Training Thermometer') is a recently developed 15-item, 3-domain (i.e., content, atmosphere and organisation of training) instrument, based on a generic theoretical framework of human interaction.- Both D-RECT and SPEED are validated instruments to be used to reliably assess the clinical learning environment for Dutch residents in postgraduate medical education programmes.

Open-book tests to complement assessment-programmes: analysis of open and closed-book tests.

Today's health sciences educational programmes have to deal with a growing and changing amount of knowledge. It is becoming increasingly important for students to be able to use and manage knowledge. We suggest incorporating open-book tests in assessment programmes to meet these changes. This view on the use of open-book tests is discussed and the influence on test quality is examined. To cope with the growing amount of medical knowledge, we have divided the body of knowledge into core knowledge, which students must know without need for references, and backup knowledge, which students need to understand and use properly with the help of references if so desired. As a result, all tests consist of a subtest for reproduction and understanding of core knowledge (a closed-book test) and a subtest for the ability to understand and manage backup knowledge (an open-book test). Statistical data from 14 such double-subtest exams for first and second-year students were analyzed for two cohorts (N = 435 and N = 449) with multilevel analysis, in accordance with generalizability theory. The reliability of the open and closed-book sections of the separate tests varied between 0.712 and 0.850. The open-book items reduce reliability somewhat. The estimated disattenuated correlation was 0.960 and 0.937 for cohorts 1 and 2 respectively. It is concluded that the use of open-book items with closed-book items slightly decreases test reliability but the overall index is acceptable. In addition, open and closed-book sections are strongly positively related. Therefore, open-book tests could be helpful in complementing today's assessment programmes.