Data set characteristics
When analysing the data, the researchers came across some interesting characteristics. Other than the meta-analytic studies and review research, the locations of the remaining surveys are as follows: 33% conducted in Europe, 22% in Asia, and 18% in the USA, whereas 24% of the articles do not directly mention a location (Fig. 4). Most of the articles come from the USA, the UK, and the Netherlands.
With respect to genre, there is a diverse representation of games and simulations. The most prominent game genre identified in the relevant literature seems to be simulation games in general, that is to say, virtual/online games or simulations, computer-based learning, role-playing games, serious games, and business simulation games. This representation is illustrated below (Fig. 5):
With respect to the busiest publication period, the majority of studies that meet the inclusion criteria were published between 2013 and 2016, as shown in the following bar chart (Fig. 6). This finding demonstrates a notable trend amongst researchers discussing the topic of games and simulations in recent years, due to increased awareness of the use of technological games in higher education.
The data also represents a wide range of subject areas. Some cover multiple areas, for example Engineering, Management, Science, Law, Social Sciences and Humanities (Tao et al., 2015), or even just two areas, such as Biology and Computer Sciences (Yang & Chang, 2013), while others refer to only one academic discipline. The subject areas are sorted into larger categories, with the most common area being Business Management and Marketing. The results are shown in the figure below (Fig. 7):
The reviewed articles include data from 99 samples and 20,406 participants, which is a considerably large grouping. The population tested in the literature review ranges from 5 participants in small qualitative studies (Ke et al., 2015) to 5071 participants in extensive quantitative quasi-experimental research (Lu et al., 2014). Most of the participants are young undergraduate, graduate or post-graduate students, and faculty members. The studies consistently indicate a good gender balance in participants. In some studies, there is both student and faculty participation (Kapralos et al., 2011; Felicia, 2011; Hess & Gunter, 2013; Hämäläinen & Oksanen, 2014; Beuk, 2015; Crocco, 2016), whereas in others, only instructors are chosen as participants (Tanner, 2012; Badea, 2015; Franciosi, 2016). On the whole, most studies use students as participants.
Procedures and research methodologies
Most studies use either an experimental or a quasi-experimental design employing a pre-test and/or a post-test evaluation, with four using only a pre-test questionnaire, and six using only post-test evaluations. The effects of games and simulations on learning outcomes are measured through calculating the difference between pre-test and post-test scores of the experimental or quasi-experimental design. More specifically, the researchers compare the increases in scores between control and experimental groups to evaluate the effectiveness of using the tested games and simulations. The studies include longitudinal surveys (e.g. Hainey, 2011) conducted for a specified number of years, whereas others are comparative studies (e.g., Boeker, 2013; Poikela, 2015).
Researchers use quantitative methods in the majority of studies (68.6%), while13.1% use qualitative methodology. Some studies follow a mixed research methodology (nearly 18.2%), providing pragmatic perceptions and methodological triangulation of the results. The measures utilized in quantitative studies include knowledge questionnaires, as well as academic, evaluation, and cognitive tests, while in qualitative studies the methods used include interviews, case studies, observations and focus groups.
The studies portray a variety of time periods spent playing games and simulations: some of the participants interact with games over a single session, while others are involved in the gaming process for several weeks or even months (e.g., Yang & Chang, 2013; Woo, 2014). The studies include multi-player games (e.g., Silvia, 2012; Yin, 2013), as well as single-player games.
Learning outcomes of games and simulations
In the present review, keeping in mind the aforementioned research questions (p.3), the researchers break down their findings in relation to the learning outcomes of games and simulations into three categories, namely cognitive, behavioural, and affective outcomes. A map of the emerging concepts, which will be further discussed, is illustrated below (Fig. 8):
Cognitive outcomes
Many reviewed studies discuss the impact of GBL activities in learner knowledge acquisition and conceptual understanding (Hainey et al., 2011; Connolly et al., 2012; Fu et al., 2016; Geithner & Menzel, 2016). There has been an impact evaluation across subject disciplines, such as Computer Science (Strycker, 2016), Engineering (Chaves et al., 2015), Physics (Adams, 2016), Medicine (Dankbaar, 2016), Nursing (Sarabia-Cobo, 2016), Management (Geithner & Menzel, 2016), Political Sciences (Jones & Bursens, 2015), Education (Ke, 2015), Languages (Franciosi, 2016), and Social Sciences (Cózar-Gutiérrez & Sáez-López, 2016).
Knowledge acquisition
Cognitive outcomes refer “to the knowledge structures relevant to perceiving games as artefacts for linking knowledge-oriented activities with cognitive outcomes” (Lameras et al., 2016, p. 10). Tasks framed as games and simulations are deployed to develop a diverse range of cognitive skills, such as deep learning (Vos & Brennan, 2010; Young et al., 2012; Erhel & Jamet, 2013; Crocco et al., 2016), critical thinking and scientific reasoning (Beckem & Watkins, 2012; Halpern et al., 2012; Ahmad, 2013), action-directed learning (Lu et al., 2014), transformative learning (Kleinheskel, 2014), decision-making (Tiwari, 2014), knowledge acquisition and content understanding (Terzidou, 2012; Elias, 2014; Fu et al., 2016), spatial abilities (Adams et al., 2016), and problem solving (Liu, 2011; Lancaster, 2014).
The effect of games and simulations on learning remains a controversial issue amongst researchers in the field, as it will be further confirmed in this article. Some reviewed studies indicate improved learning, while others show no positive effect on knowledge and skill acquisition compared to traditional learning methods. The value of simulations can be examined from the perspective of content change as discussed in Kovalic and Kuo’s study (2012). Simulations are directly linked to the course content and students are given the opportunity to apply and better understand theoretical concepts. Additionally, simulations provide an environment in which students can experiment with different strategies, adopt different roles, and take charge of their own decisions by assuming responsibility. The latter issue is discussed at length by Liu et al. (2011), who find that, when solving problems, students are more likely to learn via playing a game than via a traditional learning experience.
Serious gaming, especially given the context of enthusiastic students, has proved to be an effective training method in domains such as medical education, for example, in clinical decision-making and patient interaction (de Wit-Zuurendonk & Oei, 2011). Similarly, Kleinheskel (2014) illustrates the importance of designing self-reflective simulating activities for nursing students, and aligning such design with cognitive outcomes. When students self-reflect on simulated clinical experiences, they add to their existing knowledge, and apply new knowledge to transformative learning. Poikela et al. (2015), in a simulated nursing procedure, compare a computer-based simulation with a lecture to examine the meaningful learning students may achieve via the two teaching methods. They conclude that students who participate in the computer simulation are more likely to report meaningful learning outcomes than those taking the lecture, due to the strong presence of reflection-based activities and metacognitive themes. Similar results are present in Chen, (2015), survey in which both solitary players and collaborative groups achieve equally positive learning outcomes in a game. Students significantly improve judging by their pre- and post-test assessments, which indicates that the gaming experience affects their overall performance, and, most likely, promotes conceptual understanding. Moreover, collaborative GBL allows students to re-construct and co-construct knowledge, thus encouraging problem-solving through peer discussion.
Challenging games enhance participant performance (Wang & Chen, 2010; Gold, 2016). This finding is supported by von Wangenheim, (2012), who analyse the cognitive dimension of an educational game focusing on memory, understanding and conceptual application. The validity of micro-simulation games is identified by participants in Lukosch, (2016), research who evaluate a specific microgame as an excellent instrument for enhancing situated and experiential learning by transferring knowledge to an actual situation at the workplace. The results comply with those of Riemer and Schrader (2015), where the application of comprehension and transfer of knowledge are best achieved using simulations.
Furthermore, the impact of game-based learning on learning performance has been observed by numerous researchers across diverse subjects, as reported above (Zacharia & Olympiou, 2011; Rutten et al., 2012; Beckem & Watkins, 2012; Boeker et al., 2013; Shin et al., 2015; Hou, 2015; Chen et al., 2015; Tao et al., 2015). For instance, Divjak and Tomić (2011) provide evidence that computer games impact mathematical learning, revealing the positive effect of games on student learning outcomes. Reviews by Young et al. (2012) confirm the effectiveness of using videogames on History, Languages, and Physical Education. The analysis of four experimental virtual conditions in pre- and post-test assessments reveal that virtual experimentation promotes conceptual understanding in Physics students (Zacharia & Olympiou, 2011). A 3D visualisation and simulation laboratory activity on protein structure is more effective than traditional instruction modules, as described in White, (2010), research resulting in students preferring to work with visualized simulations.
Simulation games also positively affect clinical practice situations. “The Ward”, a simulation game in Stanley and Latimer’s (2011) research proves to be an enjoyable and valuable learning tool in addressing clinical skill practice, nursing practice knowledge, critical thinking and decision-making. Vos and Brennan (2010) highlight the effectiveness of marketing simulation games, where students perceive simulations as an enjoyable learning approach, contributing to decision-making, as well as other valuable knowledge and skills, a finding consistent with Tiwari et al. (2014) survey. Swanson et al. (2011) created a rubric to measure the effectiveness of teaching strategies in nursing education. The experimental post-test assessment survey aims to evaluate the effects of three teaching strategies on the outcome of performance and retention of intervention activities, student satisfaction, self-confidence and practical educational preferences. Results reveal significantly higher retention scores compared to the first assessment, indicating that high scores in the improved rubric are related to the interactivity of the simulation scenario.
Nevertheless, it should not be taken for granted that students consistently prefer virtual learning settings to more traditional face-to-face environments (Hummel et al., 2011). Serious games concerning cognitive perceptions show varying results. For example, simulations are shown to support the comprehension and application of knowledge, albeit less effectively than quizzes and adventures (Riemer & Schrader, 2015). In Fu et al. (2016) review, despite GBL providing a motivating and enjoyable experience, there is a lack of strong evidence to show that games lead to effective learning outcomes. In some cases, there is inconsistency in student views regarding the integration of online games as a positive learning method (Bolliger, 2015). Similar views are supported by some researchers, who acknowledge students’ and educators’ hesitation towards virtual simulations and serious games, but they insist on the inclusion of games into course material, and on instructors’ familiarization with their use (Kapralos et al., 2011).
Perceptual skills
Other studies confirm the power of games and simulations in developing cognition abilities, especially in the instances of virtual simulations enhancing complex cognitive skills (Helle et al., 2011; Siewiorek, 2013), such as self-assessment (Arias Aranda, 2010), or higher-order thinking (Crocco et al., 2016). These are meta-cognitive skills, regarded as essential elements of in-depth learning. The incorporation of game mechanisms into simulations is widely recognised by researchers as beneficial, especially regarding laboratory tasks, where simulation scenarios urge students towards problem-solving and, reflection, thus achieving metacognitive outcomes (Hou & Li, 2014; Hou, 2015). Kikot, (2013) concur with the above researchers, stating that students perceive simulation-based learning (SBL) environments positively when asked to achieve dynamic learning outcomes, including thinking, interpreting, and associative skills.
Silvia (2012) also references cognitive and metacognitive outcomes derived from a multi-role simulation. The simulation helps students apply the concepts they learn in class by connecting the theoretical issues with real-world situations, thus developing their analytical skills, and through comparing different viewpoints, which leads to enhanced critical thinking. Students use the interactive nature of simulations to develop arguments, make judgements and evaluate situations. More importantly, simulations encourage students to develop self-awareness. Similarly, Cela-Ranilla, (2014) conducted a study in which students display a tendency to perform better in analytical work, such as monitoring, planning and assessment rather than in action-based work. Wouters et al. (2013), on the other hand, find serious games to be more effective in terms of learning and retention.
Learners can also actively participate in a web-based simulation to facilitate immersion and reflection, leading to deeper understanding of the content (Helle et al., 2011). A simulation framework can facilitate learning in terms of flow experience and learning strategies. Indeed, in a study conducted by Li, Cheng, and Liu (2013), the framework helps students lacking background knowledge to balance challenge and skill perceptions, while for students with average to advanced levels of knowledge, it facilitates the learning experience by either reducing the challenge perception or promoting the skill perception. Along the same lines, Pasin and Giroux (2011), analyse the mistakes students make in simulations using an empirical prototype. Results show that, although simple decision-making skills are easily acquired through conventional teaching methods, simulation games are useful tools for mastering managerial skills, such as complex and dynamic decision-making. Lin and Tu (2012) also confirm that simulations enable students to train themselves in decision-making.
Instructors’ engagement
Students are challenged to develop interpersonal, analytical and creative skills, discouraging absenteeism, feelings of boredom and reluctance, leading to academic achievement. However, simulations not only exhibit positive effects in the learning experience of the student, but, also, do so for instructors, as well, in the context of teaching experience. For academics, simulations raise the level of performance, encouraging students to be more alert and attentive during class activities (Navidad, 2013), and thus to achieve better learning outcomes. In this vein, instructors are urged to design simulations to be as challenging as possible to stimulate student interest in interacting with the simulation as well as with their peers. Felicia (2011) denotes that instructors agree with students in acknowledging the educational benefits of video games, such as an understanding of difficult concepts, improvement of spatial awareness and analytical skills, critical thinking, and problem-solving strategies. To enable them to do so, instructors emphasize the importance of clearly expressed learning goals to guide students when using simulations in an online instructional technology course (Kovalik & Kuo, 2012).
Even setting aside the potential learning benefits derived from participation in GBL, a stronger connection between games and curricula remains to be forged, as well as the application of more dynamic academic challenges, so as to better adapt to the knowledge of diverse learners (Pløhn, 2013). Following such reasoning, as indicated in the literature, faculty plays a key role in achieving learning goals via the use of games and simulations. The instructor role correlates with the demand for abstract learning concepts. In their meta-analysis, Wouters and Van Oostendorp (2013) show how instructors, acting in a facilitating and supporting role, can foster learning, particularly in selecting and discussing new information and where higher order skills are involved in the learning outcomes. Similarly, instructors can monitor student behaviour and evaluate not only the capabilities, but also the attitudes of tomorrow’s higher education managers during the decision-making process. Rutten et al. (2012) focus in their literature review on the level of instructional support in GBL, and suggest that a pedagogical framework for the application of computer simulations in education requires a corresponding integration of the educator’s role.
Behavioural outcomes
Behavioural objectives for higher education students refer to the enhancement of teamwork and improvement in relational abilities (Ranchhod, 2014), as well as stronger organisational skills, adaptability and the ability to resolve conflicts (Vos & Brennan, 2010).
Social skills/teamwork
Simulation games are often seen as powerful tools in promoting teamwork and team dynamics (Stanley & Latimer, 2011; Tiwari et al., 2014; Lin, 2016; Wang, 2016), collaboration (Hanning, 2012), social and emotional skills (Ahmad et al., 2013), and other soft skills, including project management, self-reflection, and leadership skills (Siewiorek, 2012; Wang et al., 2016), which are acquired through a reality-based scenarios with action-oriented activities (Geithner & Menzel, 2016).
In a Spanish management course, simulations enabled students to build pivotal capacities, such as management abilities and team working to enable the success of future managers (Arias Aranda et al., 2010). A computer simulation at a university in Taiwan led to comparatively higher learning gains against traditional teaching through collaborative laboratory activities (Shieh, 2010), by facilitating students to carry out more active learning and improving their conceptual understanding. Simulation scenarios provide improved social and communication skills, which lead to the enhancement of student knowledge (Sarabia-Cobo et al., 2016).
Additionally, collaboration is considered an essential element in the learning process (Elias, 2014). The findings of Hummel et al. (2011) reveal that serious online games improve the quality of learning when it comes to problem-based situations in the workplace by using active collaboration. For this reason, faculty members are urged to create learning environments to support active participation by students in the educational process. Moreover, according to the constructivist approach, the instructor’s role is a significant factor in empowering groups to construct knowledge in a collaborative manner (Hämäläinen & Oksanen, 2014). The instructors engage higher education students in the process of formulating hypotheses, interpreting context, providing explanations, and describing observations, by designing and implementing a collaborative and interactive GBL environment. In Yin et al.’s study (2013), students react positively to participatory simulations, due to the belief that the system helps them advance their conceptual understanding effectively through scaffolding, discussion, and reflection. Participants in Cózar-Gutiérrez and Sáez-López’s study (2016), while stating that video games are non-essential tools in an educational context, nevertheless, value GBL as an immersive environment that facilitates increased activity and student engagement.
Teamwork, however, seems to be a controversial issue in Costa, (2014) which evaluates improvement of knowledge sharing. Some learners consider teamwork as a means to facilitate decision making in a game, while others express dissatisfaction due to their peers, be it the latter’s reluctance to take on responsibility or poor negotiation capabilities. Research by Bolliger et al. (2015) similarly indicates that some learners remain hesitant, as they feel the use of games may actually decrease opportunities for communication with peers and instructors. Merchant et al. (2014) conclude that student performance is enhanced when playing individually rather than in a group.
Interaction and feedback
In GBL methods, meaningful feedback is a key factor in students achieving the objectives, as well as in being encouraged to reflect on misunderstandings and to transfer learning to new educational contexts (Swanson et al., 2011). In the current study, the scope is to investigate learner-learner interaction and social feedback through game mechanics. Higher education students evaluate games and simulations focusing on behavioural change and improvement of interactive abilities. The computer game DELIVER! for example, is evaluated very positively by students due to its focus on active student participation and overall positive impact on social interaction (von Wangenheim et al., 2012). Simulations provide visual feedback, encouraging active exploration of the student’s own understanding, enabling a move beyond knowing-in action and beginning to reflect-on and in-action during training, resulting in the contextual application of prior knowledge (Söderström, 2014). Real-time feedback in simulation games enables students to clearly define the objectives and expectations in the interactive environment, leading to a reduction in anxiety and uncertainty, thus encouraging better performance (Nkhoma et al., 2014).
The literature extensively documents the interaction between behavioural outcomes, learning performance and communication especially in Online Distance Learning (ODL). Indeed, regular feedback on student performance during DGBL facilitates deep learning (Erhel & Jamet, 2013). A survey conducted by Chen, (2010) shows that online games can be social and interactive technologies, helping students form friendships with their peers and providing multiple types of interaction.
Ke et al. (2015) stress the importance of player interaction, indicating that the inherent interaction between players and their gaming-situated learning environment supplies structured challenges and feedback. Huang, (2010) share the same view, confirming that, due to the necessity of receiving feedback from peers and the game itself, increased interaction opportunities arise in game-play, adding that interaction is a decisive factor in the construction of knowledge (Seng & Yatim, 2014). In a survey conducted by Denholm et al. (2012), students report improved team working through the use of serious games. They attribute this to receiving feedback, and stressing that even conflict is often considered valuable as it brings diverse views to the fore.
To conclude, the main body of literature explores the impact of games and simulations on learning outcomes on the behavioural level, especially when students are involved in interactive and participatory simulation tasks. The majority of studies reveal a positive effect on behavioural outcomes, concluding that students benefit from appropriate feedback, and reflection through game-based communication activities.
Affective outcomes
Many studies highlight the affective outcomes of using games and simulations in the learning process. The majority of them includes student engagement (Auman, 2011; Hainey et al., 2011; Lin & Tu, 2012; Kikot et al., 2013; Lu et al., 2014; Ke et al., 2015), motivation (Liu et al., 2011; Liao & Wang, 2011; Costa et al., 2014; Lukosch et al., 2016), and satisfaction (Cvetić et al., 2013; Dzeng, 2014; Lancaster, 2014; Sarabia-Cobo et al., 2016).
Motivation and engagement
Engagement and motivation are major factors in enhancing higher education learning objectives (Connolly et al., 2012; Erhel & Jamet, 2013; Ke et al., 2015; Nadolny & Halabi, 2015). Motivation is considered a central factor in the majority of reviewed studies (Felicia, 2011; Ljungkvist & Mozelius, 2012; von Wangenheim et al., 2012; Bellotti et al., 2013; Hannig et al., 2013; Ahmad et al., 2013; Pløhn, 2013; Li et al., 2013; Denholm et al., 2012; Dzeng et al., 2014; Lancaster, 2014; Ariffin et al., 2014; Bolliger et al., 2015; Cózar-Gutiérrez, & Sáez-López, 2016; Dankbaar et al., 2016; Fu et al., 2016). Some results suggest the effectiveness of GBL in motivating and achieving learning goals can be found at the lower levels of Bloom’s taxonomy (e.g. Connolly et al., 2012). In the context of digital SBL environments, other motivational dimensions are highlighted, such as self-efficacy (Sitzmann, 2011), in conjunction with the transfer of learning (Gegenfurtner et al., 2014).
Motivation is a combination of elements such as attention, relevance, confidence, and satisfaction, which can increase germane cognitive loads. Chang, (2010) examine the effects of motivation in an instructional simulation game, called SIMPLE. According to the post-game evaluation, student motivation comes from peer learning and user cooperation. Moreover, when instructors teach strategy, this enhances student motivation and engagement, encouraging acceptance of the game, and leading to stronger interest in course-directed learning. Thus, teachers should create a flexible learning environment, giving due consideration to peer interaction, learning motivation, pedagogical support and encouragement to help students develop their autonomy and retain an interest in learning.
Another important element contributing to affective outcomes is challenge. Hainey et al. (2011) find the presence of a challenge to be the top ranked motivation for online game players, while recognition is the lowest ranked motivation regardless of gender or amount of players in the game. Gamers in a multiplayer environment tend to report competition, cooperation, recognition, fantasy and curiosity when playing games, while online players experience challenge, cooperation, recognition and control. By contrast, fanatical computer game players experience disappointment and a lack of challenge, as they tend to value the technical aspect over the challenges presented by game play. In Hess and Gunter’s survey (2013), students in a game-based course are motivated, because of the positive social interaction they experience while playing the game; this intrinsic motivation is positively correlated to student performance. Computer games can thus be seen as a learning tool motivating players to acquire many competences. Connolly et al. (2012) share the same view, seeing the role of challenge as a predictive factor with respect to game engagement and achievement. Similarly, in Ke et al.’s study (2015), the game-play actions include optimal challenge expectation for the user. These results can also be seen in Badea (2015), who concludes that the majority of participants in her study acknowledge the highly motivating quality of games, which are complemented by the relaxed class atmosphere when games are used.
However, despite the benefits reaped from the implementation of games and simulations concerning affective outcomes, some researchers underline that motivation is not always related to GBL, emphasizing cases where students who use games in solitary or collaborative environments experience no significant difference in terms of learning motivation (Chen et al., 2015). There are indeed cases where serious games are no more motivating than conventional instructional methods (Wouters et al., 2013). In Cela-Ranilla et al.’s survey (2014), despite the suitability of the 3D simulation environment, students do not feel highly motivated or particularly engaged, mostly because they prefer analysis to actions in the particular learning process.
Faculty role
The benefits of a pedagogical shift from a teacher-focused and lecture-based classroom to a student-centred, active-learning environment through the adoption of simulation-based strategies to achieve engagement are relevant to both students and instructors (Auman, 2011). There is a progression in student emotion from uncertainty and nervousness to satisfaction and excitement within the gaming experience. Auman (2011), as an instructor, provides a positive description: she is drawn in by student enthusiasm, her interest in the material is reinvigorated, she feels empowered in her teaching, and ready to guide her class. In this context, it’s easy to see how instructors ought to play a significant role in motivating and engaging students to achieve learning goals. De Porres and Livingston (2016) concur with Auman (2011), as their study also indicates increased levels of excitement in doctoral students studying Computer Science, when evaluated in a post-test intervention.
Faculty acting as motivators are key in engaging students in the learning process, working to ensure focus on pre-existing knowledge, as well as to transfer knowledge to game settings (Lameras et al., 2016), to reward students for their effort, and support them by providing continuous guidance and pathways for further consideration. The quality of the teacher/facilitator has a strong influence on the learning satisfaction of the students. Also, instructors should facilitate and engage students via in-game discussion forums to help overcome misconceptions, and to lead the game-based learning. The way instructors interact, facilitate and motivate students to construct GBL experiences depends on the design stage, particularly on the way games are incorporated into the curriculum in a traditional course (Wouters et al., 2013). This is because motivation exhibits a significant correlation with cognitive and skill performance (Woo, 2014). In research conducted by Franciosi (2016), despite faculty acknowledging the beneficial impact of games on student motivation, they nevertheless, remain doubtful about the effectiveness of games in learning outcomes, thus resulting in neutral attitudes. Interestingly, although instructors perceive simulations as engaging learning technologies, they do not however consider them superior to traditional teaching methods (Tanner et al., 2012).
Another aspect, less frequently discussed in the relevant literature, is students’ performing self-assessments with regard to effective learning, as seen in Jones and Bursens study (2015). This ability is supported by constructivism, since simulations are developed in an active learning environment, where faculty act more as facilitators rather than as instructors and students are provided with feedback to carry out their self-assessments.
Attitudes and satisfaction
A vital element in achieving learning goals is the relationship between motivational processing and the outcome processing (satisfaction), especially in an online instructional game, as seen in the experiment carried out by Huang et al. (2010). There seems to be a significant relation between these two variables, which suggests that designers of DGBL need to consider extrinsic rewards to achieve motivational development and satisfaction. Learning satisfaction is strongly correlated with student motivation and attitude towards GBL before the game, with actual enjoyment and effort during the game, as well as with the quality of the teacher/facilitator (Mayer, 2013). Specifically, students with a higher level of inner motivation and positive attitude towards GBL are more likely to have higher learning expectations, and to experience more satisfaction in their GBL participation.
In general, most studies report that students develop a positive attitude toward the pedagogical adoption of games and simulations in education (Divjak & Tomić, 2011; Bekebrede, 2011; Ibrahim et al., 2011; Beckem & Watkins, 2012; Tanner et al., 2012; von Wangenheim et al., 2012; Halpern et al., 2012; Terzidou et al., 2012; Hanning et al., 2013; Giovanello, 2013; Cvetić et al., 2013; Kovalik & Kuo, 2012; Li & Tsai, 2013; Hainey et al., 2011; Boeker et al., 2013; Nkhoma et al., 2014; Costa et al., 2014; Chaves et al., 2015; Riemer & Schrader, 2015; Angelini, 2016; Geithner & Menzel, 2016). The participants in Dudzinski et al. (2013) respond positively towards a serious web-based game, describing the experience as interesting, stimulating and helpful, as well as a valuable addition to their pharmacy curriculum. Other students perceive simulation games as fun, but not particularly useful as an instructional method compared to lectures, and about equally useful as case discussions (Beuk, 2015). In another study, the majority of students show a positive attitude towards games, positing that they make subjects more fun and provide more opportunities for learning (Ibrahim et al., 2011). This finding is consistent with Bekebrede et al. (2011) on the perceptions of Dutch students belonging to the “net generation”, who have been raised with technology-based games. Data reveals student preference towards active, collaborative and technology-rich learning via digital games that bring added value to the educational process.
For students, satisfaction is a deciding factor in their decision to continue using such learning methods (Liao & Wang, 2011; Liao, 2015). Terzidou et al. (2012) discuss affective outcomes, especially the way interviewees feel before and after their participation in the game. Prior to participating, the interviewees report feelings of entertainment, fascination, and satisfaction before their participation in the game, which increase after use, indicating that participants find the use of 3D virtual game appealing.
Chen et al. (2010) reveal that the majority of students show negative feelings about online gaming. Shieh et al.’s (2010) mixed methodology research reveals that experimental groups show positive attitudes toward an innovative learning environment and outperform the control groups (in conventional classes). Some studies depict either neutral effects (Rajan et al., 2013; Beuk, 2015; Bolliger et al., 2015; Dankbaar et al., 2016; Strycker, 2016) or negative attitudes towards game use in the learning experience (Jiménez-Munguía & Luna-Reyes, 2012). Students experience more anxiety and boredom during conventional courses, which acts as an impediment to acquiring substantial problem-solving skills. The educational benefits of GBL are particularly apparent in subjects over which students report greater anxiety, where it can be proven that increased enjoyment levels correlate positively with improvements in deep learning and higher-order thinking (Crocco et al., 2016). Liarokapis, (2010) show Computer Science students evaluating a serious online game, and finding it a valuable pedagogical tool, which is both useful and entertaining.
Genre/familiarity issues
Students achieving high scores respond more positively to online games compared to low achieving students. Regarding genre perceptions, male students express more enthusiasm towards digital gaming than female students, or at least spend more time playing computer games compared to girls (Hainey et al., 2011). This may be due to the fact that boys tend to be more familiar with computers and web-based technologies. Girls may choose to avoid digital game-based learning methods, due to their negative preconceptions about gaming, preventing them from harnessing the positive aspects of online gaming (Chen et al., 2010). These studies indicate a difference in perception based on gender when engaging in DGBL environments. However, research by Riemer and Schrader (2015) concluded that female students reported a more positive attitude and perception of affective quality compared to the male students. Also, high assessment scores in web-based games depend on the professional experience of the players. Unexpectedly, in Dzeng et al.’s experimental survey (2014), despite the high test scores achieved in both web-based and paper-based games, students without work experience achieve the highest post-test scores, probably because they are more familiar with using technological tools. The experiments in Erhel and Jamet’s study (2013) indicate that serious games promote learning and motivation, provided they include features that prompt learners to actively process the educational content.
To sum up, games and simulations lead to improved affective outcomes for university students such as attitudes, motivation, emotional involvement, self-efficacy and satisfaction. A growing body of literature supports the positive attitude shown by students towards games and simulations, as they consider them essential instructional tools that provide motivation and engagement in an active learning environment.
