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• Published: 17 March 2022

Effects of digital game-based STEM education on students’ learning achievement: a meta-analysis

• Liang-Hui Wang   ORCID: orcid.org/0000-0003-4256-160X 1 ,
• Bing Chen 1 ,
• Gwo-Jen Hwang 2 ,
• Jue-Qi Guan 1 &
• Yun-Qing Wang 1  

International Journal of STEM Education volume  9 , Article number:  26 ( 2022 ) Cite this article

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Many researchers have explored the impact of digital games on learning effects in different STEM subjects. The purpose of this meta-analysis is to examine the effect of digital game-based STEM education on the learning achievement of K-12 or higher education students. The analysis results of effect sizes from 33 studies ( N  = 3894) published from 2010 to 2020 showed that digital games contributed to a moderate overall effect size (ES = 0.667, 95% CI [0.520–0.814], p  < 0.001) when compared with other instructional methods. Furthermore, the study explored multiple moderator variables and their potential impacts on learning outcomes such as control treatment, subject discipline, educational level, game type, gaming platform, and intervention duration. The findings suggest that digital games are a promising pedagogical method in STEM education that effectively improves learning gains. Additionally, the study concludes with three recommendations for future research and practices on digital games in STEM education.

Introduction

The growing importance of STEM education is recognized globally, but there are multiple perspectives on its meaning. STEM education can be viewed from a broad perspective, including all STEM disciplines, such as science, mathematics, technology, engineering, and cross-disciplinary combinations of the different STEM disciplines. On the other hand, STEM education also refers to interdisciplinary combinations of the individual STEM subjects (Li, 2014 ; Li et al., 2020 ). In our current study, STEM education refers specifically to the STEM subjects of science, mathematics, technology, and engineering. However, learning these disciplines has been considered to have various difficulties and challenges due to the subject's complex, abstract, and multi-dimensional nature (Corredor et al., 2014 ; Sedig, 2008 ). Digital games are considered to have a profound potential to meet these challenges and positively impact students' learning gains and attitudes. “Games” perform an essential function of promoting cognitive development (Piaget, 1999 ), are an immersive, enjoyable, and exciting activity (Papastergiou, 2009 ), and are widely used in educational contexts (Chu & Chang, 2014 ; Gunter et al., 2008 ). The National Science Foundation proposes that STEM learning games have become a new way of learning in K-12 education and are suitable tools for teaching STEM disciplines (National Science Foundation [NSF], 2008 ). Furthermore, researchers have noted that digital games can achieve diversified STEM learning goals that enhance students' learning motivation, improve their understanding of knowledge concepts, and cultivate their problem-solving abilities (Hwang et al., 2012 ).

Several studies on the effectiveness of digital games in terms of learning outcomes have been published. However, these studies have reached no uniform conclusions regarding the effects of digital games on students' STEM learning gains. Some studies show that digital games play a significant role in enhancing students' learning performance. For example, Hung et al. ( 2014 ) developed a mathematical digital game to help children reduce their anxiety, and indicated that it improved their motivation to learn mathematics and their achievement in the subject. Studies conducted by Chu and Chang ( 2014 ), Hwang et al. ( 2013 ); ( 2016 ) supported this conclusion. Other studies, however, have reported a negative impact on students' STEM learning. For instance, by setting up reviewing as usual in the control group and playing games in the experimental group, Neimeyer ( 2006 ) found that educational games had a negative impact on mathematics achievement, as did Ferguson's ( 2014 ) study. Additionally, no significant effect on student learning was determined by other researchers (Giannakos, 2013 ; Khan et al., 2017 ). The results presented in the above studies are disparate and make it difficult for educators to decide whether to use digital games in STEM course teaching. Therefore, evaluating whether digital games have a positive impact on science, technology, engineering, and mathematics (STEM) education is necessary.

Summary of previous literature reviews

Based on a search of the literature, we found three meta-analyses (Riopel et al., 2019 ; Tokac et al., 2019 ; Tsai & Tsai, 2020 ) and two systematic reviews (Gao et al., 2020 ; Li & Tsai, 2020 ) on the application of digital games in STEM subjects. Their analysis methods and research content were quite diverse. Riopel et al. ( 2019 ) conducted a meta-analysis of 79 studies on serious games (i.e., digital software explicitly designed for learning purposes) in science education. They reported that knowledge construction and internalization (e.g., declarative and procedural knowledge, knowledge retention) was slightly higher for students. In addition, five moderators' variables (grade level, duration of intervention, level of user control, year of publication, and publication status) showed a significant impact on science learning achievement.

Tokac et al. ( 2019 ) analyzed the effects of video games on students' mathematics achievement and found significantly more positive impacts on mathematics achievement than traditional instructional methods. They also studied the moderation effects of grade level, instrument type, length of game-based intervention, country, publication type, and study year characteristics on learning achievement. Tsai and Tsai ( 2020 ) examined digital game-based science learning effectiveness. They located 26 research articles from 2000 to 2018 for a meta-analysis and found that gameplay design had a medium effect size, whereas mechanism design had a small-to-medium effect size. Tsai and Tsai also found that students at different educational levels significantly benefitted from game-based science learning. Gao et al. ( 2020 ) comprehensively analyzed 30 studies published between 2010 and 2019 on mobile games in STEM education. Their results supported mobile games in STEM education and further called for more research to apply mobile games. Li and Tsai ( 2020 ) systematically reviewed 31 studies on GBL in science education from 2000 to 2011. They summarized the fundamental theories supporting GBL and showed that most studies focused on promoting the understanding and learning of scientific knowledge and concepts rather than cultivating problem-solving skills.

Previous literature has provided many insightful conclusions about the effect of digital games on learning achievement in the subject discipline of STEM. However, the studies mentioned above also have their limitations. First, they did not comprehensively analyze the subject disciplines of STEM, but only analyzed a particular subject, such as science or mathematics. Second, they did not treat control treatment as a moderator variable for comparison, and therefore failed to accurately assess the moderator variables that may influence the effectiveness of digital game-based STEM education in terms of students' learning achievement.

Purpose of this meta-analysis

To solve the issue of the inconsistent results among the empirical studies on digital game-based STEM education, the primary purposes of this meta-analysis were to examine the overall effect size of using digital games to promote students' learning achievement in STEM education through integrating studies of different research designs and findings. After all, media comparison research is limited. Mayer ( 2019 ) suggested that media comparison research must establish adequate control groups and the potential for publication bias favoring significant media effects. Therefore, we performed a moderator analysis of control treatment, subject discipline, education level, gameplay (game type and gaming platform), and intervention duration to identify critical instructional design principles in the condition of digital game-based STEM Education on learning achievement. To achieve this study purpose, the key research questions that guided this study are as follows:

What is the overall effect of digital game-based STEM education on students' learning achievement?

Are the learning gains higher when using digital games to support STEM education as compared to non-digital game-based methods?

Does the subject discipline impact students' learning achievement in digital game-based learning settings?

Does the educational level influence students' learning achievement in digital game-based learning settings?

Do the gameplay designs (game types or gaming platforms) affect student achievement in digital game-based learning settings?

Does the intervention duration impact students' learning achievement in digital game-based learning settings?

A meta-analysis is a statistical analysis method for quantitative and comprehensive analysis of a large number of previous research results on a certain topic (Glass, 1976 ). A meta-analysis is considered a systematic study to answer specific questions or hypotheses. It has more stringent literature screening mechanisms and standards (Noble, 2006 ). It combines the collected multiple original research results (e.g., R, Mean) into a single effect quantity or effect scale to obtain the comprehensive effect of multiple independent studies, and may better ensure the rigor and effectiveness of the research conclusions. It may allow researchers to resolve disputes arising from conflicting empirical studies and draw more meaningful inferences (Paré et al., 2015 ).

Data sources and search strategy

Studies were searched for using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) method (Moher et al., 2010 , 2015 ). A total of six web databases were consulted, including the Web of Science Core Collection (WoS), Educational Resources Information Center (ERIC), ProQuest, Springer, Scopus, and Wiley. Eligible studies were published from 2010 to 2020. Simultaneously, these studies must be written in English and published in peer-reviewed journal articles. We referred to the search strategies used in previous meta-analyses (Bai et al., 2020 ; Gao et al., 2020 ; Hung et al., 2018 ; Tsai & Tsai, 2020 ). Two sets of search keywords were used in the review. The first set consisted of keywords referring to games, including “game”, “gaming”, “gameplay”, “educational game”, and “digital game”. The second set of search keywords contained keywords related to STEM: “science”, “technology”, “engineering”, and “mathematics”. These two sets of keywords were combined with the Boolean operators (AND, OR).

Inclusion and exclusion criteria

According to the following criteria, the research literature that met the meta-analysis's requirements needed to be included and excluded.

The following inclusion criteria were used in the meta-analysis:

Studies published between January 2010 and December 2020.

Studies that focused on K-12 or higher education settings.

Studies that used an intervention research design whereby a group received a digital game treatment, and another group did not.

Studies should provide sufficient data to calculate effect sizes.

The following exclusion criteria were used in the meta-analysis:

Studies that were not published in English.

Studies that had insufficient data to calculate effect sizes.

Studies that had no control/comparison groups and did not involve digital games.

Studies for which the full text was unavailable.

Studies that did not focus on STEM courses.

Figure  1 shows the data collection process, including searching, screening, and selecting qualified articles for inclusion. The 58 studies were included for further consideration in the eligibility phase. We re-read the literature's full text based on the inclusion and exclusion criteria. Finally, a total of 33 studies satisfied the inclusion criteria in this meta-analysis. From these 33 studies, we extracted 36 effect sizes; one study (Su & Cheng, 2013b ) included one group for two comparisons, and another study (Chang et al., 2015 ) compared three different grades, thus contributing five effect sizes.

PRISMA flow diagram of data collection

Moderator variables

Moderator variables referred to characteristics of studies related to the studies' results. Different moderator variables had different results and could cause variance in effect size. The most common moderator variables were subject discipline, educational level, and intervention duration. Furthermore, control treatment, game type, and gaming platform were also considered as moderator variables in this study. These moderator variables were used in previous research to examine what could contribute to the heterogeneity of effect size differences (Chen et al., 2018 ; Hung et al., 2018 ; Thompson & Gillern, 2020 ; Zheng et al., 2016 ). In order to answer the research questions raised in this meta-analysis, we coded for the following moderator variables. All moderator information of included studies is provided in Table 1 (Additional file 1 ).

Control treatment

The control treatment analysis allows us to determine whether digital game-based instruction is more conducive to promoting learning than other non-digital game-based methods. Previous studies considered “control treatment” as a moderator variable to compare the experimental treatments with the different control treatments (Garzón & Acevedo, 2019 ; Merchant et al., 2014 ; Sitzmann, 2011 ; Wouters et al., 2013 ). The two coding categories for control treatment in our meta-analysis were “traditional” and “multimedia”. Traditional instruction was assigned to curricula, traditional teacher introductions, textbooks, physical laboratories, and other resources. Studies that used videos, images, animation, or computer-assisted instruction were classified as multimedia. This category also included software, mobile devices, or web-based resources.

Subject discipline

The definition of “subject” was the name of a discipline or a class in which the STEM enactment occurred (Wahono et al., 2020 ). Referring to the classification by Wahono et al. ( 2020 ), we also coded the studies into three categories: science, mathematics, and technology or engineering. We hope to guide future development by analyzing the impact of digital game-based introduction in different subject disciplines of STEM.

Education level

Students with different knowledge levels would affect the experiment's results, leading to effect size heterogeneity (Fu et al., 2011 ). Education level is a standard moderator variable in a meta-analysis. It is crucial for educators and developers to identify the educational levels that benefit most from digital games. The education levels were divided into three groups, particularly primary education, secondary education, and higher education, aligning with standard divisions at the school level.

In the existing literature review, Li and Tsai ( 2013 ) divided the games into two types: without a role-play mechanism and with a role-play mechanism. Hung et al. ( 2018 ) identified eight game categories, namely immersive games, tutorial games, exer-games, simulation games, adventure games, music games, board games, and alternate reality games. This study adapted the classification framework for game types of Hung et al. ( 2018 ) by dividing game types into immersive, tutorial, and board games.

Gaming platform

Computers are considered the most common platforms for gameplay, followed by mobile devices (Hung et al., 2018 ). In addition, Thompson and Gillern ( 2020 ) established that different hardware types might impact how people learn through games. It was also divided into computers, mobile devices, video game consoles (e.g., PlayStation or Xbox), and unspecified devices. The study categorized game platforms as computers and mobile devices based on included articles.

Intervention duration

Based on previous studies (Bai et al., 2020 ; Chen et al., 2018 ), this study's intervention durations were coded as one of the following: (a) < 1 week, (b) 1 week-1 month, (c) 1 month-3 months, (d) ≥ 3 months, and (e) Not specified.

Data analysis

We synthesized the effect size and analyzed the moderator variables using the Comprehensive Meta-Analysis 3.0 software. Due to the goal of this study being to examine the effect size of digital game-based instruction in non-digital game-based instruction, the ES for this study was expressed as the standardized mean difference. Homogeneity analysis was computed with the Q statistic and the I 2 value to identify homogeneity across studies. A significant Q statistic rejected the null hypothesis of homogeneity and indicated heterogeneity (Lipsey & Wilson, 2001 ). Thus, the random-effects model was more appropriate (Borenstein et al., 2010 ), and showed that analysis of the moderator variables was necessary. The ES(d) was calculated by using the following formula (Hedges, 1982 ):

where \(M_{E}\) and \(M_{C}\) are the estimated means of the experimental and control groups, respectively, with \(N_{E}\) and \(N_{C}\) being the sample sizes of both groups, and \(S_{E}^{2}\) and \(S_{C}^{2}\) the respective standard deviations.

Results and discussion

Analyses of publication bias and heterogeneity.

Publication bias from multiple sources may affect the results of meta-analysis studies (Egger et al., 1997 ). When only positive study results are published, it leads to publication bias (Borenstein et al., 2009 ). Funnel plots may be useful to assess the validity of meta-analyses. If there is a publication bias in meta-analysis, the funnel plot would be an asymmetrical funnel that both bias and true heterogeneity of potential effects were the reasons for this phenomenon (Egger et al., 1997 ). Conversely, if the funnel plot is an asymmetrical inverted funnel, it suggests no publication bias. As per Fig.  2 , the funnel plot is symmetrical, and most of the studies are in the middle and upper part of the funnel plot, suggesting that there is no publication bias. In the Begg and Mazumdar rank correlation (Kendall's Tau with a continuity correction), the results ( Z  = 1.457 < 1.96, p  = 0.145 > 0.05) indicate that there is insignificant publication bias (Begg & Mazumdar, 1994 ). We compute the classic fail-safe N test to further confirm that there was no publication bias in the current sample. The classic fail-safe N test is a procedure to evaluate whether publication bias can be ignored (Rosenthal, 1979 ). If the fail-safe value is larger than Rosenthal's ( 1979 ) formula: 5 k  + 10, where k is the number of effect sizes included in the meta-analysis, it explains that there is no publication bias. The fail-safe value for this meta-analysis was computed to be 3001, which is more than 5(36) + 10. There would need to be a large number of nonsignificant unpublished studies for the effect sizes to be statistically insignificant. Based on this, we conclude the absence of publication bias.

Funnel plot of effect sizes with 95% confidence interval boundaries

The presence of heterogeneity is examined by using the I 2 values. The I 2 test supplements the Q -test, where 0%–25% indicates that heterogeneity is considered low, 25%–75% indicates moderate heterogeneity, and 75%–100% indicates substantial heterogeneity (Higgins et al., 2003 ). The larger the I 2 value, the greater the heterogeneity. The statistics ( Q  = 156.856, I 2  = 77.687, p  < 0.001) show the presence of statistical heterogeneity. When there is significant heterogeneity, using a random-effects model would better address the differences between research effect sizes (Wang et al., 2019 ). Therefore, we adopted a random-effects model for the data analysis.

What is the overall effect of digital game-based STEM education on students' learning achievement?

To answer this question, 33 studies with 36 effect sizes and 3894 participants were examined by using a meta-analysis approach. Under the random-effects model, this study reported an overall significant positive effect size (ES = 0.667, 95%CI [0.520–0.814], p  < 0.001). According to Cohen ( 1988 ), when the effect size was less than 0.2, it indicated a small effect, while when it was between 0.2 and 0.8, it was a moderate effect, and more than 0.8 was classified as a large effect. The results demonstrated that compared to non-digital game learning activities, digital game-based learning had a moderately significant effect on students' STEM learning achievement. In other words, using digital games to improve students' academic performance could be one of the effective methods for STEM education. The forest plot of all included effect sizes in the random-effects model is shown in Fig.  3 .

Forest plot of all included effect sizes in the random-effect model

This study compared digital game-based instruction with non-digital game-based instruction, which is the main contribution to the field. There was a significant relationship between digital games and learning achievement, with a moderately positive effect, suggesting that digital game approaches outperformed non-digital games. However, one must be cautious when assuming that computer games are always the most effective form of computer-assisted learning (Mayer, 2019 ). Like other instructional approaches, educators should adequately consider goals for learning and methods of integrating digital games most effectively into the STEM classroom to promote students' learning achievements.

Possible moderators and analysis of their effects

In addition to knowing that digital games affect students' learning achievement, this study also needs to look for possible moderator variables that affect the effectiveness. Subject discipline, educational level, and intervention duration could contribute to the heterogeneity of effect size differences. Similarly, the game type and gaming platform analysis are essential to the effect of digital game-based STEM education on students' learning outcomes. Under the random-effects model, moderator analyses were performed on these moderator variables. The descriptive analysis of subgroups contributed to answering the research questions of this study. The results and discussion are as follows:

Are the learning gains higher when using the digital game to support STEM education as compared to non-digital game-based methods?

The meta-analysis of the control treatment variable demonstrates no statistically significant difference between the control group treatment of traditional and multimedia approaches ( Q b  = 3.506, p  = 0.061). The effect size of digital game-based instruction compared to multimedia is 0.848 ( p  < 0.001). When comparing digital game-based instruction with traditional introduction, the effect size was 0.558 ( p  < 0.001). The results show that digital game-based instruction is more effective than other instruction strategies, indicating that intervention of digital games seems to improve student learning. Additionally, we compared the effect size found in this study with other meta-analyses on game-based STEM subjects. Tsai and Tsai ( 2020 ) analyzed the effectiveness of game-based science learning. They considered the gameplay design and game-mechanism design, and the effect sizes found were ES = 0.646 and ES = 0.270, respectively. Tokac et al. ( 2019 ) conducted a meta-analysis to measure the impact of learning video games on mathematics achievement compared with traditional methods. They found that mathematics video games contributed to learning compared with traditional methods. In summary, the results of our meta-analysis are consistent with previous meta-analyses, in that digital games were found to have a positive impact on STEM education compared with other methods.

Does the subject disciplines impact students' learning achievement?

For subject discipline, there is no significant difference between the studies for science, mathematics, and technology/engineering ( Q b  = 2.188, p  = 0.335). Digital games have a positive effect on science, mathematics, and technology/engineering. The effect size of science (ES = 0.750, p  < 0.001) is higher than that of mathematics (ES = 0.629, p  < 0.001) and technology/engineering (ES = 0.367, p  = 0.140). However, the effect size of technology/engineering showed no statistically significant difference. The results are consistent with Tsai and Tsai ( 2020 ) and Tokac et al. ( 2019 ).

Does the educational levels influence students' learning achievement?

Regarding education levels, results in Table 2 suggest no significant difference in the effect sizes for the different education levels ( Q b  = 5.184, p  = 0.075). However, it is most beneficial for primary education (ES = 0.835, p  < 0.001) to learn with the assistance of digital games, with results that were significantly better than those in secondary (ES = 0.487, p  < 0.001) and higher education (ES = 0.492, p  < 0.05). The results fully reflect the relationship of Piagetian theories between playing and cognitive development (Piaget, 1999 ). Primary school students are in the critical period of cognitive development. Interest is also a key factor. Students in primary education may not be able to fully master the game's rules and are easily attracted by the freshness of digital games. However, secondary and higher education students can understand the game's rules faster, resulting in decreased learning interest.

Do the gameplay designs (game types or gaming platforms) impact learning achievement?

As shown in Table 2 , results show that the effect sizes significantly differ among the different game types for students' academic performance ( Q b  = 11.126, p  < 0.01). The effect size of board games (ES = 1.455, p  < 0.001) significantly outperformed the other two game types. However, the research on board games (11.11%) was the least. The reason for this phenomenon is the small sample size. Additionally, the research of Chen et al. ( 2016 ) and Hwang et al. ( 2012 ) also affected the result. Immersive games (ES = 0.583, p  < 0.001) and tutorial games (ES = 0.593, p  < 0.001) also showed significant results. Reviewing previous literature shows that there has been little exploration of game types. Lamb et al. ( 2018 ) found that different game types increased students' achievement, cognition, and affect. In our meta-analysis, even if board games have a more significant impact than the other three game types, only four studies on board games were included in this meta-analysis. Nevertheless, in follow-up research on digital games, it is necessary to compare further the effects of different game types on students' learning achievement in STEM education.

The results of the subgroup analyses of gaming platforms summarize that using computers (ES = 0.625, p  < 0.001) and mobile devices (ES = 0.768, p  < 0.001) both significantly enhance students' learning, and there is no significant difference between the two subgroups’ effect sizes ( Q b  = 0.752, p  = 0.386). This means that the different gaming platforms tend to have the same learning effectiveness. Gaming platforms are also of interest to education researchers. Different game platforms (e.g., computers and mobile devices) have their own characteristics and limitations, affecting learners' interactions with games (Thompson & Gillern, 2020 ). Previous literature reviews and meta-analyses have examined the field of gaming platforms (Hung et al., 2018 ; Thompson & Gillern, 2020 ). They found that computers were considered the most common gaming platform. Thompson and Gillern ( 2020 ) reported a more significant effect size for console-based games in English vocabulary learning than computers and mobile devices. Our results are consistent with these findings. They showed that computers were the most commonly used gaming platforms. In addition, given the rapid increase in mobile technology use (Sung et al., 2016 ), mobile games have become more popular. It is necessary to further study digital games played on mobile devices and to compare the impact of different game platforms on students' learning achievement. Finally, considering that each game platform can promote academic performance, educators should choose the appropriate game platform according to the learning goals and students' characteristics.

Does the intervention duration impact students' learning achievement?

The effect size of intervention duration was also computed. Results shown in Table 2 suggest that the intervention duration of less than one week has the largest effect size (ES = 0.953, p  < 0.001). Consistent with previous discussions, short-term interventions have been associated with better learning achievement than long-term interventions (Riopel et al., 2019 ). The main reason for this is that the possibility of novelty effects gradually decreases. Learners are often excited about the use of digital games in short-term interventions, which leads to a high degree of curriculum activity participation. However, learners are only curious about new learning methods in the short term. Over time, they experience boredom due to the disappearance of the novelty effect, leading to a reduced desire to use the method. The second largest effect size was for 1 week to 1 month (ES = 0.464, p  < 0.05), followed by 1 month to 3 months (ES = 0.579, p  < 0.001), greater than or equal to 3 months (ES = 0.597, p  < 0.001), and Not specified (ES = 0.676, p  < 0.01). Moreover, the results indicate no significant differences among different intervention durations ( Q b  = 5.070, p  = 0.280), which means that digital games have positive effects on learning achievement for different intervention durations.

Conclusions

The results of this study suggest that digital games can effectively promote and enhance students' learning achievement in STEM education, enhancing our understanding of the application and practice of digital games in STEM education. We also examined the different moderator variables that may affect the effect sizes of digital games. Based on the findings in this study, three recommendations for future research on digital games in STEM education are proposed.

First, future research should strengthen the gameplay design and game mechanisms. It should also examine the effects of different types of digital games on student learning in STEM education. Most knowledge content in STEM education involves abstract and multi-dimensional concepts. These are often difficult for students to understand and cause them to lose learning motivation quickly. This in turn hinders their internalization and construction of knowledge. It develops their low academic performance and negative attitudes and may cause students to drop out of courses (Anderson & Barnett, 2011 ; Khan et al., 2017 ). Studies by Bai et al. ( 2020 ), Chen et al. ( 2020 b), Chen, Huang, et al. ( 2020 a)), and Tsai and Tsai ( 2020 ) showed that gameplay and game mechanisms, competition strategies, and gaming platforms significantly increase students' learning achievement, consistent with our research results. Different game types and platforms have promoted students' learning achievement improvement, but educational researchers need to explore the internal mechanism of digital games further to better understand their effects.

Second, future work should carefully examine the influence of the learner’s types and characteristics on their interest in digital games. Brinson ( 2015 ) believed that it was crucial to better understand the effectiveness of serious games related to students' grade levels and cognitive or psychological development. In our research, the learning effectiveness of digital games in elementary schools significantly outperformed that in secondary schools and in higher education. Similarly, Riopel et al. ( 2019 ) reported that high school students achieved significantly higher science learning gains than older college students and adults, consistent with Wouters et al. ( 2013 ). Additionally, personality traits significantly impact the game learning system's design (Jia et al., 2016 ). Therefore, in the following work, personalized digital games can be further designed according to learner’s types and characteristics to better meet different learners' preferences.

Third, future research should integrate digital games with other technologies to advance the sustainable development of digital games in educational applications. The growth of the Internet and various emerging technologies (e.g., mobile technology, AR/VR, and 3D) provides students with personalized learning support opportunities in their education (Hou et al., 2014 ; Hwang et al., 2016 ; Su & Cheng, 2013a ). According to Hwang et al. ( 2016 ), an AR-based gaming method could improve students' learning attitudes and learning outcomes. Through the implementation of quasi-experiments, Su and Cheng ( 2013a ) found that when compared to traditional teaching, a 3D GBL system with a software engineering curriculum could achieve better learning achievement and motivation through quasi-experiment implementation. Consequently, future research should make full use of various information resources and integrate emerging technology to develop a sense of immersion. The substitution of digital games helps improve students' learning experiences and mobilizes their learning enthusiasm, while also stimulating their learning motivation. Furthermore, extending digital games from computers to mobile devices is necessary. It is beneficial to realize ubiquitous and lifelong learning and to promote digital games' sustainable development in teaching practice applications.

Limitations

While this study highlights digital games as an effective method for promoting students' learning achievement in STEM education compared to non-digital games, a few limitations exist for this meta-analytic research. First, due to the intention of the meta-analysis method, our analysis excludes many empirical studies that have significant value but do not meet the requirements. This study only involves 33 empirical studies and 36 effect sizes. We believe that there may be relevant studies that have not been found. Second, the data analysis uses a random-effects model rather than a more precise fixed-effects model. It will not be comprehensive if we attempt to cover a wide range of internal and external moderator variables. Finally, the current review is not an attempt to be inclusive but rather to provide a systematic overview of digital games in STEM education. There is a paucity of reports on other aspects of DGBL, such as cognitive skills and affective influences. Therefore, it is suggested that some follow-up studies can be conducted to investigate the effects of digital game-based STEM learning from diverse perspectives by taking into account those relevant studies published in the enormous number of academic databases.

Availability of data and materials

Not applicable.

Abbreviations

Comprehensive meta-analysis software

• Digital game-based learning

Educational Resources Information Center

Game-based learning

National Science Foundation

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Science, technology, engineering, and mathematics

Web of Science

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The authors would like to express the gratefulness to the three anonymous reviewers for providing their precious comments to refine this manuscript.

Philosophy and Social Science Planning of Zhejiang Province (Grant No. 19NDJC252YB); National Education Science “13th Five-Year” Planning Key Project of Ministry of Education in China (Grant No. DCA160262).

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LHW designed the research, interpreted the data and drafted the work; BC participated in the acquisition, analysis and interpretation of data and drafted the work; GJH gave an important advise and revised the conclusion; JQG and YQW took part in the acquisition and analysis of data. All authors read and approved the final manuscript.

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Liang-Hui Wang is an associate professor at the Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University. His research interests include technology enhanced learning, learning analytics and STEM education.

Bing Chen is a graduate student at the Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University. His research interests include digital game-based learning and computational thinking.

Gwo-Jen Hwang is a chair professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology. His research interests include mobile learning, digital game-based learning, flipped classroom and AI in education.

Jue-Qi Guan is a lecturer at the Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University. Her research interests include technology enhanced learning and smart learning environment.

Yun-Qing Wang is a graduate student at the Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University. Her research interests include STEM education and learning analytics.

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The effect of games and simulations on higher education: a systematic literature review

• Dimitrios Vlachopoulos 1 &
• Agoritsa Makri 2  

International Journal of Educational Technology in Higher Education volume  14 , Article number:  22 ( 2017 ) Cite this article

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The focus of higher education institutions is the preparation of future professionals. To achieve this aim, innovative teaching methods are often deployed, including games and simulations, which form the subject of this paper. As the field of digital games and simulations is ever maturing, this paper attempts to systematically review the literature relevant to games and simulation pedagogy in higher education. Two researchers collaborate to apply a qualitative method, coding and synthesizing the results using multiple criteria. The main objective is to study the impact of games and simulations with regard to achieving specific learning objectives. On balance, results indicate that games and/or simulations have a positive impact on learning goals. The researchers identify three learning outcomes when integrating games into the learning process: cognitive, behavioural, and affective. As a final step, the authors consolidate evidence for the benefit of academics and practitioners in higher education interested in the efficient use of games and simulations for pedagogical purposes. Such evidence also provides potential options and pathways for future research.

Introduction

As rapidly evolving technological applications, games and simulations are already widely integrated in the traditional educational process. They are deployed extensively in the field of education, with an existing body of work examining the relation between games and education (Yang, Chen, & Jeng, 2010 ; Chiang, Lin, Cheng, & Liu, 2011 ). In recent years, digital or web-based games have increasingly supported learning. In the context of online education, this research area attracts a significant amount of interest from the scientific and educational community, for example tutors, students and game designers. With the growing expansion of technology, instructors and those who create educational policy are interested in introducing innovative technological tools, such as video games, virtual worlds, and Massive Multi-Player Online Games (MMPOGs) (Buckless, 2014 ; Gómez, 2014 ).

Games and simulations show mixed effects across a number of sectors, such as student performance, engagement, and learning motivation. However, as these studies focus only on certain disciplines, there remains a gap in the literature concerning a clear framework of use across academic programmes. As a result, the issue of efficiently integrating games and simulations in the educational process is often up to the instructor’s discretion. Accordingly, the aim of this paper is to develop a framework to allow educators across disciplines to better understand the advantages and draw backs of games and simulations specific to their pedagogical goals.

Rationale of the study

The researchers set out to examine the effectiveness of games and simulations in the learning experience, and immediately encounter the first challenge, which relates to a lack of clear empirical evidence on the issue (Farrington, 2011 ). The scientific field is too extensive and requires further investigation. Furthermore, there is currently no formal policy framework or guidelines recommended by governments or educational institutions on the adoption of games and simulations in education. This is the case for many countries in Europe, the US, and Australia, where it is the responsibility of the instructor or institution to incorporate games into the curriculum.

The main motivation for the current review lies in the fact that games are already, to a certain degree, integrated into educational systems to achieve a variety of learning outcomes (Connolly, 2012 ), yet a comprehensive policy is still lacking. In this paper, the first step was an attempt to conceptualize the terms “game” and “simulations”. Although the two terms are neither wholly synonymous, or completely differentiated, in the main body of this review, the focus will be on lumping them together and perceiving them as points across a multidimensional continuum (Aldrich, 2009 ; Renken, 2016 ), since these educational technologies are consolidated under the umbrella of an interactive virtual environment in digital education.

A primary aim is to identify studies concentrating on the use of games and simulations for learning purposes, and to analyse the results by comparing them to prior studies’ findings. Two research questions guide the review analysis: a) How can the best practices/methods for designing and incorporating games and simulations in student learning be identified? b) How can games/simulations enhance Higher Education?

The major difference between the current review and the previous reviews in the field is the conceptualization of the terms “games and simulations”, which acts as an umbrella for further typologies. In other words, the researchers include more genres of games and simulations in their systematic review, compared to the other literature reviews. In addition, the researchers’ intention is to focus on the impacts of games and simulations on learning outcomes. The researchers don’t focus only on the cognitive outcomes, which is the most obvious and common topic among other researchers but, simultaneously, they analyze behavioural and affective effects as well. Furthermore, most of the previous reviews focus on the impacts of games and simulations on the learning process of certain subjects (e.g. Science, Business, Nursing, etc.), whereas this study expands research in a wide spectrum of academic disciplines and subjects. Overall, the current study offers a systematic review that opens new areas for further discussion, highlighting that collaborative learning, teamwork and students’ engagement also play a significant role for a successful learning process.

Conceptualising games and simulations

In recent years, the interest in examining game use in higher education has increased. This includes educational games (Çankaya & Karamete, 2009 ), digital game-based learning (DGBL) (Yang, 2012 ), and applied games (van Roessel & van Mastrigt-Ide, 2011 ). In addition, scholars, sometimes, include interactive exercises (Mueller, 2003 ), video games (Biddiss & Irwin, 2010 ), or even expand to next generation video games (Bausch, 2008 ), in the category of games. With respect to web-based games, the technological platforms that implement digital game code include computers and consoles (Salen & Zimmerman, 2004 ). They can run on a web browser on mobile phones and other mobile gaming devices (Willoughby, 2008 ) (e.g., tablets).

Despite the abundance of game types, there is a lack of clear, shared definitions and terminology among scholars and educators, which has led to “terminological ambiguity” (Klabbers, 2009 ). Nevertheless, the need for shared terminology remains when discussing the different forms of games and simulations in higher education. Although academics and game developers may use varying taxonomy to categorise games, the majority broadly agree on the following seven genres (Gros, 2007 ):

Action games: response-based video games.

Adventure games: the player solves problems to progress through levels within a virtual world.

Fighting games: these involve fighting with computer-controlled characters or those controlled by other players.

Role-playing games: players assume the roles of fictional characters.

Simulations: games modelled after natural or man-made systems or phenomena, in which players have to achieve pre-specified goals.

Sports games: these are based on different kinds of sports.

Strategy games: these recreate historical scenes or fictional scenarios, in which players must devise an appropriate strategy to achieve the goal.

In recent years, several well-designed empirical studies investigating the effects of serious games on learning outcomes have been published. Sawyer refers to serious games as those games produced by the video game industry that have a substantial connection to the acquisition of knowledge (Sawyer, 2002 ). Zyda ( 2005 ) expands Sawyer’s definition, adding that serious games are games whose primary purpose is not entertainment, enjoyment or fun. Serious games, educational gaming, as well as virtual worlds developed for educational purposes reveal the potential of these technologies to engage and motivate beyond leisure activities (Anderson et al., 2009 ). At the same time, there is extensive literature exploring the potential learning benefits offered by game-based learning (GBL), which can be defined as the use of game-based technology to deliver, support, and enhance teaching, learning, assessment, and evaluation (Connolly, 2007 ).

• Simulations

Simulations create a scenario-based environment, where students interact to apply previous knowledge and practical skills to real-world problems, also allowing teachers to reach their own goals, as well (Andreu-Andrés & García-Casas, 2011 ; García-Carbonell & Watts, 2012 ; Angelini, 2015 ). During scenario-based training, the player acquires important skills, such as interpersonal communication, teamwork, leadership, decision-making, task prioritising and stress management (Flanagan, 2004 ). The practical scenario may be carried out individually or within a team (Robertson et al., 2009 ), leading to collaboration and knowledge sharing.

With the explosion of Web 2.0 technology, increased opportunities to engage with technological applications in a collaborative and participatory way have emerged, promoting information access, shared ideas, knowledge exchange, and content production (McLoughlin & Lee, 2008 ). Digital simulations, which engage students in the interactive, authentic, and self-driven acquisition of knowledge, are being adopted in higher education. Connolly and Stansfield ( 2006 ) define game-based e-learning as a digital approach which delivers, supports, and enhances teaching, learning, assessment, and evaluation. Game-based e-learning is differentiated from GBL, which tends to cover both computer and non-computer games.

Delivery platforms are an essential aspect for game designers when creating and distributing games and simulations (e.g. computer, video, online, mobile, 3D, etc.). Designers must pay attention to characteristics such as the technical challenges, modules and techniques associated with the game design, the players involved in gaming, and the teaching modes (e.g. single, multi-player, collaborative, synchronous, etc.). This study examines the diverse curricular areas and learning objectives each game intends to access. The above-mentioned game classification is presented below (Fig. 1 ).

Classification of games and simulations

The main difference between games and simulations is the following: games are tools which are artificial and pedagogical; they include conflict, rules, and predetermined goals, whereas simulations are dynamic tools, representing reality, claiming fidelity, accuracy, and validity (Sauve, 2007 ).

Previously conducted reviews/meta-analyses on games and simulations in higher education

To establish a context , the researchers, initially, examined the relevant literature on the effectiveness of all types of games and simulations in learning outcomes. Many papers are analysed and summarised as follows, providing useful guidance for this study.

Through their systematic review, Tsekleves et al. ( 2014 ) provide insight into the barriers and benefits of using serious games in education. (Regarding benefits, the authors catalogue: achievement and rewards, interactivity and feedback, motivation and competition, playfulness and problem-based learning, collaborative learning, progression and repetition, as well as realism and immersion. Finally, they propose some guidelines to help stakeholders better implement serious games in education. Similarly, Bellotti, ( 2013 ) suggest useful guidelines for the performance assessment of serious games. Following user performance assessments, they offer an overview on the effectiveness of serious games in relation to learning outcomes. Results reveal the effectiveness of serious games in motivating and achieving learning goals, the importance of providing appropriate user feedback, while emphasizing that new types of games are best deployed through proper instructor guidance. Moreover, they stress aspects they consider important, such as performance assessment with a view to fostering adaptivity, as well as personalisation, and meeting needs on an individual basis (e.g. learning styles, information provision rates, feedback, etc.).

The instructor’s role is also outlined by Lameras et al. ( 2016 ) who provide conceptual and empirical evidence on the manner in which learning attributes and game mechanics should be designed and incorporated by faculty, specifically with a view to fully integrate these into lesson plans and the learning process as a whole. Games allow practitioners to quickly come to grips with the way in which learning activities, outcomes, feedback and roles may vary, as well as to enhance the in-game learning experience. Similarly, the systematic review of 64 articles by de Smale, ( 2015 ) concludes that there is a positive or neutral relationship between the use of simulations and games and learning achievement. The researchers arrive at three recurring conditions for the successful use of simulations and games: the specificity of the game, its integration in the course, and the role of a guiding instructor, which are all conditions in line with Bellotti et al. ( 2013 )‘s results.

Young et al. ( 2012 ) choose 39 articles that meet the inclusion criteria related to video games and academic achievement, concentrating on the use of traditional games versus video games for educational purposes. The studies are categorised by subject, namely History, Mathematics, Physical Education, Science, and Languages. Results indicate that there exists limited evidence of the benefits of including education games in the traditional classroom environments, a finding which is contrary to the aforementioned studies. Smetana and Bell ( 2012 ) examine computer simulations to support instruction and learning in Science. In their comparative study between computer games and traditional games, they conclude that computer games can be as effective, if not more so, than traditional games in promoting knowledge, developing procedural skills and facilitating conceptual change. To integrate them properly as supplementary elements (Rajan, 2013 ), games require the adoption of high-quality support structures, student participation, as well the promotion of cognitive and metacognitive skills. This finding contradicts the study carried out by Girard, ( 2013 ). This study treats video games as serious games but considers their effectiveness as a controversial issue, finding that only few games result in improved learning, while others have no positive effect on knowledge and skills acquisition, when compared to more traditional methods of teaching.

In contrast, in their meta-analysis, Clark et al. ( 2015 ) systematically review articles to study the detailed effects of digital games on learning outcomes, concluding that games are important in supporting productive learning and highlighting the significant role of gaming design beyond its medium. Prior to this review, but running along the same lines, Backlund and Hendrix ( 2013 ), in their meta-analysis reported positive outcomes in learning when using serious games in the educational process. Wouters, ( 2013 ) performing meta-analytic techniques, used comparisons as well, to investigate whether serious games are more effective and more motivating than conventional instructional methods. They found higher effectiveness in terms of learning and retention, but less motivation compared to traditional instructional methods. Indeed, serious games tend to be more effective if regarded as a supplement to other instructional methods, and involve students in groups and multiple training sessions.

These findings are compatible with those in the survey conducted by Rutten, ( 2012 ), which focuses on implementing games as laboratory activities, concluding that simulations have gained a prominent position in classrooms by enhancing the teacher’s repertoire, either as a supplement to traditional teaching methods or as a partial replacement of the curriculum. Nevertheless, they stress that the acquisition of laboratory skills cannot be wholly conducted via simulations. However, in areas where simulations have been widely accepted as a training tool, simulations can play a significant role in making lab activities more effective when offered as pre-lab training. Fu, ( 2016 ), through a systematic literature review, identify the multi-dimensional positive impact of serious games in business education, with the most frequent outcomes being knowledge acquisition and content understanding. The study also confirms that GBL and serious games can influence player engagement, perpetual and cognitive skills and social or soft skills. The affective and motivational outcomes are examined in entertainment games, games for learning and serious games, which reflects the trend of using gaming elements as both a medium of entertainment as well as a mode of learning. Ritzhaupt, ( 2014 ) produce meta-analysis based on 73 articles, demonstrating that achievement measures (e.g., standardised test scores) are the most commonly investigated, while the second most frequent is affective measures (e.g., usability or attitudes towards technology) followed by behavioural measures (e.g., task behaviour).

Merchant, ( 2014 ), via a meta-analysis, compare the effectiveness of games, simulations and virtual worlds in improving learning outcomes. Findings indicate that playing games individually enhance student performance more than playing collaboratively. Nonetheless, the researchers claim that there is no statistically significant difference between the effects of individual and cooperative instructional modules regarding simulations. Student learning outcomes deteriorate after repeated measures, since after spending a certain amount of time playing games, the learning outcome gains start to diminish. On the contrary, Shin, ( 2015 ), through meta-analysis, aim to identify the effects of patient simulation in nursing education. They find significant post-intervention improvements in various domains for participants who receive simulation education compared to the control groups, thus leading to the conclusion that simulations are more effective than traditional learning methods, enhancing the player’s psychomotor, affective, and cognitive skills. In their work, simulations provide students with authentic clinical situations, allowing them to practice and experience in realistic and safe environments.

Connolly et al. ( 2012 ) develop a multi-dimensional approach to categorising games and offer a review of 129 papers on computer games and serious games, explicitly targeting cognitive, behavioural, affective and motivational impacts, as well as engagement. The most frequent outcomes are knowledge acquisition and content understanding, as well as affective and motivational outcomes. Gegenfurtner, ( 2014 ) in their meta-analysis of the cognitive domain, examine how design elements in simulation-based settings affect self-efficacy and transfer of learning. They conclude that gathering feedback post-training, as opposed to during the process, results in higher estimates of self-efficacy and transfer of learning.

Researchers also look at games and simulations from a theoretical perspective. Li and Tsai ( 2013 ), examine the theoretical background and models employed in the study of games and simulations. They focus principally on the theories of cognitivism, constructivism, enactivism, and the socio-cultural perspective. Results indicate that although cognitivism and constructivism are the major theoretical foundations employed by game-based science learning researchers, enactivism and the socio-cultural perspective are the emerging theoretical paradigms drawing increasing attention in this field. This literature review indicates an increasing recognition of the effectiveness of digital games in promoting scientific knowledge and concept learning, while giving lesser importance to facilitation of problem-solving skills, exploring outcomes from the viewpoint of scientific processes, affect, engagement and socio-contextual learning. This view is echoed by other researchers, such as Warren, ( 2016 ), who systematically review and demonstrate the effectiveness of simulation games on satisfaction, knowledge, attitudes, skills and learning outcomes within nurse practitioner programmes. After comparing online simulation-based learning with traditional lectures, they find an increase in student knowledge and confidence when using simulation games. Peterson ( 2010 ) also performs a meta-analysis, examining the use of computerised games and simulations in language education from a psycholinguistic and socio-cultural viewpoint. Results show valuable opportunities for effective language learning, confirming that games are beneficial in helping students learn another language.

Sitzmann ( 2011 ), using interactive cognitive complexity theory, offers a comparative review on the instructional effectiveness of computer simulations. To perform the review, she examines three affective outcomes (motivation, effort, and self-efficacy), one behavioural (effort), two cognitive (declarative knowledge and retention), and two skill-based learning outcomes (procedural knowledge and transfer). She concludes that, post-training, simulation-trained learners demonstrate higher self-efficacy and procedural knowledge. Furthermore, she highlights the significance of using specific methods to improve simulation learning, namely, integration of game use within an instructional programme, high level of learner activity, no gaming time limit, and adopting the simulation game as a supplement to other methods, which is inconsistent with Wouters et al.’s survey ( 2013 ). Hsu et al. ( 2012 ) provide a cross-analysed content analysis agreeing with the previous researchers that topics such as “Motivation, Perceptions and Attitudes” are of utmost importance.

In a recent review of business literature, Carenys and Moya ( 2016 ) discuss the impact of digital game-based learning (DGBL) on students. They examine DGBL both from a theoretical point of view and on a practical basis through three stages: a) the evaluation of digital games in the preparatory stage, b) specifying which research has been deemed appropriate for DGBL deployment, and c) the learning outcomes (cognitive, behavioural, affective, and multi-dimensional) that can be attained through digital games. This study moved current research forward in understanding the effectiveness of digital games and advanced the use of digital games in the classroom.

A variety of meta-analyses and systematic reviews have examined the implementation of games and simulations in the learning process, either as a main course element or as a supplement to conventional lectures, illustrating the ever increasing interest of researchers in this promising field.

Synthesis of previous reviews/meta-analyses

After studying the previous reviews, it is evident that the most commonly referred games in past reviews are digital and computerized games (Sitzmann, 2011 ; Young et al., 2012 ; Smetana & Bell, 2012 ; Girard et al., 2013 ; Merchant et al., 2014 ; Clark et al., 2015 ; Carenys & Moya, 2016 ; Warren et al., 2016 ). The technological revolution and the invasion of Internet in Higher Education urge students to build digital and collaborative skills for the twenty-first century through gaming. Also, the emergence of a participatory culture in education spurs researchers to get involved with digital games and simulations. Other games mentioned are serious games and their impact on the learning process (Connolly et al., 2012 ; Bellotti et al., 2013 ; Backlund & Hendrix, 2013 ; Wouters et al., 2013 ; Tsekleves et al., 2014 ; Fu et al., 2016 ). The researchers refer to serious games since they are basically considered as games with educational orientation and not with just entertaining ones.

Another important element we have identified is whether games should be fully or partially integrated into the learning process. Most of the researchers agree that games should be treated mainly as supplementary elements (Sitzmann, 2011 ) since full integration requires high-quality mechanisms, students’ engagement, and instructors’ support. In other cases, the integration of games in the curriculum could either function as a supplement to existing teaching techniques or as a partial substitute for traditional teaching methods (Rutten et al., 2012 ). Moreover, games could even be fully integrated for achieving better learning outcomes (Lameras et al., 2016 ) because games add diversity in educational teaching modules. Nevertheless, the integration of games depends on instructors’ contribution and the way they design and incorporate games in their teaching. This means that instructors should be equipped with knowledge and experience, and be aware of providing guidance to students as regards the proper way of playing games.

The beneficial contribution of game-based learning is broadly identified by the majority of previous reviewers, especially regarding cognitive outcomes. Results indicate that games can be as effective as traditional learning modes, revealing their effectiveness in promoting knowledge acquisition (Smetana & Bell, 2012 ; Backlund & Hendrix, 2013 ; Clark et al., 2015 ; Warren et al., 2016 ), as well as content understanding and concept learning (Connoly et al., 2012 ; Li & Tsai, 2013 ; Fu et al., 2016 ). Additionally, students achieve their learning goals through playfulness and problem-based learning (Tsekleves et al., 2014 ), thus leading to self-efficacy and transfer of learning (Gegenfurtner et al., 2014 ).

Another substantial impact emerged is the effectiveness of games not only in the cognitive domain but also in the affective and behavioural domains (Ritzhaupt et al., 2014 ; Shin et al., 2015 ; Tsekleves et al., 2014 ; Fu et al., 2016 ; Carenys & Moya, 2016 ). The affective domain is thoroughly discussed by the reviewers. In particular, games influence students’ motivation, engagement, and satisfaction of the game-based learning. Regarding behavioural outcomes, few reviews have been conducted, showing that games offer a plethora of opportunities for collaborative learning, enhance interactivity and feedback among players, and develop social and soft skills as well. Some other studies contradict these findings, in a way that they do not reveal positive effects of games (Young et al., 2012 ; Girard et al., 2013 ; Merchant et al., 2014 ), or reveal a rather neutral effect (de Smale et al., 2015 ). In these reviews, games and simulations appear to have some or no positive effects on knowledge and skills acquisition when comparing with traditional instructional methods.

Research method

Research selection.

The authors developed a pre-defined review protocol to answer the research questions, specifically aimed at minimising researcher bias. The literature review was carried out between July and October 2016 and followed the design stages described below.

The reviewed papers are identified through keywords in referenced electronic databases, such as Google Scholar, Web of Science, ERIC, PsycInfo, PsycArticles Fulltext Search, InterDok, ProQuest, Scopus, BEI, and SearchPlus. The keywords for learning outcomes are a combination of the term games or simulations paired with the term higher education , employing the Boolean operator “AND”. Additional keywords for learning outcomes are learning objectives, learning goals, learning objectives and effects . Keywords for platform and delivery methods include computer-based, web-based, digital, virtual, online, and technology. Keywords for games and simulations are educational games, business simulations, role-playing simulations, game-based learning, video games, and serious games . Moreover, the Boolean operator “OR” is employed to combine all these keywords. The study sets the broadest range of keywords, so as not to limit the scope of related articles.

Furthermore, the researchers conducted a comprehensive database search in bibliographic indices for the data selection. The search is related to a variety of scientific fields of study, including Education, Psychology, Information Technology, Management, and other scientific areas (e.g., Engineering, STEM, Health, etc).

Assessment and extraction

The dataset consists of journal articles referring to games, simulations or learning in their title and/or abstract. The researchers piloted and evaluated their selection criteria based on prior studies. The study selection process was conducted in two separate phases: a) the researchers, working independently, initially, and, subsequently, together, screened the titles and abstracts for inclusion criteria, and b) in the event of disagreement or insufficient information, they carried out a thorough consideration of the body of the articles (i.e. methodology and results), again independently, first, and, then, together, resulting in consensus. Then, whether to include the text or not was discussed, based on pre-determined criteria. The inclusion criteria used are as follows:

Only empirical articles across a variety of study designs may be included, so as to achieve rich data.

The participants should be over the age of 18 (e.g., students in higher education, college students, instructors, etc.)

Articles that provide an evaluation of student learning outcomes (via the use of games for pedagogical purposes) may also be included.

The resources should, mainly, consist of journal articles and conference papers, which, due to the peer review process, ensure a high quality of material to examine. Existing meta-analysis and systematic literature reviews should be included as well, in order to cross-validate the review findings.

The articles should be available in either English or French.

The articles should adhere to the objective of the study and the definition of the terms games and simulations as pedagogical applications.

Studies containing samples from higher education institutions should also be included. Conversely, research on the effects of games in primary or secondary education should be discarded.

The review should include games and simulations used in traditional, as well as in online environments.

Only peer-reviewed journal articles published between 2010 and 2016 should be included, as the intention is to include the most current research.

Several exclusion criteria, listed below, were also applied in this study:

Non-empirical studies or studies which solely describe the design of a learning environment.

Participants who are younger than 18 years old.

Non-GBL tools and entertainment games.

Book chapters -not only are books difficult to search for on databases, they are, also, hard to access as full texts. Additionally, books are not always subject to the same peer review process as scientific articles. Dissertations, theses, editorials, book reviews and reports are also excluded for similar reasons.

Articles that cannot be accessed as full texts are excluded.

Articles that do not match the research objectives.

Research focused on types of education other than higher education.

As mentioned above, articles published before 2010.

The following figure illustrates the inclusion and exclusion criteria (Fig. 2 ):

The inclusion and exclusion criteria

Application of these criteria resulted in an initial dataset, yielding 8859 studies, published between 2010 and 2016. The selected papers are derived from 67 academic journals representing a variety of disciplines. Most papers come from the scientific journal “Computers & Education”, while “British Journal of Educational Technology”, and “Simulation & Gaming” were the next two journals appearing with the most frequency. In the final stage, several meetings were organized between researchers to discuss the findings, and to decide on presentation.

The results show a steady increase in published papers discussing games from 2012 onwards. After systematically reviewing their abstracts, a final shortlist of 628 potential full text articles emerged. Two hundred and seventeen out of the 628 were excluded, primarily, due to undesirable focus (e.g. theoretical scenarios for using simulations in education). For each of the remaining 411 studies, the researchers identified and recorded some basic themes, for example, types of learning outcomes, effect or impact of game and simulation methods on learning goals, participants and settings, research questions, research methodology and results. Of these, 123 papers, which are found to contribute data, are selected for the review, whereas the remaining 288 articles are excluded, due to the fact that they are written in a language that the researchers do not understand, or because they are focused on a field other than higher education. The majority of these articles are published in scientific journals or conference proceedings, whereas 25 studies are either meta-analyses and/or systematic reviews. An outline of the entire review is depicted in the following figure (Fig. 3 ):

Research review methodological scheme

Data analysis and synthesis

The identified articles are analysed using a qualitative content analysis technique, which leads to a coding scheme, including a main category, three sub-categories and several associated topics related to the main categories. The researchers unanimously agree upon the coding that emerged from the analysis of the reviewed papers. To ensure inter-rater reliability (p) with respect to the quality of article coding procedures, a small random sample ( n  = 20) of the selected articles is coded in duplicate. The calculated reliability exceeds 93%, which is a high quality of agreement across coding categories. Furthermore, a review of mixed-methodology studies provides high-quality evidence, due to a combination of quantitative and qualitative elements in terms of methodological triangulation.

The researchers examined the studies from varying viewpoints. Firstly, they analysed the data set characteristics, such as the continent on which the studies are conducted, the subject discipline, the methodological research design, the types of games and simulations identified, and the time period in which the majority of the studies took place. The emphasis is on the analysis, measures, and design of the quantitative methodology (experimental, quasi-experimental, pre-test, post-test surveys, etc.), as well as the qualitative methods used in the reviewed surveys.

To sum up, the review studies are selected through a systematic process with pre-arranged criteria. There is no intended bias applied to the selected studies, and although the majority of studies come from Europe, this is simply the result of the systematic selection process.

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.

Continets where studies are conducted

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 ):

Representation of the game genres

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.

Years of published articles

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 ):

Subject disciplene

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 ):

Learning outcomes of Games/Simulations

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.

Research interest in the incorporation of games and simulations in higher education is constantly developing (Girard et al., 2013 ). The pedagogical shift, from lecture-centred to student-centred environments and the increasing use of games as innovative learning technologies, calls for a transformation in higher education. In this respect, games and simulations are expected to play a significant role in the learning process. In the present study, the focus is on the positive effects of games and simulations on university students’ learning outcomes. The reviewed papers are diverse in terms of research objectives, theoretical background, methodological avenues adopted, game genres, scientific domain or delivery platform, and various perspectives concerning cognitive, behavioural and affective outcomes employed. Many articles ( n  = 123) are identified, providing either empirical results or offering meta-analytic evidence.

There seems to be a lack of shared definitions or taxonomy necessary for a common classification, which, therefore, results in terminological ambiguity (Klabbers, 2009 ). The majority of GBL researchers compare the effectiveness of implementing web-based learning games to conventional instructional options (Shin et al., 2015 ).

Mapping the results, empirical evidence is identified with respect to cognitive learning outcomes including knowledge acquisition, conceptual application, content understanding and action-directed learning. Games and simulations are educational interventions, which create a supportive environment in which students may acquire knowledge across subjects and disciplines. Students have the opportunity to better understand theoretical concepts, provided that games are used as a supplement in traditional lecture-based courses. Additionally, simulations are often perceived as enjoyable learning tools, which require active and collaborative participation and contribute to the improvement of critical thinking and reasoning, higher-order- and metacognitive thinking. Simulations provide students the opportunity to observe the outcomes of their actions, and take responsibility for decision-making via problem-solving competencies, thus leading to a more active, transformative and experiential reception of knowledge.

Another important finding is that simulations have positive effects on both students and instructors. Positive outcomes exist when instructors set achievable learning goals, interact with students promoting knowledge, support, facilitate, and motivate them to construct new game-based knowledge (Kovalik & Kuo, 2012 ; Lameras et al., 2016 ). Instructors are encouraged to design games and simulations in order to make students fully aware of game activities, providing all the while continuous instructional guidance. These results generally confirm the findings from prior systematic reviews and meta-analyses. However, findings diverge slightly in Young et al.’s survey ( 2012 ), who claim that there is limited or no evidence about the effective implementation of games in the lecture-based curriculum.

This review also covers behavioural outcomes, mainly the development of social, emotional, and collaborative skills, helping students to foster strong relationships with peers, empowering them to collaborate and work in groups more efficiently, become organised, adapt to new tasks, and resolve emerging conflicts. Furthermore, reality-based scenarios and action-oriented game activities promote fruitful interactions and meaningful feedback, which leads to collaborative construction of knowledge. Overall, digital games and simulations urge students to interact not only with the game, but with their instructors and co-players as well. These results have been extensively covered in the literature review, with the majority of researchers agreeing with the current study’s results, confirming the positive effects of games and simulations on the behavioural level of learning outcomes (Bellotti et al., 2013 ; Tsekleves et al., 2014 ; Fu et al., 2016 ; Carenys & Moya, 2016 ).

However, although most reviews acknowledge the positive effects of games in behavioural outcomes, some reviewed studies contradict these positive findings, claiming that teamwork is a controversial issue when it comes to the improvement of knowledge sharing. The use of games seems to decrease opportunities for peer interaction and communication with instructors (Bolliger et al., 2015 ), whereas playing individually is sometimes considered better than working in a team (Merchant et al., 2014 ). Also, in some cases, games and simulations through collaborative activities distract students and hinder learning (Dankbaar et al., 2016 ).

The current review makes a significant contribution by investigating the affective outcomes when incorporating games and simulations in the curriculum, especially motivational and engagement outcomes, emotional development, satisfaction, attitude, emotion, self-assessment, and self-efficacy. Results show that games and simulations motivate, engage and promote effective learning goals by providing opportunities for learners to actively experience, practice, interact, and reflect in a collaborative, game-based, and learner-centred setting. The measures evaluating student attitudes reveal an increasingly positive trend towards games and simulations, especially in post-interventions (Bekebrede et al., 2011 ; Giovanello et al., 2013 ; Costa et al., 2014 ; Angelini, 2016 ; Geithner & Menzel, 2016 ).

To this end, there has been a purposeful highlighting of the instructor’s role as facilitator and motivator in this literature review. Through in-game activities and extended discussion, instructors promote student interaction and help them overcome the lack of understanding of content curriculum and achieve better learning outcomes. The literature also stresses the role of emotional development, which facilitates improvement of learning outcomes. Specifically, there seems to be a progression in student emotion, from negative feelings including uncertainty, anxiety, nervousness, and disappointment during pre-intervention, to positive feelings of satisfaction, confidence, excitement, enjoyment, effort, fascination, and enthusiasm during in-game and post-game interventions (Huang et al., 2010 ; Hummel et al., 2011 ; Liao & Wang, 2011 ; Terzidou et al., 2012 ; Woo, 2014 ; Liao et al., 2015 ).

Most of the pre-existing evidence is compatible with the findings of this systematic review (Sitzmann, 2011 ; Connolly et al., 2012 ; Wouters et al., 2013 ; Ritzhaupt et al., 2014 ; Gegenfurtner et al., 2014 ; Shin et al., 2015 ; Lameras et al., 2016 ; Carenys & Moya, 2016 ; Fu et al., 2016 ; Warren et al., 2016 ). Nevertheless, one study indicates that the overall positive perception of students depends on the different forms of games (Riemer & Schader, 2015 ), namely, simulations promote a less positive effect compared to quizzes and adventures. Some other studies diverge further in their findings, indicating either neutral (Rajan et al., 2013 ; Strycker, 2016 ; Franciosi, 2016 ) or negative student attitudes towards the use of games (Chen et al., 2010 ; Jiménez-Munguía & Luna-Reyes, 2012 ). Also, there are limited results on the effect of games on student self-efficacy, with one study demonstrating moderate post-training self-efficacy (Sitzmann, 2011 ).

Comparing the findings of the current study with the findings of previous systematic reviews and meta-analyses leads to an interesting discussion. The results of the present review illustrate that the majority of the revised articles focus on different genres of games and simulations. The mostly represented genres are virtual/online games and simulations since they can enhance learning in certain disciplines, such as Computer Studies. This finding is in agreement with most of the previous reviews (e.g. Clark et al., 2015 ; Carenys & Moya, 2016 ; Warren et al., 2016 ). Also, simulation games are found to be popular in this review, due to the fact that they are implemented in authentic learning environments, namely in Health Sciences and Biology. Also, in this study, a great representation of role - playing games and business simulation games are obviously resulted from the previous articles, due to the fact that they are implemented in specific academic disciplines, such as Business Management and Marketing. Nevertheless, in this review, serious games are not represented as much as in other reviews (e.g.Tsekleves et al., 2014 ; Fu et al., 2016 ).

Additionally, this study concentrates on the positive effects of games and simulations on learning outcomes, a finding that is compatible with previous reviews (e.g. Bellotti et al., 2013 ; Lameras et al., 2016 ; Clark et al., 2015 . This review confirms that games and simulations contribute to cognitive learning outcomes, including knowledge acquisition, conceptual application, content understanding, and action-directed learning. Other previous reviewers echoed these findings (Smetana & Bell, 2012 ; Shin et al., 2015 ; Wouters et al., 2013 ; Fu et al., 2016 ) emphasizing the important role of games in knowledge acquisition and content understanding. It has been illustrated that university students benefit from the incorporation of games into the learning process, if used as a supplement in traditional lectures, a finding that complies with other reviews (Sitzmann, 2011 ; Wouters et al., 2013 ). However, simulations’ implementation is influenced by instructors’ guidance and motivation, as these factors encourage faculty to design simulations to achieve learning outcomes.

This review also sheds light on behavioural outcomes of using games in instructional design. The emphasis is on the positive effects, namely the development of social and soft skills, emotional skills, the empowerment of collaboration with peers, and the promotion of interaction and feedback, findings that are in line with past reviews (Shin et al., 2015 ; Carenys & Moya, 2016 ). Despite the positive behavioural effects of utilizing games, some reviews find collaboration and teamwork as a hindrance for learning. The application of games seems to decrease peer interaction and communication with faculty, whereas in Merchant et al.’s review ( 2014 ), playing individually is more preferable than playing collaboratively. The current review concludes by highlighting the affective outcomes, and the emphasis is given on motivational and engaging factors that lead to emotional development, satisfaction, self-efficacy and self-assessment, findings that are also documented in other reviews (Sitzmann, 2011 ; Hsu et al., 2012 ; Tsekleves et al., 2014 ).

To conclude, this review discusses the multitude of surveys on the cognitive, behavioural, and affective outcomes related to the use of playing games and simulations in higher education. The multi-dimensional analysis of the empirical data provides a framework for understanding the major outcomes of GBL. Despite the significant benefits in learning outcomes highlighted in this paper, the high cost of designing games and simulations is still a significant challenge. To overcome this cost barrier, governments, researchers, instructors, and game designers should collaborate to find affordable solutions, for enabling the development of games and simulations. Since this review does not concern itself with advanced aspects of learning, the focus should next turn to a metacognitive-oriented survey, which will study the promotion of metacognitive skills in students, such as self-regulation, self-reflection, self-awareness, evaluation, planning, building on the ideas of others, debating, and so forth.

Future research

Considering the above discussion points, and the importance of games and simulations as derived from the relevant literature, some suggested avenues for future research are as follows:

Researchers should focus on applying the relevant theoretical frameworks, such as cognitivism, constructivism, and socio-cultural perspectives to cognitive, behavioural and affective outcomes, respectively.

More research should be conducted investigating gender issues with respect to the effectiveness of games on developmental aspects of behaviour, such as scaffolding and immersion, to counteract the present gap in the existing literature.

Comparative surveys should be included with a design focused on different target groups (adult students, or K-12 students in laboratory conditions).

Evaluation models via a mixed-method design are encouraged, especially to investigate how game designers could tailor game designs to applying different learning preferences and styles.

University instructors should take a more active role in the alignment of games with the curriculum ensuring that games and simulations are implemented in a blended learning module (face-to-face, online material, etc.), or even acting as games masters, scaffolding virtual experiences to university learners.

Faculty should design games with a view to multiplayer cooperation to achieve effectiveness in learning outcomes. Students should also be involved as co-designers, recommending innovative ideas and radical approaches in an effort to meet their own needs. An innovative approach is the adoption of metagames (Young et al., 2012 ), which consist of additional learning resources (blogs, wikis, etc.) encouraging collaboration between players.

This study makes a significant contribution to research, since no other literature review or meta-analysis has been conducted so far investigating educational and web-based games and simulations with such an extensive subject and discipline coverage in higher education. Today’s demand for student-centred teaching methods to develop highly qualified learners, capable of learning in an active and collaborative environment, calls for the deployment of game-based activities and simulations that will enable them to face the challenges of the dawning era.

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Acknowledgements

The research was sponsored by Laureate International Universities, through the “David Wilson Award for Excellence in Teaching and Learning”, won by Dr. Dimitrios Vlachopoulos (2015-2017).

Authors' contributions

DV conceived the study. AM conducted the literature review and prepared the summaries and critical reflection on the corresponding literature. DV participated in the design of the study and analysis. AM participated in the preparation of the article's structure, graphs, and reference list. Both authors read and approved the final manuscript.

Competing interest

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Vlachopoulos, D., Makri, A. The effect of games and simulations on higher education: a systematic literature review. Int J Educ Technol High Educ 14 , 22 (2017). https://doi.org/10.1186/s41239-017-0062-1

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• Game-based learning
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The MIT Game Lab has a long history of innovative research that spans game culture to design practice. Below are some highlights of our work. See specific pages in the pull down menu for more detailed information on some of them.

Games & Colonialism

2017-: mikael jakobsson (co-pi), mary flanagan (co-pi).

What does the history of colonialism-themed board games look like, and what can it tell us about the situation today? What does it mean to present these historical moments in such a lavish form and then let these artifacts serve as centerpieces to gather around for social interaction at board game cafes, meetups, and conventions? This greater project includes Playing Oppression , a forthcoming book to be published by MIT Press; Orderly Adventures, in which we play and analyze games with colonialist themes; and Creating Counter-Colonial Games, a series of workshops to prototype games through cultural engagement with people affected by the colonialist endeavor.

Diversity and Inclusion in Esports and Gaming

2015-: t.l. taylor.

Launched in 2015, AnyKey was co-founded by Dr. T.L. Taylor and Dr. Morgan Romine (with support from Intel and ESL) with the goal of building a more inclusive and accessible esports world for all. Since that inception, AnyKey has become the leading advocacy organization for inclusion and diversity in competitive gaming & live streaming. It now operates as a non-profit and Dr. Taylor has transitioned from being the Director of Research to Chair of the Advisory Board.

Playful Augmented Reality Audio Design Exploration

2018-2019: mikael jakobsson & philip tan.

The focus of this project was to explore the potential of audio augmented reality (AR) technology through design research methodology, particularly exploratory prototyping. Going into this, we understood that location-based audio AR allows the potential for telling stories using the players lived world, through innovative use of the affordances of mobile phone devices, particularly GPS. We also considered audio AR as a means of playing with sound and music. Utilizing the accelerometers of the Bose AR glasses and connected mobile device, body movement can be linked to the players’ own music collection or a music generation engine.

Our work culminated in the discovery of what we are calling locomotion-based gameplay, a modification to the assumptions that occur when considering location- based gameplay. From our explorative work, locomotion-based gameplay arises from the affordances and limitations of current audio AR technology. It considers a person’s movement through space as important, more so than their precise location. Locomotion also implies whole body movement through gestures including the nod of a head and the tap of a toe, not just the vector of movement on a map. These gestures are ephemeral and contain multiple meanings dependent on context and mood. We believe more work in discovering this style of gameplay would be fruitful, for purposes of art and entertainment, for education and tourism, and other currently unforeseen use cases.

Intimate Worlds: Reading for Intimate Affects in Contemporary Video Games

2016-2018: kaelan doyle-myerscough (s.m., comparative media studies, 2018).

When we think of pleasures to be found in video games, we often talk about power, control, agency, and fun. But to center these pleasures is to privilege certain stories, players, actions and possibility spaces. This thesis uses the framework of intimacy to closely examine three games for their capacity to create pleasure in vulnerability, the loss of control, dependence on others, and precarity.

Drawing from Deleuzian affect theory and feminist, queer and posthuman theorists, I read for intimate affects in the formal, aesthetic, proprioceptive and structural elements of Overwatch , The Last Guardian and The Legend of Zelda: Breath of the Wild . Ultimately, I argue two points: that video games have a unique capacity to generate intimate affects, and that my games of choice push us to rethink our assumptions about what constitutes intimacy more broadly.

When All You Have is a Banhammer: The Social and Communicative Work of Volunteer Moderators

2016-2018: claudia lo (s.m., comparative media studies, 2018).

The popular understanding of moderation online is that moderation is inherently reactive, where moderators see and then react to content generated by users, typically by removing it; in order to understand the work already being performed by moderators, we need to expand our understanding of what that work entails. Drawing upon interviews, participant observation, and my own experiences as a volunteer community moderator on Reddit, I propose that a significant portion of work performed by volunteer moderators is social and communicative in nature. Even the chosen case studies of large-scale esports events on Twitch, where the most visible and intense tasks given to volunteer moderators consists of reacting and removing user-generated chat messages, exposes faults in the reactive model of moderation. A better appreciation of the full scope of moderation work will be vital in guiding future research, design, and development efforts in this field.

Recasting Player Two

2016-2017: mikael jakobsson, claudia lo, kaelan doyle myerscough, richard eberhardt & dozens of game designers from near and far.

The game development industry is currently on a mission to include “non-gamers” in local co-op games. Within the development community and among players, these games are said to have a “girlfriend mode.” Developers often cast player one as an expert player in their own image, while player two is a projection of antiquated gender stereotypes who has less agency and control over their play experience. This type of interaction would be better described as mansplaining in motion. This project consists of a series of workshops with participants from the game development community, where we not just discuss and spread awareness of what is problematic with current games and development practices, but work together in creating better alternatives.

OpenRelativity

2012-2016: gerd kortemeyer, philip tan, zach sherin, ryan cheu, & steven schirra.

OpenRelativity is an open-source toolkit to simulate effects of special relativity by varying the speed of light, developed to help people create, test, and share experiments to explore the effects of special relativity. Developed by the MIT Game Lab, it contains open-source code for public use with the free and paid versions of the Unity engine. The toolkit was developed during the creation of the game A Slower Speed of Light.

Gender and Systems of Warm Interaction in Digital Games

2014-2016: kyrie caldwell (s.m., comparative media studies, 2016).

This thesis considers the ways in which digital game mechanics (interactive inputs) contribute to games’ worldbuilding. In particular, this work is concerned with the replication and reinforcement of problematic gender roles through game mechanics that express positive (“warm”) interactions between characters, namely healing, protection, and building relationships. Characters who are women and girls are often associated with physical weakness, nature-based magic, and nurturing (or absent) personalities, whereas characters who are men and boys often protect women through physical combat, heal through medical means, and keep an emotional distance from others. Relationships built through game mechanics rely on one-sided agency and potential that renders lovers and friends as characters who exist to support the player character in achieving the primary goals of the game. Even warm interactions in games carry negative, even potentially violent and oppressive, representations and that there is thusly a need for design interventions on the mechanical level to mitigate violence in game worlds and the reinforcement of negative real world stereotypes.

E-sports Broadcasting

2014-2015: jesse sell (s.m., comparative media studies, 2015).

Situating e-sports broadcasting within the larger sports media industrial complex, discussing e-sportscasters, and investigating the economics behind the growing e-sports industry. E-sports, often referred to as competitive or professional gaming, stands as a prime example of the merger of work and play. A growing body of literature has started focusing on this pastime turned profession. As more professionals enter the scene and audiences continue to grow, e-sports broadcasters look towards older models of broadcasting to inform their own style. This reapplication of former conventions stands in contrast to the trends in the larger sports media trajectory. E-sports broadcasting is largely informed by traditional sports broadcasting, yet remains unable to fully capture the success of the global sports industry. On-air talent, once informed solely by traditional sportscasters are now looking to their fellow e-sportscasters to create something new. Revenue streams which form the foundation of the sports industry are making their way into e-sports but not in the way that one might expect.

MIT Overseer: Improving Observer Experience in Starcraft 2

2013-2015: philip tan & nick mohr.

The MIT Overseer project aims to provide casters with real-time graphics to help them tell the story of a game while it is in progress. We are trying out several different ways of displaying what happened in the past of a single game and anticipating what might happen in the near future.

Subversive Game Design and Meaningful Conflict

2012-2013: konstantin mitgutsch & steven schirra.

Movers & Shakers is used as a research tool to explore how a social component influences experiences in serious games. In addition subversive game design elements are implemented in the game to foster the players’ thinking process and to get them out of unquestioned routines. In the game the players are challenged to give up their prior egoistic goals to reach their common goal – to save the world. In a nutshell, the game shifts from a competitive to a collaborational gameplay – once the players start communicating.

Playstyle Motivation Explorations

2012-2013: todd harper.

Across game genres and communities, there are as many styles of play as there are players, from the highly competitive “powergamer” to the MMO fan who’s content to just take in the scenery and everything in between. Fugue is a game that asks: what are some of the motivations behind these styles? Do players reflect themselves — or a desired projection of the self — through playstyle? Or does the shape and context of the game itself direct such decisions? In order to explore these questions, we created a small, controlled gamespace that gives players an opportunity to express themselves via play.

Procedural Puzzles as a Design Tool for Games

2011-2013: alec thomson, clara fernández-vara.

Puzzledice is a set of tools and programming libraries for procedurally generating puzzles for a wide variety of games. These tools, developed by Alec Thomson at the MIT Game Lab from 2011-2013, are the result of multiple iterations of research and were used to develop Stranded in Singapore during the 2011 summer session of the Singapore-MIT GAMBIT Game Lab. Puzzledice is the result of research into how general purpose procedural puzzles can be used as a tool by game designers. These tools were designed to meet the following three goals: Solvability, Generality, and Usability.

Televisual Sports Videogames

2012-2013: abe stein (s.m., comparative media studies, 2013).

Over the three decade long history of sports videogame development, design conventions have lead to the emergence of a new sports game genre: the televisual sports videogames. These games, which usually simulate major professional or college sports, look and sound like television, and they use televised sports as a reference point for players. This thesis takes a critical look at how these televisual sports videogames are situated in the broader sports media industrial complex of North America, while also considering how the televisual design of these games is meaningful for fans of sports. Specifically, the text looks at how sports videogames reflect or reinforce dominant ideologies of hegemonic sports culture. Building on critical theories in sports studies, and through critical close readings of videogame texts, this thesis explores the relationship between sports television production, and sports videogames, with a focus on features that are found in both. Features such as introductory sequences, audio commentary, in-game advertising, news tickers, and instant replay are all commonly found in both sports television and sports videogames.

Purposeful Games for Social Change

2011-2012: konstantin mitgutsch & narda alvarado.

“ Purposeful Games for Social Change ” is a list of serious games designed to foster social change/justice or to raise awareness. This list was created in order to create the Purposeful Games Framework , a tool used to assess the cohesiveness in design of serious games.

Singapore-MIT GAMBIT Game Lab

The Singapore-MIT GAMBIT Game Lab was a six-year research initiative that addressed important challenges faced by the global digital game research community and industry, with a core focus on identifying and solving research problems using a multi-disciplinary approach that can be applied by Singapore’s digital game industry. The Singapore-MIT GAMBIT Game Lab focused on building collaborations between Singapore institutions of higher learning and several MIT departments to accomplish both research and development.

Research topics explored included artificial intelligence, game design, computer graphics and animation, character design, procedurally generated content, interactive fiction, narrative design, and video game production. Game prototypes were made for these research topics during the GAMBIT summer internship program, many of which won international recognition at festivals like IndieCade and the Independent Games Festivals held at GDC and GDC China, as well as academic conferences such as Meaningful Play and Foundations of Digital Games.

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• 2021 — Duncan Kampert  (Masters Thesis) Mimicking the Human Approach in the Game of Hive Supervised by Ana-Lucia Varbanescu and Matthias Müller-Brockhausen and Aske Plaat
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• 2020 — Romy Koch  (Masters Thesis) Losing yourself; the bidirectional influence of the player and the role in table top role playing games Supervised by Max J. van Duijn and Marcello A. Gómez-Maureira
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• 2019 — Giulio Barbero  (Masters Thesis) Intentionality and Engagement: The effects of video game engagement on mindreading performance Supervised by Max J. van Duijn and Marcello A. Gómez-Maureira
• 2019 — Lotte van der Kamp  (Masters Thesis) First Person vs. Third Person perspective in a digital Memory Palace Supervised by Tessa
• 2018 — Yanni Xiong  (Masters Thesis) Gamified Learning: Using Narrative to Enhance Second Language Learning Supervised by Fons J. Verbeek and Marcello A. Gómez-Maureira

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The effectiveness of intervention with board games: a systematic review

• Shota Noda   ORCID: orcid.org/0000-0001-7376-7630 1 ,
• Kentaro Shirotsuki 2 &
• Mutsuhiro Nakao 3  

BioPsychoSocial Medicine volume  13 , Article number:  22 ( 2019 ) Cite this article

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To examine the effectiveness of board games and programs that use board games, the present study conducted a systematic review using the PsycINFO and PubMed databases with the keywords “board game” AND “trial;” in total, 71 studies were identified. Of these 71 studies, 27 satisfied the inclusion criteria in terms of program content, intervention style, and pre–post comparisons and were subsequently reviewed. These 27 studies were divided into the following three categories regarding the effects of board games and programs that use board games: educational knowledge (11 articles), cognitive functions (11 articles), and other conditions (five articles). The effect sizes between pre- and post-tests or pre-tests and follow-up tests were 0.12–1.81 for educational knowledge, 0.04–2.60 and − 1.14 – − 0.02 for cognitive functions, 0.06–0.65 for physical activity, and − 0.87 – − 0.61 for symptoms of attention-deficit hyperactivity disorder (ADHD). The present findings showed that, as a tool, board games can be expected to improve the understanding of knowledge, enhance interpersonal interactions among participants, and increase the motivation of participants. However, because the number of published studies in this area remains limited, the possibility of using board games as treatment for clinical symptoms requires further discussion.

A board game is a generic term for a game played by placing, moving or removing pieces on a board and that utilizes a game format in which pieces are moved in particular ways on a board marked with a pattern. Examples of board games include chess, Go, and Shogi. Research involving chess, which is played by two players on a board with 64 black and white squares and 16 pieces for each player [ 1 ], has contributed to the theoretical development of cognitive psychology [ 2 ]. For example, Burgoyne et al. [ 3 ] conducted a meta-analysis and demonstrated that chess skills are significantly and positively correlated with four broad cognitive abilities: fluid reasoning, comprehension-knowledge, short-term memory, and processing speed. Similarly, a meta-analysis by Sala and Gobet [ 4 ] found that chess instruction moderately improves the cognitive skills of children.

In contrast, Go is ancient board game that consists of simple elements (a line and circle, black and white colors, and stone and wood materials) combined with simple rules that generate subtleties that have enthralled players for millennia [ 5 ]. Go is a famous board game in Asian countries and has been used as a tool for increasing or maintaining brain activity for more than 5000 years [ 6 ]. It is currently gaining popularity in the United States and Europe [ 6 ], and Kim et al. [ 7 ] has suggested that playing Go might be effective for children with attention-deficit hyperactivity disorder (ADHD) due to its activation of hypo-aroused prefrontal cortical function and the enhancement of executive function. Lin et al. [ 8 ] conducted an intervention study using GO in patients with Alzheimer’s disease and showed that playing Go can also improve the clinical symptoms associated with depression, anxiety, and Alzheimer’s Disease. Similar to chess and Go, Shogi is a board game for two players that is also referred to as Japanese chess. Wan et al. [ 9 ] conducted an experiment with undergraduate students and found that Shogi training is related to activation in the head of the caudate nucleus. Taken together, the abovementioned findings suggest that chess, Go, and Shogi are effective ways to achieve various outcomes.

There are many board games other than chess, Go, and Shogi. For example, educational board games, such as Kalèdo, have been used to improve nutrition knowledge and promote a healthy lifestyle for children [ 10 ]. Zeedyk et al. [ 11 ] investigated the effectiveness of a board game for increasing knowledge about road safety and danger and found that the interventions were significantly effective in increasing children’s knowledge. Although the impacts of various board games have been previously examined, their effects have yet to be comprehensively reviewed. As a result, the functions and effects of board games as a whole remain unclear. Thus, the present review systematically examined the effectiveness of board games and programs that use board games.

For the present review, a literature search based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses [ 12 ] using the PsycINFO and PubMed databases was conducted to collect findings on the effectiveness of board games and programs using board games. The keywords for the literature search were “board game” AND “trial,” and the date selected was September 13th, 2018. The search identified nine studies from PsycINFO and 32 studies from PubMed. The first author of this review performed a manual search that identified six additional studies, and 24 additional studies were extracted from Sala & Gobet [ 4 ], which conducted a meta-analysis about the benefits of chess. Duplicate studies were deleted and, ultimately, a list of references consisting of 66 articles was prepared.

The inclusion criteria for the present study were as follows: (a) studied the effects of board games and programs using board games on psychological and educational outcomes, (b) included pre–post comparative tests, (c) used an interventional or experimental rather than a review approach, (d) had full text availability, (e) was written in English, and (f) was peer reviewed. A screening to remove articles that were judged not to satisfy any of the criteria from (a) to (f) was conducted, and 29 articles were extracted. Additionally, one study was excluded because it did not use a traditional board game (it used a Wii Fit balance board), and one study was excluded because the content details of the board game were unclear. Ultimately, 27 articles were selected for the present study; the literature search process is presented in Fig.  1 .

PRISMA flow chart of the study selection process

Furthermore, in the studies where the means and standard deviations of the intervention group are described, Cohen’s d was calculated to assess effect sizes between pre- and post-tests or between pre-tests and follow-up tests with the following formula based on Cohen [ 13 ].

Note: M 1 and M 2 are the mean of the intervention group at the pre-test session and the post-test session or follow-up test session, respectively. SDpooled is the pooled standard deviation ( SD 1 is the standard deviation of the intervention group at the pre-test session and SD 2 is the standard deviation at the post-test session or follow-up test session). n 1 is the number of samples at the pre-test session. n 2 is the number of samples at the post-test session or follow-up test session.

In the studies where the means and standard deviations are described in the intervention group and the other groups, Cohen’s d was also calculated to assess effect sizes compared to the other groups (control groups) with the following formula based on Sala et al. [ 14 ].

Note: Mgi and Mgc are the mean gain of the intervention group and the control group (other group) at the post-test session or at the follow-up test session, respectively, and SDpooled-pre is the pooled standard deviation of the two pre-test standard deviations. SDpre.i is the standard deviation of the intervention group at the pre-test session, and SDpre.c is the standard deviation of the control group at the pre-test session. ni is the number of samples in the intervention group who received the pre-test session and post-test session or the pre-test session and follow-up test session. nc is the number of samples in the control group who received the pre-test session and post-test session or the pre- test session and follow-up test session.

According to Cohen [ 13 ], Cohen’s d of approximately 0.20 is small, 0.50 medium, and 0.80 large.

Results and discussion

The effect of interventions with board games.

In the present review, the selected studies were divided into the following three categories regarding the effects of board games and programs that use board games: educational knowledge (11 articles), cognitive functions (11 articles), and other conditions (five articles).

An overview of the findings about the effects of board games and programs that use board games related to educational knowledge is shown in Table  1 [ 10 , 11 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Board games in this category were used for the purpose of improving educational knowledge, and the effect sizes (Cohen’s d) between pre- and post-tests or between pre-tests and follow-up tests ranged from 0.12 to 1.81 and between the mean gain of the main intervention group and the other groups ranged from 0.81 to 0.93 and − 1.84 to − 1.65.

An overview of the findings about the effects of board games and programs that use board games on cognitive functions is shown in Table  2 [ 6 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. This category included board games such as Go, Ska, and chess, and the effect sizes (Cohen’s d) between pre- and post-tests of cognitive function ranged from 0.04 to 2.60 and − 1.14 to − 0.02. The effect size of the exacerbation was calculated in only the chess group of Sala et al. [ 27 ]. The effect sizes (Cohen’s d) between the mean gain of the main intervention group and the other groups ranged from 0.06 to 2.36 and − 1.38 to − 0.22.

An overview of the findings about the effects of board games and programs that use board games on other conditions is shown in Table  3 [ 7 , 8 , 34 , 35 , 36 ]. This category addressed the impacts of board games on physical activity, anxiety, ADHD symptoms, and the severity of Alzheimer’s Disease. The effect sizes (Cohen’s d) between pre- and post-tests or between pre-tests and follow-up tests ranged from 0.06 to 0.65 for physical activity and from − 0.87 to − 0.61 for ADHD symptoms.

Board games and educational knowledge

Eleven studies that used board games to increase educational knowledge were selected for this review. The present findings showed that board games influence educational knowledge and concomitant outcomes, with the effect sizes for educational knowledge ranging from very small to large.

Board games can be used as a tool to encourage learning. In previous studies, specialized board games aimed at improving knowledge in the field of education were targeted and subsequently developed and investigated. For example, Wanyama et al. [ 16 ] conducted a study of the Make a Positive Start Today game, which is a board game aimed at improving knowledge about human immunodeficiency virus (HIV) and sexually transmitted infections (STIs). Similarly, Kalèdo is an educational board game used to increase nutrition knowledge [ 10 , 19 , 21 ]. It has been shown that these board games contribute to increasing knowledge related to each particular field.

Board games are also efficacious for goals other than increasing knowledge. According to Charlier and De Fraine [ 22 ], board games can be an enjoyable and motivational method for learning content and enhancing group interactions, competition, and fun. Martins et al. [ 18 ] reported that board games teach educational content in a playful and enjoyable way and involve interactions with family and friends; thus, they favor knowledge acquisition by enabling exchanges of experiences and learning. Furthermore, Wanyama et al. [ 16 ] showed that, as a method of health education, board games increase the acquisition of knowledge as well as result in more positive experiences than do health talks among both participants and facilitators. Amaro et al. [ 10 ] found that class teachers noted improvements in student interest and appreciation of the board game. Taken together, these findings suggest that board games may improve the motivation of participants. Furthermore, Karbownik et al. [ 20 ] showed that a board game was warmly welcomed by students; in their opinion, it facilitated clinical thinking and peer communication. Therefore, board games may also have a positive influence on interpersonal interactions among participants.

Based on the above findings, board games can be used as a tool to encourage learning as well as to enhance motivation and interpersonal interactions. In clinical treatment, it is important to increase motivation because low motivation to cooperate with a particular intervention may lead to a patient dropping out of treatment or to interference with the therapeutic effects. Based on the above findings, the use of board games may help increase the benefit of treatment for less motivated patients.

Board games and cognitive functions

In the present review, 11 of the assessed studies investigated the effects of board games and programs that use board games on cognitive functions. These studies used Go, chess, and Ska, which are not educational games but abstract strategy games. Studies investigating the use of Go found that older adults experiencing cognitive decline and/or living in nursing homes showed improvements in attention and working memory after regularly playing the game [ 6 ]. Studies assessing the use of Ska found that the game appeared to enhance the cognitive functioning of older adults in terms of memory, attention, and executive function [ 24 ]. Studies evaluating chess showed that training with the game improved the planning ability of patients with schizophrenia and the mathematical ability of children [ 25 , 26 ]. But, Sala & Gobet [ 27 ] indicated that interventions that use chess are not significantly different from interventions that use checkers and regular school activities that address the mathematical and metacognitive ability of children.

The effect sizes for cognitive functions ranged from very small to large, but the effect size of exacerbation on metacognitive ability was shown in the chess training of Sala & Gobet [ 27 ]. The number of studies included in this category was relatively limited. Further investigations will be necessary to clarify the more detailed effects of board games on cognitive function. Articles about Shogi were not selected for this category in the present review. Because Shogi was also included with the abstract strategy games, this may influence cognitive functions. In the future, it will be necessary to use intervention studies to examine the effects of additional types of board games, including Shogi, on cognitive function.

Board games and other conditions

The “other studies” category in the present review included five studies that examined the effects of board games on physical activity, physical and psychological outcomes, ADHD symptoms, and the severity of Alzheimer’s Disease. Mouton et al. [ 34 ] showed that a giant board game intervention for nursing home residents led to significant increases in ambulatory physical activity, daily energy output, quality of life, balance and gait, and ankle strength. The effect sizes in the present review of studies related to physical activity ranged from very small to medium. Fernandes et al. [ 35 ] reported that board games used as educational preoperative materials decreased the preoperative anxiety of children. Additionally, the use of board games contributed to improvements in the ADHD symptoms of children [ 7 , 35 ]. The effect sizes for ADHD symptoms in the present review ranged from medium to large. Lin et al. [ 8 ] showed that playing Go improved the symptoms of depression and anxiety and ameliorated the manifestations of Alzheimer’s Disease. Although a study by Barzegar and Barzegar [ 37 ] was not selected for the present review because it was a case report, these authors found that playing chess prevented panic attacks and contributed to the amelioration of this condition. Taken together, these findings indicate that board games might be an effective complementary intervention for the treatment of the clinical symptoms of ADHD and Alzheimer’s Disease.

In terms of Alzheimer’s disease, board games may also play a role in the prevention of the onset of this disorder. According to an epidemiological survey in Japan [ 38 ], the prevalence rates of dementia in 1980, 1990, and 2000 were 4.4, 4.5, and 5.9, respectively, for all types of dementia and 1.9, 2.5, and 3.6, respectively for Alzheimer’s Disease. In Japan, the number of patients with Alzheimer’s disease has increased, and the prevention of this disorder is a problem that must be addressed. Because playing board games ameliorates the manifestations of Alzheimer’s disease [ 8 ], these types of games may contribute to the prevention of this disorder. However, the number of studies in the present review that investigated the effects of board games on clinical symptoms was quite small, and further research will be required.

Possible clinical applications of board games

It is also important to note that board games can be played without the use of language. Language-based therapies may not be appropriate for people with underdeveloped linguistic functions, such as children and patients with speech disorders. However, board games may be a viable treatment option for these populations. In the present review, the subjects in 18 of the assessed studies included children, which is a group that is still developing linguistic functions and is more likely to have poor knowledge about diseases. The present review also revealed that board games and programs that use board games are effective for achieving various outcomes for children, including increasing educational knowledge, enhancing cognitive functions, and decreasing anxiety and the severity of ADHD. Furthermore, board games can be an enjoyable and motivational tool for children [ 22 ]. Based on these findings, it is possible that board games can be a useful intervention for children in particular because such games can be expected to result in the maintenance and promotion of health and the prevention of disease.

Limitations and future directions

Several limitations of the present study must be considered. First, the number of studies assessed in the present review was rather limited. Therefore, further investigations of the effects of board games will be necessary. Second, many of the papers selected for the present review examined the effectiveness of board games by comparing pre- post intervention for a single group or by comparing with a control group without intervention. These research designs do not control for the possibility of placebo effects. Intervention studies must include an active control group to control for possible placebo effects [ 39 ], thus it will be necessary to compare the effect of board game groups and active control groups in future research. Third, in the articles selected for the present review, some studies were conducted with relatively small sample sizes. In cases in which the sample size is small, there is the possibility of increased sampling error. In order to reduce sampling error, it is necessary to do a power analysis to set an appropriate sample size in intervention studies. In addition, it is desirable that multiple assessment indicators be used to examine the effects of board games in various perspectives and to reduce measurement errors.

Conclusions

The present systematic review showed that board games and programs that use board games have positive effects on various outcomes, including educational knowledge, cognitive functions, physical activity, anxiety, ADHD symptoms, and the severity of Alzheimer’s Disease. Additionally, board games were shown to contribute to improving these variables, enhancing the interpersonal interactions and motivation of participants, and promoting learning. Taken together, these findings suggest that board games would be an effective complementary therapy that would contribute to the improvement of many clinical symptoms.

Availability of data and materials

Not applicable.

Abbreviations

Attention-deficit hyperactivity disorder

cluster randomized controlled trial

Human immunodeficiency virus

Randomized controlled trial

Sexually transmitted infections

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Acknowledgements

The authors appreciate the support of the members of the Japan Shogi Association and the officials in Kakogawa City for conceptualizing health promotion models using board games, such as Shogi and other traditional games.

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Noda, S., Shirotsuki, K. & Nakao, M. The effectiveness of intervention with board games: a systematic review. BioPsychoSocial Med 13 , 22 (2019). https://doi.org/10.1186/s13030-019-0164-1

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Simply put Game Theory studies decision-making, where the outcome of each "player" depends on the actions of other "players".

The dictionary describes game theory as "The branch of mathematics concerned with the analysis of strategies for dealing with competitive situations where the outcome of a participant's choice of action depends critically on the actions of other participants.

Despite focusing on mathematics, Game Theory has been used in various fields such as social sciences, business and biology.

While Game Theory is a useful tool to analyze and solve problems, it does have problems.

• Game Theory relies on simplified models and on a simplified structure.
• Game Theory  has a key assumption that players will react rationally and have complete and accurate information.

For more information  see " The Limitations of Game Theory ".

Examples of Game Theory

Game Theory  is how and why people make decisions, and has applications in many different fields. Below are some examples of Game Theory:

• Prisoner's Dilemma
• Volunteer's Dilemma
• War of Attrition
• Rock Paper Scissors

Video games rarely incorporate Game Theory.  However, studies have been done on how to incorporate game theory into computer games and how it could be used in game design.

Here are some articles and sites about game theory and video games :

“ Game Theory in Video Games Explained (Essential Tips for New Designers),” October 25, 2017. https://www.gamedesigning.org/learn/game-theory/

Taylor, Mark, Mike Baskett, Denis Reilly, and Somasundaram Ravindran. “ Game Theory for Computer Games Design .” Games and Culture 14, no. 7–8 (November 2019): 843–55. https://doi.org/10.1177/1555412017740497 .

Yin, Haoran, Jiaxiang Sun, and Wei Cai. “ Honest or Dishonest? Promoting Integrity in Loot Box Games Through Evolutionary Game Theory .” IEEE Transactions on Computational Social Systems , 2024, 1–12. https://doi.org/10.1109/TCSS.2024.3376718 .

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Using ideas from game theory to improve the reliability of language models

Imagine you and a friend are playing a game where your goal is to communicate secret messages to each other using only cryptic sentences. Your friend's job is to guess the secret message behind your sentences. Sometimes, you give clues directly, and other times, your friend has to guess the message by asking yes-or-no questions about the clues you've given. The challenge is that both of you want to make sure you're understanding each other correctly and agreeing on the secret message.

MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have created a similar "game" to help improve how AI understands and generates text. It is known as a “consensus game” and it involves two parts of an AI system — one part tries to generate sentences (like giving clues), and the other part tries to understand and evaluate those sentences (like guessing the secret message).

The researchers discovered that by treating this interaction as a game, where both parts of the AI work together under specific rules to agree on the right message, they could significantly improve the AI's ability to give correct and coherent answers to questions. They tested this new game-like approach on a variety of tasks, such as reading comprehension, solving math problems, and carrying on conversations, and found that it helped the AI perform better across the board.

Traditionally, large language models answer one of two ways: generating answers directly from the model (generative querying) or using the model to score a set of predefined answers (discriminative querying), which can lead to differing and sometimes incompatible results. With the generative approach, "Who is the president of the United States?" might yield a straightforward answer like "Joe Biden." However, a discriminative query could incorrectly dispute this fact when evaluating the same answer, such as "Barack Obama."

So, how do we reconcile mutually incompatible scoring procedures to achieve coherent, efficient predictions? 

"Imagine a new way to help language models understand and generate text, like a game. We've developed a training-free, game-theoretic method that treats the whole process as a complex game of clues and signals, where a generator tries to send the right message to a discriminator using natural language. Instead of chess pieces, they're using words and sentences," says Athul Jacob, an MIT PhD student in electrical engineering and computer science and CSAIL affiliate. "Our way to navigate this game is finding the 'approximate equilibria,' leading to a new decoding algorithm called 'equilibrium ranking.' It's a pretty exciting demonstration of how bringing game-theoretic strategies into the mix can tackle some big challenges in making language models more reliable and consistent."

When tested across many tasks, like reading comprehension, commonsense reasoning, math problem-solving, and dialogue, the team's algorithm consistently improved how well these models performed. Using the ER algorithm with the LLaMA-7B model even outshone the results from much larger models. "Given that they are already competitive, that people have been working on it for a while, but the level of improvements we saw being able to outperform a model that's 10 times the size was a pleasant surprise," says Jacob. 

"Diplomacy," a strategic board game set in pre-World War I Europe, where players negotiate alliances, betray friends, and conquer territories without the use of dice — relying purely on skill, strategy, and interpersonal manipulation — recently had a second coming. In November 2022, computer scientists, including Jacob, developed “Cicero,” an AI agent that achieves human-level capabilities in the mixed-motive seven-player game, which requires the same aforementioned skills, but with natural language. The math behind this partially inspired the Consensus Game. 

While the history of AI agents long predates when OpenAI's software entered the chat in November 2022, it's well documented that they can still cosplay as your well-meaning, yet pathological friend. 

The consensus game system reaches equilibrium as an agreement, ensuring accuracy and fidelity to the model's original insights. To achieve this, the method iteratively adjusts the interactions between the generative and discriminative components until they reach a consensus on an answer that accurately reflects reality and aligns with their initial beliefs. This approach effectively bridges the gap between the two querying methods. 

In practice, implementing the consensus game approach to language model querying, especially for question-answering tasks, does involve significant computational challenges. For example, when using datasets like MMLU, which have thousands of questions and multiple-choice answers, the model must apply the mechanism to each query. Then, it must reach a consensus between the generative and discriminative components for every question and its possible answers. 

The system did struggle with a grade school right of passage: math word problems. It couldn't generate wrong answers, which is a critical component of understanding the process of coming up with the right one. 

“The last few years have seen really impressive progress in both strategic decision-making and language generation from AI systems, but we’re just starting to figure out how to put the two together. Equilibrium ranking is a first step in this direction, but I think there’s a lot we’ll be able to do to scale this up to more complex problems,” says Jacob.   

An avenue of future work involves enhancing the base model by integrating the outputs of the current method. This is particularly promising since it can yield more factual and consistent answers across various tasks, including factuality and open-ended generation. The potential for such a method to significantly improve the base model's performance is high, which could result in more reliable and factual outputs from ChatGPT and similar language models that people use daily. 

"Even though modern language models, such as ChatGPT and Gemini, have led to solving various tasks through chat interfaces, the statistical decoding process that generates a response from such models has remained unchanged for decades," says Google Research Scientist Ahmad Beirami, who was not involved in the work. "The proposal by the MIT researchers is an innovative game-theoretic framework for decoding from language models through solving the equilibrium of a consensus game. The significant performance gains reported in the research paper are promising, opening the door to a potential paradigm shift in language model decoding that may fuel a flurry of new applications."

Jacob wrote the paper with MIT-IBM Watson Lab researcher Yikang Shen and MIT Department of Electrical Engineering and Computer Science assistant professors Gabriele Farina and Jacob Andreas, who is also a CSAIL member. They presented their work at the International Conference on Learning Representations (ICLR) earlier this month, where it was highlighted as a "spotlight paper." The research also received a “best paper award” at the NeurIPS R0-FoMo Workshop in December 2023.

Jacob Andreas

Athul Paul Jacob

Research areas, press contact, rachel gordon, related news.

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How science is changing the game in sports

by Geoff Egan and Lucy Cameron, CSIRO

It's an open secret that the countries that win the most medals in the Olympics and Paralympics combine talent and technology.

Australia's athletes are preparing for the next three Olympics and Paralympics in Paris in 2024, Los Angeles in 2028, and Brisbane in 2032. Meanwhile, our sports scientists are developing new technologies to help improve sports performance across a range of fields.

Emerging digital technologies like artificial intelligence and quantum sensing are now in play, as athletes look for a new kind of competitive advantage. Athletes, teams, and coaches across the world are exploring how AI-assisted tools can "up their game," improve performance and reduce injuries.

Some of these technologies could come to your local club before you know it. Software offering insights into athletic performance and strategy is becoming more accessible, and AI-powered officiating is on the horizon. Soon, AI could be the third umpire at your local cricket match.

AI could help athletes stay healthy and recover faster

Each athlete has unique biochemistry, psychology, and physiology. They respond to working out, nutrition, and competition differently. Its why high-performance training is becoming increasingly personalized.

An athlete-centered approach to training and development was first developed in the para-athlete areas. Now it's being transferred to able-bodied sports with the assistance of digital technologies .

Eagle-eyed sports fans may have noticed footballers from multiple codes wearing vests under jerseys, or devices stitched in jerseys between their shoulder blades. These biometric trackers can provide information for coaches to monitor individual performance. This data can be combined with AI to improve performance, prevent long- and short-term injury, and optimize training.

Quantum sensors can profile the biochemistry of athletes in new ways. Quantum technology opens a range of outcomes such as different plays for injury prevention. It can also be used in drug testing, providing faster and more accurate testing than the current methods.

Combining large and disparate datasets from wearables, cameras, and body samples, sports scientists are creating digital twins of athletes that can be tested in various environments to predict performance. The digital replica can also be tweaked to advise on nutrition, technique, and strategy.

For example, a digital twin may be able to test variations of techniques to find the optimum way for a swimmer's body to move through water. A rower may be able to test multiple variations on their technique to improve their performance.

AI could drive better sports analytics

Looking for insight into what science has brought to sport? You don't need to look further than your TV.

Sophisticated player analytics are included in most major sports broadcasts. Gone are the days when the only statistics you saw in a footy game or cricket match was the score. Player performance and tracking are regularly updated on NRL and AFL matches. Cricket and tennis popularized ball-tracking technology.

Networks of on-field sensors and cameras capture computer vision of play. This can be combined with AI to analyze new dimensions of player and team performance, leading to adjustments in training and coaching. AI is also being used to inform players of their opponent's strengths and weaknesses mid-match.

AI can even assist in officiating —providing extra eyes and angles to determine line calls and whether players are onside or offside.

AI could level the playing field

And it's not just elite athletes that are benefiting from sports science . Parents and amateur coaches can use low-cost player vision, captured on apps on smartphones and tablets, to provide information on team dynamics and play.

More sophisticated setups include dynamic heat-maps of the play on the field and game analytics. There are existing coding libraries that can offer more tailored analytics and visualizations. Greater access to coaching information also necessitates stringent safeguards concerning the ethics, privacy, and usage of data and images, particularly for children in sport.

Volunteer-run local sporting competitions often struggle to find umpires and referees, AI officials could provide volunteer umpires and referees with computer-powered backup. Amateur players could have access to an AI-powered video umpire to confirm controversial decisions.

The use of video and AI in officiating has become controversial in some areas of high-performance sport. But it could show its true potential as it becomes available to leagues at all levels .

AI can keep our exercise goals on track

If you use an app to log your morning run or ride, you could already be part of the data-driven revolution in sport.

Digital technologies are changing the way people experience sports. Apps for running, cycling, and training are engaging a new generation of exercise and sports enthusiasts.

Wearable devices, most notably smart watches, are helping people track their exercise to understand their progress over time better and encourage them to work out. AI can help personalize workouts to a person's fitness levels and goals. AI-powered pose estimation tools can act as a personal yoga instructor, helping correct poses or techniques.

But AI could be an ethical sticky wicket

However, some ethical concerns remain. Is too much information skewing athletes' intuitive skills or undermining their confidence?

Our Collaborative Intelligence Future Science Platform is exploring the science of human-AI collaboration. The team is researching how AI can be best incorporated into the human workflow. The focus is on ensuring a shared understanding of the situation that the human and AI are collaborating on, and instilling trust throughout the process. Research programs like this can examine how athletes use and respond to available data, ensuring that the sports technologies are being applied correctly.

The ethics of using personal data from athletes are also evolving to ensure technologies are trusted and safe. In 2020 a group of organizations, led by the Australian Academy of Science, published a report Getting ahead of the Game . It highlighted growing concern about sensitive health data being collected from athletes through digital and other technologies.

Since then, the Australian Sports Commission and Australian Institute of Sport have been proactive in developing position statements and safeguards for certain technologies in sports training programs. This is about the use of athlete data in terms of privacy, safety and cybersecurity, and ensuring that data is not used for any purpose without consent.

As we continue embarking on a world of technology in sport science, it is important to grow the next generation of graduates skilled and enabled in the AI, emerging technologies and quantum space. We are still highly active in sports science fields.

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Teens and Video Games Today

85% of u.s. teens say they play video games, and about four-in-ten do so daily. teens see both positive and negative sides of video games – from problem-solving and making friends to harassment and sleep loss, table of contents.

• Who plays video games?
• How often do teens play video games?
• What devices do teens play video games on?
• Social media use among gamers
• Teen views on how much they play video games and efforts to cut back
• Are teens social with others through video games?
• Do teens think video games positively or negatively impact their lives?
• Why do teens play video games?
• Bullying and violence in video games
• Appendix A: Detailed charts
• Acknowledgments
• Methodology

Pew Research Center conducted this analysis to better understand teens’ use of and experiences with video games.

The Center conducted an online survey of 1,453 U.S. teens from Sept. 26 to Oct. 23, 2023, through Ipsos. Ipsos recruited the teens via their parents, who were part of its KnowledgePanel . The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. The survey was weighted to be representative of U.S. teens ages 13 to 17 who live with their parents by age, gender, race and ethnicity, household income, and other categories.

This research was reviewed and approved by an external institutional review board (IRB), Advarra, an independent committee of experts specializing in helping to protect the rights of research participants.

Here are the questions used for this analysis , along with responses, and  its methodology .

There are long-standing debates about the impact of video games on youth. Some credit them for helping young people form friendships and teaching them about teamwork and problem-solving . Others say video games expose teenagers to violent content, negatively impact their sleep and can even lead to addiction.

With this in mind, Pew Research Center surveyed 1,423 U.S. teens ages 13 to 17 about their own video game habits – from how often they play to the friends they’ve made and whether it gets in the way of them doing well in school or getting a good night’s sleep. 1

Key findings from the survey

• Video games as a part of daily teen life: 85% of U.S. teens report playing video games, and 41% say they play them at least once a day. Four-in-ten identify as a gamer.
• Gaming as a social experience: 72% of teens who play video games say that a reason why they play them is to spend time with others. And some have even made a friend online from playing them – 47% of teen video game players say they’ve done this.
• Helpful with problem-solving, less so for sleep: Over half of teens who play video games say it has helped their problem-solving skills, but 41% also say it has hurt their sleep.
• Bullying is a problem: 80% of all teens think harassment over video games is a problem for people their age. And 41% of those who play them say they’ve been called an offensive name when playing.
• Boys’ and girls’ experiences differ: Most teen boys and girls play video games, but larger shares of boys identify as gamers (62% vs. 17%) and play every day (61% vs. 22%). Boys who play them are also more likely to experience positive things from it, like making friends, and more troubling things like harassment.

Jump to read about: Who plays video games | Socializing over video games | Views about video games’ impact | Harassment and violence in video games      

Playing video games is widespread among teens. The vast majority of U.S. teens (85%) say they play them. Just 15% say they never do, according to the survey conducted Sept. 26-Oct. 23, 2023.

In addition to asking whether teens play video games, we also wanted to learn whether they consider themselves gamers. Overall, four-in-ten U.S. teens think of themselves as gamers. Just under half of teens (45%) play video games but do not think of themselves as gamers.

Nearly all boys (97%) say they play video games, compared with about three-quarters of teen girls. There is a substantial gap by gender in whether teens identify as gamers: 62% of teen boys do, compared with 17% of girls. 2

By gender and age

Younger teen girls are more likely than older girls to say they play video games: 81% of girls ages 13 to 14 compared with 67% of those ages 15 to 17. But among boys, nearly all play video games regardless of age. 

Similar shares of teens play video games across different racial and ethnic groups and among those who live in households with different annual incomes. Go to Appendix A for more detail on which teens play video games and which teens identify as gamers.

We also asked teens how often they play video games. About four-in-ten U.S. teens say they play video games daily, including 23% who do so several times a day.

Another 22% say they play several times a week, while 21% play them about once a week or less.

Teen boys are far more likely than girls to say they play video games daily (61% vs. 22%). They are also much more likely to say they play them several times a day (36% vs. 11%).

By whether someone identifies as a gamer

About seven-in-ten teens who identify as gamers (71%) say they play video games daily. This drops to 30% among those who play them but aren’t gamers.

By household income

Roughly half of teens living in households with an annual income of less than $30,000 (53%) say they play video games at least daily. This is higher than those in households with an annual income of $30,000 to $74,999 (42%) and $75,000 or more (39%).

Go to Appendix A to see more details about who plays video games and identifies as a gamer by gender, age, race and ethnicity, and household income.

Most teens play video games on a gaming console or a smartphone. When asked about five devices, most teens report playing video games on a gaming console (73%), such as PlayStation, Switch or Xbox. And 70% do so on a smartphone. Fewer – though still sizable shares – play them on each of the following:

• 49% say they play them on a desktop or laptop computer
• 33% do so on a tablet  
• 24% play them on a virtual reality (VR) headset such as Oculus, Meta Quest or PlayStation VR

Many teens play video games on multiple devices. About a quarter of teens (27%) do so on at least four of the five devices asked about, and about half (49%) play on two or three of them. Just 8% play video games on one device.

Teen boys are more likely than girls to play video games on four of the five devices asked about – all expect tablets. For instance, roughly nine-in-ten teen boys say they ever play video games on a gaming console, compared with 57% of girls. Equal shares of teen boys and girls play them on tablets.  

Teens who consider themselves gamers are more likely than those who play video games but aren’t gamers to play on a gaming console (95% vs. 78%), desktop or laptop computer (72% vs. 45%) or a virtual reality (VR) headset (39% vs. 19%). Similar shares of both groups play them on smartphones and tablets.

One way that teens engage with others about video games is through online platforms. And our survey findings show that teen gamers stand out for their use of two online platforms that are known for their gaming communities – Discord and Twitch :

• 44% of teen gamers say they use Discord, far higher than video game players who don’t identify as gamers or those who use the platform but do not play video games at all. About three-in-ten teens overall (28%) use Discord.
• 30% of teens gamers say they use Twitch. About one-in-ten other teens or fewer say the same; 17% of teens overall use the platform.

Previous Center research shows that U.S. teens use online platforms at high rates .

Teens largely say they spend the right amount of time playing video games. When asked about how much time they spend playing them, the largest share of teens (58%) say they spend the right amount of time. Far fewer feel they spend too much (14%) or too little (13%) time playing them.

Teen boys are more likely than girls to say they spend too much time playing video games (22% vs. 6%).

By race and ethnicity

Black (17%) and Hispanic (18%) teens are about twice as likely than White teens (8%) to say they spend too little time playing video games. 3

A quarter of teens who consider themselves gamers say they spend too much time playing video games, compared with 9% of those who play video games but don’t identify as gamers. Teen gamers are also less likely to think they spend too little time playing them (19% vs. 10%).

Fewer than half of teens have reduced how much they play video games. About four-in-ten (38%) say they have ever chosen to cut back on the amount of time they spend playing them. A majority (61%) report that they have not cut back at all.

This share is on par with findings about whether teenagers have cut back with their screen time – on social media or their smartphone.

Although boys are more likely to say they play video games too much, boys and girls are on par for whether they have ever cut back. About four-in-ten teen boys (39%) and girls (38%) say that they have ever cut back.

And gamers are as likely to say they have cut back as those who play video games but don’t identify as gamers (39% and 41%).

A main goal of our survey was to ask teens about their own experiences playing video games. For this section of the report, we focus on teens who say they play video games.

Socializing with others is a key part of the video game experience. Most teens who play video games do so with others, and some have developed friendships through them.

About nine-in-ten teen video game players (89%) say they play them with other people, in person or online. Far fewer (11%) play them only on their own.

Additionally, about half (47%) report that they have ever made a friend online because of a video game they both play. This equals 40% of all U.S. teens who have made a friend online because of a video game.

These experiences vary by:  

• Gender: Most teen boy and girl video game players play them with others, though it’s more common among boys (94% vs. 82%). Boys who play video games are much more likely to say they have made a friend online because of a video game (56% vs. 35%).
• Race and ethnicity: Black (55%) and Hispanic (53%) teen video game players are more likely than White teen video game players (43%) to say they have made a friend online because of them.
• Whether someone identifies as a gamer: Nearly all teen gamers report playing video games with others (98%). Fewer – though still most – of those who play video games but aren’t gamers (81%) also play them with others. And about seven-in-ten (68%) say they have made a friend online because of a video game, compared with 29% of those who play them but don’t identify as gamers.

Teens who play video games are particularly likely to say video games help their problem-solving skills. More than half of teens who play video games (56%) say this.

Additionally, more think that video games help, rather than hurt, three other parts of their lives that the survey asked about. Among teens who play video games:

• Roughly half (47%) say it has helped their friendships
• 41% say it has helped how they work with others
• 32% say it has helped their mental health

No more than 7% say playing video games has hurt any of these.

More teens who play video games say it hurts, rather than helps, their sleep. Among these teens, 41% say it has hurt how much sleep they get, while just 5% say it helps. And small shares say playing video games has impacted how well they do in school in either a positive or a negative way.

Still, many teens who play video games think playing them doesn’t have much an impact in any of these areas. For instance, at least six-in-ten teens who play video games say it has neither a positive nor a negative impact on their mental health (60%) or their school performance (72%). Fewer (41%) say this of their problem-solving skills.

Teen boys who play video games are more likely than girls to think playing them has helped their problem-solving skills, friendships and ability to work with others. For instance, 55% of teen boys who play video games say this has helped their friendships, compared with 35% of teen girls.

As for ways that it may hurt their lives, boys who play them are more likely than girls to say that it has hurt the amount of sleep they get (45% vs. 37%) and how well they do in school (21% vs. 11%). 

Teens who consider themselves gamers are more likely than those who aren’t gamers but play video games to say video games have helped their friendships (60% vs. 35%), ability to work with others (52% vs. 32%), problem-solving skills (66% vs. 47%) and mental health (41% vs. 24%).

Gamers, though, are somewhat more likely to say playing them hurt their sleep (48% vs. 36%) and how well they do in school (20% vs. 14%).

By whether teens play too much, too little or the right amount

Teens who report playing video games too much stand out for thinking video games have hurt their sleep and school performance. Two-thirds of these teens say it has hurt the amount of sleep they get, and 39% say it hurt their schoolwork. Far fewer of those who say they play the right amount (38%) or too little (32%) say it has hurt their sleep, or say it hurt their schoolwork (12% and 16%).

Teens who play video games say they largely do so to be entertained. And many also play them to be social with and interact with others. Teens who play video games were asked about four reasons why they play video games. Among those who play video games:

• Nearly all say fun or entertainment is a major or minor reason why they play video games – with a large majority (87%) saying it’s a major reason.
• Roughly three-quarters say spending time with others is a reason, and two-thirds say this of competing with others. Roughly three-in-ten say each is a major reason.
• Fewer – 50% – see learning something as a reason, with just 13% saying it’s a major reason.

While entertainment is by far the most common reason given by teens who play video games, differences emerge across groups in why they play video games.

Teens who identify as gamers are particularly likely to say each is major reason, especially when it comes to competing against others. About four-in-ten gamers (43%) say this is a major reason, compared with 13% of those who play video games but aren’t gamers.

Teen boys who play video games are more likely than girls to say competing (36% vs. 15%), spending time with others (36% vs. 27%) and entertainment (90% vs. 83%) are major reasons they play video games.

Black and Hispanic teens who play video games are more likely than White teens to say that learning new things and competing against others are major reasons they play them. For instance, 29% of Black teen video game players say learning something new is a major reason, higher than 17% of Hispanic teen video game players. Both are higher than the 7% of White teen video game players who say the same.

Teens who play video games and live in lower-income households are especially likely to say competing against others and learning new things are major reasons. For instance, four-in-ten teen video game players who live in households with an annual income of less than $30,000 say competing against others is a major reason they play. This is higher than among those in households with annual incomes of $30,000 to $74,999 (29%) and $75,000 or more (23%).

Cyberbullying can happen in many online environments, but many teens encounter this in the video game world.

Our survey finds that name-calling is a relatively common feature of video game life – especially for boys. Roughly four-in-ten teen video game players (43%) say they have been harassed or bullied while playing a video game in one of three ways: 

• 41% have been called an offensive name
• 12% have been physically threatened
• 8% have been sent unwanted sexually explicit things

Teen boys are particularly likely to say they have been called an offensive name. About half of teen boys who play video games (48%) say this has happened while playing them, compared with about a third of girls (32%). And they are somewhat more likely than girls to have been physically threatened (15% vs. 9%).

Teen gamers are more likely than those who play video games but aren’t gamers to say they been called and offensive name (53% vs. 30%), been physically threatened (17% vs. 8%) and sent unwanted sexually explicit things (10% vs. 6%).

Teens – regardless of whether they’ve had these experiences – think bullying is a problem in gaming. Eight-in-ten U.S. teens say that when it comes to video games, harassment and bullying is a problem for people their age. This includes 29% who say it is a major problem.

It’s common for teens to think harassment while playing video games is a problem, but girls are somewhat more likely than boys to say it’s a major problem (33% vs. 25%).

There have also been decades-long debates about how violent video games can influence youth behavior , if at all – such as by encouraging or desensitizing them to violence. We wanted to get a sense of how commonly violence shows up in the video games teens are playing.

Just over half of teens who play video games (56%) say at least some of the games they play contain violence. This includes 16% who say it’s in all or most of the games they play.

Teen boys who play video games are far more likely than girls to say that at least some of the games they play contain violence (69% vs. 37%).

About three-quarters of teen gamers (73%) say that at least some of the games they play contain violence, compared with 40% among video game players who aren’t gamers.   

• Throughout this report, “teens” refers to those ages 13 to 17. ↩
• Previous Center research of U.S. adults shows that men are more likely than women to identify as gamers – especially the youngest adults. ↩
• There were not enough Asian American respondents in the sample to be broken out into a separate analysis. As always, their responses are incorporated into the general population figures throughout the report. ↩

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