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Review

Serious Games in Science Education: A Systematic Bibliometric and Content Analysis

by
Deniz Poyraz Gök
* and
Nuri Kara
Department of Digital Game Design, Faculty of Communication, Istanbul Bilgi University, 34060 Istanbul, Turkey
*
Author to whom correspondence should be addressed.
Computers 2026, 15(6), 330; https://doi.org/10.3390/computers15060330 (registering DOI)
Submission received: 27 March 2026 / Revised: 12 May 2026 / Accepted: 13 May 2026 / Published: 22 May 2026
(This article belongs to the Special Issue STEAM Literacy and Computational Thinking in the Digital Era)
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Abstract

This study examines recent research trends in the use of serious games for science education through a bibliometric analysis of 340 articles and a qualitative content analysis of 56 studies published between 2020 and 2025 in the Web of Science Core Collection. By combining these approaches, the study provides a comprehensive view of both research patterns and how serious games are designed and used in science education. The findings indicate that the field is maturing, with research moving beyond general effectiveness toward understanding how serious games support learning in different contexts. Most studies report positive effects compared to traditional instructional methods. However, results vary across contexts and depend on factors such as design, implementation, and learner characteristics. Research is mainly focused on higher education and is largely driven by leading countries such as the USA and China, although participation from developing countries is increasing. The growing use of immersive technologies, such as augmented and virtual reality, offers new opportunities for interactive and multimodal learning but may also increase cognitive load in certain contexts. There is also growing interest in non-digital games, which have received limited attention despite their effectiveness. Overall, the findings show that more systematic research and clearer design frameworks are needed to better understand how serious games can be used in science education.

1. Introduction

Serious games are games with a primary purpose other than pure entertainment [1,2,3,4]. These games are utilized in a variety of non-entertainment fields such as the military, education, healthcare, and business [1,4,5,6]. Education is one of these industries that widely employs and studies serious games for educational purposes [4]. Game-based learning (GBL) is an educational method that uses games as a primary tool to help students “learn by doing” [7,8]. The core strength of GBL in education is its unique capacity to implement existing learning models to facilitate a playful learning experience that achieves optimal engagement. According to Plass et al. [9], games promote multiple types of engagement across affective, behavioral, cognitive, and sociocultural levels, which is rarely seen in traditional learning environments.
The abstract nature of scientific subjects often causes anxiety and difficulties in learning [1]. Yet meaningful understanding depends on the learner’s ability to apply these abstract concepts to solve problems in unfamiliar contexts. The traditional view of science education does not align with today’s learners’ needs [1,8,10]. In contrast, well-designed serious games can address these limitations by providing environments that facilitate situated and experiential learning [3,4,8,11,12]. Not only that, they actively engage students with scientific phenomena, enabling them to construct an accurate and intuitive understanding of these complex concepts [10]. Thanks to their ability to combine challenging scientific concepts with playful content [3], serious games are particularly well suited to support scientific learning [1,4,8]. Therefore, a growing number of educators and scholars have begun to integrate them into science education [1,11].
In the literature, numerous studies have reported sustained and growing scholarly interest in the pedagogical role of serious games [1,4,8,13]. Cheng et al. [1] conducted a comprehensive review of empirical studies published between 2002 and 2013 and identified a clear “surge in interest” in the use of serious games for science education. More recently, research such as the bibliometric analysis by Ekin and Gul [14] confirms that this upward trend has not only persisted but also continued to expand, both in terms of volume and scope. Studies have demonstrated that GBL can effectively support a diverse range of pedagogical goals, ranging from “learning by making games” [15] and multi-team participatory simulations [16] to formative assessment tools that provide immediate feedback [17]. These studies suggest that GBL not only improves knowledge acquisition but also fosters engagement and collaboration, especially compared to conventional instructional methods.
Despite these positive findings, comprehensive reviews have highlighted fragmentation in the field. Early reviews by Connolly et al. [11] and Young et al. [18] found that while games were effective for language learning and history, evidence for science education across studies was limited and inconsistent. At the same time, a colloquium article by Hwang and Wu [13] examined 137 journal articles on digital game-based learning from 2001 to 2010. They observed a similar trend, despite the rapid growth in research interest, relatively few studies focused specifically on science education [13,18]. Later, Li and Tsai [12] and Cheng et al. [1] noted that most research relied on quantitative methods and was heavily skewed toward facilitating scientific knowledge acquisition. Consequently, the affective, socio-contextual, engagement-related, and problem-solving aspects of GBL remained underexplored [1]. Further meta-analyses [3,19] have confirmed that serious games are significantly more effective for knowledge acquisition and retention than traditional methods, especially when integrated effectively into the science curriculum. More recently, Ullah et al. [4] found that science education has come a long way, becoming a prominent topic in serious games. Among scientific subjects, they found that the majority of games were designed for physics and biology, including studies using augmented reality (AR) or virtual reality (VR) technologies. Recent studies have also emphasized the growing role of adaptive and immersive gamification environments in science education, particularly in supporting student motivation, engagement, and personalized learning experiences [20,21]. Videnovik et al. [8] examined studies related to game-based learning in computer science education. They reported a growing use of games to develop higher-order skills, such as computational thinking and programming skills. The reviewed articles predominantly employed a “learning by playing” approach rather than a “learning by making games” approach. While both reviews supported the educational potential of serious games, they also highlighted ongoing gaps. Regarding this, Ullah et al. [4] noted a limited representation of research from developing countries. In contrast, Videnovik et al. [8] highlighted a lack of standardized design methods and the difficulty of generalizing results from localized studies to an international level.
Although the inherent pedagogical potential of serious games in fostering active and experiential learning is well recognized [4,8,11,22], their widespread adoption in science education remains limited. Despite their popularity and promise, there is still no clear consensus regarding their effectiveness in enhancing learning outcomes, as existing evidence remains methodologically diverse and inconclusive [3,11]. The National Research Council (as cited in Riopel et al. [3]) further emphasized that the evidence for the effectiveness of game-based science learning is emerging but remains inconclusive. This ongoing uncertainty underscores the need for further systematic research to provide more comprehensive evidence on the role of serious games in science education [3,4,8,10,11,18].
While previous reviews have primarily examined the efficacy of serious games in supporting science learning [3,18], comprehensive analyses of the broader research landscape beyond learning outcomes remain limited [12]. Furthermore, the literature has yet to fully address the developments of the most recent years. To address these gaps, this study investigates current research trends in the use of serious games for science education by combining bibliometric analysis with qualitative content analysis. Unlike prior reviews that focus primarily on effectiveness or purely thematic synthesis, this approach combines insights from publication patterns (e.g., research trends, topics, and geographical distribution) with in-depth analysis of how serious games are designed and used in educational contexts. By examining recent developments, this study seeks to provide a roadmap to guide possible future research and offer insights into the integration of serious games in educational contexts. To achieve this goal, this study addresses the following research questions:
RQ 1. How has research on serious games in science education evolved in recent years in terms of trends, key topics, and global research patterns?
RQ 2. What do recent studies reveal about how serious games are designed and used in science education?

2. Materials and Methods

An initial bibliometric analysis was conducted to provide a broad quantitative overview of the field’s publication trends, utilizing citation and co-citation analysis [23]. In addition, a systematic content analysis was implemented to qualitatively examine a smaller, focused dataset to identify and categorize recurring patterns and themes [24].
Data collection was performed on 19 August 2025 using the Web of Science (WoS) Core Collection database (Clarivate Analytics, Philadelphia, PA, USA), including the SSCI, SCI-Expanded, A&HCI, CPCI-S, CPCI-SSH, and ESCI indices, in order to create two distinct datasets containing articles related to serious games in science education. The initial search query terms were identified after a series of initial scoping searches. The terms “digital game”, “serious game”, and “educational game” are often used interchangeably in the literature. For this reason, a combination of these terms (serious game OR digital game OR educational game) was used. The initial search query strings and options, as well as the inclusion and exclusion criteria used in both queries, were chosen to best reflect the focus of the research, the research questions, and the individual aims of the two separate search queries.
For the bibliometric analysis, the first query, which aimed to form an overview of the literature, included more general terms in its initial search string and options (Table 1). The study selection process involved the sequential application of inclusion and exclusion criteria to the initial query results in the order shown in Figure 1. The following inclusion and exclusion criteria were used: (1) published in English, (2) published between 1 January 2020 and 19 August 2025, (3) a scientific article, (4) empirical, (5) not a review, bibliometric, or meta-analysis article, (6) related to the topics of serious games, educational games, or digital games in science education. This process resulted in a dataset of 340 articles (Figure 1). The Full Records and Cited References were then exported in text (.txt) format and imported into VOSviewer version 1.6.20 (Centre for Science and Technology Studies, Leiden University, Leiden, The Netherlands).
For the content analysis, this study adapted the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines [25]. PRISMA was chosen to ensure a systematic, transparent, and replicable protocol for identifying and screening studies.
In the initial identification phase, additional search terms and filters were added to the previous search query (Table 2). The revised query required the terms “science” and “game” to be present in the article title and abstract. Additionally, the following criteria were included: (7) a full-text version of the article must be available, and (8) specifically included the terms “science” and “game” in its title and abstract. The final search query identified 72 potentially relevant studies (Figure 2).
Following the identification, titles and abstracts were screened against predefined inclusion and exclusion criteria. Irrelevant records were removed. The final eligibility phase included the assessment of the full texts of the remaining articles. Of the 72 potentially relevant articles, 16 were excluded for failing to meet the eligibility criteria. The final dataset included 56 articles for systematic content analysis (Figure 2).
A custom article analysis form was developed to systematically code and analyze the selected studies. The form included thirteen categories: (1) study title and author(s), (2) abstract, (3) subject matter, (4) research methodology, (5) research question(s), (6) main goal(s), (7) keyword(s), (8) data collection method(s), (9) data analysis method(s), (10) publication journal, (11) publication year, (12) examined topic(s), and (13) main findings.
To address RQ1, a bibliometric analysis was conducted using VOSviewer on the Web of Science bibliographic dataset to examine research trends, key topics, and global research patterns through citation and co-citation network visualizations. When deemed necessary, thesaurus files were used to merge synonymous terms (e.g., “STEM” and “STEM education”) and singular/plural variations (e.g., “serious game” and “serious games”) into single nodes to prevent cluster fragmentation.
To address RQ2, a qualitative content analysis of 56 coded articles examined how serious games are designed and used in science education. This analysis focused on identifying recurring themes and patterns, which were then sorted into corresponding categories.
The integration of bibliometric and content analysis enabled a more detailed, in-depth review. The bibliometric dataset (n = 340) revealed broader research patterns, while the content analysis dataset (n = 56) allowed for an in-depth examination of how serious games are designed and used in science education. The content analysis followed an inductive coding approach, in which themes were derived from the data through iterative reading and categorization. To enhance reliability, the coding process was conducted systematically using a predefined analysis framework, and categories were refined through multiple rounds of review. All article data were manually entered into a structured analysis form. In the first round, the first author conducted the initial coding of the selected articles. In the second round, the second author reviewed the assigned categories for consistency and relevance and made necessary revisions. In the third round, both authors jointly re-examined all categories against the original articles to ensure accuracy and consistency. To further strengthen the analysis’s credibility, the overall data collection and coding process was independently reviewed by an academic from the Faculty of Communication. The materials used in the content analysis are provided as Supplementary Materials. Supplementary File S1 includes the article analysis forms for the included studies (n = 56), and Supplementary File S2 presents the content analysis coding and themes for the included studies (n = 56).

3. Results

3.1. Bibliometric Mapping Analysis Findings

A co-occurrence analysis of author keywords was conducted using VOSviewer on the Web of Science bibliographic dataset to identify the most frequently used terms. Synonymous terms (e.g., STEM and STEM education) and singular/plural variations were merged via a thesaurus file. A minimum occurrence threshold of five yielded 44 eligible keywords. The resulting network map (Figure 3) revealed six clusters. “game-based learning” (f = 58) was the most frequently used author keyword. When grouped together with its adjacent term “digital game-based learning” (f = 12), they dominate the field with 70 total occurrences. Other high-frequency terms include “gamification” (f = 43), “serious games” (f = 30), “science education” (f = 30), “education” (f = 26), “STEM education” (f = 24), “higher education” (f = 22), and “educational games” (f = 21).
Figure 4 shows the distribution frequency of keywords by year. Earlier research favored “games” (f = 18) and “mobile learning” (f = 8), whereas recent studies have shifted focus toward “medical education” (f = 6), alongside “virtual reality” (f = 5), “artificial intelligence” (f = 5), and “escape rooms” (f = 5). Furthermore, research prior to 2022 focused on “engagement” (f = 12), while more recent studies examine “active learning” (f = 10), “self-efficacy” (f = 6), and “cognitive load” (f = 6).
To visualize the most cited authors, a citation analysis was conducted, applying a minimum inclusion threshold of 3 documents and 10 citations per author. In total, six authors met these criteria that formed two disconnected clusters. Solomon Sunday Oyelere received the highest number of citations (102 citations). Together with Friday Joseph Agbo (69 citations) and Ai-Chu Elisha Ding (16 citations) form the first cluster (Figure 5). The second cluster comprises Gwo-Jen Hwang (59 citations), Patcharin Panjaburee (48 citations), and Niwat Srisawasdi (48 citations).
In addition, a co-citation analysis yielded 32 authors when a minimum threshold of 20 citations was applied (Figure 6). Gwo-Jen Hwang (75 citations) emerged as the most cited author, followed by prominent figures such as Marc Prensky (49 citations), Valerie J. Shute (49 citations), Juho Hamari (43 citations), James Paul Gee (42 citations), and Richard E. Mayer (39 citations). Besides them, Sebastian Deterding (34 citations), Richard Ryan (35 citations), Kristian Kiili (33 citations), and Jan L. Plass (32 citations) are some of the other frequently cited authors.
The citation analysis of countries revealed that the United States (589 citations, 66 documents) is the leading contributor to the field. The inclusion criteria were set at a minimum of 10 documents and 10 citations, resulting in 13 eligible countries. The nodes “Turkey” and “Türkiye” were also merged to account for the country’s rebranding in 2022. The resulting network map (Figure 7) shows three distinct clusters and an isolated node. Brazil appears as the isolated node, which may reflect limited collaboration links with other countries or the effect of the threshold applied in the analysis. The top contributor, the USA, is closely followed by the People’s Republic of China (581 citations, 30 documents). In terms of publications, Spain (392 citations, 41 documents) ranks second behind the USA. Other prominent contributors include Taiwan (380 citations, 26 documents), Greece (337 citations, 15 documents), Germany (200 citations, 11 documents), and Turkey (183 citations, 25 documents).
Based on the overlay visualization (Figure 8), earlier publications predominantly originated from the USA, Germany, and England (166 citations, 15 documents). More recently, research has shifted towards Asia and South America, namely to Malaysia (40 citations, 11 documents), China, Taiwan, and Brazil (18 citations, 11 documents).
To identify the primary research outlets, a citation analysis of publication sources was conducted. Applying a minimum inclusion threshold of three documents and three citations per source resulted in 31 journals. Table 3 presents the top 10 journals ranked by total citation count. Computers & Education (290 citations, 13 documents) was the most cited journal, followed by Education and Information Technologies (271 citations, 29 documents). Notably, Education Sciences (269 citations, 26 documents) contributed the highest number of individual studies.
In addition, a co-citation analysis of sources was performed with a threshold of 20 citations per source. The resulting map (Figure 9) shows that among 103 journals, Computers & Education (1056 co-citations) is the most cited journal by a significant margin. Computers in Human Behavior (394 co-citations), British Journal of Educational Technology (231 co-citations), Educational Technology Research and Development (ETR&D) (218 co-citations), and Education and Information Technologies (206 co-citations) were the other frequently co-cited sources.

3.2. Content Analysis Findings

Through qualitative content analysis, the 56 articles, that were selected with PRISMA guidelines, were categorized into five major themes: Impact on Learning Outcomes and Performance (n = 45); The Learners’ Affective and Cognitive Experience (n = 44); Instructional Design and Pedagogical Strategies (n = 39); Game Design, Technology, and Mechanics (n = 54); and Learner Characteristics and Education Context (n = 55).

3.2.1. Impact on Learning Outcomes and Performance

Multiple studies demonstrated that game-based learning (GBL) interventions lead to significant improvements in academic achievement. These improvements were observed across a diverse pool of scientific disciplines. In biology, GBL supported understanding of topics such as genetics [26], marine biology [16,27], and paleontology [28]. Meanwhile, in chemistry and physics, it helped with atomic structures [29], chemical compounds [30], electricity [31,32], and motion and force [33]. A primary area of research was whether games helped students learn and retain scientific knowledge more effectively than traditional means. Overall, the consensus was that GBL groups often outperformed traditional or video-based methods [31]. Liu et al. [34] reported significantly higher post-test results for the experimental group who played the SpacEscape mobile game. A similar result was observed by Szilágyi et al. [35] for students playing the Blue Yeti card game, who outperformed the control group in improper integrals. However, while both digital and non-digital formats effectively improve performance compared to conventional instructional methods [36,37], Wang and Zheng [37] reported that the digital format sometimes offered an advantage in self-efficacy. Moreover, evidence suggests that interactive multimedia and blended learning might be more effective than games for specific ability groups [38].
Another area of focus was the impact of games on students’ higher-order skills. Games have been found to facilitate the development of specific skills such as systems thinking in medical education [39]. Likewise, develop problem-solving [32], critical thinking [40], computational thinking [41,42], and scientific inquiry [43] skills. Furthermore, it was suggested that through specific mechanics, games can facilitate the development of scientific reasoning [44].

3.2.2. The Learners’ Affective and Cognitive Experience

A substantial body of research has identified games as a powerful tool for increasing intrinsic motivation and engagement [16,26,36,40,45,46,47,48]. Across these studies, the concept of ‘flow’ frequently appeared as a key metric for evaluating engagement [49,50]. The results show that the flow state is consistently higher in GBL environments [31,50]. Moreover, several studies [48,51] have reported that games positively influenced students’ attitudes toward science and their future professions. Not only did students find GBL environments more enjoyable and “fun” [35], but future teachers have also expressed positive perceptions toward the use of GBL [43].
The competitive elements in games like Kahoot! sometimes caused anxiety and distraction [52] or even hindered learning when the pressure to win overshadowed the educational content [53]. Another area of concern was the cognitive load imposed by serious games. Namely, Owen and Licorish [52] highlighted that careful design management was essential to avoid overwhelming students. Various scaffolding approaches, including AI support [46], real-time prompts [32], or microworlds [47], were also suggested to help manage this issue. Despite these challenges, several studies reported that participation in GBL reduced learning anxiety [47] and improved self-efficacy, particularly in challenging subjects like physics [37], science reading [54], and computer science tasks [40], as well as among students with special needs [47].

3.2.3. Instructional Design and Pedagogical Strategies

Game-based learning (GBL) is frequently used as a pedagogical strategy to promote collaborative learning (CL) and social interaction, where students must actively communicate and work together towards a common goal to solve problems [36,55]. Collaborative games were found to foster teamwork [36,48], improve social skills, and enhance team synchrony, thereby contributing to better knowledge acquisition [16,48,56]. Beyond this, several studies explored various other ways GBL could be employed. An approach involved students designing their own games, which was found to effectively develop critical thinking and help students clarify misconceptions since students had to clearly understand the content to gamify it [15,42,51]. Furthermore, this “learning by making games” approach was often more effective than merely playing games [15]. However, its effectiveness varied depending on students’ prior gaming experience, with those reporting medium experience benefitting the most [15]. In one study, Küçükşen Öner et al. [57] engaged pre-service art and science teachers in the design process and found that it not only enhanced their professional development but also improved the quality of the resulting educational tools.
Similarly, research has emphasized the role of serious games as effective assessment tools [17,57]. Examples included “stealth assessment”, which tracks learning via in-game mechanics [44] and game-based response systems such as Kahoot! for formative assessment in both formal and informal contexts [52,53]. Even so, gameplay alone was found to be insufficient for effective learning [32]. Studies highlighted the importance of scaffolding and instructional guidance to link gameplay to learning outcomes [15,33]. Without adequate support, open-ended games could increase cognitive load due to their complexity [46]. In other words, scaffolding lowered cognitive load [33]. Even if this is the case, findings suggest that learners may lack the skills to use such tools effectively [33].

3.2.4. Game Design, Technology, and Mechanics

Although significant research supports the effectiveness of game-based learning (GBL), relatively few studies have focused on analog games. These “unplugged” formats, such as board games [26,36,57,58], card games [35], and escape rooms [55], are praised for their ability to foster face-to-face interaction, teamwork, and knowledge retention. Several studies report that analog games can match and even outperform digital versions for specific learning outcomes [36,58]. Despite this, digital games continue to dominate the field. A growing number of studies have begun incorporating immersive technologies such as augmented reality (AR) and virtual reality (VR) to create multimodal learning experiences [28,40,59]. VR, in particular, enables embodied interaction, which has been shown to benefit students with low intrinsic motivation [60]. AR, meanwhile, acts as a bridge between the physical and the digital worlds. Studies using AR have demonstrated its potential to superimpose information onto real environments, combining the advantages of both contexts [28,43]. As a result, this approach has been linked to gains in learning achievement and engagement [59] and to scaffolding support [28]. Similarly, Bressler et al. [49] found that AR games can trigger situational interest in science. Yet the increased cognitive demands of these technologies present risks; for instance, Lu et al. [28] observed a notable decline in confidence when such tools were introduced.
Studies have also underscored the importance of designing games with inclusivity in mind [43], such as creating “motivationally appealing” games specifically for girls in computer science [61], or ensuring games are accessible for students with special needs [38,47]. Hoskins et al. [62] further emphasized leveraging students’ existing “game culture”, in this case their familiarity with the game character “Sonic the Hedgehog”, as a form of cultural wealth. With this, they aimed to make the curriculum more accessible and engaging for a diverse range of learners, including those with special needs.

3.2.5. Learner Characteristics and Education Context

Research on game-based learning (GBL) has been conducted across a wide range of educational contexts, ranging from formal K-12 classrooms [30,31] and higher education [52,63] to informal settings like museums [64], outdoor citizen science projects [27], and early childhood education [65]. The effectiveness of GBL appears to vary depending on factors such as learners’ backgrounds and environments. Students’ prior gaming experience plays a significant role in determining the effectiveness of GBL [15]. For instance, Ding and Yu [15] reported that learners with moderate gaming experience benefited most. In contrast, Nkadimeng and Ankiewicz [29] found that those unfamiliar with game mechanics struggled to focus on educational content. Demographic factors such as gender and socioeconomic status have also influenced the results. In one design workshop, affluent students’ attitudes toward computing improved, while students from underserved districts reported decreased confidence [41]. Similarly, research examining gender differences in games has produced mixed results. Rodríguez-Roca et al. [66] found that male students reported higher enjoyment, whereas other studies found no significant gender differences in platform perception or learning outcomes [15,52].

4. Discussion

4.1. RQ 1: How Has Research on Serious Games in Science Education Evolved in Recent Years in Terms of Trends, Key Topics, and Global Research Patterns?

The frequent appearance of the terms “serious games”, “science education”, “STEM education”, and “educational games” in the bibliometric analysis is to be expected, given the focus of this study on serious games for science education. The prominence of “gamification” suggests that the terms “gamification”, “serious games”, and “educational games” are being used interchangeably under the broader umbrella of “game-based learning”. This was pointed out in previous research [8,14,15]. This suggests that the lack of clear definitions of these concepts in the literature may lead to inconsistencies in how findings are interpreted and compared across studies. The dominance of “higher education” over “primary education” among the keywords indicates that research has been conducted predominantly in higher education classrooms. This finding aligns with Hwang and Wu [13] and Videnovik et al. [8]. Complex and abstract science concepts can lead to learning difficulties and reduced student motivation [1,15]. This may explain why GBL is increasingly used in higher education to sustain student motivation and interest [8,12]. From this point, it can be inferred that serious games can be used more effectively in contexts where cognitive demands are higher and traditional teaching approaches may be less effective.
Recent studies have also seen a shift from earlier emphasis on “mobile learning” toward “virtual reality”, “artificial intelligence”, and “escape rooms”. The growing adoption of these technologies and techniques has been well-observed in previous studies [4,67]. This shift suggests that game-based learning is not only incorporating new technologies but also moving toward more immersive, interactive, and multimodal learning environments. This shift demonstrates GBL’s adaptability and openness to experimenting with emerging technologies and, most importantly, novel educational techniques. This adaptability is one of the greatest strengths of the GBL approach regarding its sustained and growing scholarly interest [1,4,8,13]. In this context, adaptability can be understood not only as technological flexibility but also as GBL’s ability to adapt to evolving pedagogical needs. As this interest grows, research has become more interdisciplinary. This could be observed from the results, where the general discussions of “games” have moved toward specialized domains such as “medical education” and “computer education”. Hwang and Wu [13] have also previously reached a similar conclusion. This pattern indicates that the field is becoming increasingly domain-specific because serious games are adapted to meet the needs of specific disciplines.
Mirroring this trend, as the general consensus on the efficacy of serious games continues to become more consistent, research has shifted from basic knowledge acquisition to more complex topics. Studies that once focused solely on “engagement” are now investigating “active learning”, “self-efficacy”, and “cognitive load”. This transition suggests a growing emphasis on how learning occurs within game-based environments. With this, the lack of focus on the underexplored aspects of GBL, such as affective, socio-contextual, engagement-related, and problem-solving reported by Li and Tsai [12] and Cheng et al. [1], is being increasingly addressed. Overall, these findings indicate a shift in the field from a technology-focused perspective towards a more pedagogically grounded understanding of game-based learning in science education.
The citation analysis of authors revealed two disconnected clusters. The fact that these clusters are disconnected possibly points to the existence of two independent research communities that operate in parallel. This separation may indicate limited exchange between these communities and may slow the sharing of ideas across the field. The network map also shows limited cross-citation between the two clusters. Interestingly, a similar result was observed in Ekin and Gul’s [14] analysis. This recurring pattern across studies suggests that this fragmentation reflects a common feature of the field. Then, the presence of scholars like Gwo-Jen Hwang, Marc Prensky, James Paul Gee, Valerie Shute, Juho Hamari, Richard Mayer, and Richard Ryan in the subsequent co-citation analysis illustrates the field’s strong foundations. In other words, the field draws from a blend of educational technologies, theories, and frameworks from various fields. This diversity suggests that research on serious games is inherently interdisciplinary because it combines perspectives from learning sciences, psychology, and educational technology. Finally, Hwang’s role as an influential figure is confirmed by his frequent appearance in both the citation and co-citation analyses. This consistency highlights the influence of key researchers who shape the direction of the field.
The citation analysis of countries revealed the USA and China as the two leading contributors. These two countries are the driving force behind much of the global research in the field. Other contributors, such as Spain, Taiwan, Greece, Germany, and Turkey, play a significant supporting role, especially as emerging hubs of research. The presence of these countries suggests that research is expanding beyond traditionally dominant regions. While the USA has historically been the most prominent country [4,14], the current results differ from previous findings, as Spain holds the second-highest number of documents, surpassing Taiwan [13,14] and the Netherlands [4]. Previously, Ullah et al. [4] emphasized the limited representation from developing countries in research from 2011 to 2021. In contrast, recent years have seen increased representation from developing nations such as Turkey, Malaysia, and Brazil. This shows that more countries are becoming involved in research. The overlay visualization clearly illustrates this shift, as the early dominance of Western countries gives way to the growing activity in Asian and South American countries. As new regional research communities continue to emerge, the global diversity of research is increasing [13]. This growing diversity may contribute to a wider range of perspectives and research priorities within the field. Furthermore, the findings suggest that there is active international collaboration, but gaps persist. This implies that collaboration networks are developing but not yet fully integrated. In accordance with Ekin and Gul [14], this indicates that there remain substantial opportunities for future international collaboration.
Finally, the citation analysis identified Computers & Education, Education and Information Technologies, and Education Sciences as primary publication outlets. The co-citation analysis confirms that Computers & Education remains the primary anchor [14], with strong co-citation links to journals in educational technology, learning sciences, and psychology.

4.2. RQ2: What Do Recent Studies Reveal About How Serious Games Are Designed and Used in Science Education?

Content analysis results indicate that studies have explored the impact of serious games on a variety of topics, including but not limited to learners’ perceptions, engagement, self-efficacy, collaboration, cognitive load, anxiety, and the development of higher-order skills. However, the majority of these studies primarily examined the efficacy of GBL. This suggests that research has mainly focused on whether serious games are effective rather than on how they support learning. Although there might not yet be a clear consensus on the effectiveness of GBL in enhancing science learning outcomes [3,15], many studies have reported positive effects of serious games across different instructional settings and game formats. This suggests that serious games have the potential to support science learning across diverse educational contexts. Especially compared to traditional instructional methods, the use of GBL has demonstrated positive effects on learners’ affective, behavioral, cognitive, and sociocultural experiences [9,36,37,47,50]. This partially aligns with the previous meta-analyses of Wouters et al. [19] and Riopel et al. [3], which concluded that serious games were more effective for knowledge acquisition and retention. These findings show that GBL supports not only learning outcomes but also students’ overall learning experiences.
Serious games have also been found to facilitate the development of higher-order skills [32,39,40,41,42] and scientific reasoning [44]. These positive effects were attributed to the game’s unique capacity to provide immediate feedback and its social nature. Games create risk-free environments where instant feedback allows students to adjust their understanding in real time [31,48]. Furthermore, the social nature of GBL fosters collaborative problem-solving and teamwork [36,48]. These features show that serious games are effective because they support active and social learning. Research emphasizes the importance of this social engagement, as higher qualities of social interaction and team synchrony have been found to predict better behavioral engagement and knowledge acquisition [16,48,56]. Moreover, collaborative learning structures helped learners with varying abilities in moderating the complexity of tasks [30]. This highlights the role of game-based learning in supporting diverse learners through adaptive and collaborative learning environments. Research consistently observed these positive effects in a wide range of scientific domains. The results confirm that, among the scientific subjects, physics and biology remain the most popular. However, studies related to chemistry education were also identified in the reviewed literature [29,30]. This finding suggests that, while certain areas remain dominant, the application of serious games is spreading across different fields of science education.
It must be noted that for GBL to work effectively, its design and integration into the curriculum must be carefully managed [52,68]. In this context, proper scaffolding is critical for connecting gameplay to learning outcomes [15,33]. Otherwise, the added complexity from GBL interventions can overwhelm students and distract them from the educational content [52]. This finding is consistent with recent studies highlighting the importance of balancing engagement, immersion, and cognitive load in adaptive gamification environments for science education [21]. Besides this, some studies have reported drawbacks often associated with the fundamental nature of games [3,4]. For instance, the competitive or playful nature of games can negatively impact the affective state of students when these elements overshadow the educational content [52,53]. This suggests that game elements need to be carefully balanced with educational goals.
Meanwhile, not all students benefit equally from GBL interventions. As research spans various contexts and educational settings, learners’ backgrounds, characteristics, and environments play a significant role in influencing the effectiveness of GBL. However, the role of these factors remains unclear. This indicates that the impact of GBL can vary depending on the context and the learners involved. Recent studies have also highlighted the importance of adaptive game design that considers learners’ motivational characteristics, learning strategies, and subject-specific needs in science education [20]. Overall, these findings indicate that effective GBL depends not only on curriculum integration but also on game design that considers learners’ needs and characteristics. Therefore, games should be designed with educational goals in mind [9,15,18]. The design should ideally appeal to learners with different socioeconomic backgrounds and genders, as well as to students with special needs [43,47,61,62]. While these suggestions are valuable, it is important to acknowledge that each game’s design must appropriately align with the specific goals and requirements of its context [8,11]. For this reason, there is no universal standardized methodology for game design [8].
The evidence regarding specific outcomes remains inconclusive [3,15]. This shows that, despite generally positive findings, the effects of serious games are not consistent across all outcomes and contexts. Previously, Wouters et al. [19] found no significant improvement in learners’ motivation, whereas recent studies have concluded otherwise [36,40,45,47]. This difference suggests that results may depend on how games are designed and used, as well as the context in which they are implemented. Similar inconsistencies also appear in gender dynamics. Some studies reported higher enjoyment for men [66] while others suggested limited or no substantial gender differences in learning perceptions and engagement [52]. Furthermore, conflicting results were reported regarding the impact of prior gaming experience on learning performance [15]. These mixed findings indicate that learner-related factors do not uniformly influence outcomes. It could be argued that the previously stated lack of standardization may have contributed to these inconsistent findings [15]. This highlights the need for clearer design and research frameworks in the field. Nonetheless, further systematic research is needed to establish more consistent evidence [3,4,8,11,18].
Game-based learning is widely used as an umbrella term encompassing a variety of pedagogical strategies [8,14,15]. The broad application of this term is partly one of the reasons for the observed contradictions [15]. This suggests that differences in how GBL is defined and implemented may lead to inconsistent findings across studies. As previously reported by Videnovik et al. [8], the majority of studies implemented the “learn by playing” approach. Unlike their previous findings, the results show that a significant number of studies have examined the effectiveness of “learn by making games” [15,42,51]. This indicates increased interest in different pedagogical strategies, as evidenced by studies that not only explore but also support the potential of GBL as an assessment method [17,53]. This expansion suggests that GBL is being used not only as a teaching tool but also as a means of evaluating learning. However, as stated by Videnovik et al. [8], more effort should be put into expanding the research focus and scope of these strategies. This highlights the need to further diversify how GBL is applied in educational contexts. This includes an increased research focus on non-digital games, as various findings suggest that these games have significant positive effects on learning [36,58]. Although Kara [69] observed that analog games are less prominent in the field, these “unplugged” methods can also effectively support student learning [8]. This suggests that the potential of non-digital game-based approaches remains underexplored despite their demonstrated effectiveness.
Finally, there is an increase in the use of immersive technologies such as augmented reality (AR) and virtual reality (VR) [4,70]. These technologies are primarily utilized to create immersive and multimodal learning environments [28,40,59]. This suggests that recent developments in GBL are increasingly driven by advances in immersive technologies. AR plays a unique role in several studies [28,59] as a bridge between the physical and digital formats. Consistent with previous research [4,70], AR was also found to increase understanding, learning achievement, and engagement [28,43]. This indicates that AR supports both learning outcomes and learner engagement. Despite this, the imposed cognitive load may lead to a drop in confidence [28]. The adaptive support provided by these technologies taps into one of the prime strengths of serious games, as they allow students to learn at their own pace [17]. This suggests that immersive technologies are most effective when combined with appropriate instructional support. Future research should continue to explore these immersive technologies, as they have strong potential to advance game-based learning [4,69,70].

5. Implications and Limitations

The findings suggest that the effectiveness of serious games in science education depends not only on their use but also on how they are integrated into science curricula. In particular, scaffolding is essential for connecting gameplay to scientific concepts and processes. Without appropriate instructional support, the complexity of game-based environments may hinder students’ understanding of abstract or conceptually demanding topics such as physics or biology. Therefore, instructors should ensure that serious games align with specific scientific learning objectives and are supported by structured guidance that facilitates conceptual understanding.
The results also highlight the importance of designing serious games that support science learning processes rather than focusing solely on engagement. In science education, game mechanics should facilitate key practices such as problem solving, experimentation, and scientific reasoning. In addition, designers should carefully balance immersion and cognitive load, as highly complex environments may reduce learners’ confidence and hinder learning. These findings suggest that effective serious games for science education require alignment between game design and science teaching and learning processes.
At a broader level, the findings indicate the need for stronger institutional support for integrating serious games into science education. This includes providing instructors with training on using serious games to support science learning and integrating them into existing curricula. Furthermore, the uneven distribution of research across countries and educational levels suggests that the use of serious games may vary across contexts. Addressing these gaps will be important for extending their use to a wider range of educational settings and learner groups.
Despite these implications, this review study has several limitations. First, the review focuses solely on journal articles indexed in the Web of Science (WoS) Core Collection, published between 2020 and 2025. While limiting the scope to WoS allows the inclusion of high-impact, peer-reviewed journals, it may exclude relevant studies indexed in other databases such as Scopus, ERIC, or Google Scholar. As a result, some regional, interdisciplinary, or recently published studies may not have been captured in the analysis. Therefore, the findings may not fully reflect the broader literature on the subject. Second, the review was limited to English-language articles. This limitation may leave out valuable research published in other languages. Finally, the search strategy relies on predefined keywords; therefore, relevant studies using alternative terminology or unindexed keywords may have been excluded from the analysis.

6. Conclusions

This study examined recent research trends in the use of serious games for science education through a bibliometric analysis of 340 articles and a content analysis of 56 studies. By combining these two approaches, the study provides a comprehensive view of both research patterns and how serious games are designed and used in educational contexts. The findings indicate that the field is maturing, with research moving beyond general effectiveness toward understanding how serious games support learning in different contexts. While GBL is widely reported to have positive effects on learning outcomes and student experiences, these effects are not uniform and depend on factors such as design, implementation, and learner characteristics. In this regard, scaffolding and thoughtful integration into the curriculum are critical to ensuring effective learning.
The study also highlights several important trends. Research is mainly focused on higher education and is largely driven by a few leading countries. However, participation from developing regions is increasing. At the same time, the use of immersive technologies such as AR and VR is growing. These technologies offer new possibilities for interactive and multimodal learning, but also create challenges related to cognitive load. In addition, there is increasing interest in diverse pedagogical approaches, including “learn by making games” and the use of non-digital games. However, these approaches are still underexplored despite their demonstrated effectiveness. Despite generally positive findings, there have been inconsistencies across studies. These inconsistencies can be traced to the broad, varied use of the term “game-based learning” and to the lack of standardized design and research frameworks. This shows the need for more systematic research to better understand how and under what conditions serious games are most effective. Overall, this study contributes to the field by integrating bibliometric and content analysis to connect research trends with insights into teaching and learning. Future research should focus on developing more systematic and context-sensitive design frameworks that balance educational goals, learner characteristics, and game mechanics across different science education contexts. Future studies should continue exploring underrepresented approaches such as non-digital games. They should also examine how emerging technologies can best support learning in science education.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/computers15060330/s1, Supplementary File S1: Article Analysis Form for Included Studies (n = 56); Supplementary File S2: Content Analysis Coding and Themes for Included Studies (n = 56). References [71,72,73,74,75,76,77,78,79,80,81] are cited in the Supplementary Materials and have also been included in the main reference list.

Author Contributions

D.P.G.: data curation, formal analysis, writing—review and editing, N.K.: conceptualization, methodology, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

The authors received no financial support for the research and authorship of this article. Publication support for this article was provided by Istanbul Bilgi University.

Data Availability Statement

Data generated or analyzed during this study are available from the authors upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Study selection flow diagram for the bibliometric analysis.
Figure 1. Study selection flow diagram for the bibliometric analysis.
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Figure 2. PRISMA flow chart for study selection process.
Figure 2. PRISMA flow chart for study selection process.
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Figure 3. Network Map of the Most Used Author Keywords. Different colors represent different keyword clusters identified by the VOSviewer analysis.
Figure 3. Network Map of the Most Used Author Keywords. Different colors represent different keyword clusters identified by the VOSviewer analysis.
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Figure 4. Network Map of the Most Used Author Keywords by Year.
Figure 4. Network Map of the Most Used Author Keywords by Year.
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Figure 5. Network Map of the Most Cited Authors (Citation Analysis).
Figure 5. Network Map of the Most Cited Authors (Citation Analysis).
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Figure 6. Network Map of the Most Cited Authors (Co-citation Analysis). Different colors represent different author clusters identified by the VOSviewer co-citation analysis.
Figure 6. Network Map of the Most Cited Authors (Co-citation Analysis). Different colors represent different author clusters identified by the VOSviewer co-citation analysis.
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Figure 7. Network Map of the Most Cited Countries (Citation Analysis).
Figure 7. Network Map of the Most Cited Countries (Citation Analysis).
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Figure 8. Network Map of the Most Cited Countries by Year (Citation Analysis).
Figure 8. Network Map of the Most Cited Countries by Year (Citation Analysis).
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Figure 9. Network Map of the Most Cited Journals (Co-citation Analysis). Different colors represent different journal clusters identified by the VOSviewer co-citation analysis.
Figure 9. Network Map of the Most Cited Journals (Co-citation Analysis). Different colors represent different journal clusters identified by the VOSviewer co-citation analysis.
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Table 1. The initial search query terms for bibliometric analysis.
Table 1. The initial search query terms for bibliometric analysis.
Web of Science Index:(NOT) BKCI, BKCI-SSH
TS = (Science AND Education AND (Serious Game OR Digital Game OR Educational Game) NOT (AK = Bibliometric OR Bibliometrics OR Meta) OR KP = (Bibliometric OR Bibliometrics OR Meta))
Publication Date:1 January 2020 to 19 August 2025
Table 2. The initial search query terms for content analysis.
Table 2. The initial search query terms for content analysis.
Web of Science Index:(NOT) BKCI, BKCI-SSH
TS = (Science AND Education AND (Serious Game OR Digital Game OR Educational Game) NOT (AK = Bibliometric OR Bibliometrics OR Meta) OR KP = (Bibliometric OR Bibliometrics OR Meta))
AND
TI = (Science AND (Game OR Serious Game OR Digital Game OR Educational Game)) AND AB = (Science AND (Game OR Serious Game OR Digital Game OR Educational Game))
Publication Date:1 January 2020 to 19 August 2025
Table 3. The Top 10 Most Cited Journals Ranked by Citations (Citation Analysis).
Table 3. The Top 10 Most Cited Journals Ranked by Citations (Citation Analysis).
RankJournal NameDocumentsCitationsTotal Link Strength
1Computers & Education132901
2Education and Information Technologies2927115
3Education Sciences262693
4Interactive Learning Environments152673
5British Journal of Educational Technology102587
6Journal of Educational Computing Research51924
7Educational Technology Research and Development (ETR&D)111868
8IEEE Transactions on Learning Technologies9952
9Journal of Science Education and Technology10855
10Journal of Computer Assisted Learning5763
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MDPI and ACS Style

Gök, D.P.; Kara, N. Serious Games in Science Education: A Systematic Bibliometric and Content Analysis. Computers 2026, 15, 330. https://doi.org/10.3390/computers15060330

AMA Style

Gök DP, Kara N. Serious Games in Science Education: A Systematic Bibliometric and Content Analysis. Computers. 2026; 15(6):330. https://doi.org/10.3390/computers15060330

Chicago/Turabian Style

Gök, Deniz Poyraz, and Nuri Kara. 2026. "Serious Games in Science Education: A Systematic Bibliometric and Content Analysis" Computers 15, no. 6: 330. https://doi.org/10.3390/computers15060330

APA Style

Gök, D. P., & Kara, N. (2026). Serious Games in Science Education: A Systematic Bibliometric and Content Analysis. Computers, 15(6), 330. https://doi.org/10.3390/computers15060330

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