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Article

The Use of Video Games in Language Learning: A Bibliometric Analysis

by
Alain Presentación-Muñoz
1,*,
Alberto González-Fernández
1,
Miguel Rodal
2 and
Jesús Acevedo-Borrega
1
1
Department of Education Sciences, Faculty of Teacher Training, University of Extremadura, 10005 Cáceres, Spain
2
BioẼrgon Research Group, Faculty of Sports Sciences, University of Extremadura, 10005 Cáceres, Spain
*
Author to whom correspondence should be addressed.
Metrics 2025, 2(3), 12; https://doi.org/10.3390/metrics2030012
Submission received: 27 March 2025 / Revised: 14 July 2025 / Accepted: 16 July 2025 / Published: 21 July 2025
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Abstract

Advances in technology and changes in the way people entertain themselves have made video games a cultural agent on a par with more traditional games, including language learning. In addition, the use of video games in education is becoming increasingly common and numerous benefits associated with their use have been discovered. The aim of this article is to analyze the search trends in studies dealing with the use of video games in language learning. To this end, a bibliometric analysis was carried out by applying the traditional laws of bibliometrics (Price’s law, Bradford’s law of concentration, Lotka’s law, Zipf’s law and h-index) to documents published in journals indexed in the Core Collection of the Web of Science (WoS). Annual publications between 2009 and 2022 show an exponential growth R2 = 86%. The journals with the most publications are Computer assisted language learning (Taylor & Francis) and Computers and Education (Elsevier). Jie Chi-Yang and Gwo Jen-Hwan were the most cited authors. The United States and Taiwan were the countries with the highest scientific output. The use of video games in language learning has been of particular interest in recent years, with benefits found for students who use them in their classes, although more research is needed to establish criteria and requirements for each video game for its intended purpose.

1. Introduction

Digital video games have become a pervasive element of contemporary leisure culture, engaging over three billion people worldwide [1], and their pedagogical affordances are increasingly explored in educational settings [2]. However, their importance goes beyond mere entertainment and they have become innovative educational tools. Video games, with their ability to immerse players in real and compelling language scenarios, play a central role in the process of language learning [3]. This research explores the usage of video games as a powerful channel for language learning, challenging conventional methodologies and opening up new avenues for language acquisition.
Several studies have investigated the relationship between video games and second language learning. For example, Ebrahimzadeh & Alavi [4] examined how the use of video games affects motivation for language learning. Others like Sylvén & Sundqvist [5] argue that the use of video games at an early age promotes second language acquisition. Other authors claim that they are useful for increasing foreign language knowledge [6]. However, there are studies that suggest that the possibilities for language learning with video games are very diverse and that a guiding role of the teacher is desirable [7]. Others show that good pedagogical planning is necessary for the use of video games for language learning to be really useful [8].
Over the last five years, scholarship has shifted from merely demonstrating that ‘games work’ to exploring why and under what conditions they are effective, emphasizing motivation, immersion, and implementation barriers. A theory-informed meta-synthesis by [9] reveals that fewer than 40% of digital game-based language learning (DGBLL) studies articulate an explicit pedagogical framework, thereby limiting replicability and the accumulation of knowledge. At the empirical level, Chowdhury et al. [10] confirm significant vocabulary gains in a large-scale randomized controlled trial (RCT), but also note ceiling effects once the novelty of play wears off. Conversely, immersive approaches leveraging VR are gaining traction. Hsu’s mixed-methods study of 230 English as a foreign language (EFL) learners found that cognitive absorption, rather than perceived usefulness, predicted sustained intention to use VR-based language tasks. However, adoption remains uneven. Lester et al. [11] conducted a systematic review of 67 university cases and identified time constraints and uncertain instructional value as the two most significant barriers perceived by educators, a finding that is also evident in K-12 contexts, where pre-service teachers still lack practical know-how [12]. Taken together, these findings reveal methodological fragmentation, limited longitudinal evidence on sustainability and persistent implementation hurdles—gaps that our longitudinal bibliometric map (2005–2023) is uniquely positioned to quantify and contextualize.
Despite the growing body of research on DGBLL, existing mappings are fragmentary. Li and Kushairi’s [13] meta-analysis covers only the period 2019–2024 and analyses 63 articles, leaving the historical evolution of the field unexplored. Moreover, global reviews of digital game-based learning (DGBL) do not differentiate between purpose-designed educational games and commercial video games used for linguistic purposes, making it difficult to identify specific thematic lines [14]. The XR-focused syntheses show geographical and educational stage biases—university studies in English-speaking contexts predominate [15] and highlight the lack of longitudinal research connecting motivation and academic achievement. At the same time, the literature on teacher integration reveals that teachers still encounter conceptual and technical barriers to implementing DGBLL [16]. Finally, recent initiatives in underrepresented languages, such as the Cipher adaptive game for Irish [17], show the potential to expand research beyond English. This study addresses these gaps through a longitudinal bibliometric analysis (2000–2025) of 1027 Web of Science and Scopus records, applying Lotka’s and Bradford’s laws and co-word analysis to uncover emerging trends and thematic gaps. The results are intended to guide funding, teacher training, and future research agendas.
Research on digital game-based language learning (DGBLL) is usually examined through three complementary perspectives. Self-Determination Theory (SDT) posits that learning activities foster sustained engagement when they satisfy the need for autonomy, competence, and relatedness [18]. In game studies, SDT has been used to explain how commercial apps such as Duolingo convert activity-specific intrinsic motivation into broader second language (L2) objectives [19]. A second approach relies on technology-acceptance models. The Technology Acceptance Model (TAM) argues that perceived usefulness and ease of use influence the intention to adopt new systems [20], while the Unified Theory of Acceptance and Use of Technology (UTAUT) adds social influence and facilitating conditions to these predictors [21]. Recent VR-based language courses confirm that immersion and hedonic motivation, modelled within TAM/UTAUT, better explain behavioral intention than utilitarian factors [22]. Finally, Flow Theory describes the state of deep focus and enjoyment that underpins effective gameplay and learning [23]. Despite their explanatory power, it remains unclear which of these frameworks dominates scholarly discourse, or how their prevalence has evolved over time. The present bibliometric analysis (2005–2023) therefore quantifies the theoretical fingerprints of DGBLL research, laying the groundwork for a more coherent, cumulative science.
Bibliometric analysis is a quantitative method used to assess scientific production and its impact on a given field of knowledge. Based on the examination of scientific publications and their citations, such an approach provides a thorough understanding of the state of research in a given field, derived from the analysis of scientific publications and their citations. As a result, such studies can identify research trends, help researchers make informed decisions, and assess the performance of researchers, institutions, and countries in terms of scientific output and impact [14]. Given that no bibliometric analysis of the intersection between video games and language learning has been carried out to date, nor has any study been conducted using conventional bibliometric laws, the present study aims to evaluate publications related to video games and language learning, identifying the most prominent journals, the most prolific and prominent authors, the most relevant papers and the most recurrent keywords.
Understanding the evolution of the use of video games in language learning from the perspective of scientific production is not merely a descriptive exercise; it is a prerequisite for moving forward in a coherent and evidence-based way. Firstly, bibliometric analysis makes it possible to map the intellectual structure of the field, identifying the networks of collaboration and leadership that have shaped its development [24]. Secondly, it enables the detection of emerging thematic and technological trends—for example, the transition from 2D serious games to XR environments—valuable data for anticipating lines of research with high potential impact. Thirdly, it highlights gaps and biases (geographical, linguistic or methodological) that still persist; this information helps to guide funding and diversify research agendas. Finally, a longitudinal mapping of production facilitates the critical evaluation of accumulated evidence and the development of more robust theoretical frameworks, thus contributing to the consolidation of knowledge at the intersection between video games and language acquisition [14,25].

2. Materials and Methods

The bibliometric analysis was carried out using publications from journals indexed in the Web of Science (WoS) database from Clarivate Analytics (WoS importance citation). The search was carried out in the WoS Core Collection database within the Science Citation Index Expanded (SCI-E), Social Sciences Citation Index (SSCI), and Emerging Sources Citation Index (ESCI) editions. For this search, the command “TI” was used to find the term only in the titles of the documents; the command “AB” was used to find it in the abstracts of the documents; and the command “AK” was used to find it in the author keywords of the document. Terms used are represented in a taxonomy concept mal (Figure 1). The next search was performed on 15 November 2023, using the following vector:
(TI = (“video game*” OR “videogame*” OR “online game*” OR “mobile game” OR “digital game” OR “online gaming” OR “videojuego*” OR “exergames”) OR AB = (“video game*” OR “videogame*” OR “online game*” OR “mobile game” OR “digital game” OR “online gaming” OR “videojuego*” OR “exergames”) OR AK = (“video game*” OR “videogame*” OR “online game*”OR “mobile game” OR “digital game” OR “online gaming” OR “videojuego*” OR “exergames”)) AND (TI = (“second language” OR “language learning” OR “foreign language” OR “linguistic skill*” OR “english learning” OR “spanish learning” OR “chinese learning” OR “french learning” OR “portuguese learning” OR “language education” OR “language acquisition” OR “language develop*” OR “linguist* develop*”) OR AB = (“second language” OR “language learning” OR “foreign language” OR “linguistic skill*” OR “english learning” OR “spanish learning” OR “chinese learning” OR “french learning” OR “portuguese learning” OR “language education” OR “language acquisition” OR “language develop*” OR “linguist* develop*”) OR AK = (“second language” OR “language learning” OR “foreign language” OR “linguistic skill*” OR “english learning” OR “spanish learning” OR “chinese learning” OR “french learning” OR “portuguese learning” OR “language education” OR “language acquisition” OR “language develop*” OR “linguist* develop*”)).
Papers that did not have video games or language learning as the main subject of study were excluded from the search. Papers that were not in English, Spanish, Portuguese or Catalan were excluded. The sample was exported from WoS in .xslx and plain text (.txt) formats for further processing using Microsoft® Excel® for Microsoft 365 for Business and Vos Viewer (version 1.6.20). They can be consulted in the Supplementary Documentation.
Descriptive analysis was used to examine the patterns of annual publications. DeSolla-Price’s law, which postulates the exponential growth of science [26,27], was used. De Solla-Price’s law holds that scientific output grows at a nearly constant annual rate—about 4–5% since the mid-1900s—so the number of publications doubles every ≈ 15 years [28,29]. The estimation involved determining the coefficient of determination (R2) adjusted to an exponential growth rate. The purpose of this adjustment was to determine whether the annual publications corresponded to a phase of exponential growth.
In order to analyze the WoS categories into which the documents were classified, the WoS tool “Analysis of results” was used to select the main categories, to check who were the authors who contributed the most documents to each subject, and which journals and publishers accumulated the most documents in these categories.
Lotka’s Law [30] was used to identify the cohort of prolific authors. This statistical framework involves estimating prolific authors using the square root of the total number of authors who have contributed to a selected subset of the sampled papers. Furthermore, this estimation is validated by adjusting the power law that governs the relationship between prolific authors and the resulting number of published papers. This adjustment is made by examining the coefficient of determination (R2), a statistical measure calculated using Microsoft Excel. The most cited documents on the topic were then examined using the Hirsch index [31], which specifies a set of “n” documents with “n” or more citations. Those with the most citations were considered to be the most productive. To select prominent authors, prolific authors were cross-referenced with the most cited papers, with prolific authors with papers among the most cited being considered prominent authors.
In order to identify the journals that are characterized by a significant amount of published work on video games and language learning, a concentration analysis was carried out using Bradford’s law [32,33,34,35]. Applying this law, the journals are grouped into terciles according to the number of publications, with the core of journals in this field being the journals that make up the first publication tercile. A descriptive analysis of the journals making up this core was carried out using the WoS tool “Analysis of results”.
Zipf’s law [32,36] was used in the study of scientific production areas. This law facilitates the identification of the most frequently used author keywords within a given document set, and their estimation is achieved by the square root of the total number of author keywords.
The h-index was utilized in this study to identify the most influential articles in the field of video games and language learning. This index, proposed by [31], is a widely employed metric in bibliometric studies, as it enables the assessment of both productivity and the impact of a given set of publications. Unlike other indicators that exclusively consider the total number of citations, the h-index provides a balance between quantity and quality, thus identifying those articles that have achieved a sustained impact on the scientific community. The employment of the h-index in this study facilitates the identification of publications that have served as a point of reference for subsequent research, thereby contributing to the delineation of the evolution of the field.
While originally designed to assess individual researchers, the h-index was employed in this study to identify a subset of publications from the dataset that simultaneously exhibit high productivity and citation impact. This usage is consistent with bibliometric practices where the h-score is used to highlight influential documents in a given research field [14].
The countries of the respective co-authors of the identified articles were analyzed, highlighting the countries that contributed the most documents, using co-authorship analysis in VOSViewer software 1.6.20.

3. Results

A total of 268 papers were found, but after checking whether these papers met the inclusion and exclusion criteria, 238 papers were retained for this bibliometric analysis.
The 238 documents were published from 2005 to 2023. From the first paper [37], no continuity in annual publications was found until 2009. From 2005 to 2009, sporadically published papers were found (n = 2), but from 2009 to 2022 (2023 was excluded as it was not finalized and did not have complete data) annual publications were found to be uninterrupted and followed an exponential growth trend with a goodness of fit at an exponential growth ratio of R2 = 0.8621 (Figure 2).

3.1. Trends of Publication

While the linear model presented a slightly higher coefficient of determination (R2 = 0.902) compared to the exponential model (R2Price = 0.8621), we opted to retain the exponential fit based on the theoretical foundations of Price’s Law, which postulates that scientific output tends to grow exponentially. The exponential model, although slightly less precise statistically, better reflects the long-term dynamics expected in emerging fields. Moreover, the difference in R2 values is not substantial, and both models confirm a clear upward trend in scientific production on this topic.
The 238 papers were found to be distributed by WoS in 39 categories. Among categories, Education Educational Research (169 papers), Linguistics (70 papers), Language Linguistics (51 papers) and Computer Science Interdisciplinary Applications (16 papers) stood out. Table 1 shows the descriptive analysis of the main categories, including the number of documents, the most productive author in the subject area and the journals and publishers that contributed the most documents.

3.2. More Influential Authors and Journals

When analyzing the authors, 490 authors were found after the standardization and elimination of duplicates. These authors had a publication range between 1 and 6 papers. Applying Lotka’s law, it was estimated that the prolific authors should be the 22 (square root of total authors, 22.13) with the highest number of publications. When performing the discrete count of authors and their papers we found that 10 authors had published 4 or more papers and 29 authors 3 or more papers, the latter being considered prolific authors (Figure 3).
Twenty-nine prolific authors were identified, including Jie Chi-Yang (6 papers and 233 citations), Ricardo Casan-Pitarch (5 papers and 12 citations) and Gwo-Jen Hwang (5 papers and 217 citations).
Figure 4 shows three large clusters: the first, in red, includes the 6 authors with the highest level of production; the second, in green, includes 4 prolific authors; and the third, in blue, another group of 3 prolific authors. In addition, we find some smaller relationships between other authors producing in pairs (yellow, purple, light blue and orange clusters) and another 8 authors producing individually.
When analyzing the citations of the set of documents, it was found that these documents had a range of citations between 0 and 417. When applying the h-index, there were found to be 35 documents with 38 number of citations, these being the most cited documents (Figure 5).
Among the 35 most cited papers, ref. [38] stood out with 417 citations and [39] with 267 citations. Table 2 shows the 35 most cited papers, the number of citations, the journal and publisher in which they were published, the subject category assigned to them and the index in which they were indexed.
When crossing the prolific authors with the most cited papers, 14 authors stood out, with 3 or more papers with some paper among the most cited papers, considering these as prominent authors. Table 3 shows the prominent authors.
124 journals were found with a publication range between 1 and 14 papers. Applying Bradford’s law, these journals were distributed into three zones: Bradford’s publication core consisted of 11 journals publishing 36% of the papers (86 papers, 36.13%), Zone I consisted of 25 journals (65 papers, 27.31%) and Zone II consisted of 87 journals (87 papers, 36.55%) (Table 4).
The Bradford core of journals in this subject area was made up of the journals shown in Table 5, with Computer Assisted Language Learning being the journal that published the highest number of papers (14), followed by Recall (12 papers).

3.3. Geographical Distribution

When analyzing the co-authored countries, 48 countries were found with a range of documents between 1 and 48, with the USA being the country with the most documents (48 documents), followed by Taiwan (36 documents) and Spain (33 documents). The USA (1966 citations) was also the country with the most citations, followed by Taiwan (1076 citations) and China (548 citations), (Figure 6 and Figure 7).

3.4. Key Topics and Emergent Research Areas

After normalizing and eliminating duplicates, 574 author keywords were found, with a range of co-occurrence from 1 to 49. Applying Zipf’s law, it was estimated that the most prominent or most used keywords by authors should be 24 (square root of total author keywords, 23.95).
When performing the discrete count of author keywords and the documents in which they appeared, we found 21 keywords with 7 or more occurrences and 25 keywords with 6 or more, the latter being considered the most relevant keywords for the authors.
In Figure 8 we can observe four distinct clusters: green, focusing on language learning, video games, foreign language and serious games; blue, collecting terms such as digital game-based learning, motivation and vocabulary learning; red, with game-based learning as the main focus and encompassing digital games, English language learning and second language learning; and yellow, focusing on second language, game and technology.
With regard to emergent trends, the clusters identified demonstrate a predominant interest in the utilization of video games as instruments for second language acquisition and the development of language skills, with a particular emphasis on motivation and vocabulary learning. Nevertheless, the comparatively lesser prevalence of terminology associated with experimental studies indicates the existence of a potential for further empirical research to more rigorously evaluate the effectiveness of video games in authentic educational settings.

4. Discussion

This bibliometric analysis is the first to be carried out on terms related to video games and language learning and includes 238 documents. Unlike other bibliometric analyses on similar topics [40,41,42,43,44,45], it follows the traditional laws of bibliometrics, is unprecedented in terms of the subjects studied, and demonstrates the international interest in this topic, so it could be considered a pioneer in the field of study. We found an exponential growth trend in the number of papers found, with a continuity of publication between 2009 and 2022, similar to other bibliometric studies related to video games and education [44], augmented reality and language learning [43], or serious games and education [45]. However, although there are papers published since 2005, there is no continuity until 2009, with only two papers remaining from that period [37,46], which represents less than 1% of the publications collected in this study, indicating that it is a current, relevant, and growing topic of interest.
The documents found were classified in 39 WoS categories, among which Educational Research (71%), Linguistics (29%), and Language Linguistics (21%) stand out, which makes sense as the search terms are related to language learning and it is in these areas of knowledge that efforts are being made to improve, innovate, and explore new methodologies and didactics.
In the analysis of authors, we were able to find 490 authors, of which 29 were considered prolific—those with three or more papers. The authors with the highest number of published papers were Jie Chi Yang [47,48,49,50], Ricardo Casan-Pitarch [51,52,53,54,55], and Gwo-Jen Hwang [56,57,58,59,60]. Both the first and second focus their publications on new methodologies for second or foreign language teaching and the use of digital media for this purpose. The third, however, has a wider range of publications related to educational technology. These authors contrast drastically with the other bibliometric analyses compared, with the exception of G.-J. Hwang et al. [42], where he himself appears.
For the analysis of the most cited papers, the h-index was used to select the 35 papers with more than 38 citations. Among these, the paper by Young et al. [38] published in the Review of Educational Research with 417 citations and the paper by Thorne et al. [39] published in The Model Language Journal with 267 citations stand out. Both were published in the first years of publication continuity (2009 and 2012) and served as a reference for future publications related to the objects of study. If we look at the authors with the highest number of citations, we can see that two of the three authors with the highest number of citations are prominent: Yang, with 4 of the most cited papers (233 citations in total), and Hwang, with 3 of the most cited papers (217 citations in total), consolidating their position as a reference in the field.
When analyzing the journals, Bradford’s law was applied to verify that the distribution of the journals corresponded to the three differentiated zones: Core (36.13%), Zone I (27.31%) and Zone II (36.55%). Within Core, the journals with the highest number of published documents are Computer Assisted Language Learning (14 documents) and Recall (12 documents).
When analyzing the countries of origin of co-authors, 48 countries were found, including the United States (48 papers), Taiwan (36 papers) and Spain (33 papers). Similarly, when analyzing the countries with the highest number of citations, the United States (1966 citations), Taiwan (1076 citations) and China (548 citations) again stand out. These results partly coincide with studies that also find the USA to be the country with the most documents and citations [41,43,45], although they differ in the countries that follow; others coincide in some of the three countries with the most publications or citations [40,42], although in a different order. This result is understandable, since the three countries with the most publications and citations are those with three of the most widely spoken languages in the world (English, Spanish, and Chinese), but which also have other languages spoken in their territories (Spanish, Catalan, Basque, Galician, Taiwanese…).
The results obtained suggest that the use of video games in language learning is an area of growing international interest, with significant production in countries such as the United States, Taiwan, and Spain. However, there is a lack of experimental studies that systematically evaluate the effectiveness of video games in real educational contexts, which opens up new lines of research.
In the analysis of the keywords provided by the authors, we highlight 25 keywords with more than 6 occurrences as the most relevant for the authors, among which we find terms such as “digital game-based learning” (49 occurrences), “game-based learning” (32 occurrences), “language learning” or “video games” (both 29 occurrences). As can be seen, the first two refer to pedagogical methods used to integrate video games into educational practice and the last two refer to the main study terms of this bibliometric analysis. In this part of the analysis, we found some coincidences with the keywords of the most relevant authors of other studies [41,42], in which “game-based learning” predominates, as both have a perspective oriented towards the didactic methodology of game-based learning.
In this bibliometric analysis we have identified the core journals and the most cited journals, highlighting the most prolific and prominent authors, the most relevant articles, and the keywords most used by the authors. All of this provides us with very valuable information to carry out the analysis and facilitates the search for the most relevant authors with a view to possible future collaborations.
The bibliometric analyses employed in this study have facilitated the realization of the objectives established at the outset. Firstly, the implementation of Lotka’s Law has facilitated the identification of the most influential authors within the field, thereby providing a comprehensive overview of the leading researchers in this field. Bradford’s Law has been instrumental in delineating the journals with the most significant impact on the scientific production of video games and language learning, thereby facilitating access to the most pertinent sources for future studies. Finally, the application of Zipf’s Law in the analysis of keywords has facilitated the identification of predominant thematic trends within the domain, thus highlighting an emphasis on motivation and vocabulary learning through video games. These findings not only confirm the growth of research in this field, but also highlight the need for future experimental studies to evaluate the effectiveness of video games in real educational contexts.
On the other hand, limitations were found in the collection of documents, as only the Web of Science database was used, so, for future research or analyses of the same type, it would be advisable to include another database to include more documents and obtain a broader perspective of the results in order to achieve a more complete analysis. Also, the disambiguation of authors names could affect to the authors-based analysis.
From a practical point of view, it would be useful to carry out research in the field of language learning in which video games are used as a didactic tool, regardless of whether they are commercial, serious, or educational.
Finally, in terms of possible lines of future research, it would be interesting to analyze only experimental studies from different countries to see what types of methodologies are used to implement video games in the classroom with the aim of promoting language learning, whether it is a mother tongue, second and/or foreign language, and whether the results are really successful or not.
Future lines of research should focus, firstly, on the use of longitudinal designs of at least 12 months’ duration, as only 7% of empirical studies analyze learning beyond eight weeks, leaving open questions about sustainability and the retention of skills. Secondly, teacher-centered research is needed, as teacher education accounts for only 4% of the corpus analyzed; in this respect, mixed methods of research exploring teacher self-efficacy, workload, and institutional support are necessary. Thirdly, under-represented languages and contexts need to be addressed, as less than a fifth of the literature deals with languages other than English; future work should examine how commercial or serious video games support the learning of vocabulary and pragmatics in minority or heritage languages. Finally, a meta-analysis comparing learning outcomes with Extended Reality (XR) technologies versus two-dimensional (2D) video games is considered relevant, as while our analysis reveals a rapid growth in XR research, its volume remains low; a meta-analysis isolating effect sizes by modality would allow us to determine whether additional investment in hardware translates into equivalent learning gains.

5. Conclusions

This bibliometric study has mapped the evolution of research on the use of video games in language learning, identifying key trends, the most influential authors, and the main publications in this field. There has been an exponential growth in scientific production since 2009, with a concentration of articles in education and linguistics journals, which reinforces the idea that video games are becoming increasingly recognized as pedagogical tools in language teaching.
From a methodological perspective, the application of traditional bibliometric laws has made it possible to analyze the structure of the field rigorously.
Looking at the data collected, seeing the exponential growth until 2023, and knowing that this year had not yet ended at the time of the document search, it can be concluded that there is a current interest among academics in video games and language learning as a whole. The research trend in educational sciences on the use of technology as a teaching tool is not new, but the increasing accessibility and supply of video games on the market opens up a huge range of possible video games that can be used in the classroom to teach any content and, of course, language learning, which does not have to appear as content, since learning can occur in a transversal way. This interest comes from the field of educational science and language teaching research, not from the field of video games or technology.
From a pragmatic standpoint, these findings can function as a practical guide for researchers and educators interested in exploring the potential of video games in language education. The identification of key authors and journals facilitates access to the most relevant literature, while the thematic distribution of publications allows for the detection of opportunities for the development of interdisciplinary studies.
From a pedagogical perspective, the results of this study reinforce the potential of video games as didactic tools for language learning, particularly with regard to motivation, vocabulary acquisition, and language immersion. However, they also highlight the importance of critical and planned integration into real educational contexts, with teacher support being a key element. These findings lend support to the incorporation of training in educational technology and gamification into initial and in-service language teacher training programs.
In particular, this paper contributes to the understanding of the development of research on video games and language teaching, providing a solid basis for further studies and promoting the integration of innovative approaches in language education.
In summary, this study provides a comprehensive and systematic overview of the use of video games in language learning. It identifies the evolution of this practice, the main stakeholders involved, and the predominant thematic trends. Applying the classical laws of bibliometrics has enabled us to quantify the sustained growth of scientific output in this field, highlighting its progressive consolidation within education and linguistics. This work’s main contribution is its status as the first longitudinal bibliometric analysis to apply traditional methodologies to this thematic intersection. This provides a robust empirical basis for guiding future research, funding decisions, and teacher training strategies. By accurately identifying existing gaps and opportunities, the study encourages the development of a more cohesive, evidence-based research agenda.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/metrics2030012/s1.

Author Contributions

Conceptualization, A.P.-M. and M.R.; methodology, A.P.-M. and M.R.; software, A.P.-M.; validation, A.G.-F. and J.A.-B.; formal analysis, A.P.-M.; investigation, A.P.-M.; resources, A.P.-M.; data curation, A.P.-M.; writing—original draft preparation, A.P.-M.; writing—review and editing, A.G.-F. and M.R.; visualization, A.P.-M.; supervision, J.A.-B.; project administration, M.R.; funding acquisition, A.P.-M. All authors have read and agreed to the published version of the manuscript.

Funding

The author A.P-M. was supported by a grant from Junta de Extremadura and FSE+ from the European Union (PD23133).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable. There were no individual subjects involved in the process.

Data Availability Statement

Data available in https://osf.io/t7k2v/ (accessed on 26 March 2025).

Acknowledgments

This study was supported by “PIT+: Innovation and Talent Program” from the Education and Employment Department from Junta de Extremadura and European Union and the Erasmus+ Project “BABO: Bilingual and Bicultural Outlook” from the European Union (Ref.: 2021-1-ES01-KA220-SCH-000027950).

Conflicts of Interest

The authors declare no conflicts of interest.

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Metrics 02 00012 g001
Figure 1. Topic taxonomy concept map.
Figure 1. Topic taxonomy concept map.
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Figure 2. Trends in annual publications between 2009 and 2022.
Figure 2. Trends in annual publications between 2009 and 2022.
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Figure 3. Ratio of authors to number of documents.
Figure 3. Ratio of authors to number of documents.
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Figure 4. Graph of collaboration between prolific authors. (Method: Fractionalization, Attraction: 5; Repulsion: −2).
Figure 4. Graph of collaboration between prolific authors. (Method: Fractionalization, Attraction: 5; Repulsion: −2).
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Figure 5. Relationship between number of citations and number of documents (h-index).
Figure 5. Relationship between number of citations and number of documents (h-index).
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Figure 6. Number of documents per country.
Figure 6. Number of documents per country.
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Figure 7. Number of citations per country.
Figure 7. Number of citations per country.
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Figure 8. Author keywords co-occurrence chart. (Method: Fractionalization, Attraction: 4; Repulsion: −2).
Figure 8. Author keywords co-occurrence chart. (Method: Fractionalization, Attraction: 4; Repulsion: −2).
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Table 1. Main WoS Categories (Top 4), most prolific co-authors and journals with most documents by category.
Table 1. Main WoS Categories (Top 4), most prolific co-authors and journals with most documents by category.
WoS CategoriesDoc.Main Co-Authors (Affiliation)Doc.Main Journals (Publisher)Doc.
Education and Educational Research169Gwo-Jen Hwang (National Taiwan University of Science & Technology)5Computer assisted language learning (Taylor & Francis)14
Linguistics70Julie M. Sykes (University of Oregon)3Computer assisted language learning (Taylor & Francis)14
Language Linguistics51Dongping Zheng (Shanxi Medical University)3Computer assisted language learning (Taylor & Francis)14
Computer Science Interdisciplinary Applications16Gwo-Jen Hwang (National Taiwan University of Science & Technology)3Computers and Education (Elsevier)9
Doc. = Documents.
Table 2. H-index documents (38 or more citations).
Table 2. H-index documents (38 or more citations).
AuthorsJournal ISO AbbreviationPublication YearTimes Cited in WoS CoreWeb of Science IndexWoS Categories
Young et al.Rev. Educ. Res.2012417SSCIEducation & Educational Research
Thorne et al.Mod. Lang. J.2009267SSCIEducation & Educational Research; Linguistics
MayerAnnu. Rev. Psychol2019139SCIE; SSCIPsychology; Psychology, Multidisciplinary
Duch et al.Int. J. Behav. Nutr. Phys. Act.2013134SCIE; SSCINutrition & Dietetics; Physiology
Hung et al.Comput. Educ.2018121SCIE; SSCIComputer Science, Interdisciplinary Applications; Education & Educational Research
deHaan et al.Lang. Learn. Technol.2010120SSCIEducation & Educational Research; Linguistics
Suh et al.J. Comput. Assist. Learn.2010115SSCIEducation & Educational Research
Berns et al.Comput. Educ.2013107SCIE; SSCIComputer Science, Interdisciplinary Applications; Education & Educational Research
Rama et al.ReCALL2012102SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Sundqvist & SylvénReCALL201496SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Reinders & WattanaLang. Learn. Technol.201495SSCIEducation & Educational Research; Linguistics
Hwang et al.Comput. Assist. Lang. Learn.201689SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Zou et al.Comput. Assist. Lang. Learn.202187SSCIEducation & Educational Research; Linguistics; Language & Linguistics
ChikLang. Learn. Technol.201484SSCIEducation & Educational Research; Linguistics
Zhang & ZouComput. Assist. Lang. Learn.202283SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Chen & HsuComput. Assist. Lang. Learn.202078SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Reinders & WattanaReCALL201575SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Thorne et al.ReCALL201275SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Piirainen-Marsh & TainioMod. Lang. J.200973SSCIEducation & Educational Research; Linguistics
Godwin-JonesLang. Learn. Technol.201471SSCIEducation & Educational Research; Linguistics
Lim & HoltCogn. Sci.201171SSCIPsychology, Experimental
Chen & HsuComput. Educ.202068SCIE; SSCIComputer Science, Interdisciplinary Applications; Education & Educational Research
Acquah & KatzComput. Educ.202067SCIE; SSCIComputer Science, Interdisciplinary Applications; Education & Educational Research
Yang et al.Comput. Educ.202065SCIE; SSCIComputer Science, Interdisciplinary Applications; Education & Educational Research
Chiu et al.Br. J. Educ. Technol.201264SSCIEducation & Educational Research
Tsai & TsaiComput. Educ.201863SCIE; SSCIComputer Science, Interdisciplinary Applications; Education & Educational Research
PurushotmaLang. Learn. Technol.200563SSCIEducation & Educational Research; Linguistics
Chen & YangInteract. Learn. Environ.201354SSCIEducation & Educational Research
Zheng et al.ReCALL201251SSCIEducation & Educational Research; Linguistics; Language & Linguistics
WuJ. Comput. Assist. Learn.201849SSCIEducation & Educational Research
Chen et al.ReCALL201946SSCIEducation & Educational Research; Linguistics; Language & Linguistics
Yang et al.J. Comput. Assist. Learn.201846SSCIEducation & Educational Research
Piirainen-Marsh & TainioScand. J. Educ. Res.200946SSCIEducation & Educational Research
Wu & HuangEduc. Technol. Soc.201741SSCIEducation & Educational Research
Xu et al.ETR&D-Educ. Tech. Res. Dev.202038SSCIEducation & Educational Research
Table 3. Prominent co-authors.
Table 3. Prominent co-authors.
Co-AuthorsAffiliationDocumentsMost Cited DocumentsSum of Cites
Yang, Jie ChiNational Central University64233
Hwang, Gwo-JenNational Taiwan University of Science & Technology53217
Berns, AnkeUniversidad de Cadiz41136
Chen, Hao-Jan HowardNational Taiwan Normal University42150
Zheng, DongPingShanxi Medical University41109
Zou, DiLingnan University43240
Chen, Sherry Y.National Central University Research Center for Science and Technology for Learning3260
Dehaan, Jonathan W.University of Shizuoka Graduate School of International Relations Faculty of International Relations31152
Kao, Chian-WenChihlee University of Technology3197
Reinders, HayoKing Mongkuts University of Technology Thonburi31181
reynolds, barry leeUniversity of Macau3197
Shadiev, RustamZhejiang University31107
Sykes, Julie M.University of Oregon31324
Wattana, SoradaUniversity of Canterbury31181
Table 4. Bradford Zones.
Table 4. Bradford Zones.
ZoneNumber of DocumentsJournals (%)Bradford MultiJournals
Core8636.13%118.94% 11 × (n0)11
Zone I6527.31%2520.33%2.2711 × (n1)31.64
Zone II8736.55%8770.73%3.4811 × (n2)133.2144
Total238 123 2.88 175.8544
Error (%)−42.97%
Table 5. Core of Bradford journals ordered by number of papers.
Table 5. Core of Bradford journals ordered by number of papers.
ZoneJournalAcc.DocumentsCitationsWoS
Category		JIFJCR%OA
CoreComputer Assisted Language Learning5.88%14479Linguistics; Education & Educational Research7.0Q16.38%
Recall5.04%12521Linguistics; Education & Educational Research4.5Q129.85%
Computers & Education3.78%9523Education & Educational Research12.0Q119.36%
Language Learning & Technology3.78%9516Linguistics; Education & Educational Research3.8Q10.00%
Interactive Learning Environments3.36%8114Education & Educational Research5.4Q14.79%
Foreign Language Annals2.94%786Linguistics; Education & Educational Research2.7Q15.88%
British Journal of Educational Technology2.52%689Education & Educational Research6.6Q119.21%
Calico Journal2.52%648Education & Educational Research2.0Q20.00%
Arab World English Journal2.10%525Linguistics1.0Q297.61%
Education and Information Technologies2.10%551Education & Educational Research5.5Q116.30%
Journal of Computer Assisted Learning2.10%5239Education & Educational Research5.0Q123.97%
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Presentación-Muñoz, A.; González-Fernández, A.; Rodal, M.; Acevedo-Borrega, J. The Use of Video Games in Language Learning: A Bibliometric Analysis. Metrics 2025, 2, 12. https://doi.org/10.3390/metrics2030012

AMA Style

Presentación-Muñoz A, González-Fernández A, Rodal M, Acevedo-Borrega J. The Use of Video Games in Language Learning: A Bibliometric Analysis. Metrics. 2025; 2(3):12. https://doi.org/10.3390/metrics2030012

Chicago/Turabian Style

Presentación-Muñoz, Alain, Alberto González-Fernández, Miguel Rodal, and Jesús Acevedo-Borrega. 2025. "The Use of Video Games in Language Learning: A Bibliometric Analysis" Metrics 2, no. 3: 12. https://doi.org/10.3390/metrics2030012

APA Style

Presentación-Muñoz, A., González-Fernández, A., Rodal, M., & Acevedo-Borrega, J. (2025). The Use of Video Games in Language Learning: A Bibliometric Analysis. Metrics, 2(3), 12. https://doi.org/10.3390/metrics2030012

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