Exploring the Impact of Technology on Foreign Language Learning: A Multivariate Meta-Meta-Analysis Study
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| Title: | Exploring the Impact of Technology on Foreign Language Learning: A Multivariate Meta-Meta-Analysis Study |
|---|---|
| Language: | English |
| Authors: | Suping Yi, Wenye Li, Yanyan Zhang, Rustam Shadiev (ORCID |
| Source: | Educational Technology Research and Development. 2025 73(1):35-58. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 24 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Second Language Instruction, Second Language Learning, Meta Analysis, Language Skills, Research Reports, Teaching Methods, Information Technology, Technology Integration, Outcomes of Education, Learning Processes, Instructional Effectiveness |
| DOI: | 10.1007/s11423-024-10412-7 |
| ISSN: | 1042-1629 1556-6501 |
| Abstract: | The purpose of the present study was to analyze the impact of technology on student foreign language learning, as it has been widely used to enhance language instruction over the past few decades. This multivariate meta--meta-analysis study aimed to examine the effects of technology on various aspects of language learning, including listening, speaking, reading, writing and vocabulary, and explore how factors like educational level and technology type influenced these impacts. The researchers conducted a meta-analysis of 10 studies published prior to May 2023, using both qualitative and quantitative methods. They analyzed the descriptive and methodological characteristics of each study, and found a statistically significant overall effect size (g = 0.068, p < 0.001 with a 95% confidence interval of 0.595-0.860) indicating that technology positively impacted language learning outcomes compared to traditional learning methods. The researchers identified educational level and technology type as important factors contributing to the variability in effect size. Specifically, both higher education and K-12 settings, as well as VR tools and computing resources, had positive impacts on students' foreign language learning. Overall, the results suggest that using technology is an effective way to improve foreign language learning for students, and provide valuable recommendations for future research and practical applications in this area. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1462610 |
| Database: | ERIC |
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| FullText | Links: – Type: pdflink Url: https://content.ebscohost.com/cds/retrieve?content=AQICAHj0k_4E0hTGH8RJwT4gCJyBsGNe_WN95AvKlDbXJGqwxwEDDoIEmUe6_b_4SrkxT7AsAAAA4zCB4AYJKoZIhvcNAQcGoIHSMIHPAgEAMIHJBgkqhkiG9w0BBwEwHgYJYIZIAWUDBAEuMBEEDGZqadCzSF11zUjbcAIBEICBmyX6GhxiFt9nqqmUZAkhF4ANDsQDl_oS6F2SbKj_Km7o9DFqA7mO_ch3oQN2QQLVv3xsxRC3BwDCvcAYhgOpVSTd5H_P5nzbqUpzmfs0w4_bKLv3PcmlKqh5Dh1XZomYzFYhDXm3oK3teXGQ1THK38MAgvjv0QyaL9S1fyMg8pwWwGwyeE6SuZoXoV0RCK84Nm_o8MCZ4eCgG3ub Text: Availability: 1 Value: <anid>AN0183751057;etr01feb.25;2025Mar19.03:45;v2.2.500</anid> <title id="AN0183751057-1">Exploring the impact of technology on foreign language learning: a multivariate meta–meta-analysis study: Exploring the impact of technology on foreign language: S. Yi et al </title> <p>The purpose of the present study was to analyze the impact of technology on student foreign language learning, as it has been widely used to enhance language instruction over the past few decades. This multivariate meta–meta-analysis study aimed to examine the effects of technology on various aspects of language learning, including listening, speaking, reading, writing and vocabulary, and explore how factors like educational level and technology type influenced these impacts. The researchers conducted a meta-analysis of 10 studies published prior to May 2023, using both qualitative and quantitative methods. They analyzed the descriptive and methodological characteristics of each study, and found a statistically significant overall effect size (g =.068, p &lt;.001 with a 95% confidence interval of.595–.860) indicating that technology positively impacted language learning outcomes compared to traditional learning methods. The researchers identified educational level and technology type as important factors contributing to the variability in effect size. Specifically, both higher education and K-12 settings, as well as VR tools and computing resources, had positive impacts on students' foreign language learning. Overall, the results suggest that using technology is an effective way to improve foreign language learning for students, and provide valuable recommendations for future research and practical applications in this area.</p> <p>Keywords: Technology; Foreign language learning; Multivariate meta–meta-analysis; Effect size; Education Specialist Studies In Education Language; Communication and Culture Linguistics</p> <p>Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</p> <hd id="AN0183751057-2">Introduction</hd> <p>Over the past few decades, a growing number of studies have focused on the benefits and potential of technology in foreign language learning (Hwang et al., [<reflink idref="bib21" id="ref1">21</reflink>]; Lee, [<reflink idref="bib25" id="ref2">25</reflink>]; Nicolaidou et al., [<reflink idref="bib33" id="ref3">33</reflink>]; Wu et al., [<reflink idref="bib47" id="ref4">47</reflink>]; Yang &amp; Chen, [<reflink idref="bib49" id="ref5">49</reflink>]). This trend not only leads to a proliferation of empirical studies in this domain, e.g., experimental and quasi-experimental studies, but also to a rapid increase in the number of systematic review studies to help researchers and scholars understand how and to what extent various technologies contribute to student foreign language learning. Recent developments of meta-analysis, which is an effective and popular tool for synthesis analysis, has been generally used in the language learning field. Findings based on systematic reviews and meta-analyses provide a clear overview of existent research, lay the groundwork for future research development, and inform educators for decision-making (Cai et al., [<reflink idref="bib4" id="ref6">4</reflink>]; Hwang et al., [<reflink idref="bib20" id="ref7">20</reflink>]; Shadiev et al., [<reflink idref="bib39" id="ref8">39</reflink>]). It should be acknowledged that, however, these systematic reviews and meta-analyses may not offer consistent results because of the difference in research contents and methodologies, and even produce conflicting results. For instance, Grgurović et al. ([<reflink idref="bib14" id="ref9">14</reflink>]) synthesized 37 qualifying studies from 1970 to 2006 and found that the relationship between technology and student language learning was weak, but the effect size was positive and statistically significant. Based on 16 publications between 2000 and 2017, Xu et al. ([<reflink idref="bib48" id="ref10">48</reflink>]) reported a large effect size in relationship between technology and student language writing. In addition, a recent meta-analysis on 36 studies by Lee et al. ([<reflink idref="bib26" id="ref11">26</reflink>]) suggested the relationship between technology and student language learning was a positive, with medium effect size.</p> <p>In recent times, a significant number of studies have focused on meta-analysis. To prevent confusion arising from inconsistent conclusions in meta-analyses among researchers, the use of multivariate meta-meta–analysis has garnered increasing attention from scholars. Multivariate meta–meta-analysis, also referred to as second-order meta-analysis, is a method employed to analyze and integrate findings from various meta-analyses. Second-order meta-analysis is different from first-order meta-analysis. First-order meta-analysis uses statistical analysis tools to synthesize and evaluate the existing empirical research results of the same research topic to summarize the common effects reflected by the results. On the other hand, the second-order meta-analysis refers to the use of statistical analysis tools to re-evaluate the methodological quality and evidence quality of the results of the first-order meta-analysis (Higgins &amp; Green, [<reflink idref="bib17" id="ref12">17</reflink>]). Compared to meta-analysis, second-order meta-analysis can offer more generalized findings, leading to a more reliable assessment for particular factors. It also helps to find and examine the discrepancies and consistencies across multiple meta-analyses (Polanin et al., [<reflink idref="bib35" id="ref13">35</reflink>]). In response to the accelerated need for foreign language learning, there is a pressing need for educators to understand the effect-size variation collection of foreign language learning studies. Such information will enable stakeholders to devote various resources more reasonably to gain the greatest benefit for language learners.</p> <p>Meanwhile, previous meta-analytical studies have not extensively explored the factors influencing the relationship between foreign language learning and technology. This gap highlights a knowledge void within the current literature. Our study aims to address this gap by conducting a second-order meta-analysis to delve deeper into the relationship between foreign language learning and technology, identifying potential factors influencing this relationship.</p> <p>Due to the varying results among different meta-analyses, we first assessed the quality of prior meta-analyses. This study then provided descriptive and methodological characteristics of existing meta-analyses to comprehensively interpret their content and findings. The outcomes of language learning in previous meta-analyses were primarily divided into five categories: listening, speaking, reading, writing, and vocabulary. In this study, a first-order meta-analysis was conducted to investigate the impact of technology on students' acquisition of these skills. Additionally, prior meta-analytical studies have demonstrated that the effects of foreign language learning differ based on educational level and technology type. Therefore, moderator analyses were performed using educational level and technology type to examine how these variables explain the heterogeneity of effect sizes.</p> <p>In the subsequent sections, this study will proceed as follows. We will commence with a comprehensive review of the literature pertaining to foreign language learning and the role of technology. This foundation will allow us to articulate the specific research objectives that guide our investigation. Next, we will detail the methodology employed in this study, outlining the approach, data sources, and analytical techniques used to conduct our multivariate meta–meta-analysis. We will then present the findings of our analysis, providing a clear account of the results obtained and their implications for the field of foreign language learning. Finally, we will engage in a thorough discussion of our multivariate meta–meta-analysis, interpreting the outcomes of our study, considering its limitations, and suggesting directions for future research in this domain.</p> <hd id="AN0183751057-3">Literature review</hd> <p></p> <hd id="AN0183751057-4">Foreign language learning and technology</hd> <p>Foreign language learning refers to the process of acquiring languages in addition to an individual's native language(s). It specifically pertains to the learning and mastery of second or subsequent languages beyond one's mother tongue (Cook, [<reflink idref="bib11" id="ref14">11</reflink>]). Foreign language learning encompasses two learning environments that pertain to individual learning conditions (Chaudron, [<reflink idref="bib6" id="ref15">6</reflink>]). The first environment involves individuals being in a foreign language environment where they must acquire a second language to better acquaint themselves with others and improve their daily life. Alternatively, if an individual learns a second language such as English in Japan or French in the United States, where the surrounding society hardly uses the target language, it can be considered a second language learning environment. In such an environment, foreign language learning is simply another subject for learners to acquire knowledge, similar to geography or mathematics. As a result, this study emphasizes foreign language learning within the second language learning environment.</p> <p>Technology refers to the approach and set of principles used to solve problems. It encompasses the way individuals use existing resources to create new things or alter the functions of current ones. In the context of foreign language learning, technology pertains to how students utilize information technology to acquire the target language (Lee, [<reflink idref="bib25" id="ref16">25</reflink>]). According to Shadiev and Yang ([<reflink idref="bib41" id="ref17">41</reflink>]), the following are some of the most common language learning technologies. (<reflink idref="bib1" id="ref18">1</reflink>) AR/VR technology. AR can combine digital information with the real world and give students a sense of reality to learn a language through convenient technology. VR allows for higher-dimensional interaction and content display, and the use of VR can make real objects and scenes appear, allowing students to immerse themselves in language learning. (<reflink idref="bib2" id="ref19">2</reflink>) Speech recognition technology (SRT). It converts lexical content in human language into computer-readable content. The automatic feedback function in SRT technology is exceptionally beneficial for speaking practice and development, enabling students to develop more independent pronunciation. (<reflink idref="bib3" id="ref20">3</reflink>) Digital game. The researchers created a game-based learning system and embedded language learning knowledge into the game, allowing students to learn language skills while playing it. (<reflink idref="bib4" id="ref21">4</reflink>) Online video. Online video is video content delivered or made available via the Internet. Students can learn the target language by watching video resources on the Internet that are related to the target language. There have been a number of longitudinal studies involving technology-assisted foreign language learning that have been reported in past several decades. Up to now, computing technology is generally used to support foreign language learning (Hassani et al., [<reflink idref="bib16" id="ref22">16</reflink>]; Hwang et al., [<reflink idref="bib19" id="ref23">19</reflink>]; Kerimbayev et al., [<reflink idref="bib22" id="ref24">22</reflink>]; Wu et al., [<reflink idref="bib47" id="ref25">47</reflink>]). Shadiev and Sun ([<reflink idref="bib40" id="ref26">40</reflink>]) applied a combination of speech-to-text recognition (STR) and computer-aided translation (CAT) technologies to facilitate student comprehension of the foreign language learning content. de Vries et al. ([<reflink idref="bib12" id="ref27">12</reflink>]) discussed the performances and effects of the CALL system as an intervene tool for language learning. Nicolaidou et al. ([<reflink idref="bib33" id="ref28">33</reflink>]) designed quasi-experimental study to investigate the effect of virtual reality technology on foreign language learning and compared engagement, engrossment, and immersion between virtual reality and mobile learning.</p> <p>It can be seen that there is a general consensus on the effectiveness of various technologies in supporting foreign language learning. The incorporation of technology into foreign language learning offers immersive, interactive, and personalized learning experiences, allowing language learners to enhance their proficiency effectively. By leveraging technological advancements, language learners can engage with language learning in dynamic and engaging ways, ultimately improving their language skills and proficiency levels.</p> <hd id="AN0183751057-5">Meta-analysis on technology and foreign language learning</hd> <p>Several studies have investigated the relationship between technology and foreign language learning using meta-analysis. One such study conducted by Lin and Lin ([<reflink idref="bib30" id="ref29">30</reflink>]) analyzed student vocabulary retention in relation to mobile technology. Wang et al. ([<reflink idref="bib44" id="ref30">44</reflink>]) examined language learning and focused on 3D virtual world's usage in their meta-analysis. Tsai and Tsai ([<reflink idref="bib43" id="ref31">43</reflink>]) explored the effectiveness of applying digital games for L2 vocabulary learning. More recently, several researchers have used meta-analysis to focus on different technologies of language learning (Chen et al. [<reflink idref="bib7" id="ref32">7</reflink>]; Hao et al., [<reflink idref="bib15" id="ref33">15</reflink>]). The past decade has seen the rapid development and application of meta-analysis of technology applications to foreign language learning.</p> <p>Simultaneously, researchers have also demonstrated a growing interest in second-order meta-analysis related to education. Young ([<reflink idref="bib50" id="ref34">50</reflink>]), for instance, evaluated the accumulated impact of technology on student achievement over the past 30 years and discovered that effect size variation was primarily influenced by technology function and study quality. Wu and Shen ([<reflink idref="bib46" id="ref35">46</reflink>]) discussed the association between principal leadership and student achievement through multivariate random-effects meta–meta-analysis and obtained a statistically significant positive relationship with student achievement. Martin et al. ([<reflink idref="bib31" id="ref36">31</reflink>]) examined the impact of distance learning and the online learning on students' cognitive, affective and behavioral outcomes and revealed a statistically significant effect size between them. Therefore, application of second-order meta-analysis has received scant attention in the field of technology-enhanced language learning. In contrast, there are an increasing number of first-order meta-analysis studies focusing on the impact of technology on language learning. However, because of insufficient literature retrieval and varying quality of included literatures, the results obtained are not always consistent, making it difficult to provide reliable evidence to researchers and scholars. At the same time, in this study, second-order meta-analysis was selected as the method for analyzing first-order meta-analysis which calculates the reliability of meta-analytic differences in mean effect size, and thus, accurately estimates the true mean effect size in each first-order meta-analysis. From this perspective, the second-order meta-analysis examines the results of the first-order meta-analysis from two levels of methodological quality assessment and evidence quality assessment, allowing for the synthesis of qualitative and quantitative research and increasing the reliability of research results. Therefore, there is a need for more second-order meta-analyses to critically evaluate first-order studies about foreign language learning and examine the effectiveness of technology. The second-order meta-analysis provides several advantages when compared to the first-order meta-analysis. Firstly, it allows for the integration of results from multiple first-order meta-analysis studies, which enables the formation of more reliable conclusions based on larger sample sizes. Secondly, it utilizes the heterogeneity of first-order meta-analysis studies to analyze the effects of various moderating variables, such as publication years, study quality, and educational level. This provides a more in-depth understanding of the impact of these variables on the results. Finally, by comparing the differences between first-order meta-analysis studies, the second-order meta-analysis can assess the reliability and validity of the initial studies.</p> <p>Overall, meta-analyses on technology and foreign language learning have garnered considerable attention from researchers. By amalgamating and analyzing the results of numerous independent studies, researchers can derive more comprehensive and dependable conclusions to propel the advancement of the field. However, investigations have unearthed inherent drawbacks in first-order meta-analyses. For instance, current first-order meta-analyses predominantly focused on summarizing and amalgamating the effects of various technological applications on the efficacy of foreign language learning, yet they lack an in-depth understanding of specific influencing factors. Although some studies have delved into the overall impact of technological applications on foreign language learning, they have failed to thoroughly investigate which factors precisely influence this relationship. Specifically, while some studies had explored the effects of different technological applications on language learning, there is a dearth of in-depth research on the disparities in the effectiveness of these technologies. For instance, regarding various speech recognition technologies, virtual reality technologies, etc., there may be differences in their efficacy on foreign language learning, but current research has not extensively delved into these discrepancies.</p> <hd id="AN0183751057-6">The variables that influence language learning in multivariate meta–meta-analysis study</hd> <p>Scholars considered various research variables in their meta-analysis of studies on technology-assisted language learning, including language types, learning outcomes, technology, educational level, pedagogical approaches, instructional strategies, intervention duration, etc. (Cai et al., [<reflink idref="bib4" id="ref37">4</reflink>]; Chang &amp; Hung, [<reflink idref="bib5" id="ref38">5</reflink>]). Additionally, researchers in the second-order meta-analysis took into account variables such as technology, publication years, student grade levels, study quality, study type, subject, and outcome (Martin et al., [<reflink idref="bib31" id="ref39">31</reflink>]; Tamim et al., [<reflink idref="bib42" id="ref40">42</reflink>]; Wu &amp; Shen, [<reflink idref="bib46" id="ref41">46</reflink>]; Young, [<reflink idref="bib50" id="ref42">50</reflink>]). In this study, we initially identified several variables in our first-order meta-analysis that could potentially influence student foreign language learning outcomes. However, after a thorough review, we found that most of these variables lacked sufficient data to accurately calculate their effect sizes. This limitation necessitated the exclusion of these variables as moderators in the final analysis. Consequently, we focused on two key variables that consistently provided adequate data and demonstrated significant potential as moderators: educational level and technology type.</p> <p> <emph>The educational level</emph> in this context refers to the grade spans of students. This variable acknowledges that the developmental stages of students can significantly impact the effectiveness of instructional methods. For example, research by Alexander and Murphy ([<reflink idref="bib1" id="ref43">1</reflink>]) highlights how cognitive development and learning strategies evolve across different grade levels, suggesting that younger students may benefit more from highly structured learning environments, whereas older students might thrive in settings that promote autonomy and critical thinking. From this perspective, understanding the nuances of how different grade spans respond to instructional interventions is crucial for tailoring effective foreign language teaching strategies.</p> <p> <emph>The technology type</emph> refers to the specific technological tools used to assist students in foreign language learning. This includes a variety of technologies, such as mobile applications, computer-assisted learning software, virtual reality environments, and interactive whiteboards. Different technologies offer unique affordances that can influence learning outcomes in diverse ways. For instance, Lin and Warschauer ([<reflink idref="bib28" id="ref44">28</reflink>]) found that mobile applications designed for language learning can significantly improve vocabulary acquisition and pronunciation through repetitive practice and immediate feedback. Similarly, Cheng and Tsai ([<reflink idref="bib9" id="ref45">9</reflink>]) demonstrated that virtual reality can create immersive environments that enhance language learners' engagement and motivation, leading to better retention and understanding of complex linguistic structures.</p> <p>By focusing on these two well-defined variables (i.e. educational level and technology type), we aim to provide a more nuanced analysis of their moderating effects on the educational outcomes of foreign language learning. This approach allows us to draw more robust conclusions and offer practical recommendations. Furthermore, this study aims to fill the gap in the existing literature by providing clarity and evidence-based analysis of how educational levels and technology types specifically impact foreign language acquisition. This comprehensive approach ensures that our recommendations are grounded in rigorous scientific research, providing valuable insights for educators and policymakers seeking to enhance foreign language learning outcomes across diverse educational contexts.</p> <p>Taking into account the limitations of first-order meta-analysis and the potential variables, this study employs second-order meta-analysis to discuss the relationship between foreign language learning and technology, thereby gaining a more comprehensive understanding of the role of different factors in the process of language learning. Thus, the research questions of this second-order meta-analysis are as follows:</p> <p>(<reflink idref="bib1" id="ref46">1</reflink>) What are the descriptive and methodological characteristics of previously published meta-analyses that explore the connections between technology and student foreign language learning, specifically those published prior to May 2023?</p> <p>(<reflink idref="bib2" id="ref47">2</reflink>) What are the quantitative findings of the outcomes related to listening, speaking, reading, writing, and vocabulary reported in previously published meta-analyses?</p> <p>(<reflink idref="bib3" id="ref48">3</reflink>) What are the results of the moderator analyses on educational level and technology type for the outcomes reported in previously published meta-analyses?</p> <p>(<reflink idref="bib4" id="ref49">4</reflink>) What is the publication bias in the multivariate meta-meta-analysis?</p> <hd id="AN0183751057-7">Methods</hd> <p>This study utilized mixed methods of data analysis. In this second-order meta-analysis, the study followed the general steps of first-order meta-analysis. During the data analysis process, in addition to using quantitative analysis methods to calculate effect sizes, this study used qualitative analysis methods to code the data and conduct descriptive and methodological characteristics analysis.</p> <hd id="AN0183751057-8">Inclusion criteria</hd> <p>The purpose of this multivariate meta-meta-analysis was to synthesize findings of prior meta-analyses that examine the associations between technology and student foreign language learning. A first-order meta-analysis is eligible for this study must: (a) examine the relationship between technology and student foreign language learning, (b) be published in English and before May, 2023, (c) undergo rigorous peer review, and (d) report sufficient data to calculate the effect size and standard errors.</p> <hd id="AN0183751057-9">Databases and search strategies</hd> <p>To obtain the relevant first-order meta-analysis studies, the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines were followed (Moher et al., [<reflink idref="bib32" id="ref50">32</reflink>]). Two search strategies were used to search the target studies comprehensively. Firstly, we used the keyword search method to conduct electronic retrieval to identify eligible studies in five electronic databases (i.e.<emph>, Web of Science, ERIC, PsycINFO, Scopus, and ProQuest</emph>), the research terms included (<emph>"foreign language learning" OR "second language learning" OR "language learning" AND "technology" OR "mobile technology" OR "computer technology" AND "meta-analysis" OR "meta-analytic"</emph>). Second, the snowballing method was used to manually search the reference list of eligible studies to find the potential studies.</p> <hd id="AN0183751057-10">Data extraction</hd> <p>The selection flow diagram is shown in Fig. 1. We yielded 189 meta-analyses in the first round of database search. Among them, 101 were from Web of Science, 25 from ERIC, 37 from PsycINFO, 22 from Scopus, and 4 from ProQuest. 39 meta-analyses were selected after deleting 150 duplicate records based on the title and abstract. Next, the full text of 39 meta-analyses was screened and 23 studies were retained. That is, 16 studies were excluded because they did not examine the relationship between technology and language learning. Then, we reviewed the reference lists of these studies and identified 3 relevant articles that were not found in database searches. Furthermore, we searched and screened the full text of 23 studies, 8 of 23 studies were excluded because they (a) reported the duplicate records (n = 5), (b) a conference paper that did not undergo peer review (n = 1) and (c) did not report sufficient information (n = 7). Finally, 10 meta-analyses met the inclusion criteria and had sufficient information to calculate relevant data (see Table 1).</p> <p>Graph: Fig. 1 The studies selection flow diagram</p> <p>Table 1 Descriptive characteristics of included meta-analyses</p> <p> <ephtml> &lt;table frame="hsides" rules="groups"&gt;&lt;thead&gt;&lt;tr&gt;&lt;th align="left"&gt;&lt;p&gt;Authors&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Type journal&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Inclusion/exclusion&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Technology&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Studies&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Time frame&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Literature covered&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Educational level&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Search method&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Review process&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Database&lt;/p&gt;&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Burston and Giannakou (&lt;xref ref-type="bibr" rid="bibr3"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;84&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;1994&amp;#8211;2019&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;p&gt;Unpublished&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;p&gt;Backward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;5&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Cai et al. (&lt;xref ref-type="bibr" rid="bibr4"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;VR equipment&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;14&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2008&amp;#8211;2020&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;8&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Chang and Hung (&lt;xref ref-type="bibr" rid="bibr5"&gt;2019&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;84&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;1990&amp;#8211;2015&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;p&gt;Backward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;5&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Chen et al. (&lt;xref ref-type="bibr" rid="bibr7"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;VR equipment&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;21&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2010&amp;#8211;2021&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;4&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Cho et al. (&lt;xref ref-type="bibr" rid="bibr10"&gt;2018&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;20&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2008&amp;#8211;2017&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;p&gt;Unpublished&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;4&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;5&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Dixon et al. (&lt;xref ref-type="bibr" rid="bibr13"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;28&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2010&amp;#8211;2018&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;p&gt;Unpublished&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;&amp;#8211;&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;p&gt;Backward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;13&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Lee and Lee (&lt;xref ref-type="bibr" rid="bibr24"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2008&amp;#8211;2019&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;p&gt;Unpublished&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;p&gt;Backward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Lin (&lt;xref ref-type="bibr" rid="bibr29"&gt;2015&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;59&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2000&amp;#8211;2012&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;p&gt;Unpublished&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;p&gt;Backward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;6&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;5&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Peng et al. (&lt;xref ref-type="bibr" rid="bibr34"&gt;2021&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Yes&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;17&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2008&amp;#8211;2017&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;p&gt;Backward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;5&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Wang et al. (&lt;xref ref-type="bibr" rid="bibr44"&gt;2020&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;J&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;No&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;VR equipment&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;13&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;2008&amp;#8211;2019&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Published&lt;/p&gt;&lt;p&gt;Unpublished&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Higher education&lt;/p&gt;&lt;p&gt;K12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Forward&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <hd id="AN0183751057-11">Data coding</hd> <p>Ten meta-analyses were coded in three sections. The first section coded the descriptive characteristic information of the publication, including author names, title, year of publication, study type, journal, inclusion/exclusion, technology, number of studies, time frame, literature covered, educational level, research method, and review process. The second section included the methodological characteristic information of the included meta-analyses: independence of data, sample size, homogeneity analysis, moderate analysis, publication bias, ES type and outcome (listening, speaking, reading, writing, and vocabulary). The third section coded the results of each meta-analysis. The data information, including the effect size, standard error, 95% CI, etc., was extracted from each meta-analysis. Two researchers were involved in the coding process independently. They read all studies, coded content, and then grouped codes into categories. If there were disagreements in the coding process, two researchers discussed them until reaching an agreement.</p> <p>There were several variables existed in first-order meta-analysis, however, most of them did not provide sufficient data to calculate the effect size. Finally, there were two variables selected as moderators. (<reflink idref="bib1" id="ref51">1</reflink>) Educational level. Because the previous first-order meta-analyses focused on a more dispersed grade spans (i.e., 1–6, 7–9, 10–12), to reconcile the disagreement and make results more precise, according to Tamim et al. ([<reflink idref="bib42" id="ref52">42</reflink>]) and Young ([<reflink idref="bib50" id="ref53">50</reflink>]), the educational level in this study was coded as higher education and K-12. (<reflink idref="bib2" id="ref54">2</reflink>) Technology type. According to Cai et al. ([<reflink idref="bib4" id="ref55">4</reflink>]), the technology used to assist student foreign language learning was classified as computing resource and VR equipment.</p> <hd id="AN0183751057-12">Methodological quality</hd> <p>The adapted version of the revised assessment of multiple systematic reviews (R-AMSTAR) was applied to assess the quality of meta-analyses. The instrument had been used in Young ([<reflink idref="bib50" id="ref56">50</reflink>])'s study to assess the included meta-analyses' quality of technology-enhanced mathematics instruction. Moreover, the validity and reliability of the R-AMSTAR instrument was also tested (Kung et al., [<reflink idref="bib23" id="ref57">23</reflink>]) and scholars reported that R-AMSTAR is an effective and reliable assessment instrument for rating the quality of meta-analyses.</p> <p>R-AMSTAR consists of 10 items scored on 3 to 5 criteria, the rating score is from 0 to 4 based on the relevant criterion. The total score on the instrument is 44 points. To avoid discrepancies in R-AMSTAR ratings, two researchers independently scored 10 meta-analysis studies. If there was any inconsistency, researchers discussed them until a consensus was reached. After that, the quality of the meta-analyses was classified according to the R-AMSTAR rating criterion: low = 12–22, medium = 23–33, and high = 34–44.</p> <hd id="AN0183751057-13">Data analysis</hd> <p>Three types of effect sizes including Cohen's d (Cai et al., [<reflink idref="bib4" id="ref58">4</reflink>]), Hedges's g (Chen et al., [<reflink idref="bib7" id="ref59">7</reflink>]) and Cochran's Q (Chen et al., [<reflink idref="bib7" id="ref60">7</reflink>]) were extracted through 10. Comprehensive meta-analysis was used to perform the data analysis. We used the relevant formula to make bias correction by converting different effect sizes into the same Hedges'g (Borenstein et al., [<reflink idref="bib2" id="ref61">2</reflink>]). Additionally, standard errors or confidence intervals, sample sizes, and data of moderators were also extracted from each meta-analysis study and inputted into CMA. A random-effects model was employed in this study to calculate the data including publication bias, effect size synthesis, and moderator data through the CMA.</p> <hd id="AN0183751057-14">Results</hd> <p></p> <hd id="AN0183751057-15">Descriptive and methodological characteristics of previous meta-analyses on technology and fo...</hd> <p>This multivariate meta-meta-analysis collected the 40 effect sizes from 10 meta-analyses studies that were conducted between 2015 and 2023 to examine the impact of technology on student foreign language learning. Table 1 shows the descriptive characteristics of the 10 included studies. (<reflink idref="bib1" id="ref62">1</reflink>) All meta-analyses studies were published in journals. (<reflink idref="bib2" id="ref63">2</reflink>) All meta-analyses studies described the criterion for inclusion and exclusion. (<reflink idref="bib3" id="ref64">3</reflink>) The technologies in meta-analyses studies were divided into two categories: VR equipment, computing resource. Among them, computing resource was used widely by researchers (e.g., Burston &amp; Giannakou, [<reflink idref="bib3" id="ref65">3</reflink>]; Chang &amp; Hung, [<reflink idref="bib5" id="ref66">5</reflink>]), which including iPad, smartphone, laptop, and etc. There were studies that used VR tools (e.g. Cai et al., [<reflink idref="bib4" id="ref67">4</reflink>]; Chen et al., [<reflink idref="bib7" id="ref68">7</reflink>]). (<reflink idref="bib4" id="ref69">4</reflink>) Around the number of studies and time frame, 2 of 10 included more than 80 empirical studies (Burston &amp; Giannakou, [<reflink idref="bib3" id="ref70">3</reflink>]; Chang &amp; Hung, [<reflink idref="bib5" id="ref71">5</reflink>]), and 4 of 10 collected less than 15 empirical studies in their meta-analyses (Cai et al., [<reflink idref="bib4" id="ref72">4</reflink>]; Lee &amp; Lee, [<reflink idref="bib24" id="ref73">24</reflink>]; Wang et al., [<reflink idref="bib44" id="ref74">44</reflink>]). The included meta-analyses covered the empirical studies published between 1990 and 2021. Chen's et al. ([<reflink idref="bib7" id="ref75">7</reflink>]) meta-analysis had the longest time frame with 31 years from 1990 to 2021. (<reflink idref="bib5" id="ref76">5</reflink>) 5 of 10 covered the published empirical studies and 6 of 10 covered both published and unpublished empirical studies. (<reflink idref="bib6" id="ref77">6</reflink>) Dixon et al. ([<reflink idref="bib13" id="ref78">13</reflink>]) did not report their instructing settings, two meta-analyses focused on K12 student foreign language learning (Chang &amp; Hung, [<reflink idref="bib5" id="ref79">5</reflink>]; Cho et al., [<reflink idref="bib10" id="ref80">10</reflink>]) and the rest of meta-analyses' participants belonged to both K12 and higher education level. (<reflink idref="bib7" id="ref81">7</reflink>) In the search method, forward search method was employed in 4 meta-analyses, 6 meta-analyses conducted both forward and backward search methods to yield empirical studies. (<reflink idref="bib8" id="ref82">8</reflink>) All meta-analyses reviewed at least 2 round to yield empirical studies. Cho et al. ([<reflink idref="bib10" id="ref83">10</reflink>]) and Lin ([<reflink idref="bib29" id="ref84">29</reflink>]) did more than 4 rounds of searching the eligible studies. (<reflink idref="bib9" id="ref85">9</reflink>) Regarding the database, 7 meta-analyses searched the relevant literature from more than 5 databases, demonstrating that most meta-analyses sought many studies as pertinent as possible to improve the quality of their research.</p> <p>Methodological characteristics of 10 studies are included in Table 2. (<reflink idref="bib1" id="ref86">1</reflink>) All meta-analyses' data was independent. (<reflink idref="bib2" id="ref87">2</reflink>) Effect size was weighted by sample size in each meta-analysis to examine whether technology had a positive and significant effect on student foreign language learning compared to a control condition. (<reflink idref="bib3" id="ref88">3</reflink>) Both homogeneity test and publication bias were concerned by each meta-analysis, and the researchers discussed reasons for such condition. (<reflink idref="bib4" id="ref89">4</reflink>) Moderate analysis was performed by all studies to identify whether the effect of the technology intervention varied according to the variables (i.e., age, intervention duration, educational level, and etc.) of the study. (<reflink idref="bib5" id="ref90">5</reflink>) There were two types of effect sizes including Cohen's d, and Hedges' g.</p> <p>Table 2 Methodological characteristics of overviews</p> <p> <ephtml> &lt;table frame="hsides" rules="groups"&gt;&lt;thead&gt;&lt;tr&gt;&lt;th align="left"&gt;&lt;p&gt;Authors (DoP)&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Independence of data&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Sample size&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Homogeneity analysis&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Moderate analysis&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Publication bias&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;ES type&lt;/p&gt;&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Burston and Giannakou (&lt;xref ref-type="bibr" rid="bibr3"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Hedges' g&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Cai et al. (&lt;xref ref-type="bibr" rid="bibr4"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Chang and Hung (&lt;xref ref-type="bibr" rid="bibr5"&gt;2019&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Chen et al. (&lt;xref ref-type="bibr" rid="bibr7"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Hedges' g&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Cho et al. (&lt;xref ref-type="bibr" rid="bibr10"&gt;2018&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Dixon et al. (&lt;xref ref-type="bibr" rid="bibr13"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Lee and Lee (&lt;xref ref-type="bibr" rid="bibr24"&gt;2022&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Lin (&lt;xref ref-type="bibr" rid="bibr29"&gt;2015&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Hedges' g&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Peng et al. (&lt;xref ref-type="bibr" rid="bibr34"&gt;2021&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Independent&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Not Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Wang et al. (&lt;xref ref-type="bibr" rid="bibr44"&gt;2020&lt;/xref&gt;)&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Unknown&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Weight&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Conducted&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Exist&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;Cohen's d&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <hd id="AN0183751057-16">Quantitative findings of the outcomes related to listening, speaking, reading, writing, and v...</hd> <p>The forest plot of 10 meta-analyses with 352 empirical studies on technology and foreign language learning is plotted in Fig. 2. Based on the previous first-order meta-analyses and the purpose of this study, the random-effects model was adopted to calculate the relevant data. The results of the model revealed a significant overall average effect size (g =.727, p &lt;.001) with a standard error of.068 and a 95% confidence interval of.595–.860. This finding suggested that technology has a significant positive effect on student foreign language learning compared with traditional language learning. Statistically significant heterogeneity was observed in the present study, Q-value = 48.190, p &lt;.001, I<sups>2</sups> = 74.578. According to Higgins et al. ([<reflink idref="bib18" id="ref91">18</reflink>]), the high I<sups>2</sups> value in the current study suggests that moderator analysis is indispensably explore what factors may affect these variances.</p> <p>Graph: Fig. 2 Forest plot of foreign language learning meta-analysis studies: random effects model</p> <p>In this study, we conducted a sub-group analysis focused on learning outcomes. Language learning inherently emphases the diverse abilities and skills that students develop throughout the learning process, collectively forming the essential components of language acquisition. Therefore, in this study, learning outcomes are defined as these integral components of language learning. Figure 3 presents the forest plot of the five subgroups of meta-analyses comparing impact of technology-assisted learning with that in traditional learning on listening (k = 5), speaking (k = 6), reading (k = 8), writing (k = 7), and vocabulary (k = 11). Based on the previous first-order meta-analyses and the purpose of this study, the random-effects model was adopted to calculate the relevant data. Technology supported student language learning had a statistically significant impact on listening (g =.676, p &lt;.001), speaking (g =.316, p &lt;.001), reading (g =.577, p &lt;.05), writing (g =.595, p &lt;.001), and vocabulary (g =.810, p &lt;.001) compared with traditional learning.</p> <p>Graph: Fig. 3 Forest plot grouped by listening, speaking, reading, writing, and vocabulary: Random effects model. L Listening, R reading, S speaking, R reading, W writing, and V vocabulary.</p> <hd id="AN0183751057-17">Results of quantitative analyses of instructional setting and technology type on learning out...</hd> <p>Based on the results of the heterogeneity analysis, an exploration of the variability was performed through the moderator analysis by a mixed effects model. A random-effects model was used to calculate the effect sizes within subgroups and a fixed effects model was used to calculate the between-group Q value following the guidelines of Borenstein et al. ([<reflink idref="bib2" id="ref92">2</reflink>]). Moderator analyses were conducted to examine if the effect sizes varied with educational level and technology. The coded data was screened in Excel to ensure that there was enough potential information for each moderator to observe the variability. Table 3 presents the results of the moderator analyses.</p> <p>Table 3 Results of analysis of moderator variables</p> <p> <ephtml> &lt;table frame="hsides" rules="groups"&gt;&lt;thead&gt;&lt;tr&gt;&lt;th align="left"&gt;&lt;p&gt;Level&lt;/p&gt;&lt;/th&gt;&lt;th align="left" colspan="6"&gt;&lt;p&gt;Effect size and 95% confidence interval&lt;/p&gt;&lt;/th&gt;&lt;th align="left" colspan="3"&gt;&lt;p&gt;Heterogeneity&lt;/p&gt;&lt;/th&gt;&lt;/tr&gt;&lt;tr&gt;&lt;th align="left" /&gt;&lt;th align="left"&gt;&lt;p&gt;k&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;g&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;SE&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;95%CI&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Z&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;p&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;Q-value&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;df&lt;/p&gt;&lt;/th&gt;&lt;th align="left"&gt;&lt;p&gt;p&lt;/p&gt;&lt;/th&gt;&lt;/tr&gt;&lt;/thead&gt;&lt;tbody&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Overall&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;16&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.665&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.033&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.601,.729]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;11.475&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;48.190&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;11&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Listening&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;5&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.676&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.080&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.661,1.233]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;4.545&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="5"&gt;&lt;p&gt;1.803&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="5"&gt;&lt;p&gt;4&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="5"&gt;&lt;p&gt;.772&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Speaking&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;6&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.316&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.123&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.075,.557]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;4.560&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Reading&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;8&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.577&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.577&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.425,.729]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;2.732&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.010&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Writing&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;7&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.595&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.595&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.460,.731]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;6.754&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Vocabulary&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;11&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.810&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.810&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.705,.916]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;4.174&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Educational level&lt;/p&gt;&lt;/td&gt;&lt;td align="left" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td align="left" rowspan="3"&gt;&lt;p&gt;.871&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="3"&gt;&lt;p&gt;1&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="3"&gt;&lt;p&gt;.351&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Higher Education&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;3&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.461&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.204&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.062,.861]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;2.265&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.024&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;K-12&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;13&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.658&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.056&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;[.549,.768]&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;11.783&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Technology&lt;/p&gt;&lt;/td&gt;&lt;td align="left" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td char="." align="char" /&gt;&lt;td align="left" rowspan="3"&gt;&lt;p&gt;.452&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="3"&gt;&lt;p&gt;1&lt;/p&gt;&lt;/td&gt;&lt;td align="left" rowspan="3"&gt;&lt;p&gt;.502&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;Computing resource&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;9&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.898&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.102&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;.698,1.098&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;8.796&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;tr&gt;&lt;td align="left"&gt;&lt;p&gt;VR equipment&lt;/p&gt;&lt;/td&gt;&lt;td align="left"&gt;&lt;p&gt;4&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.781&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.140&lt;/p&gt;&lt;/td&gt;&lt;td char="," align="char"&gt;&lt;p&gt;.506,1.056&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;5.566&lt;/p&gt;&lt;/td&gt;&lt;td char="." align="char"&gt;&lt;p&gt;.000&lt;/p&gt;&lt;/td&gt;&lt;/tr&gt;&lt;/tbody&gt;&lt;/table&gt; </ephtml> </p> <p>The examination of educational level (K12, higher education) indicated that it was not a statistically significant moderator of effect size (Q-value = 1.803, df = 4, p =.772). Although the effect size between different educational level was not statistically significant, statistically significant effects of technology on student foreign language learning existed in both higher education (k = 3, g =.461, p &lt;.001) and K-12 (k = 13, g =.658, p &lt;.001) educational levels. Estimate effect sizes of the K-12 level setting were significantly greater than those estimated in the higher education.</p> <p>The analysis revealed that both computing resources and VR tools were not statistically significant moderators of effect size (Q-value =.452, df = 1, p =.502). Although the effect size between computing resource and VR tools was not statistically significant, there was a statistically significant effect size of computing resource (k = 9, g =.898, p &lt;.001) and VR tools (k = 4, g =.781, p &lt;.001). Estimate effect sizes of computing resource and VR tools both had significant effect sizes on the student foreign language learning.</p> <hd id="AN0183751057-18">The publication bias in the multivariate meta–meta-analysis</hd> <p>To make the results of publication bias more persuasive, two methods were used to explore the publication bias. The first method was making a judgment based on funnel plot. The funnel plot is presented in Fig. 4. Borenstein et al. ([<reflink idref="bib2" id="ref93">2</reflink>]) stated that publication bias is absent if the symmetrical distribution of effect sizes around the mean. According to the funnel plot in the current study, there was no publication bias. However, fewer included studies may result in reporting the result of publication bias inaccurately. This study adopted the second method, the result of Classic fail-safe N, to assist in interpreting the result of the funnel plot (Rosenthal, [<reflink idref="bib36" id="ref94">36</reflink>]). It is suggested that this study needed 1156 studies with an effect size of zero to reach a non-significant overall effect size. Therefore, both two methods offered evidence that publication bias did not exist in this study.</p> <p>Graph: Fig.4 Funnel plot for the random effect model</p> <hd id="AN0183751057-19">Discussion</hd> <p>The purpose of this multivariate meta-meta-analysis was to investigate the effect of technology on student foreign language learning from related studies published between 1990 and 2023. There were only a few empirical studies before 2000. However, there were more than 100 studies published from 2000 to 2023. We also found at least 10 meta-analyses published since 2010. This is encouraging to witness the increase of empirical studies regarding the topic of technology's effect on student foreign language learning in recent decades. This significant change reflects the growing attention that researchers, scholars, policymakers and others have paid to the contribution of technology to student foreign language learning. The increase in the meta-analysis seems to indicate a new tendency to estimate technology's impacts on foreign language learning. Our results of multivariate meta-meta-analysis are discussed below.</p> <p>Firstly, in this second order meta-analysis, the results revealed a statistically significant overall effect size through a random-effects model. This indicated that technology generated greater learning outcomes than traditional learning. Specifically, technology had a more significant effect on writing than on listening. Similarly, effect sizes on listening were significantly higher than effect sizes on speaking, effect sizes on speaking were significantly higher than effect sizes on vocabulary, and effect sizes on vocabulary were significantly larger than effect sizes on reading. These findings suggested that technology appeared to have a more robust effect on student foreign language learning outcomes. It is evident that instructional methods which integrate technology have a more significant positive impact on students' abilities in listening, speaking, reading, and writing compared to those that do not. This integration not only enhances their language skills but also motivates them to engage more actively in the learning process. This finding is similar to some of those reported in the previous first-order meta-analysis studies (Chang &amp; Hung, [<reflink idref="bib5" id="ref95">5</reflink>]; Chen et al., [<reflink idref="bib7" id="ref96">7</reflink>]). The main reason for this phenomenon may be that, in traditional classroom environments, students often rely heavily on face-to-face interactions with instructors and peers, as well as printed materials such as textbooks and handouts. This mode of instruction may promote more structured and linear approaches to language learning, with a focus on grammar rules, vocabulary lists, and traditional language exercises. In contrast, learners in online or blended learning settings have access to a wide range of digital resources and tools, including interactive multimedia materials, virtual classrooms, and online language learning platforms. These technologies afford learners greater autonomy and flexibility in their learning process, allowing them to engage in self-directed learning activities, collaborate with peers in virtual environments, and receive immediate feedback on their language skills.</p> <p>Secondly, in examining the moderators that impact the relationship between technology and student foreign language learning, variables, including educational level and technology, were involved in the exploration on how they affected the outcomes.</p> <hd id="AN0183751057-20">Educational level</hd> <p>We investigated whether the educational level moderates the effect of technology on students' foreign language learning. The meta-analysis revealed that K-12 settings exhibited significantly larger effect sizes than those in higher education, suggesting that educational level may impact outcomes in technology-assisted language learning. However, caution is warranted in interpreting these results, as few studies specifically focused on higher education. Most meta-analyses have typically combined data from K-12 and higher education students when discussing the findings. Overall, technology is widely used in K-12 and higher education teaching contexts. For instance, Shadiev et al. ([<reflink idref="bib38" id="ref97">38</reflink>]) explored junior high school students' foreign language learning experiences using the learning system and their perceptions of the system, and scholars assessed their performances on the different tasks. A contextual game-based learning approach was proposed and presented to an EFL grammar course for first-year college students in Lin et al. ([<reflink idref="bib27" id="ref98">27</reflink>])'s study. There are numerous causes for this situation. First, K-12 students' cognitive levels differ from those of higher education students, resulting in different content that students learn. On this basis, researchers reach conclusions and implement various teaching strategies for various groups. Second, the benefits of technology encourage researchers and educators to use multiple technologies in language learning to improve classroom teaching and student learning efficiency.</p> <hd id="AN0183751057-21">Technology</hd> <p>Technology was not a statistically significant moderator in the effects on student foreign language learning. Two types of specific technology had significant effect sizes on the student foreign language learning. It suggests that technology supports student listening, speaking, reading, writing, and vocabulary in foreign language learning regardless of the didactical functionality of the technology. This is consistent with findings from previous first-order meta-analysis studies (Lin, [<reflink idref="bib29" id="ref99">29</reflink>]; Wang &amp; Sun [<reflink idref="bib45" id="ref100">45</reflink>]). The classification of technology is determined by its inherent functions, and educators design foreign language learning courses based on the functions of various technologies. At the same time, we recognize that technology offers distinct language teaching and learning advantages. For example, in the listening and speaking courses, the use of virtual reality immersion allows students to immerse themselves in the language learning environment, communicate with other learners in real-time, and provide students with a language learning context that cannot be achieved in traditional classrooms (Chen &amp; Hwang, [<reflink idref="bib8" id="ref101">8</reflink>]). Simultaneously, speech translation technology can reduce students' anxiety about learning a foreign language and improve the quality of spoken language output (Shadiev &amp; Huang, [<reflink idref="bib37" id="ref102">37</reflink>]). Introverted students can also actively participate in interactive teaching, boost their self-esteem and self-efficacy, and practice spoken foreign languages.</p> <p>In summary, it is essential to acknowledge that this study primarily concentrated on language learning abilities such as speaking, listening, reading, writing, and vocabulary. While these skills are undoubtedly crucial in foreign language learning, it is also essential to recognize the significance of non-linguistic abilities such as communication, teamwork, critical thinking, and cognitive skills in language acquisition. These skills play a vital role in real-world language use and proficiency and could potentially influence the effectiveness of technology-enhanced language learning. However, the study did not cover these non-linguistic abilities or explore learner characteristics such as motivation, anxiety experience, and engagement. One of the main reasons for this limitation is the lack of sufficient information to examine the effect sizes of these variables adequately. Previous first-order meta-analyses may not have frequently examined these factors, leading to a gap in the available data for analysis in this study. Moving forward, it is crucial to acknowledge the complexity of the relationship between technology and foreign language learning. While technology can undoubtedly enhance language learning outcomes, its impact is not solely determined by technological interventions. Instead, it is mediated by various individual factors such as motivation, anxiety experience, engagement, and other non-linguistic abilities. Therefore, future research should aim to explore the interaction between technology and these individual factors to gain a more comprehensive understanding of their combined influence on language learning outcomes.</p> <p>Based on the findings of the preceding analysis, we make the following recommendations for the use of technology in student language learning in the future. (<reflink idref="bib1" id="ref103">1</reflink>) Future research should carefully select participants from various educational backgrounds. Language learning effects differ depending on the educational background of the student. The cognitive structures of participants with varying educational levels differ. Middle school participants, for example, differ from college participants in terms of knowledge and understanding, vocabulary mastery, technology experience, and so on. For instance, middle school students may have limited exposure to technology compared to college students, while adult learners may have different motivation levels and language learning strategies. By including participants from various educational backgrounds, researchers can capture a broader spectrum of perspectives and experiences, leading to more comprehensive and generalizable findings. Therefore, future research should select research objects according to the research objectives to ensure that they can effectively participate in the whole learning activities and maximize learning benefits. (<reflink idref="bib2" id="ref104">2</reflink>) Future research can explore these differences in cognitive processes and learning strategies is crucial for designing effective technology-enhanced language learning interventions. For example, in traditional classroom settings, technology can be used to supplement and enhance existing instructional materials, such as incorporating multimedia elements into presentations or providing access to online grammar and vocabulary exercises. In online or blended learning environments, technology can play a more central role in facilitating communication, collaboration, and personalized learning experiences. For instance, virtual reality simulations can immerse learners in authentic language contexts, while social networking platforms can connect students with native speakers and language exchange partners. (<reflink idref="bib3" id="ref105">3</reflink>) Furthermore, researchers and educators should consider how individual differences, such as learner motivation, cognitive abilities, and prior language learning experiences, interact with educational levels and technology use. For example, students who are highly motivated and self-regulated may thrive in online learning environments, where they have greater control over their learning pace and content selection. In contrast, students with lower levels of motivation or self-regulation may require additional scaffolding and support to navigate the complexities of online language learning. (<reflink idref="bib4" id="ref106">4</reflink>) It is suggested that educators use various technologies in language teaching in the future, as this study confirms that both computing technology and VR technology positively affect student language learning. The primary positive effects are as follows: (a) multimedia technology creates a rich learning environment, facilitating students' motivation and enthusiasm for learning; (b) the virtual environment is immersive, which can help language learners immerse into target language context as well as promote interactive communication in the target language; and (c) real-time interactive communication technology assists students in carrying out social interaction and meaning negotiation in real situations, as well as improving their language skills. Educators should choose technical tools appropriate for student's needs to help students achieve better learning outcomes in language learning courses. In light of the positive impact of technology on student second language learning, future prospects involve further harnessing technological advancements to optimize language learning experiences. This entails continued innovation in educational technology, including the development of interactive language learning platforms, adaptive learning algorithms, and immersive virtual reality environments tailored to language acquisition. Additionally, fostering collaboration between educators, technologists, and language learning researchers can lead to the creation of effective pedagogical strategies and tools that integrate seamlessly into language learning curricula. Moreover, promoting equitable access to technology and digital resources will be essential to ensure that all learners, regardless of background or location, can benefit from these advancements. By embracing these future prospects, we can cultivate a more dynamic and inclusive learning environment that empowers students to achieve proficiency and fluency in their second language.</p> <p>While the meta-analysis highlights the positive impact of technology on language learning outcomes, it is essential to consider potential drawbacks associated with technology integration in educational settings. One concern is the potential for technology to exacerbate existing inequalities in access to education. Not all students may have equal access to digital devices, high-speed internet, or the necessary technical skills to effectively utilize technology for language learning. This digital divide could widen disparities in academic achievement, particularly among underserved or marginalized student populations. Additionally, the reliance on technology in language learning may inadvertently diminish opportunities for face-to-face interaction and interpersonal communication skills development. Language learning is not merely about acquiring vocabulary and grammar rules but also about cultural immersion, social interaction, and real-world communication. Over-reliance on technology-mediated learning environments may limit students' exposure to authentic language use and cultural contexts, potentially hindering their language proficiency development in meaningful ways. Therefore, while technology can offer valuable resources and tools for language learning, educators must carefully consider its implications and ensure equitable access and balanced integration with traditional pedagogical approaches to promote holistic language learning outcomes.</p> <hd id="AN0183751057-22">Conclusion</hd> <p>This study presents a multivariate meta-meta-analysis on exploring the impact of technology on foreign language learning based on research published from 2015 to 2023. This study aims to investigate the impact of technology on different facets of language learning, encompassing listening, speaking, reading, writing, and vocabulary. Additionally, the study sought to explore the influence of factors such as educational level and the type of technology on these effects. After a systematic search in five electronic databases by keywords search and snowballing approaches, 10 articles were selected and reviewed. As a results, we addressed the research questions proposed in this study and obtained the following results.</p> <p></p> <ulist> <item> The descriptive and methodological characteristics. All studies were published in journals and provided clear inclusion criteria. Technologies were categorized into VR equipment and computing resources. Some studies focused on K12 students. Various search methods were employed, and most studies conducted multiple rounds of searching. Methodologically, all studies weighted effect sizes by sample size, addressed homogeneity and publication bias, and performed moderation analysis. Effect sizes included Cohen's d, Hedges's g, and Cochran's Q.</item> <p></p> <item> The quantitative findings of listening, speaking, reading, writing, and vocabulary. The meta-analysis demonstrated that technology-supported language learning significantly enhanced listening, speaking, reading, writing, and vocabulary skills compared to traditional methods.</item> <p></p> <item> The moderator analyses for educational level and technology type on the outcomes. Educational level and technology types both were no statistically significant moderators of effect size, however, statistically significant effects of technology on student foreign language learning existed in both higher education and K-12. A statistically significant effect size of computing resource and VR tools also existed.</item> <p></p> <item> The publication bias. The analysis of publication bias using both the funnel plot and Classic fail-safe N method indicated no evidence of publication bias in this study.</item> </ulist> <p>According to the findings, we believe that a second-order meta-analysis of the effects of technology on language learning is still important and warrants additional attention from scholars and researchers.</p> <p>To begin with, this study is the first multivariate meta-meta-analysis on how technology affects student language learning. Firstly, in light of the identified limitations in existing first-order meta-analyses, there is an opportunity to provide additional value and address pertinent issues in the field of technology and foreign language learning. By conducting second-order meta-analyses, researchers can delve deeper into the intricacies of the relationship between technology and language acquisition, thus offering more nuanced insights. Specifically, such analyses could explore not only the overall impact of technological applications but also the specific factors that influence this relationship.</p> <p>Secondly, the theoretical significance lies in its innovative approach as the first multivariate meta-meta-analysis in the realm of technology's impact on language learning. By integrating qualitative and quantitative methodologies, this study offers a more comprehensive understanding of the complex dynamics between technology and language acquisition. Furthermore, the study provides a synthesized overview of previous meta-analyses, offering scholars insights into the existing research landscape and paving the way for further advancements in the field of technology-assisted language learning.</p> <p>Thirdly, this study suggests future research directions in the field of technology-assisted language learning. For example, using technologies (e.g., translation technology, VR, and etc.) to examine their effects on language learning, and examining the role of moderator variables involved, e.g. educational level, technology type. Finally, this study assists educators and policymakers in developing and implementing effective technology-assisted language learning curriculum, as well as promulgating corresponding educational policies, with technology serving as an important tool in improving student language learning performance. Moreover, the exploration of moderator variables like educational level and technology type provides actionable insights for optimizing technology integration in language learning environments. Ultimately, the findings of this study empower educators and policymakers to make informed decisions in adopting and implementing effective technology-enhanced language learning strategies, thereby fostering improved student language learning outcomes.</p> <p>Overall, second-order meta-analyses offer the opportunity to enhance the rigor and depth of research in the field of technology and foreign language learning. By addressing the limitations of previous studies and providing insights into specific influencing factors, these analyses contribute to the advancement of knowledge and the development of evidence-based practices in language education.</p> <hd id="AN0183751057-23">Limitation and future study</hd> <p>Meta-analysis conventionally assumes that each study is independent, implying that their results are not influenced by one another. However, this assumption is not always valid, as various studies can be affected by comparable factors or may be associated in other ways. Consequently, determining the correlation between studies can be exceptionally challenging, and this represents another limitation of our current study. In future research, we plan to tackle this challenge by integrating additional methods.</p> <p>Based on the preceding discussions and recommendations, future research on technology-assisted language learning could take several directions. Firstly, researchers could conduct qualitative analyses of the growing number of meta-analyses on this topic, providing deeper insights into the underlying mechanisms and nuances of technology's impact on language acquisition. Secondly, there's a need to expand research on immersive technologies like virtual reality, exploring their potential to enhance language learning outcomes further. Thirdly, empirical studies should investigate how factors such as educational level and technology type influence the effectiveness of technology in language learning, providing valuable insights for both research and practice. Finally, future research should explore learning outcomes beyond linguistic abilities, delving into non-linguistic skills and learner characteristics to paint a more comprehensive picture of technology's role in language acquisition. By addressing these areas, future studies can contribute significantly to advancing our understanding of technology-assisted language learning and optimizing its effectiveness in educational settings.</p> <hd id="AN0183751057-24">Acknowledgements</hd> <p>This research is supported by the Jiangsu Provincial Educational Sciences "14th Five-Year Plan" Major Project Fund for "Research on Artificial Intelligence and Educational Reform" (Grant Number: A/2021/03).</p> <hd id="AN0183751057-25">Data availability</hd> <p>The data that support the findings of this study are not publicly available due to privacy restrictions and will be provided on a reasonable request by the corresponding author.</p> <hd id="AN0183751057-26">Declarations</hd> <p></p> <hd id="AN0183751057-27">Conflict of interest</hd> <p>The authors declare that there are no conflicts of interest.</p> <hd id="AN0183751057-28">Ethical approval</hd> <p>In this research article, we affirm our commitment to upholding ethical principles, even though the study does not involve human or animal participants.</p> <hd id="AN0183751057-29">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0183751057-30"> <title> References </title> <blist> <bibl id="bib1" idref="ref18" type="bt">1</bibl> <bibtext> Alexander PA, Murphy PKLambert N, McCombs BL. 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Educational Research Review. 2017; 22: 19-33. 10.1016/j.edurev.2017.07.001</bibtext> </blist> </ref> <aug> <p>By Suping Yi; Wenye Li; Yanyan Zhang and Rustam Shadiev</p> <p>Reported by Author; Author; Author; Author</p> <p></p> <p>Suping Yi Suping Yi is an associate professor at the School of Education Science, Jiangsu Second Normal University, China. Her research interests relate to learning science, learning analytics, and knowledge building.</p> <p>Wenye Li Wenye Li is a doctoral student from the School of Education Science, Nanjing Normal University, China. Her research interests include education and information technologies.</p> <p>Yanyan Zhang Yanyan Zhang is a lecturer at the College of Education Science and Technology of Nanjing University of Posts and Telecommunications, China. Her research interest covers learning and instruction.</p> <p>Rustam Shadiev Rustam Shadiev is a professor at the College of Education of Zhejiang University, China. His research focuses on advanced educational technologies and their applications in language and culture learning contexts.</p> </aug> <nolink nlid="nl1" bibid="bib21" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib25" firstref="ref2"></nolink> <nolink nlid="nl3" bibid="bib33" firstref="ref3"></nolink> <nolink nlid="nl4" bibid="bib47" firstref="ref4"></nolink> <nolink nlid="nl5" bibid="bib49" firstref="ref5"></nolink> <nolink nlid="nl6" bibid="bib20" firstref="ref7"></nolink> <nolink nlid="nl7" bibid="bib39" firstref="ref8"></nolink> <nolink nlid="nl8" bibid="bib14" firstref="ref9"></nolink> <nolink nlid="nl9" bibid="bib48" firstref="ref10"></nolink> <nolink nlid="nl10" bibid="bib26" firstref="ref11"></nolink> <nolink nlid="nl11" bibid="bib17" firstref="ref12"></nolink> <nolink nlid="nl12" bibid="bib35" firstref="ref13"></nolink> <nolink nlid="nl13" bibid="bib11" firstref="ref14"></nolink> <nolink nlid="nl14" bibid="bib41" firstref="ref17"></nolink> <nolink nlid="nl15" bibid="bib16" firstref="ref22"></nolink> <nolink nlid="nl16" bibid="bib19" firstref="ref23"></nolink> <nolink nlid="nl17" bibid="bib22" firstref="ref24"></nolink> <nolink nlid="nl18" bibid="bib40" firstref="ref26"></nolink> <nolink nlid="nl19" bibid="bib12" firstref="ref27"></nolink> <nolink nlid="nl20" bibid="bib30" firstref="ref29"></nolink> <nolink nlid="nl21" bibid="bib44" firstref="ref30"></nolink> <nolink nlid="nl22" bibid="bib43" firstref="ref31"></nolink> <nolink nlid="nl23" bibid="bib15" firstref="ref33"></nolink> <nolink nlid="nl24" bibid="bib50" firstref="ref34"></nolink> <nolink nlid="nl25" bibid="bib46" firstref="ref35"></nolink> <nolink nlid="nl26" bibid="bib31" firstref="ref36"></nolink> <nolink nlid="nl27" bibid="bib42" firstref="ref40"></nolink> <nolink nlid="nl28" bibid="bib28" firstref="ref44"></nolink> <nolink nlid="nl29" bibid="bib32" firstref="ref50"></nolink> <nolink nlid="nl30" bibid="bib23" firstref="ref57"></nolink> <nolink nlid="nl31" bibid="bib24" firstref="ref73"></nolink> <nolink nlid="nl32" bibid="bib13" firstref="ref78"></nolink> <nolink nlid="nl33" bibid="bib10" firstref="ref80"></nolink> <nolink nlid="nl34" bibid="bib29" firstref="ref84"></nolink> <nolink nlid="nl35" bibid="bib18" firstref="ref91"></nolink> <nolink nlid="nl36" bibid="bib36" firstref="ref94"></nolink> <nolink nlid="nl37" bibid="bib38" firstref="ref97"></nolink> <nolink nlid="nl38" bibid="bib27" firstref="ref98"></nolink> <nolink nlid="nl39" bibid="bib45" firstref="ref100"></nolink> <nolink nlid="nl40" bibid="bib37" firstref="ref102"></nolink> |
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| Items | – Name: Title Label: Title Group: Ti Data: Exploring the Impact of Technology on Foreign Language Learning: A Multivariate Meta-Meta-Analysis Study – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Suping+Yi%22">Suping Yi</searchLink><br /><searchLink fieldCode="AR" term="%22Wenye+Li%22">Wenye Li</searchLink><br /><searchLink fieldCode="AR" term="%22Yanyan+Zhang%22">Yanyan Zhang</searchLink><br /><searchLink fieldCode="AR" term="%22Rustam+Shadiev%22">Rustam Shadiev</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-5571-1158">0000-0001-5571-1158</externalLink>) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Educational+Technology+Research+and+Development%22"><i>Educational Technology Research and Development</i></searchLink>. 2025 73(1):35-58. – Name: Avail Label: Availability Group: Avail Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 24 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22Second+Language+Instruction%22">Second Language Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Second+Language+Learning%22">Second Language Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Meta+Analysis%22">Meta Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Language+Skills%22">Language Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Research+Reports%22">Research Reports</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Technology%22">Information Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Integration%22">Technology Integration</searchLink><br /><searchLink fieldCode="DE" term="%22Outcomes+of+Education%22">Outcomes of Education</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Processes%22">Learning Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Effectiveness%22">Instructional Effectiveness</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1007/s11423-024-10412-7 – Name: ISSN Label: ISSN Group: ISSN Data: 1042-1629<br />1556-6501 – Name: Abstract Label: Abstract Group: Ab Data: The purpose of the present study was to analyze the impact of technology on student foreign language learning, as it has been widely used to enhance language instruction over the past few decades. This multivariate meta--meta-analysis study aimed to examine the effects of technology on various aspects of language learning, including listening, speaking, reading, writing and vocabulary, and explore how factors like educational level and technology type influenced these impacts. The researchers conducted a meta-analysis of 10 studies published prior to May 2023, using both qualitative and quantitative methods. They analyzed the descriptive and methodological characteristics of each study, and found a statistically significant overall effect size (g = 0.068, p < 0.001 with a 95% confidence interval of 0.595-0.860) indicating that technology positively impacted language learning outcomes compared to traditional learning methods. The researchers identified educational level and technology type as important factors contributing to the variability in effect size. Specifically, both higher education and K-12 settings, as well as VR tools and computing resources, had positive impacts on students' foreign language learning. Overall, the results suggest that using technology is an effective way to improve foreign language learning for students, and provide valuable recommendations for future research and practical applications in this area. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: EJ1462610 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11423-024-10412-7 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 24 StartPage: 35 Subjects: – SubjectFull: Second Language Instruction Type: general – SubjectFull: Second Language Learning Type: general – SubjectFull: Meta Analysis Type: general – SubjectFull: Language Skills Type: general – SubjectFull: Research Reports Type: general – SubjectFull: Teaching Methods Type: general – SubjectFull: Information Technology Type: general – SubjectFull: Technology Integration Type: general – SubjectFull: Outcomes of Education Type: general – SubjectFull: Learning Processes Type: general – SubjectFull: Instructional Effectiveness Type: general Titles: – TitleFull: Exploring the Impact of Technology on Foreign Language Learning: A Multivariate Meta-Meta-Analysis Study Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Suping Yi – PersonEntity: Name: NameFull: Wenye Li – PersonEntity: Name: NameFull: Yanyan Zhang – PersonEntity: Name: NameFull: Rustam Shadiev IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 1042-1629 – Type: issn-electronic Value: 1556-6501 Numbering: – Type: volume Value: 73 – Type: issue Value: 1 Titles: – TitleFull: Educational Technology Research and Development Type: main |
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