A Bayesian Meta-Analysis of Digital Game-Enhanced Vocabulary Learning
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| Title: | A Bayesian Meta-Analysis of Digital Game-Enhanced Vocabulary Learning |
|---|---|
| Language: | English |
| Authors: | Sofiya Shahiwala (ORCID |
| Source: | Journal of Computer Assisted Learning. 2026 42(3). |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 23 |
| Publication Date: | 2026 |
| Document Type: | Journal Articles Reports - Research Information Analyses |
| Descriptors: | Bayesian Statistics, Meta Analysis, Game Based Learning, Vocabulary Development, Computer Games, Instructional Effectiveness |
| DOI: | 10.1002/jcal.70246 |
| ISSN: | 0266-4909 1365-2729 |
| Abstract: | Background: Digital game-enhanced vocabulary learning (DGEVL), referring to the use of commercial off-the-shelf games for vocabulary learning, has attracted growing scholarly interest. Although existing studies predominantly report positive effects, previous reviews have conflated different game types, restricted their scope or overlooked the processes that mediate learning outcomes. As a result, there is limited understanding of how and under what conditions DGEVL works, leaving gaps in theory and research practice. Objectives: This study aimed to examine the effectiveness of digital game-enhanced vocabulary learning and identify the factors that facilitate or hinder its impact. Methods: A meta-analysis of 12 studies (14 samples, 765 participants) was conducted using a Bayesian random-effects model to assess the overall impact of DGEVL. Subgroup analyses explored the influence of study, participant, intervention and assessment characteristics. To contextualise these findings, a systematic review of 25 studies, comprising 12 quantitative studies included in the meta-analysis and an additional 13 qualitative studies, was carried out, and a thematic analysis was conducted to construct a conceptual model of the learning process. Results and Conclusions: DGEVL demonstrates a strong positive effect on vocabulary learning (posterior median g[subscript within] = 1.11, 95% credible interval (CI) [0.62, 1.61]; g[subscript between] = 1.40, 95% CI [0.58, 2.25]), with substantial between-study heterogeneity (τ[subscript within] = 0.56, 95% CI [0.26, 1.00]; τ[subscript between] = 0.80, 95% CI [0.26, 1.68]). These effects vary depending on factors such as the length of the intervention, learner proficiency, and the type of game played. The cyclical model conceptualises vocabulary learning as a cyclical process shaped by gameplay, language interactions and metacognitive regulation. The study highlights the need for balanced assessment techniques, prolonged interventions, micro-longitudinal data collection, comparative designs and rigorous trials. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1506850 |
| Database: | ERIC |
| Abstract: | Background: Digital game-enhanced vocabulary learning (DGEVL), referring to the use of commercial off-the-shelf games for vocabulary learning, has attracted growing scholarly interest. Although existing studies predominantly report positive effects, previous reviews have conflated different game types, restricted their scope or overlooked the processes that mediate learning outcomes. As a result, there is limited understanding of how and under what conditions DGEVL works, leaving gaps in theory and research practice. Objectives: This study aimed to examine the effectiveness of digital game-enhanced vocabulary learning and identify the factors that facilitate or hinder its impact. Methods: A meta-analysis of 12 studies (14 samples, 765 participants) was conducted using a Bayesian random-effects model to assess the overall impact of DGEVL. Subgroup analyses explored the influence of study, participant, intervention and assessment characteristics. To contextualise these findings, a systematic review of 25 studies, comprising 12 quantitative studies included in the meta-analysis and an additional 13 qualitative studies, was carried out, and a thematic analysis was conducted to construct a conceptual model of the learning process. Results and Conclusions: DGEVL demonstrates a strong positive effect on vocabulary learning (posterior median g[subscript within] = 1.11, 95% credible interval (CI) [0.62, 1.61]; g[subscript between] = 1.40, 95% CI [0.58, 2.25]), with substantial between-study heterogeneity (τ[subscript within] = 0.56, 95% CI [0.26, 1.00]; τ[subscript between] = 0.80, 95% CI [0.26, 1.68]). These effects vary depending on factors such as the length of the intervention, learner proficiency, and the type of game played. The cyclical model conceptualises vocabulary learning as a cyclical process shaped by gameplay, language interactions and metacognitive regulation. The study highlights the need for balanced assessment techniques, prolonged interventions, micro-longitudinal data collection, comparative designs and rigorous trials. |
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| ISSN: | 0266-4909 1365-2729 |
| DOI: | 10.1002/jcal.70246 |
