In Thailand, children with hearing impairments represent a significant population within the broader category of students with special educational needs. National policies, such as the Education for Persons with Disabilities Act 2008 and the Fourth Education Plan for Persons with Disabilities 2023-2027, emphasize equitable access to quality education and the development of linguistic skills for learners with disabilities (Ministry of Education, 2025). However, despite these policies, gaps in language processing, especially in terms of response efficiency, remain a pressing challenge (National Association of the Deaf, 2023).

Recent advances in educational technology highlight virtual reality (VR) as a promising intervention to support language development among students with hearing impairments. VR offers immersive environments that rely heavily on visual-spatial engagement rather than auditory input, allowing learners to process linguistic stimuli through multiple sensory channels (Parmaxi & Demetriou, 2020). This multimodal approach is particularly relevant for learners with limited auditory access, as it leverages visual learning strengths while promoting language comprehension and production (Hua & Wang, 2023). Research in Thai educational contexts has emphasized the critical role of visual perception in early learning (Ammawat et al., 2022), suggesting that visually-oriented interventions may be especially effective for Thai students with sensory impairments.

The effectiveness of VR in language learning can be theoretically grounded in Mayer’s Multimedia Learning Theory (Mayer, 2014), which posits that people learn more effectively when information is presented through multiple modalities simultaneously. According to this theory, meaningful learning occurs when learners actively select relevant visual and auditory information, organize it into coherent mental representations, and integrate these representations with prior knowledge. For students with hearing impairments, VR environments capitalize on the visual processing channel while potentially reducing cognitive load through well-designed instructional presentations that align with multimedia learning principles such as the modality effect, the redundancy principle, and the coherence principle.

Evidence suggests that VR-based interventions not only increase motivation and engagement but also improve the efficiency of language learning. Studies have shown that immersive VR can accelerate the speed of cognitive processing by simulating authentic communication contexts where learners must recognize, interpret, and respond rapidly to linguistic cues (Bailenson, 2018; Schorr et al., 2024). For students with hearing impairments, these simulated environments reduce reliance on auditory channels and instead encourage faster recognition of visual signs, written texts, and symbolic representations (Rakhmadi et al., 2024).

Furthermore, VR allows for repeated practice within controlled, context-rich scenarios, which facilitates the transition from effortful, conscious language processing to more automatic responses. This process is consistent with theories of motor adaptation and spatial working memory, in which repeated interaction with stimuli fosters quicker encoding, retrieval, and response (Kagerer et al., 2004; Makmee & Wongupparaj, 2022). Thus, VR does not simply improve accuracy in verbal tasks but has the potential to significantly reduce response time, reflecting more fluent and efficient processing (Makmee & Wongupparaj, 2025).

Although many studies have demonstrated the potential of VR in supporting language learning, most studies have focused primarily on accuracy outcomes, such as vocabulary acquisition, reading comprehension, or grammar (T. J. Lin & Lan, 2015; Peixoto et al., 2021). While these findings are valuable, they overlook an equally critical dimension of verbal proficiency: response time. Processing speed is not only an indicator of linguistic fluency but also directly influences the ability of learners to participate in real-time communication, whether in classroom discussions or everyday interactions (Gardner, 2011; McGrew, 2009).

Response time in verbal tasks has long been regarded as a vital measure of cognitive processing, reflecting the efficiency with which learners could access, retrieve, and apply linguistic information (McGrew, 2009). While accuracy captures whether a response is correct, response time offers insight into the underlying automaticity and fluency of language use. For students with hearing impairments, slower response times are often due to limited auditory input during critical periods of language acquisition, reduced exposure to phonological structures, and reliance on compensatory communication strategies such as sign language or visual cues (Marschark et al., 2014; Zhang et al., 2024). These delays in processing can impede classroom participation, slow reading comprehension, and contribute to persistent educational disparities (Rosfiani et al., 2022; Schick et al., 2007).

Despite this, empirical evidence on whether VR-based interventions can reduce response times in verbal tasks remains scarce. Most available research has been conducted in contexts emphasizing English language acquisition or American Sign Language (ASL), with limited attention to non-English-speaking settings such as Thailand (Serafin et al., 2023). In addition, differences in educational policies, classroom practices, and the use of Thai Sign Language, which is shaped by local linguistic and cultural conventions, may influence how students with hearing impairments process and respond to language compared to learners in Western contexts (Mirzaei et al., 2020). These differences highlight the need for context-specific empirical research.

Given the limitations of existing research, the present study aims to investigate the effects of a VR innovation on verbal abilities, with a particular focus on accuracy and response time, among elementary students with hearing impairments in Thailand. Using a pretest-posttest control group design, the study compares performance between experimental and control groups before and after VR training to determine whether immersive VR can facilitate faster recognition, interpretation, and responses to linguistic stimuli. This design allows for the identification of causal effects of VR on processing speed, complementing prior research that has primarily emphasized accuracy outcomes (Makmee, 2022; Schorr et al., 2024). By incorporating response time as an outcome measure, the study adopts a broader conceptualization of verbal ability that encompasses both correctness and fluency of response (Gardner, 2011; McGrew, 2009).

Ultimately, this research contributes to the field of special education by addressing a dimension of verbal development in students with hearing impairments. Evidence from this study may provide practical insights for educators, curriculum developers, and policymakers on the role of VR in promoting not only accurate but also rapid and fluent language processing. Such findings are expected to support the development of inclusive, technology-enhanced learning environments that reduce educational inequality and promote equality in linguistic competence (Marschark et al., 2014; Ministry of Education, 2025).

This study employed a quantitative experimental design using a pretest-posttest control group design, which is widely recognized as a rigorous experimental method for examining causal relationships between interventions and outcomes (Edmonds & Kennedy, 2017). Participants were randomly assigned into an experimental group, which received training through the VR-based application, and a control group, which received traditional instruction without VR. Both groups completed a computerized verbal ability test before (pretest) and after (posttest) the intervention.

In this section, the researcher presents the experimental results, which basic statistics of participants classified by group shown below.

As shown in Table 1, this experimental study involved a total of 50 participants, divided equally into an experimental group and a control group, with 25 participants in each. Within the experimental group, the majority were males (13 participants, 52%), whereas in the control group, the majority were females (14 participants, 56%). However, Preliminary analyses examined baseline equivalence between experimental and control groups. Chi-square tests revealed no significant differences in gender distribution, χ² = 0.32, df = 1, p = .57, or grade level distribution, χ² = 0.22, df = 5, p = 1.00. An independent samples t-test showed no significant difference in mean age between the experimental group (M = 10.20, SD = 1.50) and control group (M = 9.80, SD = 2.06), t(48) = 0.78, p > .05. Additionally, no significant differences were found in age range distribution, χ² = 0.24, df = 2, p = .89. These results confirm that both groups were comparable on all demographic variables prior to the intervention.

Table 2 shows the mean scores, standard deviations, skewness, kurtosis, minimum, and maximum values of language ability variables, divided into two dimensions: (1) accuracy and (2) response time. Before conducting the MANCOVA, the assumptions of the analysis were rigorously examined. Multivariate normality was tested through Kolmogorov-Smirnov test, with a p > .05 indicating that the data were normally distributed. The assumption of homogeneity of covariance matrices was satisfied, as indicated by a non-significant Box’s M test (Box’s M = 2.17, F = 0.69, p = .56). Linearity was verified through scatterplots, which revealed no curvilinear patterns. Furthermore, the homogeneity of regression slopes was confirmed, with the interaction term yielding a non-significant result (p > .05), suggesting consistent relationships between covariates and dependent variables across groups. Moreover, the correlation between accuracy and response time was r = -.16, which is below the threshold of .80, indicating that the dependent variables are moderately correlated and free from multicollinearity. Therefore, the data were suitable for analysis using the paired-sample t-test and MANCOVA, as presented in Tables 3 and 4.

In Table 3, the results of the comparative analysis of language ability scores within and between groups are summarized. For the experimental group, significant differences were found between the pretest and posttest in both accuracy, t(24) = 2.51, p < .05, and response time, t(24) = –2.38, p < .05. The effect sizes were at a medium level (d = 0.50 and 0.49, respectively). In contrast, the control group showed no significant differences between pretest and posttest.

Several previous studies indicating that variables such as academic year, gender, and age may act as confounding factors affecting research outcomes; the researchers therefore conducted a statistical analysis using MANCOVA, as shown in Table 4.

Table 4 shows the comparison of language ability scores between the experimental and control groups after the training showed that academic year acted as a covariate affecting the analysis of the training outcomes in accuracy scores for students with hearing impairments. After controlling this covariate, the post-training comparison between the experimental and control groups revealed a significant difference, F(1) = 5.92, p = .02, with a medium effect size (η² = .12). However, for response time, no covariates were identified, and no significant difference was found between the two groups, F(1) = 0.84, p = .34. The comparison of mean scores between groups after the experiment is presented in Figures 2 and 3 below.

This study examined the effectiveness of a VR innovation in enhancing the verbal abilities of elementary students with hearing impairments, with a focus on accuracy and response time. Using a pretest-posttest control group design, the results showed that students who received VR training demonstrated significant improvements in both accuracy and response time from pretest to posttest, whereas no significant changes were observed in the control group. Posttest comparisons further indicated that the experimental group achieved significantly higher accuracy scores than the control group, although no significant between-group difference was found for response time.

These findings indicate that VR-based interventions can effectively support the development of accurate verbal responses in students with hearing impairments. Immersive and interactive VR environments provide opportunities for contextualized language practice, visual engagement, and immediate feedback, which together promote vocabulary acquisition, comprehension, and learner motivation. While improvements in response time were evident within the experimental group, the absence of significant between-group differences suggests that gains in processing speed may require longer or more intensive exposure to VR-based training.

Overall, the results highlight the potential of VR as a pedagogical tool for supporting verbal development in learners with hearing impairments, particularly in visually oriented learning contexts. Future research should explore the long-term effects of VR on language fluency, examine the role of individual differences and prior experience with technology, and investigate the scalability of VR-based interventions across diverse educational settings.