Does gender, age or seniority influence the satisfaction with Virtual Reality Training and its success in the financial sector?

¿Influye el género en la satisfacción con la formación en Realidad Virtual y en su éxito en el sector financiero?

O gênero influencia a satisfação com o treinamento em Realidade Virtual e o seu sucesso no setor financeiro?

Belén Díaz Díaz^1*
Rebeca García-Ramos^1**
Sandro Arrufat Martín^2***

¹ Universidad de Cantabria, España
² Universidad Rey Juan Carlos, España
* Financial Economics and Accounting, Universidad de Cantabria, España. Email: diazb@unican.es
** Associate Professor of Financial Economics and Accounting, Universidad de Cantabria, España. Email: rebeca.garciaramos@unican.es
*** Associate Professor of Communication, Universidad Rey Juan Carlos, España. Email: sandro.arrufat@urjc.es (Corresponding Author)

Abstract

Purpose: Virtual Reality (VR) is increasingly used in corporate training because of its immersive potential. However, evidence regarding the influence of demographic variables on training effectiveness and satisfaction remains inconclusive. This study examines whether gender, age, and seniority affect learning outcomes and user satisfaction in VR training within the financial sector. Methodology: The study involved 249 employees from a financial institution who completed a 30-minute VR training session on insurance management. Training effectiveness was assessed through performance tests, while satisfaction was measured using a five-point Likert scale. Kruskal–Wallis tests and multiple regression analyses were conducted to evaluate the influence of personal and contextual variables. Results: Gender and age did not significantly affect training performance or satisfaction. In contrast, seniority showed a negative relationship with performance, indicating that more experienced employees achieved lower scores. Training duration and gender were not significant predictors of outcomes. Overall satisfaction with the VR experience was high across all groups, with only minor differences related to office type and location. Conclusions: VR training appears to be equally effective and satisfactory regardless of gender or age. However, the negative association between seniority and performance may reflect greater resistance or adaptation difficulties among more experienced employees. These findings support inclusive VR training strategies focused on technological adaptation rather than demographic segmentation.

Keywords
Virtual reality; Training performance; Training satisfaction; Immersive environments; Gender diversity; Learning outcomes.

Resumen

Propósito: La Realidad Virtual (RV) se utiliza cada vez más en la formación corporativa debido a su capacidad inmersiva. Sin embargo, la evidencia sobre la influencia de variables demográficas en la efectividad y satisfacción de la formación sigue siendo inconclusa. Este estudio analiza si el género, la edad y la antigüedad laboral influyen en los resultados de aprendizaje y en la satisfacción de programas de formación basados en RV en el sector financiero. Metodología: El estudio contó con 249 empleados de una entidad financiera que realizaron una sesión de formación en RV de 30 minutos sobre gestión de seguros. La efectividad formativa se evaluó mediante pruebas de rendimiento y la satisfacción mediante una escala Likert de cinco puntos. Se aplicaron pruebas de Kruskal-Wallis y análisis de regresión múltiple para examinar la influencia de variables personales y contextuales. Resultados: Los resultados muestran que ni el género ni la edad tuvieron un impacto significativo en el rendimiento o la satisfacción. Por el contrario, la antigüedad laboral presentó una relación negativa con el desempeño, indicando que los empleados con mayor experiencia obtuvieron puntuaciones inferiores. La satisfacción con la experiencia de RV fue elevada en todos los grupos, observándose únicamente pequeñas diferencias según el tipo de oficina y la localización geográfica. Conclusiones: La formación en RV parece ser igualmente efectiva y satisfactoria independientemente del género o la edad. Sin embargo, la relación negativa entre antigüedad y rendimiento podría reflejar mayores dificultades de adaptación tecnológica entre empleados más experimentados.

Palabras clave
Realidad virtual; Rendimiento en la formación; Satisfacción con la formación; Entornos inmersivos; Diversidad de género; Resultados de aprendizaje.

Resumo

Objetivo: A Realidade Virtual (RV) vem sendo cada vez mais utilizada na formação corporativa devido ao seu potencial imersivo. Contudo, as evidências sobre a influência de variáveis demográficas na eficácia e satisfação do treinamento permanecem inconclusivas. Este estudo analisa se gênero, idade e antiguidade profissional afetam os resultados de aprendizagem e a satisfação em treinamentos baseados em RV no setor financeiro. Metodologia: Participaram do estudo 249 colaboradores de uma instituição financeira que realizaram uma sessão de treinamento em RV de 30 minutos sobre gestão de seguros. A eficácia do treinamento foi avaliada por meio de testes de desempenho, enquanto a satisfação foi medida utilizando uma escala Likert de cinco pontos. Foram aplicados testes de Kruskal-Wallis e análises de regressão múltipla para examinar o impacto de variáveis pessoais e contextuais. Resultados: Os resultados indicam que gênero e idade não exerceram influência significativa sobre o desempenho ou a satisfação dos participantes. Em contrapartida, a antiguidade profissional apresentou relação negativa com o desempenho, sugerindo que colaboradores mais experientes obtiveram resultados inferiores. A satisfação geral com a experiência em RV foi elevada entre todos os grupos, com apenas pequenas diferenças relacionadas ao tipo de escritório e à localização geográfica. Conclusões: O treinamento em RV mostrou-se igualmente eficaz e satisfatório independentemente de gênero ou idade. Entretanto, a relação negativa entre antiguidade e desempenho pode indicar maiores dificuldades de adaptação tecnológica entre profissionais mais experientes.

Palavras-chave
Realidade virtual; Desempenho na formação; Satisfação com a formação; Ambientes imersivos; Diversidade de género; Resultados de aprendizagem.

1. Introduction

Over last decades, Virtual Reality (VR) has emerged as a revolutionary tool in education and training (Smutny, 2022). It offers an immersive experience that goes beyond conventional learning methods. VR provides trainers with the opportunity to immerse themselves in secure learning environments, enhancing their ability to absorb knowledge and comprehend key concepts effectively (Jarvelainen et al., 2018). Nevertheless, previous literature offers limited empirical evidence linking the use of VR to enhanced learning outcomes. Moreover, current research presents inconsistent findings (e. g., Makowski et al., 2017; Makransky et al., 2019) or fails to establish a statistically significant improvement in performance for learners trained using VR compared to those trained through traditional instruction methods (Grassini et al., 2020).

The exploration of the training effects of immersive VR is still in its early stages within the scientific literature sphere. Further investigation is needed to determine whether VR training can offer measurable advantages in task performance.

Although VR-based training has been widely studied across several industries, its application in the financial sector—particularly in banking—remains largely unexplored. This context is relevant because VR can support the development of customer-service skills and decision-making in complex situations while enabling scalable training for geographically dispersed employees.

In addition, examining demographic factors such as gender and age is particularly relevant in the context of VR-based training. Prior research on technology adoption has frequently identified these variables as potential sources of differences in attitudes toward new technologies, perceived usability, and learning outcomes.

In a meta-analysis conducted by Yu (2023), the impact of VR technologies on educational outcomes across various components is reviewed. The study suggests an overall strong and positive influence of VR technologies on educational outcomes, even though the identification of adverse effects in terms of anxiety, cognition, creativity, gender differences, learning attitudes, learner satisfaction, and engagement.

The experience reported by the user of Head Mounted Displays-mediated VR, is not always positive. Several users report experiencing adverse symptoms, including nausea and disorientation or headaches, among others (Kennedy et al., 1993; Duzmanska et al., 2018). These symptoms are commonly known as simulator sickness (SS) that some authors have found to have higher incidence in women than in men (Munafo et al., 2017).

The reasons behind the disparity in experiencing symptoms of SS among genders remain unclear. Some researchers attribute differences to hormonal variations in the female menstrual cycle, while others propose alternative explanations. Biocca (1992) suggested that a broader field of view (FOV), typically observed in females, may increase vulnerability to SS. Since SS assessments often rely on self-reports, it has also been argued that males may underreport discomfort (Biocca, 1992; Kolasinski, 1995). Other perspectives relate the imbalance to cognitive differences between sexes (Giammarco et al., 2015) or to sexual dimorphism, which may influence movement stability (Munafo et al., 2017). Nevertheless, Grassini and Laumann’s (2020) review found no consistent association between gender and SS.

Although gender differences appear in VR adoption, research indicates no disparities in VR-based pedagogy or learning outcomes (Annetta et al., 2009; Huang et al., 2020; Yu, 2021). Similarly, Grassini et al. (2020) reported no differences between men and women in performance, sense of presence, or SS. However, a minority of studies suggest females may outperform males in certain VR tasks (Allen et al., 2016; Liang et al., 2019). Enhanced presence reported among females (Gamito et al., 2008) could explain these findings, as presence has been linked to better performance in learning (Yang et al., 2016).

Grassini and Laumann’s (2020) systematic review confirmed heterogeneous evidence: while most studies found no gender differences in cognition, memory, perception, or enjoyment, some reported female advantages (greater emotional sensitivity and presence), whereas others suggested males might perform better due to FOV perception (Czerwinski et al., 2002).

The debate on gender differences in VR training remains open. Success and satisfaction with VR, considering gender, age, or seniority, are largely unexplored. Addressing these gaps, this study investigates immersive VR training in the financial sector. To our knowledge, it is the first to analyse gender differences in VR training in banking. The results may provide useful insights for both academics and Learning & Development leaders by exploring whether gender and age are associated with training outcomes and satisfaction, and how these factors could be considered in the design and evaluation of future VR-based training initiatives.

1.1. Gender difference in Digital Learning

Over the past two decades, several studies have highlighted gender differences in technology use and related skills, often described as a “digital gender gap” which may influence users’, behavior, outcomes, and evaluations in VR-based training (Baraybar-Fernández et al., 2025).

Evidence suggests that this gap may emerge early in life, with boys typically reporting more frequent computer use, greater confidence in ICT-related tasks, and stronger interest in computers than girls, often accompanied by higher digital skill levels and broader use for educational and entertainment purposes (Kayany and Yelsma, 2000; Colley and Comber, 2003; Mucherah, 2003; Li and Kirkup, 2007; Drabowicz, 2014). In contrast, girls have been found to use digital technologies more frequently for communication and social interaction (McSporran and Young, 2001). However, findings in digital learning contexts are mixed: while males often report higher confidence in ICT abilities (Vekiri and Chronaki, 2008), females may show stronger competence beliefs and academic self-efficacy in learning contexts (Britner and Pajares, 2001; Perkowski, 2013) as well as higher learning motivation (McSporran and Young, 2001; Price, 2006). More recent studies also suggest that gender differences in digital competence and attitudes may be narrowing or even disappearing (Vekiri, 2013; Korlat et al., 2021).

1.2. Differences in individual characteristics between genders and learning performance

Gender-related individual characteristics may contribute to differences in learning performance, although they do not fully explain them (Spinath et al., 2014). Some research suggests that females may adapt better to contemporary learning environments due to factors such as higher verbal intelligence, greater agreeableness, stronger self-discipline, and motivational traits. Women’s persistence and commitment (Richardson & Woodley, 2003), as well as stronger self-regulation (Alghamdi et al., 2020), may also support better learning outcomes.

However, empirical evidence remains mixed: some studies report better academic results for women, such as higher course grades (Dwyer & Johnson, 1997), whereas others find advantages for men, particularly in test performance (Ackerman et al., 2001). Additionally, several studies report no significant relationship between gender and learning outcomes, suggesting that males may show more stable attitudes while females demonstrate stronger engagement (Nistor, 2013), and that gender may not significantly contribute to explaining learning outcomes (Yu, 2021).

Given these inconsistent findings, we will analyse the role of gender and training success in our study with the aim of finding if there are gender differences in learning achievements when using VR Technology. In doing so, we will answer to the following research question:

• RQ1: Do women perform better than men in VR training?

1.3. Does gender affect VR training satisfaction?

Previous empirical evidence about the effect of gender on VR training satisfaction is scarce and far from conclusive. While Lu and Chiou (2010) found that females tend to have lower satisfaction with digital learning than male students, there are studies suggesting that there are no differences between men and women in attitudes towards digital learning (Cuadrado-García et al., 2010; Hung et al., 2010) and that there are not significant gender differences in the learning satisfaction of online millennial learners (Harvey et al., 2017). However, other studies suggest women have higher engagement and higher intrinsic motivation in digital learning contexts (Korlat et al., 2021) which could lead to a higher satisfaction with VR training.

Given these contradictory findings, we will analyse if there are gender differences in training satisfaction when using VR Technology. We will answer to the following research question:

• RQ2: Do women feel greater satisfaction than men in VR training?

1.4. Age and training success

The age of trainees has been suggested to influence the VR experience (Latu et al., 2019). Previous literature presents varied findings regarding the association between age and training outcomes. Some studies report a positive correlation between age and training outcomes, as well as job performance (Beier and Ackerman, 2005). However, other studies have observed that older learners may advance more slowly and exhibit poorer performance compared to their younger counterparts, as indicated by the findings of Kubeck et al. (1996). Moreover, Hertzog et al. (2008) explain the negative impact of age on training outcomes, attributing it to changes in cognitive functions such as reduced concentration, lower processing speed, and decreased memory capacity. This aligns with the idea that age-related cognitive changes can influence an individual's ability to effectively engage in and benefit from training programs. Also, Korlat et al. (2021) showed lower competence beliefs and intrinsic value for digital learning with increasing age.

However, there is evidence suggesting that the relationship between age and training success is not uniform across different dimensions of measurement. Warr et al. (1999) proposed that the association may vary depending on the specific measure of training success. For instance, Colquitt et al. (2000) found a nuanced relationship between age and training outcomes. While age was negatively correlated with overall performance, it showed a positive association with skill acquisition and the successful transfer of training to practical applications. This suggests that, despite potential challenges in immediate performance, older individuals may demonstrate a capacity for effective skill acquisition and application of training over time.

Exploring the role that age may play in training outcomes can provide valuable insights for organizations aiming to better align training design with learners’ needs. We will answer to the following research question:

• RQ3: Do older trainees perform worse than younger trainees in VR training?

1.5. Interaction of age and gender on training success

Few studies have analysed the combined influence of age and gender on learning outcomes and the results have been mixed. According to Williamson (2000), older women demonstrated a heightened learning orientation and made more significant progress compared to their male counterparts of the same age. This aligns with the observations of Caprara et al. (2003), who found that, in women, the increase in age led to improvement in various aspects related to personality, contributing to their significant improvement in training success, and that, however, this did not occur in men. Similarly, Bausch et al. (2014) reported that older women experienced a more positive development compared to older men. Interestingly, when introducing the interaction term age × gender into the explanation of training success, neither age nor gender displayed a significant direct effect. However, the interaction of both factors proved to be significant, revealing that, as age advanced, women experienced an enhancement in training success, while men witnessed a decline.

While earlier research primarily focused on either age or gender, our study delves into their combined influence. By examining the interaction of age × gender on training outcomes, we aim to contribute to the ongoing discourse in training research, particularly in the context of VR training outcomes. We will answer to the following research question:

• RQ4: Does gender affect the relationship between age and training success?

2. Materials and Methods

With the aim to answer the research questions stated above, in this paper we investigate the use of VR in an immersive training experience in the banking sector using a specific VR experience 30 minutes long about comprehensive insurance management in Santander Bank, accomplished by 249 employees between November 2022 and March 2023. This training was conducted in person using head-mounted displays for mobile devices (Google Cardboard).

The VR- training included four situations with individuals or a legal entity with the aim to increase or maintain insurance sales:

• Situation 1 with an individual – Conducting a meeting with a private client interested in a home insurance – 8 minutes.

• Situation 2 with a legal entity – Carrying out a commercial visit to a new store – 6 minutes.

• Situation 3 with an individual – Reversing a potential cancellation – 6 minutes.

• Situation 4 with an individual – Scheduling an appointment for comprehensive insurance management – 10 minutes.

In the analysis of training KPIs, we considered two dependent variables:

- Success on VR training. This variable is measured by the percentage of questions about the training correctly answered during and at the end of the training through the HMDs (5 questions for each situation described above). With this indicator, we will analyse if there are differences in the results obtained in VR training when we distinguish different characteristics of the trainees (such as gender, age, seniority).

- Satisfaction with VR training. This variable is measured by the valuation given to the VR training ranging from 1 to 5 (being 5 the best valuation). With this indicator, we will analyse which kind of trainee values best VR-based training.

Firstly, we conducted a nonparametric test to value if there are differences among groups when valuing the success and the satisfaction in VR training. In particular, we run a Kruskal-Wallis test, in order to examine if samples are drawn from identical distributions, the Kruskal-Wallis test expands on the Mann-Whitney U test for more than two groups. The test's null hypothesis posits that the mean ranks of the groups are equal.

Secondly, we conducted separate stepwise multiple regressions with training success and satisfaction as dependent variables, using Stata software. The independent variables include personal characteristics of the trainee, such as gender, age and seniority. We also included control variables, such as duration of the training, job classification, office characteristics (type of office) and location of the office.

In order to test whether the effects of age and seniority on the two defined dependent variables (success and satisfaction) were moderated by gender, we also introduce the interactive effect LnAge x Gender and LnSeniority x Gender. We also considered the interaction effect LnDuration x Gender because the greater engagement of women with the training found in previous literature (Nistor, 2013; Korlat et al., 2021) could explain differences in the time spent in the training between genders.

Table 1 shows the definition of the variables used for the analysis of VR training and for the regression analysis.

2.1. Methodological limitations

This study presents several methodological limitations that should be considered when interpreting the results. First, the research follows an observational design and does not include a control group or comparison with alternative training modalities, such as non-VR training. Consequently, the findings should be interpreted as associations rather than causal relationships. While the results provide insights into how participants experience VR-based training and how different characteristics relate to training outcomes, they do not allow for causal inference regarding the effectiveness of VR training compared to other methods.

Second, the analysis employs stepwise regression techniques to explore the relationship between participant characteristics and training outcomes. Although this approach can help identify relevant predictors in exploratory contexts, it has been widely debated due to the risk of model instability and overfitting. Therefore, the results should be interpreted with caution, and future research could complement this approach with theory-driven models or alternative analytical strategies to confirm the robustness of the findings.

Finally, participant satisfaction was measured using a single-item scale. Although commonly used for their simplicity, such measures may not fully capture the multidimensional nature of satisfaction. Future studies could benefit from validated multi-item scales to provide a more comprehensive assessment of participants’ satisfaction with VR-based training.

3. Results and discussion

3.1. Findings about the success in VR training

To test which type of trainee achieves better results in VR-based training (success), we considered the percentage of questions about the training correctly answered during and at the end of the training through the HMDs by different groups of trainees. Table 2 shows mean differences analysed.

The mean value of success is 0.7658, which means that employees who did the VR training answered correctly to 76.58% of the questions included in the training. According to the results showed in Table 2, no difference is found in the percentage of questions correctly answer when we distinguish between women and men. It is worth noting that even though women spent more time in the VR training than men (Table 3) this result is not linked to a better training success and to obtaining better results.

Table 2 also shows that there are not significant differences in the success in the VR training according to the seniority and age of the trainee. Therefore, being older or younger or having more experience in the job does not affect the success in the VR training.

In fact, no differences among groups were found when analysing the success in VR. Since VR training success does not appear to depend on personal characteristics (such as gender, age, or seniority), office type, or location, these findings challenge common assumptions that VR training is primarily suited to younger employees. Therefore, in the view of our findings, VR in training in the financial sector could be used by every kind of trainee/employee because all succeed the same.

Following the analysis of differences in mean values of success in VR training, we accomplished a stepwise regression analysis, where the dependent variable was Success and the independent variables were Gender, Age and Seniority, and the control variables were Duration, Job classification, Type of Office and Location. We also introduce the interactive effect LnAge x Gender, LnSeniority x Gender, LnDuration x Gender (see Table 4). The JOINT F-tests showed on Table 4 confirm that all the regression models were significant.

Regressions 1 and 2 in Table 4 show the absence of significance of gender in explaining training success. These results are consistent with those of Korlat et al. (2021) and Yu (2021) among others. The results also show the absence of significance of age (regression 1) and, therefore, we found no evidence that supports a positive correlation between age and training outcomes, as Beier and Ackerman (2005) previously found, and neither that older learners exhibit poorer performance, as Kubeck et al. (1996) concluded.

However, when we consider seniority of the employee instead of age, a negative and significant effect is found (regression 2). Therefore, those with higher experience in their jobs show lower training success. This behaviour could be explained by the fact that more senior employees pay less attention to training and are more reluctant to VR technology. This result confirms Abich IV et al. (2021) finding that VR is more effective for those that have less familiarity with the training content. Therefore, it is not the employees´ age, but their job experience, what seems to affect the success of the VR training.

In regressions 3 to 6 we analyse the moderating effect of gender by including interaction variables (variable x gender). In doing so, regressions show the different effect of the considered independent variables (age, seniority and duration) for women and men.

The results in regression 3 and 4 show that the effect of age and seniority on VR training Success is not significant for both men and women, without being significant difference between both groups.

Also, the results in regressions 5 and 6 show that the time spent in the VR training (Duration) is not significant to explain the success in the training. This absence of significance remains in both men and women.

3.2. Findings about the satisfaction with VR training

We also explored trainees’ prior experience with VR and whether perceptions of VR-based training differ across trainee groups. Following the same methodology as in the previous section, we considered the valuation given to VR-training ranging from 1 to 5 and dividing the sample into different groups according to the trainee characteristics, the office characteristics or location.

As shown on Table 5, employees reported high levels of satisfaction with VR training, giving a mean value of 4.5. When we divide the employees in different groups according to personal characteristics (gender, seniority, age group and job classification), we find no differences in the valuation given to VR training. However, when we divide employees according to office characteristics and location we find significant statistical differences.

In addition, the type of office is found to be significant in explaining differences in the valuation given to VR training. In universal offices (general or smart) a lower valuation is found (between 4.26 and 4.68) as compared to business-oriented offices or workcafe. The workload could explain the worse rating given in more generalist offices with a more diverse clientele and whose employees are less receptive to receiving training.

Location is also statistically significant to explain differences in VR-training valuation. Employees from Aragón and Cantabria value the training between 4.8 and 4.9, while employees in Castilla y Leon and Pais Vasco value the training between 3.2 and 3.5. It should be noted that employees in each region were summoned at the same time to experience the virtual reality experience. How the project was communicated in each region, the place where employees were summoned, the first experience with the HMDs and the support of the regional director could explain the differences in the valuation of VR training.

Following the analysis of differences in mean values of satisfaction with VR training, we performed a stepwise regression analysis, where the dependent variable was Satisfaction, the independent variables were Gender, Age and Seniority, and the control variables were Duration, Job classification, Type of Office and Location. We also introduce the interactive effect LnAge x Gender, LnSeniority x Gender, LnDuration x Gender (see Table 6).

Regression 1 and 3 in Table 6 show the absence of significance of gender and age in explaining training satisfaction, which supports Cuadrado-García et al. (2010), Hung et al. (2010) and Harvey et al. (2017). Moreover, regression 3 also shows that gender does not moderate the effect of age on training satisfaction, being the effect of age nonsignificant for both women and men.

Regressions 2 and 4 show that seniority is neither significant in explaining VR training satisfaction. In addition, regression 4 also shows that gender does not moderate the effect of seniority on training satisfaction, being the effect of seniority non-significant for both women and men.

Finally, the results in regressions 5 and 6 show that the time spent in the VR training (Duration) is not significant to explain the success in the training. Regression 6 also shows that gender does not moderate the effect of duration on training satisfaction, being the effect of duration non-significant for both women and men.

In the view of our results, we did not find empirical evidence that corroborates the initial prejudices with the VR training, such as, that women, older people or more experienced employees could show a lower satisfaction with the technology employed in the training.

In sum, the answer to our research questions would be the following:

- According to our first research question about whether women perform better than men in VR training, we found no evidence of this behaviour and the absence of a significant effect of gender on VR training success.

- Women neither feel greater satisfaction than men in VR training, which answers our second research question.

- Older trainees don´t perform worse than younger trainees in VR training. However, in relation with our third research question we found evidence about a negative relationship between seniority and success.

- Gender does not affect the relationship between age and training success and it neither affects the relationship between the different variables (age, seniority, duration) and satisfaction with the training.

4. Conclusions

This study reinforces the growing evidence that VR is an effective tool for human resource training. By offering immersive, multisensory environments, VR enhances learning and knowledge retention, positioning itself as a valuable alternative to traditional methods.

One of the main contributions of this research is the analysis of whether individual characteristics—particularly gender, age, and seniority—affect training outcomes and satisfaction. The findings indicate that gender does not play a significant role in training success or user satisfaction, supporting the view that differences in digital learning are more related to individual traits than to biological sex.

Similarly, age does not significantly influence training outcomes, challenging stereotypes that older employees struggle with digital tools. In contrast, employees across age groups achieve comparable levels of success and satisfaction.

However, seniority emerges as a relevant factor. The study finds a negative relationship between job experience and training success, suggesting that more experienced employees may benefit less from VR environments. This effect is consistent across genders. A possible explanation is that experienced employees rely more on established routines, making adaptation to new learning formats more difficult.

Additionally, the duration of VR training does not significantly impact success or satisfaction, suggesting that effectiveness depends more on training design than on time spent.

Overall, the study challenges preconceived notions about VR training, showing it can provide an inclusive learning environment where employees with diverse profiles achieve similar outcomes.

From a practical perspective, these findings offer insights for Learning & Development professionals. Training programs should prioritize inclusivity while considering job-related factors such as seniority.

Finally, although this study contributes to the literature, its findings should be interpreted within its context. Future research should replicate this analysis in different industries and use more controlled designs to validate and generalize the results.

Author contribution

Belén Díaz Díaz: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Methodology, Investigation, Project Administration, Resouces, Supervision, Validation, Visualization, Writing – original draft, Writing – Review & Editing. Rebeca García-Ramos: Conceptualization, Data Curation, Formal Analysis, Methodology, Investigation, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – Review & Editing. Sandro Arrufat Martín: Visualization, Writing – review & editing. All authors have read and agreed to the published version of the manuscript.

Conflict of interests

No conflict of interest to declare.

Acknowledgments

We would like to acknowledge UCEIF Foundation for financial support to accomplish this research. The VR training analysed in this research was awarded the prize to the best training experience in 2023 by GREF (Group of training and development CEOs in financial entities and insurance companies).

Ethics committee

An ethics self-assessment was conducted in accordance with the University of Cantabria guidelines. The assessment concluded that formal review and approval by the Research Projects Ethics Committee (CEPI) were not required for this study.

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