¿Influye el género en la satisfacción con la formación en Realidad Virtual y en su éxito en el sector financiero?
Barra lateral del artículo
Contenido principal del artículo
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.
Descargas
Métricas
Detalles del artículo
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Esta obra está bajo una licencia de Creative Commons Reconocimiento 4.0 Internacional.
Citas
Abich IV, Julian; Parker, Jason; Murphy, Jennifer S.; & Eudy, Morgan Eudy. (2021). A review of the evidence for training effectiveness with virtual reality technology. Virtual Reality, 25(4), 919–933. https://doi.org/10.1007/s10055-020-00498-8
Ackerman, Phillip; Bowen, Kristy; Beier, Margaret; & Kanfer, Ruth. (2001). Determinants of individual differences and gender differences in knowledge. Journal of Educational Psychology, 93(4), 797–825. https://doi.org/10.1037/0022-0663.93.4.797
Alghamdi, Ahlam.; Karpinski, Aryn; Lepp, Andrew; & Barkley, Jacob. (2020). Online and face-to-face classroom multitasking and academic performance: Moderated mediation with self-efficacy for self-regulated learning and gender. Computers in Human Behavior, 102, 214–222. https://doi.org/10.1016/j.chb.2019.08.018
Allen, Brian; Hanley, Taylor; Rokers, Bas; & Green, Shawn. (2016). Visual 3D motion acuity predicts discomfort in 3D stereoscopic environments. Entertain. Comput., 13, 1–9. https://doi.org/10.1016/j.entcom.2016.01.001
Annetta, Leonard; Mangrum, Jennifer; Holmes, Shawn; Collazo, Kimberly; & Cheng, Meng-Tzu. (2009). Bridging realty to virtual reality: Investigating gender effect and student engagement on learning through video game play in an elementary school classroom. International Journal of Science Education, 31(8), 1091–1113. https://doi.org/10.1080/09500690801968656
Baraybar-Fernández, Antonio; Arrufat-Martín, Sandro; & Arrufat-Reboso, Eduardo. (2025). ClosingGap: Driving social change in gender equality. European Research on Management and Business Economics, 31, 100263. https://doi.org/10.1016/j.iedeen.2024.100263
Bausch, Sonja; Michel, Alexandra.; & Sonntag, Karlheinz. (2014). How gender influences the effect of age on self-efficacy and training success. International Journal of Training and Development, 18, 3, 171-187. https://doi.org/10.1111/ijtd.12027
Beier, Margaret; & Ackerman, Phillip. (2005). Age, ability, and the role of prior knowledge on the acquisition of new domain knowledge: promising results in a real-world learning environment. Psychology and Aging, 20(2), 341–55.
Biocca, Frank. (1992). Will simulation sickness slow down the diffusion of virtual environment technology? Presence, 1, 334–343. https://doi.org/10.1162/pres.1992.1.3.334
Britner, Shari; & Pajares, Frank. (2001). Self-efficacy beliefs, motivation, race, and gender in middle school science. J. Women Minor. Sci. Eng., 7, 271–285. https://doi.org/10.1615/JWomenMinorScienEng.v7.i4.10
Caprara, Gian Vittorio; Caprara, Mariagiovanna; & Steca, Patrizia. (2003). Personality’s correlates of adult development and aging. European Psychologist, 8(3), 131–47.
Colley, Ann; & Comber, Chris. (2003). Age and gender differences in computer use and attitudes among secondary school students: what has changed? Educ. Res., 45, 155–165. https://doi.org/10.1080/0013188032000103235
Colquitt, Jason; LePine, Jeffrey; & Noe, Raymond. (2000). Toward an integrative theory of training motivation: a meta-analytic path analysis of 20 years of research. Journal of Applied Psychology, 85(5), 678–707. https://doi.org/10.1037/0021-9010.85.5.678
Cuadrado-García, Manuel; Ruiz-Molina, María Eugenia; & Montoro-Pons, Juan. (2010). Are there gender differences in e-learning use and assessment? Evidence from an interuniversity online project in Europe. Proc. Soc. Behav. Sci., 2, 367–371. https://doi.org/10.1016/j.sbspro.2010.03.027
Czerwinski, Mary; Tan, Desney; & Robertson, George. (2002). “Women take a wider view”. En Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Minnesota). 195–202. https://doi.org/10.1145/503376.503412
Drabowicz, Tomasz. (2014). Gender and digital usage inequality among adolescents: a comparative study of 39 countries. Comput. Educ., 74, 98–111. https://doi.org/10.1016/j.compedu.2014.01.016
Duzmanska, Natalia; Strojny, Pawet; & Strojny, Agnieszka. (2018). Can simulator sickness be avoided? A review on temporal aspects of simulator sickness. Front. Psychol., 9, 2132. https://doi.org/10.3389/fpsyg.2018.02132
Dwyer, Carol; & Johnson, Linda. (1997). Grades, Accomplishments, and Correlates. En W. W. Willingham & N. S. Cole (Eds.), Gender and Fair Assessment (Mahwah, NJ: Lawrence Erlbaum Associates), pp. 127–56. https://doi.org/10.1016/j.compedu.2014.01.016
Gamito, Pedro; Oliveira, Jorge; & Santos, Paulo. (2008). Presence, immersion and cybersickness assessment through a test anxiety virtual environment. Ann. Rev. Cyberther. Telemed., 6, 83–90.
Giammarco, Erica; Schneider, Travis; Carswell, Julie; & Knipe, William. (2015). Video game preferences and their relation to career interests. Pers. Individ Differ., 73, 98–104. https://doi.org/10.1016/j.paid.2014.09.036.
Grassini, Simone; & Laumann, Karin. (2020). Are Modern Head-Mounted Displays Sexist? A Systematic Review on Gender Differences in HMD-Mediated Virtual Reality. Front. Psychol., 11, 1604. https://doi.org/10.3389/fpsyg.2020.01604
Grassini, Simone; Laumann, Karine; & Rasmussen Skogstad, Martin. (2020). The Use of Virtual Reality Alone Does Not Promote Training Performance (but Sense of Presence Does). Front. Psychol., 11, 1743. https://doi.org/10.3389/fpsyg.2020.01743
Harvey, Lea; Parahoo, Sanjai; & Santally, Mohammad. (2017). Should gender differences be considered when assessing student satisfaction in the online learning environment for millennials? Higher Education Quarterly, 71(2), 141–158. https://doi.org/10.1111/hequ.12116
Hertzog, Cristopher; Kramer, Arthur; Wilson, Robert; & Lindenberger, Ulman. (2008). Enrichment effects on adult cognitive development: can the functional capacity of older adults be preserved and enhanced? Psychological Science in the Public Interest, 9(1), 1–65. https://doi.org/10.1111/j.1539-6053.2009.01034.x
Huang, Hsinfu; Lin, Chiaying; & Cai, Dengchuan. (2020). Enhancing the learning effect of virtual reality 3D modeling: A new model of learner’s design collaboration and a comparison of its field system usability. Universal Access in the Information Society. https://doi.org/10.1007/s10209-020-00750-7
Hung, Min-Ling; Chou, Chien; Chen, Chao Hsiu; & Own, Zang Yuan. (2010). Learner readiness for online learning: scale development and student perceptions. Comput. Educ., 55, 1080–1090. https://doi.org/10.1016/j.compedu.2010.05.004
Jarvelainen, Monica; Cooper, Simon; & Jones, Janet. (2018). Nursing students’ educational experience in regional Australia: Reflections on acute events. A qualitative review of clinical incidents. Nurse Education in Practice, 31, 188–193. https://doi.org/10.1016/j.nepr.2018.06.007
Kayany, J. M.; & Yelsma, P. (2000). Displacement Effects of Online Media in the Socio-Technical Contexts of Households. Journal of Broadcasting & Electronic Media, 44(2), 215–229. https://doi.org/10.1207/s15506878jobem4402_4
Kennedy, Robert; Lane, Norman; Berbaum, Kevin; & Lilienthal, Michael. (1993). Simulator sickness questionnaire: An enhanced method for quantifying simulator sickness. Int. J. Aviat. Psychol., 3, 203–220. https://doi.org/10.3389/fpsyg.2022.931955
Kolasinski, Eugenia. (1995). Simulator Sickness in Virtual Environments, Vol. 1027. US Army Research Institute for the Behavioral and Social Sciences. https://doi.org/10.21236/ADA295861
Korlat, Selma; Kollmayer, Marlene; Holzer, Julia; Lüftenegger, Marko; Pelikan, Rosa; Schober, Bárbara; & Spiel, Christiane. (2021). Gender Differences in Digital Learning During COVID-19: Competence Beliefs, Intrinsic Value, Learning Engagement, and Perceived Teacher Support. Front. Psychol., 12. https://doi.org/10.3389/fpsyg.2021.637776
Kubeck, Jean; Delp, Norma; Haslett, Tammy; & McDaniel, Michael. (1996). Does job-related training performance decline with age? Psychology and Aging, 11(1), 92–107. https://doi.org/10.1037/0882-7974.11.1.92
Latu, Ioana; Mast, Marianne; Bombari, Dario; Lammers, Joris; & Hoyt, Crystal. (2019). Empowering mimicry: Female leader role models empower women in leadership tasks through body posture mimicry. Sex Roles, 80, 11–24. https://doi.org/10.1007/s11199-018-0911-y
Li, Nai; & Kirkup, Gill. (2007). Gender and cultural differences in Internet use: a study of China and the UK. Comput. Educ., 48, 301–317. https://doi.org/10.1016/j.compedu.2005.01.007
Liang, Hai-Ning; Lu, Feiyu; Shi, Yuwei; Nanjappan, Vijayakumar; & Papangelis, Konstantinos. (2019). Evaluating he effects of collaboration and competition in navigation tasks and spatial knowledge acquisition within virtual reality environments. Futur. Gener. Comput. Syst., 95, 855–866. https://doi.org/10.1016/j.future.2018.02.029
Lu, His; & Chiou, Ming-Jen. (2010). The impact of individual differences on e-learning system satisfaction: a contingency approach. Brit. J. Educ. Technol., 41, 307–323. https://doi.org/10.1111/j.1467-8535.2009.00937.x
Makowski, Dominique; Sperduti, Marco; Nicolas, Serge; & Piolino, Pascale. (2017). “Being there” and remembering it: presence improves memory encoding. Conscious. Cogn., 53, 194–202. https://doi.org/10.1016/j.concog.2017.06.015
Makransky, Guido; Terkildsen, Thomas; & Mayer, Richard. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learn. Instr., 60, 225–236. https://doi.org/10.1016/j.learninstruc.2017.12.007
McSporran, Mae; & Young, Stuart. (2001). Does gender matter in online learning? Res. Learn. Technol., 9, 3–15. https://doi.org/10.1080/0968776010090202
Mucherah, Mucherah. (2003). The influence of technology on the classroom climate of social studies classrooms: a multidimensional approach. Learn. Environ. Res., 6, 37–57. https://doi.org/10.1023/A:1022903609290
Munafo, Justin; Diedrick, Meg; & Stoffregen, Thomas. (2017). The virtual reality head-mounted display Oculus Rift induces motion sickness and is sexist in its effects. Exp. Brain Res., 235, 889–901. https://doi.org/10.1007/s00221-016-4846-7
Nistor, Nicolae. (2013). Stability of attitudes and participation in online university courses: Gender and location effects. Computers & Education, 68, 284–292. https://doi.org/10.1016/j.compedu.2013.05.016
Perkowski, Justine. (2013). The role of gender in distance learning: a meta-analytic review of gender differences in academic performance and self-efficacy in distance learning. J. Educ. Technol. Syst., 41, 267–278. https://doi.org/10.2190/ET.41.3.e
Price, Linda. (2006). Gender differences and similarities in online courses: challenging stereotypical views of women. J. Comp. Assist. Learn., 22, 349–359. https://doi.org/10.1111/j.1365-2729.2006.00181.x
Richardson, John; & Woodley, Alan. (2003). Another look at the role of age, gender and subject as predictors of academic attainment in higher education. Studies in Higher Education, 28(4), 475–493. https://doi.org/10.1080/0307507032000122305
Smutny, Pavel. (2022). Learning with virtual reality: A market analysis of educational and training applications. Interactive Learning Environments, 1–14. https://doi.org/10.1080/10494820.2022.2028856
Spinath, Birgit; Eckert, Christine; & Steinmayr, Ricarda. (2014). Gender differences in school success: what are the roles of students’ intelligence, personality and motivation? Educational Research, 56(2), 230–243, https://dx.doi.org/10.1080/00131881.2014.898917
Vekiri, Ioanna. (2013). Information science instruction and changes in girls’ and boy’s expectancy and value beliefs: in search of gender-equitable pedagogical practices. Comp. Educ., 64, 104–115. https://doi.org/10.1016/j.compedu.2013.01.011
Vekiri, Ionna; & Chronaki, Anna. (2008). Gender issues in technology use: perceived social support, computer self-efficacy and value beliefs, and computer use beyond school. Comput. Educ., 51, 1392–1404. https://doi.org/10.1016/j.compedu.2008.01.003
Warr, Peter; Allan, Catriona; & Birdi, Kamal. (1999). Predicting three levels of training outcome. Journal of Occupational and Organizational Psychology, 72(3), 351–75. https://doi.org/10.1348/096317999166725
Williamson, Alan. (2000). ‘Gender issues in older adults’ participation in learning: viewpoints and experiences of learners in the university of the third age (U3A). Educational Gerontology, 26(1), 49–66. https://doi.org/10.1080/036012700267394
Yang, Jie Chi; Quadir, Benazir; Chen, Nian-Shing; & Miao, Qiang. (2016). Effects of online presence on learning performance in a blog-based online course. Internet High. Educ., 30, 11–20. https://doi.org/10.1016/j.iheduc.2016.04.002
Yu, Zhonggen. (2021). The effects of gender, educational level, and personality on online learning outcomes during the COVID‑19 pandemic. Int J Educ Technol High Educ, 18(14). https://doi.org/10.1186/s41239-021-00252-3
Yu, Zhonggen. (2023). A meta-analysis of the effect of virtual reality technology use in education. Interactive Learning Environments, 31(8), 4956–4976. https://doi.org/10.1080/10494820.2021.1989466