Skip to main content
SpringerLink
Log in

How do autonomy and learner characteristics combine to influence learners’ learning outcomes and cognitive load in virtual reality learning environments? A fuzzy-set qualitative comparative analysis approach

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

Virtual reality learning environment (VRLE), which allow students to transcend time and space and provide them with a sense of immersion, is becoming more common in education. Although many studies have explored the effects of VRLE on learners’ learning outcomes as well as learning experiences, the results of these studies indicate that the effects of VRLE on learning outcomes and cognitive load are mixed. This is influenced by multiple factors that can be broadly grouped into two categories: learner characteristics and VRLE features. This study aimed to investigate how the autonomy of VRLE and learner characteristics affect learning in the VRLE. 94 volunteered students (aged 18 to 26) were randomly assigned to a high-autonomy VRLE (N = 47) or a low-autonomy VRLE (N = 47). We did a fuzzy-set qualitative comparative analysis (fsQCA) and discovered that VRLE is not good for all students but only for those with particular features. According to the findings, teachers should personalize their use of instructional technology depending on the profiles of their students.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

The collected and analyzed data during the current study are available from the corresponding author on reasonable request.

References

  • Albus, P., Vogt, A., & Seufert, T. (2021). Signaling in virtual reality influences learning outcome and cognitive load. Computers & Education, 166, 104154. https://doi.org/10.1016/j.compedu.2021.104154

  • Antón-Sancho, Á., Vergara, D., Fernández-Arias, P., & Ariza-Echeverri, E. A. (2022). Didactic use of virtual reality in colombian universities: Professors’ perspective. Multimodal Technologies and Interaction, 6(5), 38. https://doi.org/10.3390/mti6050038

    Article  Google Scholar 

  • Blascovich, J., Loomis, J., Beall, A. C., Swinth, K. R., Hoyt, C. L., & Bailenson, J. N. (2002). TARGET ARTICLE: Immersive virtual environment technology as a methodological tool for social psychology. Psychological Inquiry, 13(2), 103–124. https://doi.org/10.1207/S15327965PLI1302_01

    Article  Google Scholar 

  • Brown, M., McCormack, M., Reeves, J., Brook, D. C., Grajek, S., Alexander, B., Bali, M., Bulger, S., Dark, S., Engelbert, N., Gannon, K., Gauthier, A., Gibson, D., Gibson, R., Lundin, B., Veletsianos, G., & Weber, N. (2020). 2020 Educause horizon report teaching and learning edition. Louisville, CO: EDUCAUSE. Retrieved October 12, 2023 from https://www.learntechlib.org/p/215670/

  • Chan, C. S., Bogdanovic, J., & Kalivarapu, V. (2022). Applying immersive virtual reality for remote teaching architectural history. Education and Information Technologies, 27(3), 4365–4397. https://doi.org/10.1007/s10639-021-10786-8

    Article  Google Scholar 

  • Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332.

    Article  Google Scholar 

  • Chang, H. Y., Liang, J. C., & Tsai, C. C. (2020). Students’ context-specific epistemic justifications, prior knowledge, engagement, and socioscientific reasoning in a mobile augmented reality learning environment. Journal of Science Education and Technology, 29(3), 399–408. https://doi.org/10.1007/s10956-020-09825-9

    Article  Google Scholar 

  • Chen, A. P., Darst, W., & Pangrazi, R. P. (1999). What constitutes situational interest? Validating a construct in physical education. Measurement in Physical Education and Exercise Science, 3(3), 157–180. https://doi.org/10.1207/s15327841mpee0303_3

  • Chen, G., Ma, F., Jiang, Y., & Liu, R. (2018). Virtual reality interactive teaching for Chinese traditional Tibetan clothing. Art Design & Communication in Higher Education, 17(1), 51–59.

    Article  Google Scholar 

  • Cheng, K. H. (2017). Reading an augmented reality book: An exploration of learners’ cognitive load, motivation, and attitudes. Australasian Journal of Educational Technology, 33(4).

  • Crosier, J. K., Cobb, S. V., & Wilson, J. R. (2000). Experimental comparison of virtual reality with traditional teaching methods for teaching radioactivity. Education and Information Technologies, 5, 329–343.

    Article  Google Scholar 

  • Cuesta Cambra, D. U., & Mañas Viniegra, L. (2016). Integración de la realidad virtual inmersiva en los Grados de Comunicación. Revista ICONO14. Revista científica de Comunicación y Tecnologías Emergentes, 14(2), 1. https://doi.org/10.7195/ri14.v14i2.953

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Article  Google Scholar 

  • Deci, E. L., & Ryan, R. M. (Eds.). (2004). Handbook of self-determination research. University Rochester Press.

    Google Scholar 

  • Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of Research in Personality, 19(2), 109–134.

    Article  Google Scholar 

  • Deci, E. L., & Ryan, R. M. (2013). Intrinsic motivation and self-determination in human behavior. Springer Science and Business Media.

    Google Scholar 

  • Demitriadou, E., Stavroulia, K. E., & Lanitis, A. (2020). Comparative evaluation of virtual and augmented reality for teaching mathematics in primary education. Education and Information Technologies, 25(1), 381–401. https://doi.org/10.1007/s10639-019-09973-5

    Article  Google Scholar 

  • DeSanctis, G., & Poole, M. S. (1994). Capturing the complexity in advanced technology use: Adaptive structuration theory. Organization Science, 5(2), 121–147. https://doi.org/10.1287/orsc.5.2.121

    Article  Google Scholar 

  • Duncan, I., Miller, A., & Jiang, S. (2012). A taxonomy of virtual worlds usage in education: A taxonomy of virtual worlds usage in education. British Journal of Educational Technology, 43(6), 949–964. https://doi.org/10.1111/j.1467-8535.2011.01263.x

    Article  Google Scholar 

  • Endres, T., Lovell, O., Morkunas, D., Rieß, W., & Renkl, A. (2022). Can prior knowledge increase task complexity? – Cases in which higher prior knowledge leads to higher intrinsic cognitive load. British Journal of Educational Psychology, bjep.12563. https://doi.org/10.1111/bjep.12563

  • Gajendran, R. S., & Harrison, D. A. (2007). The good, the bad, and the unknown about telecommuting: Meta-analysis of psychological mediators and individual consequences. Journal of Applied Psychology, 92(6), 1524–1541. https://doi.org/10.1037/0021-9010.92.6.1524

    Article  Google Scholar 

  • Großmann, N., & Wilde, M. (2020). Promoting interest by supporting learner autonomy: The effects of teaching behaviour in biology lessons. Research in Science Education, 50(5), 1763–1788. https://doi.org/10.1007/s11165-018-9752-5

    Article  Google Scholar 

  • Hamilton, D., McKechnie, J., Edgerton, E., & Wilson, C. (2021). Immersive virtual reality as a pedagogical tool in education: A systematic literature review of quantitative learning outcomes and experimental design. Journal of Computers in Education, 8(1), 1–32. https://doi.org/10.1007/s40692-020-00169-2

    Article  Google Scholar 

  • Han, J., Liu, G., & Zheng, Q. (2023). Prior knowledge as a moderator between signaling and learning performance in immersive virtual reality laboratories. Frontiers in Psychology, 14, 1118174. https://doi.org/10.3389/fpsyg.2023.1118174

    Article  Google Scholar 

  • Harackiewicz, J. M., Smith, J. L., & Priniski, S. J. (2016). Interest matters: The importance of promoting interest in education. Policy Insights from the Behavioral and Brain Sciences, 3(2), 220–227.

    Article  Google Scholar 

  • Harrington, C. M., Kavanagh, D. O., Ballester, W., Wright Ballester, G., Dicker, A., Traynor, P., Hill, O., & Tierney, S. (2018). 360° operative videos: A randomised cross-over study evaluating attentiveness and information retention. Journal of Surgical Education, 75(4), 993–1000. https://doi.org/10.1016/j.jsurg.2017.10.010

    Article  Google Scholar 

  • Haryana, M. R. A., Warsono, S., Achjari, D., & Nahartyo, E. (2022). Virtual reality learning media with innovative learning materials to enhance individual learning outcomes based on cognitive load theory. The International Journal of Management Education, 20(3)

  • Hauptman, H., & Cohen, A. (2011). The synergetic effect of learning styles on the interaction between virtual environments and the enhancement of spatial thinking. Computers & Education, 57(3), 2106–2117. https://doi.org/10.1016/j.compedu.2011.05.008

    Article  Google Scholar 

  • Howard, M. C., & Lee, J. (2020). Pre-training interventions to counteract seductive details in virtual reality training programs. Human Resource Development Quarterly, 31(1), 13–29.

    Article  Google Scholar 

  • Hsieh, Y. H., & Tsai, C. C. (2014). Students’ scientific epistemic beliefs, online evaluative standards, and online searching strategies for science information: The moderating role of cognitive load experience. Journal of Science Education and Technology, 23, 299–308.

    Article  Google Scholar 

  • Hu, P. J. H., Hu, H. F., & Fang, X. (2017). Examining the mediating roles of cognitive load and performance outcomes in user satisfaction with a website. MIS Quarterly, 41(3), 975–A11.

  • Huang, C. L., Luo, Y. F., Yang, S. C., Lu, C. M., & Chen, A. S. (2020). Influence of students’ learning style, sense of Presence, and cognitive load on learning outcomes in an immersive virtual reality learning environment. Journal of Educational Computing Research, 58(3), 596–615. https://doi.org/10.1177/0735633119867422

    Article  Google Scholar 

  • Huang, W. (2020). Investigating the novelty effect in virtual reality on stem learning (Doctoral dissertation, Arizona State University).

  • Hughes, M., Cesinger, B., Cheng, C. F., Schuessler, F., & Kraus, S. (2019). A configurational analysis of network and knowledge variables explaining born globals’ and late internationalizing SMEs’ international performance. Industrial Marketing Management, 80, 172–187. https://doi.org/10.1016/j.indmarman.2017.12.001

    Article  Google Scholar 

  • Johnson-Glenberg, M. C., Bartolomea, H., & Kalina, E. (2021). Platform is not destiny: Embodied learning effects comparing 2D desktop to 3D virtual reality STEM experiences. Journal of Computer Assisted Learning, 37(5), 1263–1284. https://doi.org/10.1111/jcal.12567

    Article  Google Scholar 

  • Jung, Y. (2011). Understanding the role of sense of presence and perceived autonomy in users’ continued use of social virtual worlds. Journal of Computer-Mediated Communication, 16(4), 492–510. https://doi.org/10.1111/j.1083-6101.2011.01540.x

    Article  Google Scholar 

  • Koch, M., von Luck, K., Schwarzer, J., & Draheim, S. (2018). The novelty effect in large display deployments–Experiences and lessons-learned for evaluating prototypes. In Proceedings of 16th European conference on computer-supported cooperative work-exploratory papers. European Society for Socially Embedded Technologies (EUSSET).

  • Kraus, S., Ribeiro-Soriano, D., & Schüssler, M. (2018). Fuzzy-set qualitative comparative analysis (fsQCA) in entrepreneurship and innovation research–the rise of a method. International Entrepreneurship and Management Journal, 14, 15–33.

    Article  Google Scholar 

  • Larmuseau, C., Evens, M., Elen, J., Van Den Noortgate, W., Desmet, P., & Depaepe, F. (2018). The relationship between acceptance, actual use of a virtual learning environment and performance: An ecological approach. Journal of Computers in Education, 5(1), 95–111. https://doi.org/10.1007/s40692-018-0098-9

    Article  Google Scholar 

  • Lin, H. C. S., Yu, S. J., Sun, J. C. Y., & Jong, M. S. Y. (2021). Engaging university students in a library guide through wearable spherical video-based virtual reality: Effects on situational interest and cognitive load. Interactive Learning Environments, 29(8), 1272–1287. https://doi.org/10.1080/10494820.2019.1624579

    Article  Google Scholar 

  • Ling, Y., Zhu, P., & Yu, J. (2021). Which types of learners are suitable for augmented reality? A fuzzy set analysis of learning outcomes configurations from the perspective of individual differences. Educational Technology Research and Development, 69, 2985–3008.

    Article  Google Scholar 

  • Liu, Q. T., Liu, B. W., & Lin, Y. R. (2019). The influence of prior knowledge and collaborative online learning environment on students’ argumentation in descriptive and theoretical scientific concept. International Journal of Science Education, 41(2), 165–187.

    Article  Google Scholar 

  • Liu, J., Liu, Q., Yu, S., Ma, J., Liu, M., & Wu, L. (2022, May). Which types of learners are suitable for the virtual reality environment: A fsQCA approach. In 2022 8th International Conference of the Immersive Learning Research Network (iLRN) (pp. 1–5). IEEE.

  • Makransky, G., & Petersen, G. B. (2021). The cognitive affective model of immersive learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educational Psychology Review, 33(3), 937–958. https://doi.org/10.1007/s10648-020-09586-2

    Article  Google Scholar 

  • Makransky, G., Terkildsen, T. S., & Mayer, R. E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225–236. https://doi.org/10.1016/j.learninstruc.2017.12.007

    Article  Google Scholar 

  • Marraffino, M. D., Johnson, C. I., and Garibaldi, A. E. (2022). Virtual reality is better than desktop for training a spatial knowledge task, but not for everyone. In J. Y. C. Chen & G. Fragomeni (Eds.), Virtual, augmented and mixed reality: design and development (Vol. 13317, pp. 212–223). Springer International Publishing. https://doi.org/10.1007/978-3-031-05939-1_14

  • Martín-Gutiérrez, J., Mora, C. E., Añorbe-Díaz, B., & González-Marrero, A. (2017). Virtual technologies Trends in education. EURASIA Journal of Mathematics Science and Technology Education, 13(2), https://doi.org/10.12973/eurasia.2017.00626a

  • Maxwell, J. P., Masters, R. S. W., & Eves, F. F. (2003). The role of working memory in motor learning and performance. Consciousness and Cognition, 12(3), 376–402. https://doi.org/10.1016/S1053-8100(03)00005-9

    Article  Google Scholar 

  • Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94(3), 598–610. https://doi.org/10.1037/0022-0663.94.3.598

    Article  Google Scholar 

  • Moreno, R., & Mayer, R. E. (2005). Role of guidance, reflection, and interactivity in an agent-based multimedia game. Journal of Educational Psychology, 97(1), 117–128.

    Article  Google Scholar 

  • Niemiec, C. P., & Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom: Applying self-determination theory to educational practice. Theory and Research in Education, 7(2), 133–144.

    Article  Google Scholar 

  • Nowlan, N., Arya, A., Qorbani, H. S., & Abdinejad, M. (2023). Higher-order thinking skills assessment in 3D virtual learning environments using motifs and expert data. Computers & Education: X Reality, 2, 100012.

    Google Scholar 

  • Olufadi, Y. (2015). A configurational approach to the investigation of the multiple paths to success of students through mobile phone use behaviors. Computers & Education, 86, 84–104. https://doi.org/10.1016/j.compedu.2015.03.005

    Article  Google Scholar 

  • Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4.

    Article  Google Scholar 

  • Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set qualitative comparative analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58, 102310. https://doi.org/10.1016/j.ijinfomgt.2021.102310

    Article  Google Scholar 

  • Parong, J., & Mayer, R. E. (2018). Learning science in immersive virtual reality. Journal of Educational Psychology, 110(6), 785–797. https://doi.org/10.1037/edu0000241

    Article  Google Scholar 

  • Petersen, G. B., Petkakis, G., & Makransky, G. (2022). A study of how immersion and interactivity drive VR learning. Computers & Education, 179, 104429. https://doi.org/10.1016/j.compedu.2021.104429

    Article  Google Scholar 

  • Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ).

  • Ragin, C. C., & Davey, S. (2016). Fuzzy-set/qualitative comparative analysis (Version 3.0)[Computer software]. Department of Sociology, University of California.

  • Ragin, C. C. (2000). Fuzzy-set social science. University of Chicago Press.

    Google Scholar 

  • Ragin, C. C. (2008). Redesigning social inquiry: Fuzzy sets and beyond. University of Chicago Press.

    Book  Google Scholar 

  • Refat, N., Kassim, H., & Rahman, M. A. (2020). A cognitive approach-based instructional design for managing cognitive load and improving learning outcome. 2020 Emerging Technology in Computing, Communication and Electronics (ETCCE), 1–6. https://doi.org/10.1109/ETCCE51779.2020.9350864

  • Richards, D., & Taylor, M. (2015). A comparison of learning gains when using a 2D simulation tool versus a 3D virtual world: An experiment to find the right representation involving the marginal value Theorem. Computers & Education, 86, 157–171. https://doi.org/10.1016/j.compedu.2015.03.009

    Article  Google Scholar 

  • Romine, W., Tsai, C. L., Miller, M., Tang, N. E., & Folk, W. (2020). Evaluation of a process by which individual interest supports learning within a formal middle school classroom context. International Journal of Science and Mathematics Education, 18(7), 1419–1439. https://doi.org/10.1007/s10763-019-10032-1

    Article  Google Scholar 

  • Rotgans, J. I., & Schmidt, H. G. (2014). Situational interest and learning: Thirst for knowledge. Learning and Instruction, 32, 37–50.

    Article  Google Scholar 

  • Ryan, R. M., & Patrick, H. (2009). Self-determination theory and physical. Hellenic Journal of Psychology, 6(2), 107–124.

    Google Scholar 

  • Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: A self-determination theory approach. Motivation and Emotion, 30(4), 344–360. https://doi.org/10.1007/s11031-006-9051-8

    Article  Google Scholar 

  • Sagnier, C., Loup-Escande, E., & Valléry, G. (2020). Effects of gender and prior experience in immersive user experience with virtual reality. In T. Ahram & C. Falcão (Eds.), Advances in usability and user experience (Vol. 972, pp. 305–314). Springer International Publishing. https://doi.org/10.1007/978-3-030-19135-1_30

  • Schutte, N. S. (2020). The impact of virtual reality on curiosity and other positive characteristics. International Journal of Human–Computer Interaction, 36(7), 661–668.

    Article  Google Scholar 

  • Seufert, T., Jänen, I., & Brünken, R. (2007). The impact of intrinsic cognitive load on the effectiveness of graphical help for coherence formation. Computers in Human Behavior, 23(3), 1055–1071. https://doi.org/10.1016/j.chb.2006.10.002

    Article  Google Scholar 

  • Shen, B., Chen, A., & Guan, J. (2007). Using achievement goals and interest to predict learning in physical education. The Journal of Experimental Education, 75(2), 89–108.

    Article  Google Scholar 

  • Shin, E. C., Schallert, D. L., & Savenye, W. C. (1994). Effects of learner control, advisement, and prior knowledge on young students’ learning in a hypertext environment. Educational Technology Research and Development, 42(1), 33–46. https://doi.org/10.1007/BF02298169

    Article  Google Scholar 

  • Smith, S. J., Farra, S. L., Ulrich, D. L., Hodgson, E., Nicely, S., & Mickle, A. (2018). Effectiveness of two varying levels of virtual reality simulation. Nursing Education Perspectives, 39(6), E10–E15. https://doi.org/10.1097/01.NEP.0000000000000369

    Article  Google Scholar 

  • Stepan, K., Zeiger, J., Hanchuk, S., Del Signore, A., Shrivastava, R., Govindaraj, S., & Iloreta, A. (2017). Immersive virtual reality as a teaching tool for neuroanatomy: Immersive VR as a neuroanatomy teaching tool. International Forum of Allergy & Rhinology, 7(10), 1006–1013. https://doi.org/10.1002/alr.21986

    Article  Google Scholar 

  • Su, J., Yang, W., & Zhong, Y. (2023). Influences of gender and socioeconomic status on children’s use of robotics in early childhood education: A systematic review. Early Education and Development, 34(4), 910–926.

    Article  Google Scholar 

  • Sweller, J., Van Merrienboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10, 251–296. https://doi.org/10.1023/A:1022193728205

  • Tai, K. H., Hong, J. C., Tsai, C. R., Lin, C. Z., & Hung, Y. H. (2022). Virtual reality for car-detailing skill development: Learning outcomes of procedural accuracy and performance quality predicted by VR self-efficacy, VR using anxiety, VR learning interest and flow experience. Computers & Education, 182, 104458.

    Article  Google Scholar 

  • Taylor, G., Singer, M. J., & Jerome, C. J. (2009). Development and evaluation of the game-based performance assessment battery (GamePAB) and game experience measure (GEM). In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 53, No. 27, pp. 2014–2018). SAGE Publications.

  • Thompson, M., Tutwiler, M. S., & Bressler, D. (2020). Beyond the novelty effect–examining learning affordances of XR educational technologies in STEM conceptual understanding and skill development. Association Research Science Teaching, 25(2020), 1–11.

  • van Kesteren, M. T. R., Ruiter, D. J., Fernández, G., & Henson, R. N. (2012). How schema and novelty augment memory formation. Trends in Neurosciences, 35(4), 211–219. https://doi.org/10.1016/j.tins.2012.02.001

    Article  Google Scholar 

  • Villena Taranilla, R., Cózar-Gutiérrez, R., González-Calero, J. A., & López Cirugeda, I. (2022). Strolling through a city of the Roman Empire: An analysis of the potential of virtual reality to teach history in primary education. Interactive Learning Environments, 30(4), 608–618. https://doi.org/10.1080/10494820.2019.1674886

    Article  Google Scholar 

  • Villena-Taranilla, R., Tirado-Olivares, S., Cózar-Gutiérrez, R., & González-Calero, J. A. (2022). Effects of virtual reality on learning outcomes in K-6 education: A meta-analysis. Educational Research Review, 35, 100434. https://doi.org/10.1016/j.edurev.2022.100434

    Article  Google Scholar 

  • Whitelock, D., Romano, D., Jelfs, A., & Brna, P. (2000). Perfect presence: What does this mean for the design of virtual learning environments? Education and Information Technologies, 5, 277–289. https://doi.org/10.1023/A:1012001523715

    Article  Google Scholar 

  • Woodside, A. G., Ko, E., & Huan, T. (T. C. ). (2012). The new logic in building isomorphic theory of management decision realities. Management Decision, 50(5), 765–777. https://doi.org/10.1108/00251741211227429

  • Yu, S., Liu, Q., Johnson-Glenberg, M. C., Han, M., Ma, J., Ba, S., & Wu, L. (2023). Promoting musical instrument learning in virtual reality environment: Effects of embodiment and visual cues. Computers & Education, 198, 104764.

  • Zhang, L., & Liu, G. (2023). A review of factors affecting cognitive load in immersive virtual learning environment. 2023 IEEE 12th International Conference on Educational and Information Technology (ICEIT), 48–52. https://doi.org/10.1109/ICEIT57125.2023.10107848

  • Zhao, J., Lin, L., Sun, J., & Liao, Y. (2020). Using the summarizing strategy to engage learners: Empirical evidence in an immersive virtual reality environment. The Asia-Pacific Education Researcher, 29(5), 473–482. https://doi.org/10.1007/s40299-020-00499-w

    Article  Google Scholar 

  • Zheng, J., Wu, C. Z., Li, F., & Li, J. (2021). Research status of the application of virtual reality technology on self-efficacy. 2021 3rd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI), 608–611.https://doi.org/10.1109/MLBDBI54094.2021.00121

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (No. 62277021 and No. 62277029), Humanities and Social Sciences Research Project of the Ministry of Education of China (No. 22YJAZH067), and Fundamental Research Funds for the Central Universities (No. CCNU22JC011).

Author information

Authors and Affiliations

  1. Faculty of Artificial Intelligence Education, Central China Normal University, Wuhan, China

    Jiaxu Liu, Qingtang Liu, Shufan Yu, Jingjing Ma & Linjing Wu

  2. Hubei Research Center for Educational Informationization, Central China Normal University, Wuhan, China

    Jiaxu Liu, Qingtang Liu, Shufan Yu, Jingjing Ma & Linjing Wu

  3. Hongxing Experimental School, Shenzhen, Guangdong, China

    Mengfan Liu

Authors
  1. Jiaxu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qingtang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shufan Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jingjing Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Mengfan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Linjing Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jiaxu Liu or Qingtang Liu.

Ethics declarations

Competing interests

There is no competing interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Liu, Q., Yu, S. et al. How do autonomy and learner characteristics combine to influence learners’ learning outcomes and cognitive load in virtual reality learning environments? A fuzzy-set qualitative comparative analysis approach. Educ Inf Technol 29, 77–101 (2024). https://doi.org/10.1007/s10639-023-12262-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-023-12262-x

Keywords

Search

Navigation