Skip to main content
SpringerLink
Log in

Educational UTAUT-based virtual reality acceptance scale: a validity and reliability study

  • Original Research
  • Published:
Virtual Reality Aims and scope Submit manuscript

Abstract

This study aims to fill a gap in current research on virtual reality (VR) by developing a valid and reliable educational VR acceptance scale based on the unified theory of acceptance and use of technology (UTAUT) model to measure the level of students’ acceptance and use of VR systems. In three phases, the reliability and validity studies of the scale were performed with a total sample of 440 second, third, and fourth-year undergraduate students studying at various faculties in the 2021–2022 academic year. The face validity and content validity of the scale were examined by obtaining expert opinions. Exploratory factor analysis (EFA) was carried out with the first group of samples (n = 186) and confirmatory factor analysis (CFA) was carried out with the second group of samples (n = 219). After conducting EFA, the scale had four factors with 18 items, explaining 67.62 percent of the total variance. According to CFA, the construct of the 4-factor with 21 items scale had a good fit with the data. Cronbach’s alpha coefficient and test–retest methods reliability coefficient of scale that were calculated to determine the reliability of the measurements were found to be .88 and .89, respectively. The discriminatory power of the items was examined by comparing the participants’ bottom 27 percent and top 27 percent and calculating adjusted item-total correlations. The findings revealed that the educational UTAUT-based virtual reality acceptance scale was a valid and reliable instrument to measure students’ acceptance and use of VR systems.

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

Similar content being viewed by others

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Akbulut Y (2010) Sosyal bilimlerde SPSS uygulamaları [SPSS applications in social sciences]. İdeal Kültür Yayıncılık, İstanbul

    Google Scholar 

  • Al-Emran M, Mezhuyev V, Kamaludin A (2018) Technology acceptance model in m-learning context: a systematic review. Comput Educ 125:1–41

    Google Scholar 

  • Alfadil M (2020) Effectiveness of virtual reality game in foreign language vocabulary acquisition. Comput Educ 153:103893

    Google Scholar 

  • Alshehri A, Rutter MJ, Smith S (2019) An implementation of the UTAUT model for understanding students’ perceptions of learning management systems: a study within tertiary institutions in Saudi Arabia. Int J Distance Edu Technol 17(3):1–24

    Google Scholar 

  • Alwahaishi S, Snásel V (2013) Acceptance and use of information and communications technology: a UTAUT and flow based theoretical model. J Technol Manag Innov 8(2):61–73

    Google Scholar 

  • Bonde MT, Makransky G, Wandall J, Larsen MV, Morsing M, Jarmer H, Sommer MO (2014) Improving biotech education through gamified laboratory simulations. Nat Biotechnol 32(7):694–697

    Google Scholar 

  • Buabeng-Andoh C, Baah C (2020) Pre-service teachers’ intention to use learning management system: an integration of UTAUT and TAM. Interact Technol Smart Edu 17(4):455–473

    Google Scholar 

  • Burdea GC, Coiffet P (2003) Virtual reality technology, 2nd edn. John Wiley & Sons, New York

    Google Scholar 

  • Buyukozturk Ş (2010) Sosyal bilimler için veri analizi el kitabı [The data analysis handbook for social sciences]. Pegem Akademi Yayınları, Ankara

    Google Scholar 

  • Byrne BM (2010) Structural equation modeling with AMOS: Basic concepts, applications and programming. Taylor & Francis, New York, NY

    Google Scholar 

  • Cattell RB (1978) The scientific use of factor analysis in behavioral and life sciences. Plenum, New York, NY

    MATH  Google Scholar 

  • Cokluk Ö, Şekercioğlu G, Büyüköztürk Ş (2012) Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları [Multivariate statistics for the social sciences: SPSS and LISREL applications]. Pegem Akademi Yayıncılık, Ankara

    Google Scholar 

  • Comrey AL, Lee HB (1992) A first course in factor analysis. Erlbaum, Hillsdale, NJ

    Google Scholar 

  • Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13:319–340

    Google Scholar 

  • Davis FD, Bagozzi RP, Warshaw PR (1989) User acceptance of computer technology: a comparison of two theoretical models. Manage Sci 35:982–1003

    Google Scholar 

  • El Beheiry M, Doutreligne S, Caporal C, Ostertag C, Dahan M, Masson JB (2019) Virtual reality: beyond visualization. J Mol Biol 431(7):315–321

    Google Scholar 

  • Erkus A (2012) Psikolojide ölçme ve ölçek geliştirme [Measurement and scale development in psychology]. Pegem Akademi Yayınları, Ankara

    Google Scholar 

  • Fornell C, Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50

    Google Scholar 

  • Fraenkel JR, Wallen NE, Hyun HH (2012) How to design and evaluate research in education. 8th ed. New York, NY: McGraw–Hill.

  • Fransson G, Holmberg J, Westelius C (2020) The challenges of using head mounted virtual reality in K-12 schools from a teacher perspective. Educ Inf Technol 25(4):3383–3404

    Google Scholar 

  • Gadelha R (2018) Revolutionizing education: the promise of virtual reality. Child Educ 94(1):40–43

    Google Scholar 

  • Garone A, Pynoo B, Tondeur J, Cocquyt C, Vanslambrouck S, Bruggeman B, Struyven K (2019) Clustering university teaching staff through UTAUT: implications for the acceptance of a new learning management system. Br J Edu Technol 50(5):2466–2483

    Google Scholar 

  • Granić A, Marangunić N (2019) Technology acceptance model in educational context: a systematic literature review. Br J Edu Technol 50(5):2572–2593

    Google Scholar 

  • Hair JF, Anderson RE, Tatham RL, Grablowsky BJ (1979) Multivariate data analysis. Pipe Books, Tulsa, OK

    Google Scholar 

  • Hanson K, Shelton BE (2008) Design and development of virtual reality: analysis of challenges faced by educators. Educ Technol Soc 11(1):118–131

    Google Scholar 

  • Hooper D, Coughlan J, Mullen MR (2008) Structural equation modelling: guidelines for determining modelfit. Electron J Bus Res Methods 6(1):53–60

    Google Scholar 

  • Hu LT, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structural analysis: conventional criteria versus new alternatives. Struct Equ Model 6(1):1–55

    Google Scholar 

  • Huang HM, Rauch U, Liaw SS (2010) Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Comput Educ 55(3):1171–1182

    Google Scholar 

  • Huang KT, Ball C, Francis J, Ratan R, Boumis J, Fordham J (2019) Augmented versus virtual reality in education: an exploratory study examining science knowledge retention when using augmented reality/virtual reality mobile applications. Cyberpsychol Behav Soc Netw 22(2):105–110

    Google Scholar 

  • Ilhan M, Cetin B (2014) Development of classroom assessment environment scale (CAES): validity and reliability study. Edu Sci. https://doi.org/10.15390/EB.2014.3334

    Article  Google Scholar 

  • Jensen L, Konradsen F (2018) A review of the use of virtual reality head-mounted displays in education and training. Educ Inf Technol 23(4):1515–1529

    Google Scholar 

  • Kamińska D, Sapiński T, Wiak S, Tikk T, Haamer RE, Avots E, Anbarjafari G (2019) Virtual reality and its applications in education: survey. Information 10(10):318

    Google Scholar 

  • Karaoglan-Yilmaz FG, Zhang K, Ustun AB, Yilmaz R (2022) Transactional distance perceptions, student engagement, and course satisfaction in flipped learning: a correlational study. Interact Learn Environ. https://doi.org/10.1080/10494820.2022.2091603

    Article  Google Scholar 

  • Kline RB (1994) An easy guide to factor analysis. Routledge, New York, NY

    Google Scholar 

  • Krokos E, Plaisant C, Varshney A (2019) Virtual memory palaces: immersion aids recall. Virtual Reality 23(1):1–15

    Google Scholar 

  • Macedo IM (2017) Predicting the acceptance and use of information and communication technology by older adults: an empirical examination of the revised UTAUT2. Comput Hum Behav 75:935–948

    Google Scholar 

  • Magsamen-Conrad K, Upadhyaya S, Joa CY, Dowd J (2015) Bridging the divide: using UTAUT to predict multigenerational tablet adoption practices. Comput Hum Behav 50:186–196

    Google Scholar 

  • Makransky G, Lilleholt L (2018) A structural equation modeling investigation of the emotional value of immersive virtual reality in education. Educ Tech Res Dev 66(5):1141–1164

    Google Scholar 

  • Makransky G, Terkildsen T, Mayer RE (2019) Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learn Instr 60:225–236

    Google Scholar 

  • Manis KT, Choi D (2019) The virtual reality hardware acceptance model (VR-HAM): extending and individuating the technology acceptance model (TAM) for virtual reality hardware. J Bus Res 100:503–513

    Google Scholar 

  • Marangunić N, Granić A (2015) Technology acceptance model: a literature review from 1986 to 2013. Univ Access Inf Soc 14:81–95

    Google Scholar 

  • McGovern E, Moreira G, Luna-Nevarez C (2020) An application of virtual reality in education: Can this technology enhance the quality of students’ learning experience? J Edu Bus 95(7):490–496

    Google Scholar 

  • Moon J, Kim Y (2001) Extending the TAM for a world-wide-web context. Inform Manag 38:217–230

    Google Scholar 

  • Norris MW, Spicer K, Byrd T (2019) Virtual reality: the new pathway for effective safety training. Prof Saf 64(06):36–39

    Google Scholar 

  • Pallant J (2005) SPSS survival manual: a step by step guide to data analysis using SPSS for windows. Allen & Unwin, Sydney

    Google Scholar 

  • Pan X (2020) Technology acceptance, technological self-efficacy, and attitude toward technology-based self-directed learning: learning motivation as a mediator. Front Psychol 11:564294

    Google Scholar 

  • Papanastasiou G, Drigas A, Skianis C, Lytras M, Papanastasiou E (2019) Virtual and augmented reality effects on K-12, higher and tertiary education students’ twenty-first century skills. Virtual Reality 23(4):425–436

    Google Scholar 

  • Parsons S (2016) Authenticity in Virtual Reality for assessment and intervention in autism: a conceptual review. Educ Res Rev 19:138–157

    Google Scholar 

  • Radianti J, Majchrzak TA, Fromm J, Wohlgenannt I (2020) A systematic review of immersive virtual reality applications for higher education: design elements, lessons learned, and research agenda. Comput Educ 147:103778

    Google Scholar 

  • Rebenitsch L, Owen C (2016) Review on cybersickness in applications and visual displays. Virtual Reality 20(2):101–125

    Google Scholar 

  • Rogers S (2019) Virtual reality: the learning aid of the 21st century. Forbes. https://www.forbes.com/sites/solrogers/2019/03/15/virtualreality-the-learning-aid-of-the-21stcentury/#7b5ad441139b

  • Sánchez-Cabrero R, Costa-Román Ó, Pericacho-Gómez FJ, Novillo-López MÁ, Arigita-García A, Barrientos-Fernández A (2019) Early virtual reality adopters in Spain: sociodemographic profile and interest in the use of virtual reality as a learning tool. Heliyon 5(3):e01338

    Google Scholar 

  • Sezer B, Yilmaz R (2019) Learning management system acceptance scale (LMSAS): a validity and reliability study. Australas J Educ Technol 35(3):15–30

    Google Scholar 

  • Shiferaw KB, Mehari EA (2019) Modeling predictors of acceptance and use of electronic medical record system in a resource limited setting: using modified UTAUT model. Inform Med Unlocked 17:100182

    Google Scholar 

  • Slater M (2003) A note on presence terminology. Presence Connect 3(3):1–5

    Google Scholar 

  • Stevens J (1996) Applied multivariate statistics for the social sciences. Erlbaum, Mahwah, NJ

    MATH  Google Scholar 

  • Tabachnick BG, Fidell LS (2007) Using multivariate statistics. Pearson, Boston, MA

    Google Scholar 

  • Taherdoost H (2018) A review of technology acceptance and adoption models and theories. Procedia Manuf 22:960–967

    Google Scholar 

  • Tezbaşaran A (1997) Likert tipi ölçek hazırlama kılavuzu [Likert type scale preparation guide]. Türk Psikologlar Derneği, Ankara

    Google Scholar 

  • Tondeur J (2020) Teachers’ pedagogical beliefs and technology use. In: Peters M (ed) Encyclopaedia of teacher education. Springer, Singapore, pp 1–5

    Google Scholar 

  • Tyng CM, Amin HU, Saad MNM, Malik AS (2017) The influences of emotion on learning and memory. Front Psychol 8:1454

    Google Scholar 

  • Ustun AB, Yilmaz R, Yilmaz FGK (2020) Virtual reality in medical education. In: Umair S (ed) Mobile devices and smart gadgets in medical sciences. IGI Global, pp 56–73. https://doi.org/10.4018/978-1-7998-2521-0.ch004

    Chapter  Google Scholar 

  • Ustun AB, Karaoglan Yilmaz FG, Yilmaz R (2021) Investigating the role of accepting learning management system on students’ engagement and sense of community in blended learning. Educ Inf Technol 26(4):4751–4769

    Google Scholar 

  • Üstün AB (2022) Sanal gerçeklik ve dil öğretimi [Virtual reality and language teaching]. In: Şimsek E, Üstün AB (eds) Yabancı dil öğretiminde teknoloji uygulamaları. Nobel, pp 127–142

    Google Scholar 

  • Velev D, Zlateva P (2017) Virtual reality challenges in education and training. Int J Learn Teach 3(1):33–37

    Google Scholar 

  • Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage Sci 46(2):186–204

    Google Scholar 

  • Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: Toward a unified view. MIS Q 27(3):425–478

    Google Scholar 

  • Venkatesh V, Thong JYL, Xin X (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 36(1):157–178

    Google Scholar 

  • Yu CS (2012) Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. J Electron Commer Res 13(2):104

    Google Scholar 

  • Zhang M, Zhang Z, Chang Y, Aziz ES, Esche S, Chassapis C (2018) Recent developments in game-based virtual reality educational laboratories using the Microsoft Kinect. Int J Emerg Technol Learn 13(1):138–159

    Google Scholar 

Download references

Acknowledgements

The present study was based on a part of a scientific research project funded by the Scientific Research Coordinator of Bartin University (Grant Number: 2020-SOS-A-002)

Author information

Authors and Affiliations

  1. Faculty of Sciences, Department of Computer Technology and Information Systems, Bartin University, Bartın, Turkey

    Ahmet Berk Ustun, Fatma Gizem Karaoglan-Yilmaz & Ramazan Yilmaz

Authors
  1. Ahmet Berk Ustun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fatma Gizem Karaoglan-Yilmaz
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramazan Yilmaz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ahmet Berk Ustun.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interests.

Additional information

Publisher's Note

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

Appendix 1

Appendix 1

Factor

Item

(1) Strongly disagree

(2) Disagree

(3) Neither agree or disagree

(4) Agree

(5) Strongly agree

Performance Expectancy

Using virtual reality increases my chances of solving the problems I come across

     

Using virtual reality makes my life easier

     

Using virtual reality enables me to accomplish tasks more quickly

     

Using virtual reality increases my productivity

     

I find virtual reality useful for my daily life

     

Using virtual reality allows me to take responsibility for my own learning

     

Social Influence

Most people who are important to me encourage me to use virtual reality for learning purposes

     

Most people who are important to me use virtual reality for learning purposes

     

Most people who are important to me think that I should use virtual reality for learning purposes

     

Most people who are important to me find it helpful to use virtual reality for learning purposes

     

Effort Expectancy

Learning how to use Virtual Reality is easy for me

     

I find virtual reality easy to use

     

I can use virtual reality without any hassle

     

My interaction with virtual reality is clear and understandable

     

Learning the use of virtual reality is not difficult for me

     

Facilitating Conditions

I can easily get technical support if I have problems using virtual reality

     

I know whom to contact if I experience any problems in using virtual reality

     

If I have any problems while using virtual reality, I can reach the necessary information for a solution

     

The instrument can be used as long as copyright and attribution are noted.

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

Ustun, A.B., Karaoglan-Yilmaz, F.G. & Yilmaz, R. Educational UTAUT-based virtual reality acceptance scale: a validity and reliability study. Virtual Reality 27, 1063–1076 (2023). https://doi.org/10.1007/s10055-022-00717-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10055-022-00717-4

Keywords

Search

Navigation