The effect of performance expectancy on BIM learning performance throughout the mediation role of learning intention
DOI:
https://doi.org/10.22399/ijcesen.3233Keywords:
Building Information Modelling (BIM), Performance Expectancy, Learning Intention, Vocational Education, Technology Acceptance Model (TAM)Abstract
Building Information Modelling (BIM) is a new technology with transformative capabilities in the AEC industry. Increasing emphasis is being placed on integrating this technology into vocational education to enhance students' employment opportunities and industry readiness. Founded upon the Unified Theory of Acceptance and Use of Technology (UTAUT) and Technology Acceptance Model (TAM), this study has examined the effect of performance expectancy (PE) on vocational college students' BIM learning performance (BLP) through intention to learn BIM (ILB) as a mediating variable. A quantitative cross-sectional survey design collected data from 190 students enrolled in BIM-related courses across China. Upon employing exploratory factor analysis, correlation, and multiple regression analyses, the assumption of unidimensionality along with internal consistency of the Greater PE, ILB, and BLP constructs were corroborated. The findings revealed that PE has no direct relationship on BLP, but PE has a strong effect on ILB, which then positively impacts BLP, thus indicating the presence of full mediation. These results underscore the critical role of students’ motivational and career-driven expectations in shaping their engagement with BIM technologies. The study contributes to the theoretical advancement of UTAUT and TAM in vocational learning contexts and offers practical recommendations for curriculum designers, educators, and policymakers to foster BIM proficiency through enhanced student motivation and goal alignment.
References
[1] Abualdenien, J., & Borrmann, A. (2020). Advanced Engineering Informatics Vagueness visualization in building models across different design stages. Advanced Engineering Informatics, 45.
[2] Andretta, J. R., & Mckay, M. T. (2020). Children and Youth Services Review Self-efficacy and well-being in adolescents: A comparative study using variable and person-centered analyses. Children and Youth Services Review, 118, 1–7.
[3] Baharuddin, F. R., Syafrudie, H. A., Sudjimat, D. A., & Syam, H. (2017). The Contribution of Work Environment and Motoric Cognition on Work Readiness of Vocational colleges Student. Advances in Social Science, Edu. and Humanities Research (ASSEHR), Vol. 149 2nd Int. Conf. on Edu., Sci., and Tech. (ICEST 2017), 149(Icest), 112–114
[4] Bandura, A. (2012). On the Functional Properties of Perceived Self-Efficacy Revisited. J. of Management, 38(9–44).
[5] Camargo, A., Çelik, P., & Storme, M. (2020). Cultural self-efficacy increases creativity in bicultural dyads: Evidence from two dyadic divergent thinking tasks. Thinking Skills and Creativity.
[6] Capron, I., & Audrin, C. (2021). Improving self-efficacy and creative self-efficacy to foster creativity and learning in schools. Thinking Skills and Creativity, 42.
[7] Creswell, J. W. (2010). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE Publications.
[8] Eastmen, C., Teicholz, P., Sacks, R., & Liston, K. (2008). BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers, and Contractors. John Wiley and Sons, Inc.
[9] Ganiyu, S. A., Oyedele, L. O., Akinade, O., Owolabi, H., Akanbi, L., & Gbadamosi, A. (2020). Developments in the Built Environment BIM competencies for delivering waste-ef fi cient building projects in a circular economy. Developments in the Built Environment, 4.
[10] Jendra, A. F. (2020). Pengaruh Efikasi Diri Terhadap Kecemasan Presentasi Siswa Kelas XI di SMA Negeri 1 Wuryantoro[The Effect of Self-Efficacy on Presentation Anxiety of Grade XI Students at SMA Negeri 1 Wuryantoro]. 4(1), 138–159.
[11] Kia, S. (2014). Review of BIM Software Packages Based on Assets Management. Amirkabir University of Technology.
[12] Kim, M., Oh, J., & Beomsoo Kim. (2021). Experience of digital music services and digital self-efficacy among older adults: Enjoyment and anxiety as mediators. Technology in Society, 67(101773).
[13] Kjartansdóttir, I. B., Mordue, S., Nowak, P., Philp, D., & Snæbjörnsson, J. T. (2017). Building Information Modelling (BIM). Civil Engineering Faculty of Warsaw University of Technology.
[14] Li, J., Afsari, K., Li, N., Peng, J., Wu, Z., & Cui, H. (2020). A review for presenting building information modeling education and research in China. Journal of Cleaner Production, 259(120885), 1–17.
[15] Marmo, R., Polverino, F., Nicolella, M., & Tibaut, A. (2020). Automation in Construction Building performance and maintenance information model based on IFC schema. Automation in Construction, 118, 17.
[16] Romijn, B. R., Slot, P. L., Leseman, P. P. M., & Pagani, V. (2020). Teachers’ self-efficacy and intercultural classroom practices in diverse classroom contexts: A cross-national comparison. International Journal of Intercultural Relations, 79, 58–70.
[17] Saari, A., Rasul, M. S., Yasin, R. M., Rauf, R. A. A., Ashari, Z. H. M., & Pranita, D. (2021). Skills sets for workforce in the IR4.0: Expectation from authorities and industrial players. J. of Tech. Edu. and Training, 13(2), 1–9.
[18] Sacks, R., Girolami, M., & Brilakis, I. (2020). Building Information Modelling, Arti fi cial Intelligence and Construction Tech. Developments in the Built Environment, 4, 1–9.
[19] Watson, S., & Marschall, G. (2019). How a trainee mathematics teacher develops teacher self-efficacy. Teacher Development, 23(4), 469–487.
[20] Wyatt, M. (2014). Towards a re-conceptualization of teachers’ self-efficacy beliefs: tackling enduring problems with the quantitative research and moving on. International Journal of Research and Method in Education, 37(2), 166–189.
[21] Xu, Z., Zhang, L., Li, H., Lin, Y., & Yin, S. (2020). Automation in Construction Combining IFC and 3D tiles to create 3D visualization for building information modeling. Automation in Construction Journal, 109.
[22] Yeh, C., Lin, H., Wang, Y., Wang, Y., & Lo, C. (2021). The International Journal of Management Education Investigating the relationships between entrepreneurial education and self-efficacy and performance in the context of internet entrepreneurship. The International Journal of Management Education.
[23] Sari, N. P. W. P., Duong, M. P. T., Li, D., Nguyen, M. H., & Vuong, Q. H. (2024). Rethinking the effects of performance expectancy and effort expectancy on new technology adoption: Evidence from Moroccan nursing students. Teaching and Learning in Nursing, 19(3), e557-e565.
[24] Sewandono, R.E., Thoyib, A., Hadiwidjojo, D. et al. (2023). Performance expectancy of E-learning on higher institutions of education under uncertain conditions: Indonesia context. Educ Inf Technol 28, 4041–4068. https://doi.org/10.1007/s10639-022-11074-9
[25] Rumangkit, S., Surjandy, S., & Billman, A. (2023). The effect of performance expectancy, facilitating condition, effort expectancy, and perceived easy to use on intention to using media support learning based on unified theory of acceptance and use of technology (UTAUT). In E3S Web of Conferences (Vol. 426, p. 02004). EDP Sciences.
[26] Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology, 10, 1652.
[27] Bamigbola, A.A. and Udomah, U.F. (2025), Facilitating conditions, performance expectancy and use of electronic devices by senior secondary school students in Ibadan North Local Government Area, Oyo State, Nigeria, Digital Library Perspectives, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/DLP-08-2024-0125
[28] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478. https://doi.org/10.2307/30036540
[29] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. https://doi.org/10.2307/249008
[30] 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. https://doi.org/10.1287/mnsc.35.8.982
[31] Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace 1. Journal of applied social psychology, 22(14), 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
[32] Thompson, R. L., Higgins, C. A., and Howell, J. M. (1991), Personal Computing: Toward a Conceptual Model of Utilization, MIS Quarterly (15:1), 124-143.
[33] Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222. https://doi.org/10.1287/isre.2.3.192
[34] Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 189-211. https://doi.org/10.2307/249688
[35] Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS quarterly, 145-158. https://doi.org/10.2307/249749
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 International Journal of Computational and Experimental Science and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.
