Influence of Computer Self-Efficacy, Socio Economic Status, and Facilitating Conditions on the Learning Abilities of Digital Arts Students
Keywords:
computer self-efficacy; creative performance; digital arts; facilitating conditions; socio-economic factorsAbstract
The learning landscape of digital arts has been transformed by the integration of digital technology into creative education. Disparities in students’ technological confidence, socio-economic backgrounds, and institutional support hinder equitable participation and learning outcomes. This study explored how computer self-efficacy, socio-economic factors, and facilitating conditions influence the academic learning needs of digital arts students at the University of the Witwatersrand, including motivation, engagement, and creative performance. The study employed a quantitative, correlational design based on Bandura’s self-efficacy theory, Venkatesh et al.’s unified theory of acceptance and use of technology, and Bourdieu’s theory of social capital. A stratified random sample of 120 students was selected from 400 digital arts students using a validated questionnaire. Structural equation modelling was used to analyse the relationships between the variables. The results indicated that computer self-efficacy and facilitating conditions were significant predictors of academic learning needs, while socio-economic factors had an indirect yet meaningful influence. The findings highlight the significance of digital confidence, institutional support, and resource accessibility in influencing student success in creative technology environments. The study concluded that a general approach is necessary to address the relationship between individual ability and environmental barriers. It is recommended that educational institutions implement digital literacy interventions, improve access to creative tools, and strengthen supportive infrastructure for inclusive and equitable digital arts education.
https://doi.org/10.26803/ijlter.24.7.23
References
Aboagye, E., Yeboah, I., & Mensah, F. (2022). The role of facilitating conditions in promoting student engagement in digital creative arts. International Journal of Educational Technology, 18(2), 112–134.
Agbo, F. J. (2022). Digital arts and creative education: Exploring the role of institutional support in creative pedagogy. Arts and Education Quarterly, 29(3), 45–63. http://doi.org/10.4236/jss.2016.47034
Alabi, O. T., & Abdulahi, M. (2022). Socioeconomic disparities in digital technology use among African students: Implications for digital skills acquisition. Journal of Educational Technology Development, 28(3), 143–158. https://doi.org/10.1007/s12345-022-0035-6
Al-Fraihat, D., Joy, M., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behaviour, 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004
Avvisati, F., & Wuyts, C. (2024). The measurement of socio-economic status in PISA. [Education Working Papers No. 321]. OECD Publishing. https://www.oecd.org/content/dam/oecd/en/publications/reports/2024/09/the-measurement-of-socio-economic-status-in-pisa_e87a4e29/0c5b793c-en.pdf
Azevedo, J. P., Hasan, A., Goldemberg, D., Iqbal, S. A., & Geven, K. (2021). Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes: A set of global estimates. The World Bank Research Observer, 36(1), 1–40. https://doi.org/10.1093/wbro/lkab003
Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman. https://psycnet.apa.org/record/1997-08589-000
Becker, H. J. (2000). Who’s wired and who’s not: Children’s access to and use of computer technology. The Future of Children, 10(2), 44–75. http://doi.org/10.2307/1602689
Bourdieu, P. (1986). The forms of capital. In J. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). Greenwood. https://doi.org/10.4324/9780429494338-6
Calaguas, N. P., & Consunji, P. M. P. (2022). A structural equation model predicting adults’ online learning self -efficacy. Education and Information Technologies, 27, 6233–6249. https://doi.org/10.1007/s10639-021-10871-y
Chong, S. W., & Reinders, H. (2025). Autonomy of English language learners: A scoping review of research and practice. Language Teaching Research, 29(2), 607–632. https://doi.org/10.1177/13621688221075812
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688
Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
Do?ru, O. (2020). An investigation of pre-service visual arts teachers’ perceptions of computer self-efficacy and attitudes towards web-based instruction. International Journal of Research in Education and Science, 6(4), 629–637. https://doi.org/10.46328/ijres.v6i4.1454
Farida, Prabowo, H. A., Anton, & Rizki, H. T. (2025). Technology acceptance model in the application of online learning during COVID-19 pandemic: Case study in a remote area of Indonesia. E-Learning Innovations Journal, 3(1), 4-28. https://www.el-journal.org/index.php/journal/article/view/46
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Gay, L. R., Mills, G. E., & Airasian, P. W. (2011). Educational research: Competencies for analysis and applications (10th ed.). Pearson Education.
Heinz, M. (2016). Digital skills and the influence of students’ socio-economic background: An exploratory study in German elementary schools. Education and Information Technologies, 21(6), 1–18. http://doi.org/10.14658/pupj-ijse-2016-2-9
Lan, M., & Zhou, X. (2025). A qualitative systematic review on AI empowered self-regulated learning in higher education. NPJ Science of Learning, 10, Article 21. https://doi.org/10.1038/s41539-025-00319-0
Lin, C.-H., Cheng, Y.-C., & Huang, Y.-C. (2019). Understanding creative self-efficacy in the context of digital game based learning. Computers & Education, 138, 49–60. https://doi.org/10.1016/j.compedu.2019.04.004
Lin, C. P., Liao, J. Y., Huang, C. H., Cheng, S. Y., Tseng, W. Z., Mori, M., Chang, H. C., Li, C. M., Sun, W. J., Wu, C. Y., Chiou, H. Y., Yu, S. J., Hsiung, C. A., & Chen, P. J. (2025). Association between current medical decision-making participation self-efficacy and advance care planning engagement among older adults: Baseline findings from a nationwide longitudinal cohort study. Journal of Palliative Medicine, 28(1), 50–58. https://doi.org/10.1089/jpm.2024.0106
Liu, N., & Quanlin, P. (2023). Factors influencing learners’ continuance intention toward one-to-one online learning. Interactive Learning Environments, 31(3), 1742–1763. https://doi.org/10.1080/10494820.2020.1857785
McKenna, G., & Richardson, S. (2022). Digital arts education: Transformative potentials and pedagogical challenges. Journal of Creative Education, 13(4), 367–381. https://doi.org/10.4236/ce.2022.134028
Memon, J. A., Baloch, A., & Irqai, K. M. (2025). Strategic visionary leadership and sustainable governance: Navigating higher education reforms for optimal performance in the age of disruptive technologies. FWU Journal of Social Sciences, 18(4), 40–53. https://doi.org/10.51709/19951272/winter2024/3
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467 9620.2006.00684.x
Nurhasanah, A., & Ningsih, A. (2022). Effect of motivation, work environment, and computer self-efficacy to employee of PDAM Tirta Kencana performance in Samarinda City, East Kalimantan. Proceedings of the International Conference on Applied Science and Technology on Social Science 2021 (iCAST-SS 2021) (pp. 957–961). Atlantis Press SARL. http://doi.org/10.2991/assehr.k.220301.159
Olivares, A., & Piatak, J. (2021). Race, ethnicity, and museum participation: Examining the role of education and income. Journal of Cultural Economics, 45, 123–142. https://doi.org/10.1007/s11266-021-00322-0
Ollonen, M., & Kangas, M. (2024). Academic self-efficacy, online self-efficacy, and fixed and faded scaffolding in computer-based learning environments. Computers & Education, 210, Article 104783.
Onwuagboke, B. B. C. (2016). Effects of computer self-efficacy on pre-service art teachers’ achievement in graphic design. Pertanika Journal of Social Science and Humanities, 24(4), 1315–1333. https://www.researchgate.net/publication/310753052_Effects_of_Computer_Self-Efficacy_on_Pre-Service_Art_Teachers’_Achievement_in_Graphic_Design
Randle, O. A. (2024). Factors affecting students’ acceptance of gamified learning (SAGL). Studies in Learning and Teaching, 5(3), 547–569. https://scie-journal.com/index.php/SiLeT/article/view/431
Randle, O. A., & Kayode, O. (2025). Examining the factors influencing undergraduate students’ use of digital arts playrooms in South African university game studies programs. African Perspectives of Research in Teaching and Learning, 9(1), 60-71. https://doi.org/10.70875/v9i1article5
Reisdorf, B. C., & Groselj, D. (2017). Internet (non-)use types and motivational access: Implications for digital inequalities research. New Media & Society, 19(8), 1157–1176. https://doi.org/10.1177/1461444815621539
Satar, M. (2021). Introducing virtual exchange: Towards digital equity in internationalisation. In M. Satar (Ed.), Virtual Exchange: Towards Digital Equity in Internationalisation (pp. 1–13. Research-publishing.net. https://doi.org/10.14705/rpnet.2021.53.1285
Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling (2nd ed.). Psychology Press. https://www.researchgate.net/publication/362079746_A_beginner’s_Guide_to_Structural_Equation_Modeling
?endurur, P., & Y?ld?r?m, ?. S. (2019). Teachers’ computer self-efficacy scale: Development and validation. Kastamonu E?itim Dergisi, 27(2), 433–441. https://doi.org/10.24106/kefdergi.2497
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. http://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology (UTAUT2). MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Wang, Q., Zhao, G., & Zeng, J. (2024). The effects of facilitating conditions, digital competence, and technostress on higher education students. Internet and Higher Education, 60, Article 100882. https://www.researchgate.net/publication/384462663_The_effects_of_facilitating_conditions_digital_competence_and_technostress_on_higher_education_students’_digital_informal_learning_A_moderated_mediation_examination
Warschauer, M. (2004). Technology and social inclusion: Rethinking the digital divide. MIT Press. https://doi.org/10.7551/mitpress/6699.001.0001
Warschauer, M., & Matuchniak, T. (2010). New technology and digital worlds: Analyzing evidence of equity in access, use, and outcomes. Review of Research in Education, 34(1), 179–225. https://doi.org/10.3102/0091732X09349791
Whitaker, A., & Wolniak, G. C. (2022). Social exclusion in the arts: The dynamics of social and economic mobility across three decades of undergraduate arts alumni in the United States. Review of Research in Education, 46(1), 198–228. https://doi.org/10.3102/0091732X221089947
Zhou, Z., Hussain, Y., & Kamarudin, D. (2023). The influence of digital technology on art teaching and learning in China high schools. Journal of Art & Technology Education, 18(2), 45–62. https://doi.org/10.59021/ijssbm.v1i02.43
Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82–91. https://doi.org/10.1006/ceps.1999.1016
Zimmerman, B. J., & Schunk, D. H. (2011). Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed.). Routledge. https://doi.org/10.4324/9781410601032
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