Skip to main content

Do school reputation and price matter? The choice for continuing education in acquiring digital skills by adult learners

Abstract

Taking courses by continuing education (CE) providers is one of the main ways for adults to learning digital skills. CE is provided in either face-to-face (F2F) or online distance learning (ODL) mode. While F2F courses are natural and well-understood, ODL is flexible and less expensive. However, ODL lacks the natural teacher-student and student-student interaction. It is important to find out the factors that affect the adult learner’s preferred learning mode for gaining digital skills. This study examined these factors by modifying the Unified Theory Of Acceptance And Use Of Technology (UTAUT). The authors modified the UTAUT by adding the reputation of the provider (RP) and price perception (PP) as moderators. The data from an online survey involving 125 adult learners was analyzed using Smart PLS 3.0. It was found that among the four original UTAUT constructs, social influence is not related to the attitude towards the preferred learning mode. Furthermore, RP has a significant moderation effect on the Performance Expectancy, and Effort Expectancy. Lastly, PP affects the Facilitating Conditions. The implication for CE providers is that they should try to maintain a good reputation for their CE courses. In particular, for MOOC platforms, the providers should have more courses that are created by professional bodies or universities. Interestingly, the adult learners perceive the price as an indicator of facilitating conditions. Hence, the provider should charge their courses that reflect the quality of the infrastructure of, and the support for, the technologies used in delivering those courses. (246 words).

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

References

  • Akhmetshin, Ilyina, I., Kulibanova, V., Teor, T., & Okagbue, H. (2021). The formation of the university reputation capital under the digital transformation of the environment. IOP Conference Series. Earth and Environmental Science, 699(1), 12001. https://doi.org/10.1088/1755-1315/699/1/012001

    Article  Google Scholar 

  • Alraimi, Zo, H., & Ciganek, A. P. (2015). Understanding the MOOCs continuance: The role of openness and reputation. Computers in Education, 80, 28–38. https://doi.org/10.1016/j.compedu.2014.08.006

    Article  Google Scholar 

  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254. https://doi.org/10.17705/1jais.00122

    Article  Google Scholar 

  • Balderas, E. S. (2018). Adult and continuing education Students' success and intergenerational socio-economic mobility in era of rapid global technology. Commission for International Adult Education, 67–78.

  • Bayeck, R. (2016). Exploratory study of MOOC Learners' demographics and motivation: The case of students involved in groups. Open Praxis, 8(3), 223–233.

    Article  Google Scholar 

  • Cantor, J. A. (2006). Lifelong learning and the academy: The changing nature of continuing education. ASHE Higher Education Report, 32(2), 1. https://doi.org/10.1002/aehe.3202

    Article  Google Scholar 

  • Chan, H. Y., Ma, H., & Zhou, J. (2021). Public transportation and social movements: Learning from the Hong Kong anti-extradition bill protests. Transportation Research Record, 03611981211044466.

  • Chen, Wang, X., Wang, J., Zuo, C., Tian, J., & Cui, Y. (2021). Factors affecting college students’ continuous intention to use online course platform. SN Computer Science, 2(2), 114–114. https://doi.org/10.1007/s42979-021-00498-8

    Article  Google Scholar 

  • Cimperman, M., & Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior—Applying an extended UTAUT model. International Journal of Medical Informatics (Shannon, Ireland), 90, 22–31. https://doi.org/10.1016/j.ijmedinf.2016.03.002

    Article  Google Scholar 

  • de Moura, V. F., de Souza, C. A., & Viana, A. B. N. (2021). The use of massive open online courses (MOOCs) in blended learning courses and the functional value perceived by students. Computers & Education, 161. https://doi.org/10.1016/j.compedu.2020.104077

  • Dečman. (2015). Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender. Computers in Human Behavior, 49, 272–281. https://doi.org/10.1016/j.chb.2015.03.022

    Article  Google Scholar 

  • Engel, C. J. (2019). The acceptability of online degrees in accounting: A literature review. Global Journal of Business Pedagogy, 3(1), 10–26.

    Google Scholar 

  • Feldman, P. M., Bahamonde, R. A., & Velasquez Bellido, I. (2014). A new approach for measuring corporate reputation. Revista de Administração de Empresas, 54, 53–66.

    Article  Google Scholar 

  • Fong, J. (2013). Preparing Marketing for the Future: Strategic marketing challenges for continuing education. New Directions for Adult and Continuing Education, 2013(140), 89–100. https://doi.org/10.1002/ace.20077

    Article  Google Scholar 

  • Gaskell, & Mills, R. (2014). The quality and reputation of open, distance and e-learning: What are the challenges? Open Learning, 29(3), 190–205. https://doi.org/10.1080/02680513.2014.993603

    Article  Google Scholar 

  • Globenewswire.com. (2021, April 6). Growing at 14.6 % CAGR, The Global E-learning Market Size Will Exceed a Value of $374.3 Billion by 2026. GlobeNewswire by Notified. Retrieved June 6, 2021, from https://www.globenewswire.com/news-release/2021/04/06/2205170/0/en/Growing-at-14-6-CAGR-The-Global-E-learning-Market-Size-Will-Exceed-a-Value-of-374-3-Billion-by-2026.html

  • González-Patiño, J. (2018). Learn, teach and share, participation in expanded educational communities: Madrid Pikler Seminar as a Practice of Continuing Education between Childhood Professionals. Digital Education Review, 33, 203–216.

    Article  Google Scholar 

  • Günther, J. (2007). Digital natives & digital immigrants. StudienVerlag.

    Google Scholar 

  • Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Planning, 45(5–6), 320–340. https://doi.org/10.1016/j.lrp.2012.09.008

    Article  Google Scholar 

  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.

    Book  Google Scholar 

  • Hanson, M. (2013). Advances in Technology in Continuing Education: Who should foot the bill? Journal of Inquiry and Action in Education, 5(2), 38–42.

    Google Scholar 

  • Harris, J., & Wihak, C. (2018). The recognition of non-formal education in higher education: Where are we now, and are we learning from experience? International Journal of E-Learning & Distance Education, 33(1), 1–19.

    Google Scholar 

  • Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In: New Challenges to International Marketing (Vol. 20, pp. 277–319). Emerald Group Publishing Limited. https://doi.org/10.1108/S1474-7979(2009)0000020014.

  • Hoffmann, C. P., Lutz, C., & Meckel, M. (2014). Digital natives or digital immigrants? The impact of user characteristics on online trust. Journal of Management Information Systems, 31(3), 138–171.

    Article  Google Scholar 

  • Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics (Shannon, Ireland), 101, 75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002

    Article  Google Scholar 

  • Kaliisa, R., Palmer, E., & Miller, J. (2019). Mobile learning in higher education : A comparative analysis of developed and developing country contexts. British Journal of Educational Technology, 50(2), 546–561. https://doi.org/10.1111/bjet.12583

    Article  Google Scholar 

  • Khechine, H., Lakhal, S., Pascot, D., & Bytha, A. (2014). UTAUT model for blended learning: The role of gender and age in the intention to use webinars. Interdisciplinary Journal of E-Learning and Learning Objects, 10(1), 33–52.

    Google Scholar 

  • Kimiloglu, H., Ozturan, M., & Kutlu, B. (2017). Perceptions about and attitude toward the usage of e-learning in corporate training. Computers in Human Behavior, 72, 339–349. https://doi.org/10.1016/j.chb.2017.02.062

    Article  Google Scholar 

  • Kohl, K. J. (2010). Coping with change and fostering innovation: An agenda for professional and continuing education. Continuing Higher Education Review, 74, 9–22.

    Google Scholar 

  • Kohnke, L., & Moorhouse, B. L. (2021). Adopting HyFlex in higher education in response to COVID-19: Students’ perspectives. Open Learning: The Journal of Open, Distance and e-Learning, 36(3), 231–244.

    Article  Google Scholar 

  • Kordzadze, M. (2020). The role of universities of Georgia in providing continuing education courses of local self-government public servants. World Journal of Education, 10(2), 69–77.

    Article  Google Scholar 

  • Lapidos, A., & Ruffolo, M. (2017). Access to Interprofessional continuing education in integrated care through digital instructional technology. Journal of Social Work Education, 53(sup1), S40–S46. https://doi.org/10.1080/10437797.2017.1288596

    Article  Google Scholar 

  • Lee, H. D., & Nam, M. W. (2018). The analysis of academic achievement based on Spatio-temporal data relate to e-learning patterns of university e-learning learners. Journal of Convergence Information Technology, 8(4), 247–253. https://doi.org/10.22156/CS4SMB.2018.8.4.247

    Article  Google Scholar 

  • Liu, Y., Lin, F., & Wang, X. (2003). Education practice and analysing behaviour of students in a web-based learning environment: An exploratory study from China. Online Information Review, 27(2), 110–119. https://doi.org/10.1108/14684520310471725

    Article  Google Scholar 

  • Long, G. L., & Beil, D. H. (2005). The importance of direct communication during continuing education workshops for deaf and hard-of-hearing professionals. Journal of Postsecondary Education and Disability, 18(1), 5–11.

    Google Scholar 

  • Long, T., Cummins, J., & Waugh, M. (2019). Investigating the factors that influence higher education instructors’ decisions to adopt a flipped classroom instructional model. British Journal of Educational Technology, 50(4), 2028–2039. https://doi.org/10.1111/bjet.12703

    Article  Google Scholar 

  • Ma, L., & Lee, C. S. (2020). Drivers and barriers to MOOC adoption: Perspectives from adopters and non-adopters. Online Information Review, 44(3), 671–684. https://doi.org/10.1108/OIR-06-2019-0203

    Article  Google Scholar 

  • Mason, R. (2006). Learning technologies for adult continuing education. Studies in Continuing Education, 28(2), 121–133. https://doi.org/10.1080/01580370600751039

    Article  Google Scholar 

  • Moen, M. H., Mandel, L. H., & Karno, V. (2020). Continuing education for public library staff: Valued competencies and preferred delivery format. Education for Information, 36(2), 177–198. https://doi.org/10.3233/EFI-190311

    Article  Google Scholar 

  • Moghavvemi, S., & Janatabadi, H. S. (2018). Incremental impact of time on students’ use of E‐learning via Facebook. British Journal of Educational Technology, 49(3), 560–573. https://doi.org/10.1111/bjet.12545

  • Mulik, S., Srivastava, M., & Yajnik, N. (2012). Extending UTAUT model to examine MOOC adoption. NMIMS Management Review, 36(2), 26–44.

    Google Scholar 

  • Negahban, A., & Chung, C.-H. (2014). Discovering determinants of users perception of mobile device functionality fit. Computers in Human Behavior, 35, 75–84. https://doi.org/10.1016/j.chb.2014.02.020

    Article  Google Scholar 

  • Pappas, C. (2015, January 25). The top eLearning statistics and facts for 2015 you need to know. E-learning industry association. Retrieved January 6, 2022, from http://elearningindustry.com/elearning-statistics-and-facts-for-2015.

  • Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.

    Article  Google Scholar 

  • Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: Towards a unified view. Information Systems Frontiers, 19(3), 549–568. https://doi.org/10.1007/s10796-015-9613-y

    Article  Google Scholar 

  • Reimers, F. (2009). Enlightening globalization: An opportunity for continuing education. Continuing Higher Education Review, 73, 32.

    Google Scholar 

  • Ringle, C., Da Silva, D., & Bido, D. (2015). Structural equation modeling with the SmartPLS. Brazilian Journal of Marketing, 13(2).

  • Rodrigues, G., Sarabdeen, J., & Balasubramanian, S. (2016). Factors that influence consumer adoption of E-government services in the UAE: A UTAUT model perspective. Journal of Internet Commerce, 15(1), 18–39. https://doi.org/10.1080/15332861.2015.1121460

    Article  Google Scholar 

  • Scanlan, C. S., & Darkenwald, G. G. (1984). Identifying deterrents to participation in continuing education. Adult Education Quarterly (American Association for Adult and Continuing Education), 34(3), 155–166. https://doi.org/10.1177/0001848184034003004

    Article  Google Scholar 

  • Shaikh, A. A., & Karjaluoto, H. (2015). Making the most of information technology & systems usage: A literature review, framework and future research agenda. Computers in Human Behavior, 49, 541–566. https://doi.org/10.1016/j.chb.2015.03.059

    Article  Google Scholar 

  • Shamsideen, S. A. (2015). Effect of computer assisted learning methods on facilitating continuing education in Lagos state, Nigeria. African Educational Research Journal, 3(4), 204–208.

    Google Scholar 

  • Shinagel, M. (2008). A passage to India: A case study of Harvard's division of continuing education and the Indian computer academy. Continuing Higher Education Review, 72, 74–84.

    Google Scholar 

  • Smyrnova-Trybulska, E., Ogrodzka-Mazur, E., Szafrańska-Gajdzica, A., Morze, N., Makhachashvili, R., Noskova, T., … Issa, T. (2016). MOOCs – Theoretical and practical aspects: Comparison of selected research results: Poland, Russia, Ukraine, and Australia. In: International conferences ITS, ICEduTech and STE 2016, Dec 6-8, Melbourne, Australia, edited by: Piet Kommers, TomayessIssa, Theodora Issa, Elspeth McKay, Pedro Isaías, Associate editor: Luís Rodrigues, ISBN: 978-989-8533-58-6, 107–114.

  • So, S. (2016). Mobile instant messaging support for teaching and learning in higher education. The Internet and Higher Education, 31, 32–42. https://doi.org/10.1016/j.iheduc.2016.06.001

    Article  Google Scholar 

  • Stevens, J. (2014). Perceptions, attitudes, & preferences of adult learners in higher education: A National Survey. The Journal of Learning in Higher Education, 10(2), 65–78.

    Google Scholar 

  • Tabatabaei, M., & Gardiner, A. (2012). Recruiters' perceptions of information systems graduates with traditional and online education. Journal of Information Systems Education, 23(2), 133.

    Google Scholar 

  • Tarhini, El-Masri, M., Ali, M., & Serrano, A. (2016). Extending the UTAUT model to understand the customers’ acceptance and use of internet banking in Lebanon. Information Technology & People (West Linn, Or.), 29(4), 830–849. https://doi.org/10.1108/ITP-02-2014-0034

    Article  Google Scholar 

  • Tella, A., Tsabedze, V., Ngoaketsi, J., & Enakrire, R. T. (2021). Perceived usefulness, reputation, and Tutors' advocate as predictors of MOOC utilization by distance learners: Implication on library Services in Distance Learning in Eswatini'. Journal of Library & Information Services in Distance Learning, 15(1), 41–67.

    Article  Google Scholar 

  • Vargo, D., Zhu, L., Benwell, B., & Yan, Z. (2021). Digital technology use during COVID-19 pandemic: A rapid review. Human Behavior and Emerging Technologies, 3(1), 13–24.

    Article  Google Scholar 

  • 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. https://doi.org/10.2307/30036540

    Article  Google Scholar 

  • Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232. https://doi.org/10.1016/j.chb.2016.10.028

    Article  Google Scholar 

  • Yee, M. L. S., & Abdullah, M. S. (2021). A review of UTAUT and extended model as a conceptual framework in education research. Jurnal Pendidikan Sains Dan Matematik Malaysia, 11, 1–20.

    Google Scholar 

  • Yuan, S., Ma, W., Kanthawala, S., & Peng, W. (2015). Keep using my health apps: Discover Users' perception of health and fitness apps with the UTAUT2 model. Telemedicine Journal and E-Health, 21(9), 735–741. https://doi.org/10.1089/tmj.2014.0148

    Article  Google Scholar 

  • Zaghab, R. W., Maldonado, C., Whitehead, D., Bartlett, F., & de Bittner, M. R. (2015). Online continuing education for health professionals: Does sticky design promote practice-relevance? Electronic Journal of E-Learning, 13(6), 466–474.

    Google Scholar 

Download references

Acknowledgments

The work described in this paper was fully supported by a grant from the College of Professional & Continuing Education, an affiliate of The Hong Kong Polytechnic University.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adam Wong.

Ethics declarations

Competing interests

The authors have no competing interests to declare that are relevant to the content of this article.

Additional information

Publisher’s note

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wong, A., Lee, D. & Chan, C. Do school reputation and price matter? The choice for continuing education in acquiring digital skills by adult learners. Educ Inf Technol (2022). https://doi.org/10.1007/s10639-022-11133-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10639-022-11133-1

Keywords

  • Continuing education
  • Digitial skills
  • Online distance learning
  • Unified theory of acceptance and use of technology
  • Reputation of the provider
  • Price perception