Skip to main content

Advertisement

SpringerLink
Log in

Course quality and perceived employability of Malaysian youth: The mediating role of course effectiveness and satisfaction

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

Abstract

In today's rapidly changing job market, digital competence is quickly becoming a requirement for employability. This has put pressure on the next generation, particularly digital natives, to be well-equipped to deal with the turbulence of technology. This paper aims to compare youth's pre-course and post-course digital competency levels and examine students' perceptions of their employability after taking digital-skills-related courses. The Penang government initiative of an online learning program named "Penang Young Digital Talent Program" is designed to foster digital competencies. The program comprises online courses such as web design, digital marketing, etc. Therefore, the current study has examined the current level of Penag youth's digital readiness and digital competency (survey 1, N = 662) and the evaluate program's effectiveness while determining the impact of course quality on perceived employability (survey 2, N = 385) students undergo. The participants of this program range from 18–30 years old (post-secondary school and graduates), who are either born in Penang or have resided in Penang for a minimum of 3 years. The participants reported that their digital competency improved after participating in the talent program. The results of Smart PLS reported that course quality has a significant and positive relationship with perceived employability. Moreover, there is an indirect impact of student satisfaction and course effectiveness on the perceived employability of Malaysian youth. These findings have implications for educational policymakers who should prioritize young people acquiring digital skills to compete in the modern labor market.

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

Due to the nature of this research, participants of this study did not agree with their data to be shared publicly, so supporting data is not available.

References

  • Adeyemon, E. (2009). Integrating digital literacies into outreach services for underserved youth populations. Reference Librarian, 50(1) https://doi.org/10.1080/02763870802546423.

  • Afrouz, R., & Crisp, B. R. (2021). Online education in social work, effectiveness, benefits, and challenges: A scoping review. Australian Social Work, 74(1), 55–67.

    Article  Google Scholar 

  • Al-Khateeb, A. A. M. (2017). Measuring Digital Competence and ICT Literacy: An Exploratory Study of In-Service English Language Teachers in the Context of Saudi Arabia. International Education Studies, 10(12), 38. https://doi.org/10.5539/ies.v10n12p38

    Article  Google Scholar 

  • Almaiah, M. A., & Alyoussef, I. Y. (2019). Analysis of the effect of course design, course content support, course assessment and instructor characteristics on the actual use of E-learning system. Ieee Access, 7, 171907–171922.

    Article  Google Scholar 

  • Alqurashi, E. (2019). Predicting student satisfaction and perceived learning within online learning environments. Distance Education, 40(1), 133–148. https://doi.org/10.1080/01587919.2018.1553562

    Article  Google Scholar 

  • Barczyk, C. C., Hixon, E., Buckenmeyer, J., & Ralston-Berg, P. (2017). The Effect of Age and Employment on Students’ Perceptions of Online Course Quality. American Journal of Distance Education, 31(3), 173–184. https://doi.org/10.1080/08923647.2017.1316151

    Article  Google Scholar 

  • Budur, T., Mahsum Faraj, K., & Ali Karim, L. (2019). Benchmarking Operations Strategies via Hybrid Model: A Case study of Café-Restaurant Sector. Revista Amazonia Investiga, 8(23), 6923–6947.

    Google Scholar 

  • Carretero, S., Vuorikari, R., & Punie, Y. (2017). The Digital Competence Framework for Citizens. With eight proficiency levels and examples of use. In Joint Research Centre. http://publications.jrc.ec.europa.eu/repository/bitstream/JRC106281/web-digcomp2.1pdf_(online).pdf.

  • Cavanaugh, C. (2002). Distance education quality: Success factors for resources, practices and results. In The design and management of effective distance learning programs (pp. 171–189). IGI Global.

  • Chao, I. T., Saj, T., & Hamilton, D. (2010). Using collaborative course development to achieve online course quality standards. The International Review of Research in Open and Distributed Learning, 11(3), 106. https://doi.org/10.19173/irrodl.v11i3.912.

  • Cheng, Y.-M. (2020). Students’ satisfaction and continuance intention of the cloud-based e-learning system: roles of interactivity and course quality factors. Education + Training, 62(9), 1037–1059. https://doi.org/10.1108/ET-10-2019-0245.

  • Cole, M. T., Shelley, D. J., & Swartz, L. B. (2014). Online instruction, e-learning, and student satisfaction: A three year study. The International Review of Research in Open and Distributed Learning, 15(6).

  • Commission on Science and Technology for Development. (2018). Building digital competencies to benefit from existing and emerging technologies, with a special focus on gender and youth dimensions. United Nations Economic and Social Council, March, 1–18. https://ec.europa.eu/jrc/en/news/job-market-fails-unleash-ict-potential-9692.

  • Danchikov, E. A., Prodanova, N. A., Kovalenko, Y. N., & Bondarenko, T. G. (2021). potential of online learning in modern conditions and its use at different levels of education. Linguistics and Culture Review, 5(S1), 578–586. https://doi.org/10.21744/lingcure.v5nS1.1442.

  • Doménech-Betoret, F., Gómez-Artiga, A., & Abellán-Roselló, L. (2019). The Educational Situation Quality Model: A New Tool to Explain and Improve Academic Achievement and Course Satisfaction. Frontiers in Psychology, 10, 1–9. https://doi.org/10.3389/fpsyg.2019.01692

    Article  Google Scholar 

  • Ehiyazaryan, E., & Barraclough, N. (2009). Enhancing employability: integrating real world experience in the curriculum. Education + Training, 51(4), 292–308. https://doi.org/10.1108/00400910910964575.

  • Federal Ministry for Digital and Economic Affairs. (2018). Digital competence framework for austria (T. Nárosy, D. Röthler, & E. Svecnik, Eds.; p. 36). Federal Ministry for Digital and Economic Affairs. https://www.bmdw.gv.at/dam/jcr:f64dce35-0e93-4505-b867-def111cc88dc/DigComp_2_EN-korrigierte Version_barrierefrei.pdf.

  • Finch, D. J., Hamilton, L. K., Baldwin, R., & Zehner, M. (2013). An exploratory study of factors affecting undergraduate employability. Education + Training, 55(7), 681–704. https://doi.org/10.1108/ET-07-2012-0077.

  • Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18(3). https://doi.org/10.1177/002224378101800313.

  • Gopal, R., Singh, V., & Aggarwal, A. (2021). Impact of online classes on the satisfaction and performance of students during the pandemic period of COVID-19. Education and Information Technologies, 26(6), 6923–6947. https://doi.org/10.1007/s10639-021-10523-1

    Article  Google Scholar 

  • Hair, J. F., Howard, M. C., & Nitzl, C. (2020). Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. Journal of Business Research, 109, 101–110. https://doi.org/10.1016/j.jbusres.2019.11.069

    Article  Google Scholar 

  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). In SAGE Publications (2nd ed.). SAGE Publications, Inc.

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202

    Article  Google Scholar 

  • Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128

    Article  Google Scholar 

  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

    Article  Google Scholar 

  • Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(2009), 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014

    Article  Google Scholar 

  • Hillage, J., & Pollard, E. (1998). Employability: Developing a Framework for Policy Analysis, Department for Education and Employment. Institute for Employment Studies, 85(85).

  • Hoyle, R. H. (1995). The Structural Equation Modeling Approach. Basic Concepts and Fundamental Issues. In Structural Equation Modeling: Concepts, Issues, and Applications (pp. 1–15). SAGE Publications, Inc.

  • Ikhsan, R. B., Saraswati, L. A., Muchardie, B. G., Vional, & Susilo, A. (2019). The Determinants of Students’ Perceived Learning Outcomes and Satisfaction in BINUS Online Learning. 2019 5th International Conference on New Media Studies (CONMEDIA), 68–73. https://doi.org/10.1109/CONMEDIA46929.2019.8981813.

  • Ismail, M., Abd Rahim, A. N., Lee, K. H., & Mohd Thahrir, N. F. (2016). Cultural values and career goal of gen-x and gen-y employees: Evidence from selected Malaysian companies. Organizations and Markets in Emerging Economies, 7(2), 43–64. https://doi.org/10.15388/omee.2016.7.2.14207.

  • James, M., & Yun, D. (2018). Exploring student satisfaction and future employment intentions: A case study examination: Is there a link between satisfaction and getting a job?". Higher Education, Skills and Work-Based Learning, 8(2), 117–133. https://doi.org/10.1108/HESWBL-03-2017-0019

    Article  Google Scholar 

  • Jorre de St Jorre, T., & Oliver, B. (2018). Want students to engage? Contextualize graduate learning outcomes and assess for employability. Higher Education Research and Development, 37(1). https://doi.org/10.1080/07294360.2017.1339183.

  • Kang, H. (2021). Sample size determination and power analysis using the G*Power software. Journal of Educational Evaluation for Health Professions, 18(17), 17. https://doi.org/10.3352/jeehp.2021.18.17

    Article  Google Scholar 

  • Kim, C., Li, H., Shin, S.-Y., & Hwang, K.-B. (2013). An Efficient and Effective Wrapper based on Paired t-test for Learning Naive Bayes Classifiers from Large-scale Domains. Procedia Computer Science, 23, 102–112. https://doi.org/10.1016/j.procs.2013.10.014

    Article  Google Scholar 

  • Kock, N. (2017). Common method bias: A full collinearity assessment method for PLS-SEM. In: Latan H. and Noonan R., eds., Partial Least Squares Path Modeling. [online] Cham: Springer International Publishing, pp.245–257. https://doi.org/10.1007/978-3-319-64069-3_11.

  • Krumsvik, R. J. (2008). Situated learning and teachers’ digital competence. Education and Information Technologies, 13(4). https://doi.org/10.1007/s10639-008-9069-5.

  • Kutner, M., Nachtsheim, C., Neter, J., & Li, W. (2005). Applied linear statistical models (5th ed., p. 294). Mcgraw-Hill Irwin.

  • Law, N., Woo, D., de la Torre, J., & Wong, G. (2018). A global framework of reference on digital literacy for indicator 4.4.2. In Educational Technology Research and Development.

  • Lim, Y. S., Halim, H. A., & Ramayah, T. (2022). Should Teachers be Agile Postulating the Self-Determination Theory. International Journal of Management in Education, 16(6), 1. https://doi.org/10.1504/ijmie.2022.10050303

    Article  Google Scholar 

  • Lin, C.-P., Tsai, Y.-H., Joe, S.-W., & Chiu, C.-K. (2012). Modeling the Relationship Among Perceived Corporate Citizenship, Firms’ Attractiveness, and Career Success Expectation. Journal of Business Ethics, 105(1), 83–93. https://doi.org/10.1007/s10551-011-0949-z

    Article  Google Scholar 

  • Moore, J. C. (2005). The Sloan Consortium quality framework and the five pillars. In The Sloan Consortium.

  • Nilashi, M., Abumalloh, R. A., Zibarzani, M., Samad, S., Zogaan, W. A., Ismail, M. Y., Mohd, S., & Akib, N. A. M. (2022). What Factors Influence Students Satisfaction in Massive Open Online Courses? Findings from User-Generated Content Using Educational Data Mining. Education and Information Technologies, 1–35. https://doi.org/10.1007/S10639-022-10997-7/TABLES/8.

  • Olson, K. E., O’Brien, M. A., Rogers, W. A., & Charness, N. (2011). Diffusion of Technology: Frequency of use for Younger and Older Adults. Ageing International, 36(1), 123–145. https://doi.org/10.1007/s12126-010-9077-9

    Article  Google Scholar 

  • Panigrahi, R., Srivastava, P. R., & Panigrahi, P. K. (2021). Effectiveness of e-learning: The mediating role of student engagement on perceived learning effectiveness. Information Technology & People, 34(7), 1840–1862. https://doi.org/10.1108/ITP-07-2019-0380

    Article  Google Scholar 

  • Petruzziello, G., Chiesa, R., & Mariani, M. G. (2022). The Storm Doesn’t Touch me!—The Role of Perceived Employability of Students and Graduates in the Pandemic Era. Sustainability, 14(7), 4303. https://doi.org/10.3390/su14074303

    Article  Google Scholar 

  • Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891.

    Article  Google Scholar 

  • Ringle, C., Wende, S., & Becker, J. (2015). Smart PLS 3.2.8. www.smartpls.com. http://www.smartpls.com.

  • Rothwell, A., Herbert, I., & Rothwell, F. (2008). Self-perceived employability: Construction and initial validation of a scale for university students. Journal of Vocational Behavior, 73(1), 1–12. https://doi.org/10.1016/j.jvb.2007.12.001

    Article  Google Scholar 

  • Scoppio, G., & Luyt, I. (2017). Mind the gap: Enabling online faculty and instructional designers in mapping new models for quality online courses. Education and Information Technologies, 22(3), 725–746. https://doi.org/10.1007/s10639-015-9452-y

    Article  Google Scholar 

  • Scott, F. J., Connell, P., Thomson, L. A., & Willison, D. (2019). Empowering students by enhancing their employability skills. Journal of Further and Higher Education, 43(5), 692–707. https://doi.org/10.1080/0309877X.2017.1394989

    Article  Google Scholar 

  • Shakina, E., Parshakov, P., & Alsufiev, A. (2021). Rethinking the corporate digital divide: The complementarity of technologies and the demand for digital skills. Technological Forecasting and Social Change, 162, 120405. https://doi.org/10.1016/j.techfore.2020.120405.

  • Siddoo, V., Sawattawee, J., Janchai, W., & Thinnukool, O. (2019). An exploratory study of digital workforce competency in Thailand. Heliyon, 5(5), e01723. https://doi.org/10.1016/j.heliyon.2019.e01723.

  • Sinclaire, J. K. (2014). An Empirical Investigation of Student Satisfaction with College Courses. Research in Higher Education Journal, 22, 1–21. http://www.aabri.com/copyright.html.

  • Šiška, L. (2017). The First and the Second Generation of Statistical Methods in Management Accounting Research. The Impact of Globalization on International Finance and Accounting, 441–448. https://doi.org/10.1007/978-3-319-68762-9_48.

  • Soffer, T., & Nachmias, R. (2018). Effectiveness of learning in online academic courses compared with face-to-face courses in higher education. Journal of Computer Assisted Learning, 34(5), 534–543. https://doi.org/10.1111/jcal.12258

    Article  Google Scholar 

  • Vanhercke, D., De Cuyper, N., Peeters, E., & De Witte, H. (2014). Defining perceived employability: A psychological approach. Personnel Review, 43(4), 592–605. https://doi.org/10.1108/PR-07-2012-0110

    Article  Google Scholar 

  • Zimmerman, W., Altman, B., Simunich, B., Shattuck, K., & Burch, B. (2020). Evaluating Online Course Quality: A Study on Implementation of Course Quality Standards. Online Learning, 24(4). https://doi.org/10.24059/olj.v24i4.2325.

Download references

Funding

This research was funded by Penang Youth Development Corporation, grant number 304 /PMGT /6501158 /P164. The funding source did not play a role in the study design, the collection, analysis, and interpretation of data, the writing of the report, or the decision to submit this manuscript for publication.

Author information

Authors and Affiliations

  1. School of Management, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia

    Daisy Mui Hung Kee & Aizza Anwar

  2. Ministry of Education, Putrajaya, Malaysia

    Lim Yi Shern

  3. Penang Youth Development Corporation, Jelutong, Malaysia

    Sai Ling Gwee

Authors
  1. Daisy Mui Hung Kee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Aizza Anwar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lim Yi Shern
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sai Ling Gwee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Daisy Mui Hung Kee.

Ethics declarations

Institutional review board

Not Applicable.

Informed consent statement

Informed consent was obtained from all subjects before the study.

Conflicts of interest

The authors declare no conflict of 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

Kee, D.M.H., Anwar, A., Shern, L.Y. et al. Course quality and perceived employability of Malaysian youth: The mediating role of course effectiveness and satisfaction. Educ Inf Technol 28, 13805–13822 (2023). https://doi.org/10.1007/s10639-023-11737-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-023-11737-1

Keywords

Search

Navigation