The Influence of Cognitive Absorption on Perceived Usefulness and Ease of Use in Online Learning: A Study of Ghanaian Distance Learning Students
DOI:
https://doi.org/10.26437/ajar.v11i4.1224Keywords:
Absorption. cognitive. distance learning. online. studentsAbstract
Purpose: This study, therefore, sought to measure the effect of cognitive absorption on the intention to use an online learning system. Additionally, evaluate the effect of perceived usefulness on the intention to use the online learning system.
Design/methodology/approach: A Quantitative research approach was employed in this study. the population of this study includes all distance learning undergraduate and graduate students pursuing various programs in Ghana. A convenient sampling method was used to sample 595 distance learning students. The study then employed SMART PLS 3.0 to estimate the various objectives of the study.
Research limitations: The study only sampled distance learning students within the greater Accra region. This overlooks students in other regions of Ghana who may face unique challenges not commonly encountered in cities like Accra.
Findings: The results revealed that perceived usefulness had a positive effect on the intention to use online learning systems. Additionally, perceived ease of use has a positive and significant effect on the intention to use the online learning system. The study's findings show that perceived ease of use had a positive effect on the intention to use the online system.
Practical Implication: The study suggests that universities should adopt robust information technology systems to enhance the ease of use for students.
Social Implication: This finding suggests that students from institutions with weaker technological resources or support systems may experience reduced cognitive absorption, potentially widening the digital divide and exacerbating educational inequality.
Originality/value: This paper was conducted to examine the interaction between cognitive absorption and intention to use online learning systems.
References
Abawi, K. (2008). Qualitative and Quantitative Research. 3–12.
Agyeiwaah, E., Badu, F., Gamor, E., & Hsu, F. (2020). Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID- 19 . The COVID-19 resource centre is hosted on Elsevier Connect , the company ’ s public news and information . January.
Akkuş Çutuk, Z. (2021). Investigating the Relationship Among Social Media Addiction, Cognitive Absorption, and Self-Esteem. Malaysian Online Journal of Educational Technology, 9(2), 42–51. https://doi.org/10.52380/mojet.2021.9.2.211
Al-Rahmi, W. M., Othman, M. S., & Yusuf, L. M. (2015). Exploring the factors that affect student satisfaction through using E-learning in Malaysian higher education institutions. Mediterranean Journal of Social Sciences, 6(4S1), 299–310. https://doi.org/10.5901/mjss.2015.v6n4s1p299
Alvarez, L., Carrupt, R., Audrin, C., & Gay, P. (2022). Self-Reported Flow in Online Learning Environments for Teacher Education: A Quasi-Experimental Study Using a Counterbalanced Design. Education Sciences, 12(5), 351. https://doi.org/10.3390/educsci12050351
Ansong-Gyimah, K. (2020). Students’ perceptions and continuous intention to use elearning systems: The case of google classroom. International Journal of Emerging Technologies in Learning, 15(11), 236–244. https://doi.org/10.3991/IJET.V15I11.12683
Asiamah, N., Mensah, H. K., & Oteng-abayie, E. F. (2017). Do Larger Samples Really Lead to More Precise Estimates ? A Simulation Study. 5(January), 9–17. https://doi.org/10.12691/education-5-1-2
Aspers, P., & Corte, U. (2019). What is Qualitative in Qualitative Research. Qualitative Sociology. https://doi.org/10.1007/s11133-019-9413-7
Babeș, O.-R. I. (2020). Feedforward for University Geographical Online Education during the COVID- 19 Pandemic. 19, 76–85.
Balakrishnan, J., & Dwivedi, Y. K. (2021). Role of cognitive absorption in building user trust and experience. Psychology and Marketing, 38(4), 643–668. https://doi.org/10.1002/mar.21462
Butt, S., Mahmood, A., & Saleem, S. (2022). The role of institutional factors and cognitive absorption on students’ satisfaction and performance in online learning during COVID 19. Plos One, 17(6), e0269609. https://doi.org/10.1371/journal.pone.0269609
Cavus, N., Sani, A. S., Haruna, Y., & Lawan, A. A. (2021). Efficacy of social networking sites for sustainable education in the era of COVID-19: A systematic review. Sustainability (Switzerland), 13(2), 1–18. https://doi.org/10.3390/su13020808
Celik, V., Yesilyurt, E., Korkmaz, O., & Usta, E. (2017). From the Perspective of Loneliness and Cognitive Absorption Internet Addiction as Predictor and Predicted. EURASIA Journal of Mathematics, Science and Technology Education, 10(6), 581–594. https://doi.org/10.12973/eurasia.2014.23560a
Cheng, Y. M. (2022). What roles do quality and cognitive absorption play in evaluating cloud-based e-learning system success? Evidence from medical professionals. Interactive Technology and Smart Education. https://doi.org/10.1108/ITSE-12-2021-0222
Ching-Ter, C., Hajiyev, J., & Su, C. R. (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? The General Extended Technology Acceptance Model for E-learning approach. Computers and Education, 111, 128–143. https://doi.org/10.1016/j.compedu.2017.04.010
Conrad, C., & Bliemel, M. (2016). Psychophysiological measures of cognitive absorption and cognitive load in E-learning applications. 2016 International Conference on Information Systems, ICIS 2016, 2014, 1–9.
Creswell, J. W. (2014). The Selection of a Research Approach. Research Design, 3–23. https://doi.org/45593:01
Creswell, J. W., & Creswell, J. D. (2018). Qualitative, Quantitative, and Mixed Methods Approaches.
Doyle, L., Brady, A. M., & Byrne, G. (2009). An overview of mixed methods research. Journal of Research in Nursing, 14(2), 175–185. https://doi.org/10.1177/1744987108093962
Elumalai, K. V., Sankar, J. P., Kalaichelvi, R., John, J. A., Menon, N., Alqahtani, M. S. M., & Abumelha, M. A. (2019). Factors Affecting The Quality Of E-Learning During The Covid-19 Pandemic From The Perspective Of Higher Education Students. Journal of Information Technology Education: Research, 19, 731–753. https://doi.org/10.28945/4628
Fianu, E., Blewett, C., Ampong, G. O. A., & Ofori, K. S. (2018). Factors affecting MOOC usage by students in selected Ghanaian universities. Education Sciences, 8(2). https://doi.org/10.3390/educsci8020070
Guinaliu-Blasco, M., Hernández-Ortega, B., & Franco, J. L. (2019). The effect of cognitive absorption on marketing learning performance. Spanish Journal of Marketing - ESIC, 23(2), 249–271. https://doi.org/10.1108/SJME-10-2018-0048
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
Hammouri, Q., & Abu-Shanab, E. (2017). Exploring the factors influencing employees’ satisfaction toward e-tax systems. International Journal of Public Sector Performance Management, 3(2), 169–190. https://doi.org/10.1504/IJPSPM.2017.084673
Hou, A. C. Y., Shiau, W. L., & Shang, R. A. (2019). The involvement paradox: The role of cognitive absorption in mobile instant messaging user satisfaction. Industrial Management and Data Systems, 119(4), 881–901. https://doi.org/10.1108/IMDS-06-2018-0245
Ismail, S. (2006). Detailed review of Roger’s Diffusion of innovations theory and educational technology. The Turkish Online Journal of Educational Technology, 5(2), 14–23. https://files.eric.ed.gov/fulltext/ED501453.pdf
Jaiyeoba, O. O., & Iloanya, J. (2019). E-learning in tertiary institutions in Botswana: apathy to adoption. International Journal of Information and Learning Technology, 36(2), 157–168. https://doi.org/10.1108/IJILT-05-2018-0058
Kalyar, M. N., Shoukat, A., & Shafique, I. (2019). Enhancing firms’ environmental performance and financial performance through green supply chain management practices and institutional pressures. Sustainability Accounting, Management and Policy Journal, 11(2), 451–476. https://doi.org/10.1108/SAMPJ-02-2019-0047
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(8), 607–610. https://doi.org/10.1261/rna.2763111
Latifi, M. A., Nikou, S., & Bouwman, H. (2021). Business model innovation and firm performance: Exploring causal mechanisms in SMEs. Technovation. https://doi.org/10.1016/j.technovation.2021.102274
Leong, P. (2011). Role of social presence and cognitive absorption in online learning environments. Distance Education, 32(1), 5–28. https://doi.org/10.1080/01587919.2011.565495
Maarouf, H. (2019). Pragmatism as a Supportive Paradigm for the Mixed Research Approach: Conceptualizing the Ontological, Epistemological, and Axiological Stances of Pragmatism. International Business Research. https://doi.org/10.5539/ibr.v12n9p1
Mertens, D. M. (2010). Transformative mixed methods research. Qualitative Inquiry. https://doi.org/10.1177/1077800410364612
Mill, R. C. (2011). A Comprehensive Model Of Customer Satisfaction In Hospitality And Tourism: Strategic Implications For Management. International Business & Economics Research Journal (IBER), 1(6), 7–18. https://doi.org/10.19030/iber.v1i6.3942
Moreno, V., Cavazotte, F., & Alves, I. (2017). Explaining university students’ effective use of e-learning platforms. British Journal of Educational Technology, 48(4), 995–1009. https://doi.org/10.1111/bjet.12469
Muijs, D. (2015). Quantitative research. In Doing Quantitative Research in Education with SPSS (Vol. 29, Issue 31). https://doi.org/10.7748/ns.29.31.44.e8681
Nathan, S., Newman, C., & Lancaster, K. (2019). Qualitative interviewing. In Handbook of Research Methods in Health Social Sciences. https://doi.org/10.1007/978-981-10-5251-4_77
Park, Y. S., Konge, L., & Artino, A. R. (2020). The Positivism Paradigm of Research. In Academic Medicine. https://doi.org/10.1097/ACM.0000000000003093
Reychav, I., & Wu, D. (2015). Are your users actively involved? A cognitive absorption perspective in mobile training. Computers in Human Behavior, 44, 335–346. https://doi.org/10.1016/j.chb.2014.09.021
Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. International Journal of Human Resource Management. https://doi.org/10.1080/09585192.2017.1416655
Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of Human Computer Studies, 64(8), 683–696. https://doi.org/10.1016/j.ijhcs.2006.01.003
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019). Diffusion of innovations. In An Integrated Approach to Communication Theory and Research, Third Edition. https://doi.org/10.4324/9780203710753-35
Salimon, M. G., Sanuri, S. M. M., Aliyu, O. A., Perumal, S., & Yusr, M. M. (2021). E-learning satisfaction and retention: a concurrent perspective of cognitive absorption, perceived social presence and technology acceptance model. Journal of Systems and Information Technology, 23(1), 109–129. https://doi.org/10.1108/JSIT-02-2020-0029
Samuel, N., Onasanya, S. A., & Olumorin, C. O. (2018). Perceived usefulness, ease of use and adequacy of use of mobile technologies by Nigerian university lecturers. International Journal of Education and Development Using Information and Communication Technology (IJEDICT), 14(3), 5–16.
Schoonenboom, J., & Johnson, R. B. (2017). Wie man ein Mixed Methods-Forschungs-Design konstruiert. Kolner Zeitschrift Fur Soziologie Und Sozialpsychologie, 69, 107–131. https://doi.org/10.1007/s11577-017-0454-1
Syed, A. A. B., Hashim, F., & Amran, A. (2019). Determinants of Green Banking Adoption: A Theoretical Framework. KnE Social Sciences, 2019, 1–14. https://doi.org/10.18502/kss.v3i22.5041
Tagoe, M. (2012). Students ’ perceptions on incorporating e-learning into teaching and learning at the University of Ghana. International Journal of Education and Development Using Information and Communication Technology, 8(1), 91–103.
Teeratansirikool, L., Siengthai, S., Badir, Y., & Charoenngam, C. (2013). Competitive strategies and firm performance: The mediating role of performance measurement. International Journal of Productivity and Performance Management, 62(2), 168–184. https://doi.org/10.1108/17410401311295722
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003a). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems. https://doi.org/10.2307/30036540
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003b). Venkatesh et al (2003) User acceptance of information technology (1). MIS Quarterly.
Voogt, J. (2009). How different are ICT-supported pedagogical practices from extensive and non-extensive ICT-using science teachers? Education and Information Technologies, 14(4), 325–343. https://doi.org/10.1007/s10639-009-9092-1
Zare, H., & Yazdanparast, S. (2013). The causal Model of effective factors on Intention to use of information technology among payam noor and Traditional universities students. Life Science Journal, 10(2), 46–50.
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