Keywords
consumer satisfaction
future intension to use
computer self-efficacy
university students
How to Cite
Abstract
With the growing interest in e-education, particularly in the context of the pandemic, more scientific studies have been undertaken recently to analyze and identify factors influencing e-learning acceptance. Indeed, e-learning acceptance depends on many different factors, but no consensus has been reached on factors that contribute most to the acceptance of e-learning solutions. Consequently, this article ascertains the factors and their relationships behind the satisfaction and the future intention to use e-learning among Polish university students. From among the factors analyzed in the literature, the author examined the relationship between computer self-efficacy (CSE), facilitating conditions (FC), satisfaction (S) and the future intention to use e-learning (FI). Data were gathered using structured questionnaires and computer-assisted web interviewing (CAWI). Students at Bialystok University of Technology (Poland) were sent an electronic link to the questionnaires using the internal e-mail system. Eight hundred three forms were returned fully filled out. Aiming to ascertain the extent to which measured variables describe the number of constructs, the author made the Confirmatory Factor Analysis (CFA). The Generalized Least Squares (GLS) estimator was used to calculate the values of model parameters.The results confirmed that higher computer self-efficacy and better facilitation conditions result in greater user satisfaction with e-learning. However, facilitating conditions impact user satisfaction more than computer self-efficacy construct variables. Based on the findings, user satisfaction is a strong anticedents of the future intention to use e-learning.
References
Abdullah F., Ward R., Ahmed E. (2016) Investigating the influence of the most commonly used external variables of TAM on students' Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75-90. https://doi.org. DOI: https://doi.org/10.1016/j.chb.2016.05.014
Agudo-Peregrina A.F., Hernández-García A., Pascual-Miguel F.J. (2014) Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning. Computers in Human Behavior, 34, 301-314. https://doi.org. DOI: https://doi.org/10.1016/j.chb.2013.10.035
Ahmad N., Norazah Umar, Kadar R., Othman J. (2020) Factors Affecting Students' Acceptance of e-Learning System in Higher Education. Journal of Computing Research and Innovation, 5(2), 54-65. DOI: https://doi.org/10.24191/jcrinn.v5i2.134
Al-Azawei A. (2019) What drives successful social media in education and e-learning? A comparative study on Facebook and Moodle. Journal of Information Technology Education: Research, 18, 253-274. DOI: https://doi.org/10.28945/4360
Al-Azawei, A., Parslow P., Lundqvist, K. (2017) Investigating the effect of learning styles in a blended e-learning system: An extension of the technology acceptance model (TAM). Australasian Journal of Educational Technology, 33(2), 11-23. DOI: https://doi.org/10.14742/ajet.2741
Al-Emran M., Mezhuyev V., Kamaludin A. (2018) Technology Acceptance Model in M-learning context: A systematic Review. Computers & Education, 125, 389-412. DOI: https://doi.org/10.1016/j.compedu.2018.06.008
Al-Fraihat D., Joy M., Masa'deh R., Sinclair J. (2020) Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, 102, 67-86. DOI: https://doi.org/10.1016/j.chb.2019.08.004
Al-Maroof R.S., Alhumaid K., Akour I., Salloum S. (2021) Factors That Affect E-Learning Platforms after the Spread of COVID-19: Post Acceptance Study. Data, 6(5), 49. DOI: https://doi.org/10.3390/data6050049
Alamri M.M., Almaiah M.A., Al-Rahmi W.M. (2020) The Role of Compatibility and Task-Technology Fit (TTF): On Social Networking Applications (SNAs) Usage as Sustainability in Higher Education. IEEE Access, 8, 161668-161681. DOI: https://doi.org/10.1109/ACCESS.2020.3021944
Aldammagh Z. Abdaljawad R., Obaid T. (2021) Factor Driving E-Learning Adoption in Palestine: An Integration of Technology Acceptance Model and is Success Model. Financial Internet Quarterly, 17(1), 41-49. DOI: https://doi.org/10.2478/fiqf-2021-0005
Alenezi A.R., Karim A. (2010) An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students' intention to use e-learning: A case study from Saudi Arabian governmental universities. Turkish Online Journal of Educational Technology-TOJET, 9(4), 22-34.
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. DOI: https://doi.org/10.1109/ACCESS.2019.2956349
Alsabawy A.Y., Cater-Steel A., Soar J. (2013) IT infrastructure services as a requirement for e-learning system success. Computers & Education, 69, 431-451. DOI: https://doi.org/10.1016/j.compedu.2013.07.035
Alyoussef I.Y. (2021) E-Learning Acceptance: The Role of Task-Technology Fit as Sustainability in Higher Education. Sustainability, 13, 6450. https://doi.org/0.3390/su13116450.
Ameen N., Willis R., Noori Abdullah M., Shah M. (2019) Towards the successful integration of e-learning systems in higher education in Iraq: A student perspective. British Journal of Educational Technology, 50(3), 1434. DOI: https://doi.org/10.1111/bjet.12651
Aparicio M., Bacao F., Oliveira T. (2017) Grit in the path to e-learning success. Computers in Human Behavior, 66, 388-399. DOI: https://doi.org/10.1016/j.chb.2016.10.009
Arain A.A., Hussain Z., Rizvi W.H., Vighio M.S. (2019) Extending UTAUT2 toward acceptance of mobile learning in the context of higher education. Universal Access in the Information Society, 18, 659-673. DOI: https://doi.org/10.1007/s10209-019-00685-8
Arteaga Sánchez R., Duarte Hueros A. (2010) Motivational factors that influence the acceptance of Moodle using TAM. Computers in Human Behavior, 26(6), 1632-1640. DOI: https://doi.org/10.1016/j.chb.2010.06.011
Asher Irfan Saroia, Shang Gao (2019) Investigating university students' intention to use mobile learning management systems in Sweden. Innovations in Education and Teaching International, 56(5), 569-580. DOI: https://doi.org/10.1080/14703297.2018.1557068
Baber H. (2021) Modelling the acceptance of e-learning during the pandemic of COVID-19-A study of South Korea. The International Journal of Management Education, 19(2), 100503. DOI: https://doi.org/10.1016/j.ijme.2021.100503
Bharadwaj S., Deka S. (2021) Behavioural intention towards investment in cryptocurrency: an integration of Rogers' diffusion of innovation theory and the technology acceptance model. Forum Scientiae Oeconomia, 9(4). DOI: https://doi.org/10.23762/FSO_VOL9_NO4_7
Buckley K.M. (2003) Evaluation of classroom-based, Web-enhanced, and Web-based distance learning nutrition courses for undergraduate nursing. The Journal of Nursing Education, 42(8), 367-370. DOI: https://doi.org/10.3928/0148-4834-20030801-09
Chang C. (2013) Exploring the determinants of e-learning systems continuance intention in academic libraries. Library Management, 34(1/2), 40-55. DOI: https://doi.org/10.1108/01435121311298261
Chen H.R., Tseng H.F. (20212) Factors that influence acceptance of web-based e-learning system for the in-service education of junior high school teachers in Taiwan. Evaluation and Program Planning, 35, 398-406. DOI: https://doi.org/10.1016/j.evalprogplan.2011.11.007
Cheng W.W.L. (2019) Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM). Educational Technology Research & Development, 67(1), 21-37. DOI: https://doi.org/10.1007/s11423-018-9598-6
Choudhury V., Karahanna E. (2008) The relative advantage of electronic channels: A multidimensional view. MIS Quarterly, 32(1), 179-200. DOI: https://doi.org/10.2307/25148833
Compeau D.R., Higgins C.A. (1995) Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211. DOI: https://doi.org/10.2307/249688
Davis F.D. (1985) A technology acceptance model for empirically testing new end-user information systems: Theory and results, Cambridge, MA: MIT Sloan School of Management.
DeLone W.H., McLean E.R. (2003) The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9-30. DOI: https://doi.org/10.1080/07421222.2003.11045748
Dečman M. (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. DOI: https://doi.org/10.1016/j.chb.2015.03.022
Duffin E. (2020) E-learning and digital education - Statistics & Facts, 2020. https://www.statista.com/topics/3115/e-learning-and-digital-education/, дата обращения 01.03.2021.
Ejdys J. (2018) Zaufanie do technologii w e-administracji, Białystok: Oficyna Wydawnicza Politechniki Białostockiej (in Polish).
Ejdys J. (2021) Factors Affecting the Adoption of e-Learning at University Level. WSEAS Transactions on Business and Economics, 18(3), 13-323. DOI: https://doi.org/10.37394/23207.2021.18.32
Ejdys J., Gulc A. (2020) Trust in Courier Services and Its Antecedents as a Determinant of Perceived Service Quality and Future Intention to Use Courier Service. Sustainability, 12(21), 9088. DOI: https://doi.org/10.3390/su12219088
Ejdys J., Halicka K. (2018) Sustainable Adaptation of New Technology - The Case of Humanoids Used for the Care of Older Adults. Sustainability, 10(10), 3770. DOI: https://doi.org/10.3390/su10103770
Emelyanova N., Voronina E. (2014) Introducing a learning management system at a Russian university: Students' and teachers' perceptions. The International Review of Research in Open and Distance Learning, 15(1), 272-289. DOI: https://doi.org/10.19173/irrodl.v15i1.1701
Fianu E., Blewett C., Ampong G.O. (2020) Toward the development of a model of student usage of MOOCs. Education + Training, 62(5), 521-541. 10.1108/ ET-11-2019-0262. DOI: https://doi.org/10.1108/ET-11-2019-0262
Fornell C., Larcker D. (1981) Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50. DOI: https://doi.org/10.2307/3151312
Fritsch M., Greve M., Wyrwich M. (2021) The COVID-19 Pandemic and Entrepreneurship in Germany. Foresight and STI Governance, 15(4), 42-51. DOI: https://doi.org/10.17323/2500-2597.2021.4.42.51
Gulc A. (2020) Determinants of Courier Service Quality in e-Commerce from Customers' Perspective. Quality Innovation Prosperity, 24(2), 137-152. DOI: https://doi.org/10.12776/QIP.V24I2.1438
Gulc A. (2021) Multi-stakeholder perspective of courier service quality in B2C e-commerce. PLoS ONE, 16(5), 0251728. DOI: https://doi.org/10.1371/journal.pone.0251728
Hair J.F., Black W.C., Babin B.J., Anderson R.E., Tatham R.L. (2013) Multivariate Data Analysis. Technometrics, 49, 103-104.
Hassanzadeh A., Kanaani F., Elahi S. (2012) A model for measuring e-learning systems success in universities. Expert Systems with Applications, 39(12), 10959-10966. DOI: https://doi.org/10.1016/j.eswa.2012.03.028
Hsiao C.H., Yang C. (2011) The intellectual development of the technology acceptance model: A co-citation analysis. International Journal of Information Management, 31(2), 128-136. DOI: https://doi.org/10.1016/j.ijinfomgt.2010.07.003
Hwang Y., Kim D. J. (2007) Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746-760. DOI: https://doi.org/10.1016/j.dss.2006.12.008
Iacobucci D. (2010) Structural equations modeling: Fit Indices, sample size, and advanced topics. Journal of Consumer Psychology, 20, 90-98. 10.1016/j. jcps.2009.09.003. DOI: https://doi.org/10.1016/j.jcps.2009.09.003
Ibrahim R., Leng N.S., Yusoff R.C.M., Samy G.N., Masrom S., Rizman Z.I. (2017) E-learning acceptance based on technology acceptance model (TAM). Journal of Fundamental and Applied Sciences, 9(4S), 871-889. DOI: https://doi.org/10.4314/jfas.v9i4s.50
Islam M.T., Selim A.S.M. (2006) Information and Communication Technologies for the Promotion of Open and Distance Learning in Bangladesh. Journal of Agriculture & Rural Development, 4(1), 36-42. DOI: https://doi.org/10.3329/jard.v4i1.765
Jimenez I.A.C., García L.C.C., Violante M.G., Marcolin F., Vezzetti E. (2021) Commonly Used External TAM Variables in e-Learning, Agriculture and Virtual Reality Applications. Future Internet, 13(1), 7. DOI: https://doi.org/10.3390/fi13010007
Jung Y., Lee J. (2018) Learning engagement and persistence in massive open online courses (MOOCS). Computers and Education, 122, 9-22. DOI: https://doi.org/10.1016/j.compedu.2018.02.013
Jöreskog K.G., Sörbom D. (1979) Advances in Factor Analysis and Structural Equation Models, Cambridge: Abt Books.
Karaali D., Gumussoy C.A., Calisir F. (2011) Factors affecting the intention to use a web-based learning system among blue-collar workers in the automotive industry. Computers in Human Behavior, 27(1), 343-354. DOI: https://doi.org/10.1016/j.chb.2010.08.012
Kim T.T., Suh Y.K., Lee G., Choi B. (2010) Modelling roles of task-technology fit and self-efficacy in hotel employees' usage behaviours of hotel information systems. International Journal of Tourism Research, 12(6), 709-725. DOI: https://doi.org/10.1002/jtr.787
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. DOI: https://doi.org/10.1016/j.chb.2017.02.062
Konarski R. (2010) Modele równań strukturalnych. Teoria i praktyka, Warszawa: PWN (in Polish).
Kurfal M., Arifoglu A., Tokdemir G., Paçin Y. (2017) Adoption of e-government services in Turkey. Computers in Human Behavior, 66, 168-178. DOI: https://doi.org/10.1016/j.chb.2016.09.041
Mathivanan S.K., Jayagopal P., Ahmed S., Manivannan S.S., Kumar P.J., Raja K.T., Dharinya S.S., Prasad R.G. (2021) Adoption of E-Learning during Lockdown in India. International Journal of System Assurance Engineering and Management. DOI: https://doi.org/10.1007/s13198-021-01072-4
Milićević V., Denić N., Milićević Z., Arsić L., Spasić-Stojković M., Petković D., Stojanović J., Krkic M., Milovančević N.S., Jovanović A. (2021) E-learning perspectives in higher education institutions. Technological Forecasting and Social Change, 166. DOI: https://doi.org/10.1016/j.techfore.2021.120618
Mohammadi H. (2015a) Social and individual antecedents of m-learning adoption in Iran. Computers in Human Behavior, 49, 191-207. DOI: https://doi.org/10.1016/j.chb.2015.03.006
Mohammadi H. (2015b) Investigating users' perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-374. DOI: https://doi.org/10.1016/j.chb.2014.07.044
Mohan M.M., Upadhyaya P., Pillai K.R. (2020) Intention and barriers to use MOOCs: An investigation among the post graduate students in India. Education and Information Technologies, 25, 5017-5031. DOI: https://doi.org/10.1007/s10639-020-10215-2
Mouakket S., Bettayeb A.M. (2015) Investigating the factors influencing continuance usage intention of learning management systems by university instructors: The Blackboard system case. International Journal of Web Information Systems, 11(4), 491-509. DOI: https://doi.org/10.1108/IJWIS-03-2015-0008
Muyesser Eraslan Yalcin, Birgul Kutlu (2019) Examination of students' acceptance of and intention to use learning management systems using extended TAM. British Journal of Educational Technology, 50(5), 2214-2431. DOI: https://doi.org/10.1111/bjet.12798
OECD (2020) The potential of Online Learning for adults: Early lessons from the COVID-19 crisis, Paris: OECD. https://www.oecd.org/coronavirus/policy-responses/the-potential-of-online-learning-for-adults-early-lessons-from-the-covid-19-crisis-ee040002/, дата обращения 06.04.2021.
Odegbesan O.A., Ayo Ch., Oni A.A., Tomilayo F.A., Gift O.Ch., Nnaemeka E.U. (2019) The prospects of adopting e-learning in the Nigerian education system: A case study of Covenant University. Journal of Physics: Conference Series, 1299. DOI: https://doi.org/10.1088/1742-6596/1299/1/012058
Olum R., Atulinda L., Kigozi E., Nassozi D.R., Mulekwa A., Bongomin F., Kiguli S. (2020) Medical Education and E-Learning During COVID-19 Pandemic: Awareness, Attitudes, Preferences, and Barriers Among Undergraduate Medicine and Nursing Students at Makerere University, Uganda. Journal of Medical Education and Curricular Development, 7, 1-9. DOI: https://doi.org/10.1177/2382120520973212
Ozdamli F., Uzunboylu H. (2014) M-learning adequacy and perceptions of students and teachers in secondary schools. British Journal of Educational Technology, 46(1), 159-172. DOI: https://doi.org/10.1111/bjet.12136
Passmore D.L. (2000) Impediments to adoption of web-based course delivery among university faculty. ALN Magazine, 4(2).
Petter S., McLean E.R. (2009) A meta-analytic assessment of the DeLone and McLean IS success model: An examination of IS success at the individual level. Information & Management, 46(3), 159-166. DOI: https://doi.org/10.1016/j.im.2008.12.006
Pituch K.A., Lee Y.K. (2006) The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222-244. DOI: https://doi.org/10.1016/j.compedu.2004.10.007
Rajeh M.T., Abduljabbar F.H., Alqahtani S.M., Waly F.J., Alnaami I., Aljurayyan A., Alzaman N. (2021) Students' satisfaction and continued intention toward e-learning: A theory-based study. Medical Education Online, 26, 1961348. DOI: https://doi.org/10.1080/10872981.2021.1961348
Raza S.A., Qazi W., Khan K.A., Salam J. (2021) Social Isolation and Acceptance of the Learning Management System (LMS) in the time of COVID-19 Pandemic: An Expansion of the UTAUT Model. Journal of Educational Computing Research, 59(2), 183-208. DOI: https://doi.org/10.1177/0735633120960421
Recker J. (2016) Reasoning about discontinuance of information system use. Journal of Information Technology Theory and Application, 17(1), 41-66.
Salloum S.A., Alhamad A.Q.M., Al-Emran M., Monem A.A., Shaalan K. (2019) Exploring Students' Acceptance of E-Learning Through the Development of a Comprehensive Technology Acceptance Model. IEEE Access, 7, 128445-128462. DOI: https://doi.org/10.1109/ACCESS.2019.2939467
Sanchez-Franco M.J. (2009) The Moderating Effects of Involvement on the Relationships between Satisfaction, Trust and Commitment in e-Banking. Journal of Interactive Marketing, 23(3), 247-258. DOI: https://doi.org/10.1016/j.intmar.2009.04.007
UNESCO (2020) School closures caused by Coronavirus (Covid-19), Paris: UNESCO. https://en.unesco.org/covid19/educationresponse, дата обращения 15.05.2021.
Venkatesh V., Davis F.D. (1996) A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. DOI: https://doi.org/10.1111/j.1540-5915.1996.tb00860.x
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. DOI: https://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. MIS Quarterly, 36(1), 157-178. DOI: https://doi.org/10.2307/41410412
Wang W.T., Wang C.C. (2009) An empirical study of instructor adoption of web-based learning systems. Computers & Education, 53(3), 761-774. DOI: https://doi.org/10.1016/j.compedu.2009.02.021
Weerathunga P.R., Samarathunga W.H.M.S., Rathnayake H.N., Agampodi S.B., Nurunnabi M., Madhunimasha M.M.S.C. (2021) The COVID-19 Pandemic and the Acceptance of E-Learning among University Students: The Role of Precipitating Events. Education Science, 11(8), 436. DOI: https://doi.org/10.3390/educsci11080436
Williams M.D., Rana N.P., Dwivedi Y.K. (2015) The unified theory of acceptance and use of technology (UTAUT): A literature review. Journal of Enterprise Information Management, 28(3), 443-488. DOI: https://doi.org/10.1108/JEIM-09-2014-0088
Wu J. H., Tennyson R. D., Hsia T. L. (2010). A study of student satisfaction in a blended e-learning system environment. Computers & Education, 55(1), 155-164. DOI: https://doi.org/10.1016/j.compedu.2009.12.012
Yakubu M.N., Dasuki S.I. (2018) Assessing eLearning systems success in Nigeria: An application of the DeLone and McLean information systems success model. Journal of Information Technology Education: Research, 17, 182-202. DOI: https://doi.org/10.28945/4077
Yang H.H., Zhu S., MacLeod J. (2018) Promoting education equity in rural and underdeveloped areas: Cases on computer-supported collaborative teaching in China. Eurasia Journal of Mathematics, Science and Technology Education, 14(6), 2393-2405. DOI: https://doi.org/10.29333/ejmst/89841
Yekefallah L., Namdar P., Panahi R., Dehghankar L. (2021) Factors related to students' satisfaction with holding e-learning during the Covid-19 pandemic based on the dimensions of e-learning. Heliyon, 7, e07628. DOI: https://doi.org/10.1016/j.heliyon.2021.e07628
Yi M., Hwang Y. (2003) Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 431-449. DOI: https://doi.org/10.1016/S1071-5819(03)00114-9
Zardari B.A., Hussain Z., Arain A.A., Rizvi W.H., Vighio M.S. (2021) Development and Validation of User Experience-Based E-Learning Acceptance Model for Sustainable Higher Education. Sustainability, 13, 6201. DOI: https://doi.org/10.3390/su13116201
This work is licensed under a Creative Commons Attribution 4.0 International License.