Quality Requirements for Continuous Use of E-learning Systems at Public vs. Private Universities in Spain

Referencias bibliográficas

• Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior, 56, 238-256. doi:10.1016/j.chb.2015.11.036.
• Al-Husseini, S., & Elbeltagi, I. (2016). Transformational leadership and innovation: a comparison study between Iraq's public and private higher education. Studies in Higher Education, 41(1), 159-181. doi:10.1080/03075079.2014.927848.
• Al-Samarraie, H., Teng, B. K., Alzahrani, A. I., & Alalwan, N. (2018). E-learning continuance satisfaction in higher education: a unified perspective from instructors and students. Studies in Higher Education, 43(11), 2003-2019. doi:10.1080/03075079.2017.1298088
• Almutairi, B. M., & Albraithen, M. A. (2018). A Framework on the Critical Success Factors of Virtual School System Implementation: A Systematic Literature Review. In 2018 1st International Conference on Computer Applications & Information Security (ICCAIS) (pp. 1-6). IEEE.
• Ameen, N., Willis, R., Abdullah, M. N., & 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), 1434-1446. doi: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:10.1016/j.chb.2016.10.009
• Arheiam, A. A., El Tantawi, M., Al-Omami, M., Peeran, S. W., & Elmisalati, W. (2019). Perceptions of Stress Among Dental Students Living in a War-Affected Zone. Journal of dental education, 83(1), 48-55. doi:10.21815/JDE.019.006
• Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94. doi:10.1007/BF02723327
• Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173-1182. http://webcom.upmf-grenoble.fr/LIP/Perso/DMuller/GSERM/Articles/Journal%20of%20Personality%20and%20Social%20Psychology%201986%20Baron.pdf
• Bates, A.W. (T) (2015). Teaching in a Digital Age: Guidelines for designing teaching and learning for a digital age. University of British Columbia.https://opentextbc.ca/teachinginadigitalage/
• Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS Quarterly, 25(3), 351-370. doi:10.2307/3250921
• Chatterjee, A., Ghosh, K., & Chatterjee, B. (2020). A Study on Content Selection and Cost-Effectiveness of Cognitive E-Learning in Distance Education of Rural Areas. In Emerging Technology in Modelling and Graphics (pp. 783-786). Springer, Singapore. doi:10.1007/978-981-13-7403-6_69
• Chung, C., & Babin, L. A. (2017). New technology for education: Moodle. In The Customer is NOT Always Right? Marketing Orientationsin a Dynamic Business World (pp. 661-661). Springer, Cham.
• Cidral, W. A., Oliveira, T., Di Felice, M., & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education, 122, 273-290. doi:10.1016/j.compedu.2017.12.001
• Ćukušić, M., Alfirević, N., Granić, A., & Garača, Ž. (2010). e-Learning process management and the e-learning performance: Results of a European empirical study. Computers & Education, 55(2), 554-565. doi:10.1016/j.compedu.2010.02.017
• de la Iglesia Villasol, M. C. (2021). Cambios en el patrón de los usos digitales por el Covid-19. Aplicación del Learning Analytics a un estudio de caso entre estudiantes universitarios. Digital Education Review, (39), 192-212.
• DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95. doi:10.1287/isre.3.1.60
• 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:10.1080/07421222.2003.11045748
• Diamantopoulos, A., & Winklhofer, H. M. (2001). Index construction with formative indicators: An alternative to scale development. Journal of marketing research, 38(2), 269-277. doi:10.1509/jmkr.38.2.269.18845
• Dias-Trindade, S., & Moreira, J. A. (2019). Pedagogical Scenarios Enriched with Audiovisual Technologies and Their Impact on the Promotion of the Learning Skills of Inmate Students in Portugal. Digital Education Review, 35, 97-110.
• Evans, J. C., Yip, H., Chan, K., Armatas, C., & Tse, A. (2020). Blended learning in higher education: professional development in a Hong Kong university. Higher Education Research & Development, 1-14. doi:10.1080/07294360.2019.1685943
• Falk, R. F., & Miller, N. B. (1992). A primer for soft modeling. University of Akron Press.
• Fernández-Quero, J. L. (2021). El uso de las TIC como paliativo de las dificultades del aprendizaje en las ciencias sociales. Digital Education Review, (39), 213-237
• Fichten, C., Olenik-Shemesh, D., Asuncion, J., Jorgensen, M., & Colwell, C. (2020). Higher Education, Information and Communication Technologies and Students with Disabilities: An Overview of the Current Situation. In Improving Accessible Digital Practices in Higher Education (pp. 21-44). Palgrave Pivot, Cham. doi:10.1007/978-3-030-37125-8_2
• Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., & Babin, B. J. (2016). Common methods variance detection in business research. Journal of Business Research, 69(8), 3192–3198. doi:10.1016/j.jbusres.2015.12.008
• Gandolfi, E., Ferdig, R. E., & Kratcoski, A. (2021). A new educational normal an intersectionality-led exploration of education, learning technologies, and diversity during COVID-19. Technology in Society, 66, 101637.
• Gunn, C. (2010). Sustainability factors for e-learning initiatives. ALT-J, 18(2), 89-103. doi:10.1080/09687769.2010.492848
• Hadullo, K., Oboko, R., & Omwenga, E. (2018). Status of e-learning Quality in Kenya: Case of Jomo Kenyatta University of Agriculture and Technology Postgraduate Students. The International Review of Research in Open and Distributed Learning, 19(1), 138-160. doi:10.19173/irrodl.v19i1.3322
• Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Sage Publications.
• 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:10.1016/j.eswa.2012.03.028
• 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. doi:10.1007/s11747-014-0403-8
• Herzberg, F., Mausner, B., & Snyderman, B. S. (1959). The Motivation to Work. New York: Wiley.
• Ifinedo, P. (2017). Examining students' intention to continue using blogs for learning: Perspectives from technology acceptance, motivational, and social-cognitive frameworks. Computers in Human Behavior, 72, 189-199. doi:10.1016/j.chb.2016.12.049
• Johnson, A., Galloway, C., Friedlander, E., & Goldenberg, C. (2019). Advancing educational quality in Rwanda: Improving teachers’ literacy pedagogy and print environments. International Journal of Educational Research, 98, 134-145. doi:10.1016/j.ijer.2019.08.016
• Jung, I. (2011). The dimensions of e-learning quality: from the learner’s perspective. Educational Technology Research and Development, 59(4), 445-464. doi:10.1007/s11423-010-9171-4
• Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353-364. doi:10.1016/j.chb.2009.11.006
• Kettunen, J. (2008). A conceptual framework to help evaluate the quality of institutional performance. Quality Assurance in Education, 16(4), 322-332. doi:10.1108/09684880810906472
• Khan, I. U., Hameed, Z., Yu, Y., & Khan, S. U. (2017). Assessing the determinants of flow experience in the adoption of learning management systems: the moderating role of perceived institutional support. Behaviour & Information Technology, 36(11), 1162-1176. doi:10.1080/0144929X.2017.1362475
• Kim, K., Trimi, S., Park, H., & Rhee, S. (2012). The impact of CMS quality on the outcomes of e‐learning systems in higher education: an empirical study. Decision Sciences Journal of Innovative Education, 10(4), 575-587. doi:10.1111/j.1540-4609.2012.00360.x
• Kim, H. J., Lee, J. M., & Rha, J. Y. (2017). Understanding the role of user resistance on mobile learning usage among university students. Computers & Education, 113, 108-118. doi:10.1016/j.compedu.2017.05.015
• Kurt, Ö. E. (2019). Examining an e-learning system through the lens of the information systems success model: Empirical evidence from Italy. Education and Information Technologies, 24(2), 1173-1184. doi:10.1007/s10639-018-9821-4
• Lee, Y., Hsieh, Y., & Ma, C. (2011). A model of organizational employees' e-learning systems acceptance. Knowledge-Based Systems, 24(3), 355-366. doi:10.1016/j.knosys.2010.09.005
• Li, Y., Duan, Y., Fu, Z., & Alford, P. (2012). An empirical study on behavioural intention to reuse e‐learning systems in rural China. British Journal of Educational Technology, 43(6), 933-948. doi:10.1111/j.1467-8535.2011.01261.x
• Lin, W. S. (2012). Perceived fit and satisfaction on web learning performance: IS continuance intention and task-technology fit perspectives. International Journal of Human-Computer Studies, 70(7), 498-507. doi:10.1016/j.ijhcs.2012.01.006
• Martínez-Argüelles, M. J., & Batalla-Busquets, J. M. (2016). Perceived service quality and student loyalty in an online university. The International Review of Research in Open and Distributed Learning, 17(4), 264-279. doi:10.19173/irrodl.v17i4.2518
• McGill, T. J., & Klobas, J. E. (2009). A task–technology fit view of learning management system impact. Computers & Education, 52(2), 496-508. doi:10.1016/j.compedu.2008.10.002
• McGill, T. J., Klobas, J. E., & Renzi, S. (2014). Critical success factors for the continuation of e-learning initiatives. The Internet and Higher Education, 22, 24-36. doi:10.1016/j.iheduc.2014.04.001
• MCIU (Ministerio de Ciencia, Innovación y Universidades) (2019). Datos y cifras del sistema universitario español. Publicación 2018-2019. Accessed 13 September 2020. http://www.educacionyfp.gob.es/dam/jcr:2af709c9-9532-414e-9bad-c390d32998d4/datos-y-cifras-sue-2018-19.pdf
• Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-374. doi:10.1016/j.chb.2014.07.044
• Mushtaq, N., & Malik, A. B. (2018). The Role of Public and Private Universities of Pakistan as Learning Organization. Journal of Research in Social Sciences, 6(1), 277-290. https://search.proquest.com/openview/03a356a0cdc150f11a900e716a06475c/1?pq-origsite=gscholar&cbl=2030756
• Naidu, P., & Derani, N. E. S. (2016). A comparative study on quality of education received by students of private universities versus public universities. Procedia Economics and Finance, 35, 659-666. doi:10.1016/S2212-5671(16)00081-2
• Nijman, D. J., & Gelissen, J. (2011). Direct and indirect effects of supervisor support on transfer of training. In Supporting workplace learning (pp. 89-106). Springer, Dordrecht.
• 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:10.1016/j.im.2008.12.006
• Pham, L., Williamson, S., & Berry, R. (2018). Student perceptions of e-learning service quality, e-satisfaction, and e-loyalty. International Journal of Enterprise Information Systems, 14(3), 19-40. doi:10.4018/IJEIS.2018070102
• 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. doi:10.1037/0021-9010.88.5.879
• Prensky, M. (2013). Enseñar a nativos digitales. México: SM Ediciones.
• Pucciarelli, F., & Kaplan, A. (2016). Competition and strategy in higher education: Managing complexity and uncertainty. Business Horizons, 59(3), 311-320. doi:10.1016/j.bushor.2016.01.003
• Queiros, D. R., & de Villiers, M. R. (2016). Online learning in a South African higher education institution: Determining the right connections for the student. The International Review of Research in Open and Distributed Learning, 17(5), 165-185. doi:10.19173/irrodl.v17i5.2552
• Raposo-Rivas, M., & de la Serna, M. C. (2019). Technology to Improve the Assessment of Learning. Digital Education Review, (35).
• Rey, E. D. & Romero, L. (2004). Competition between public and private universities: quality, prices and exams. Documentos de trabajo. Economic series (Universidad Carlos III. Departamento de Economía), 23, 1-24. https://ideas.repec.org/p/cte/werepe/we046423.html
• Tashakkori, A., & Teddlie, C. (2010). Sage handbook of mixed methods in social and behavioral research. SAGE publications
• Uppal, M. A., Ali, S., & Gulliver, S. R. (2018). Factors determining e‐learning service quality. British Journal of Educational Technology, 49(3), 412-426. doi:10.1111/bjet.12552
• Velásquez, R. M. A., & Lara, J. V. M. (2021). Knowledge management in two universities before and during the COVID-19 effect in Peru. Technology in Society, 64, 101479
• Vernadakis, N., Antoniou, P., Giannousi, M., Zetou, E., & Kioumourtzoglou, E. (2011). Comparing hybrid learning with traditional approaches on learning the Microsoft Office Power Point 2003 program in tertiary education. Computers & Education, 56(1), 188-199. doi:10.1016/j.compedu.2010.08.007
• Wang, H. C., & Chiu, Y. F. (2011). Assessing e-learning 2.0 system success. Computers & Education, 57(2), 1790-1800. doi:10.1016/j.compedu.2011.03.009
• Wang, Y. S., & Liao, Y. W. (2008). Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government information quarterly, 25(4), 717-733. doi:10.1016/j.giq.2007.06.002
• Wang, Y. S., Wang, H. Y., & Shee, D. Y. (2007). Measuring e-learning systems success in an organizational context: Scale development and validation. Computers in Human Behavior, 23(4), 1792-1808. doi:10.1016/j.chb.2005.10.006
• Wilkinson, R., & Yussof, I. (2005). Public and private provision of higher education in Malaysia: A comparative analysis. Higher Education, 50(3), 361-386. doi:10.1007/s10734-004-6354-0
• Williams, C., & Beam, S. (2019). Technology and writing: Review of research. Computers & Education, 128, 227-242. doi:10.1016/j.compedu.2018.09.024
• Wu, H. Y., & Lin, H. Y. (2012). A hybrid approach to develop an analytical model for enhancing the service quality of e-learning. Computers & Education, 58(4), 1318-1338. doi:10.1016/j.compedu.2011.12.025
• Yakubu, N., & Dasuki, S. (2018). Measuring e-learning success in developing countries: applying the updated DeLone and McLean model. Journal of Information Technology Education: Research. http://shura.shu.ac.uk/21526/