Abstract

Subject Review: The Effectiveness Of Integrating E-Learning On Learning Outcome And Student Perceptions In Tertiary Education

Zena Abdulameer Mohammad

Volume: 13 Issue: 2 2023

Abstract:

The literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claimed that both instructors and students must work together to engage in extensive collaboration and engagement with both students and one another. Since educational institutions must be ready for the sustainability regarding e-learning adoption, the presented work argues that there is a requirement for better identification and knowledge of this. The results revealed that a university's competency and capacity for meeting e-learning demand stemmed from actual requirement for the implementation of e-learning for specific academic environment hinged on sustainability related to implementation of e-learning. In addition to that, each university's local culture influenced and supported the implementation process, where the inhibiting and driving variables had a substantial effect on the continuity and outcome of the process. The range of digital tools that can successfully encourage social interactions as well as the learning community need to be further researched. With regard to higher education, there is an increase in innovative assessments of variables to assess learning results in the settings of digital learning. Researchers should carefully evaluate their study designs and study subjects in digital learning environments for this reason, as well as how to handle measuring learning.

DOI: http://doi.org/10.37648/ijrssh.v13i02.006

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References

• Adams, A. E., Randall, S., & Traustadóttir, T. (2015). A tale of two sections: An experiment to compare the effectiveness of a hybrid versus a traditional lecture format in introductory microbiology. CBE—Life Sciences Education, 14(1), ar6.
• Anstine, J., & Skidmore, M. (2005). A small sample study of traditional and online courses with sample selection adjustment. The Journal of Economic Education, 107-127.
• Ameen, N., & Willis, R. (2017). The use of e-learning of students in Iraqi universities: potential and challenges.
• 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.
• Au, T. W., Sadiq, S., & Li, X. (2009, June). Learning from experience: Can e-learning technology be used as a vehicle. In Proceedings of the 4th International Conference on E-Learning (pp. 32-39).
• Bernard, R. M., Borokhovski, E., Schmid, R. F., Tamim, R. M., & Abrami, P. C. (2014). A meta-analysis of blended learning and technology use in higher education: From the general to the applied. Journal of Computing in Higher Education, 26, 87-122.
• Brown, B. W., & Liedholm, C. E. (2002). Can web courses replace the classroom in principles of microeconomics?. American Economic Review, 92(2), 444-448
• Cennamo, K., & Kalk, D. (2019). Real world instructional design: An iterative approach to designing learning experiences. Routledge.
• Brindley, J. E., Blaschke, L. M., & Walti, C. (2009). Creating effective collaborative learning groups in an online environment. International Review of Research in Open and Distributed Learning, 10(3).
• Brocato, B. R., Bonanno, A., & Ulbig, S. (2015). Student perceptions and instructional evaluations: A multivariate analysis of online and face-to-face classroom settings. Education and Information Technologies, 20, 37-55.
• Chen, P. S. D., Lambert, A. D., & Guidry, K. R. (2010). Engaging online learners: The impact of Web-based learning technology on college student engagement. Computers & Education, 54(4), 1222-1232.
• Chin, J. P., Diehl, V. A., & Norman, K. L. (1988, May). Development of an instrument measuring user satisfaction of the human-computer interface. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 213-218).
• Coates, H. B. (2009). Engaging students for success: Australasian student engagement report
• Coates, D., Humphreys, B. R., Kane, J., & Vachris, M. A. (2004). “No significant distance” between face-toface and online instruction: Evidence from principles of economics. Economics of Education Review, 23(5), 533- 546
• Crawford-Ferre, H. G., & Wiest, L. R. (2012). Effective online instruction in higher education. Quarterly Review of Distance Education, 13(1), 11.
• del Barrio-García, S., Arquero, J. L., & Romero-Frías, E. (2015). Personal learning environments acceptance model: The role of need for cognition, e-learning satisfaction and students' perceptions. Journal of Educational Technology & Society, 18(3), 129-141.
• Duncan, H. E., Range, B., & Hvidston, D. (2013). Exploring student perceptions of rigor online: Toward a definition of rigorous learning. Journal on Excellence in College Teaching, 24(4)
• Fahad, A. N., Hassan, Z., Sulaiman, R. B., & Rahman, Z. (2015). Usability evaluation of e-learning systems in the Iraqi higher education institutions. International Journal of Internet of Things, 4(1), 30-34.
• Farhan, M. K., Talib, H. A., & Mohammed, M. S. (2019). Key factors for defining the conceptual framework for quality assurance in e-learning. Journal of Information Technology Management, 11(3), 16-28.
• Fuchs, T., & Woessmann, L. (2004). Computers and student learning: Bivariate and multivariate evidence on the availability and use of computers at home and at school (No. 1321). CESIFO working paper.
• Gallagher, S., & LaBrie, J. (2012). Online Learning 2.0: Strategies for a Mature Market. Continuing Higher Education Review, 76, 65-73.
• Garratt-Reed, D., Roberts, L. D., & Heritage, B. (2016). Grades, student satisfaction and retention in online and face-to-face introductory psychology units: A test of equivalency theory. Frontiers in psychology, 7, 673.
• González-Gómez, D., Jeong, J. S., Airado Rodríguez, D., & Cañada-Cañada, F. (2016). Performance and perception in the flipped learning model: an initial approach to evaluate the effectiveness of a new teaching methodology in a general science classroom. Journal of Science Education and Technology, 25, 450-459.
• Hampton, D., & Pearce, P. F. (2016). Student engagement in online nursing courses. Nurse educator, 41(6), 294- 298.
• Hiltz, S. R., & Turoff, M. (2002). What makes learning networks effective?. Communications of the ACM, 45(4), 56-59.
• Holsapple, C. W., & Lee‐Post, A. (2006). Defining, assessing, and promoting e‐learning success: An information systems perspective. Decision sciences journal of innovative education, 4(1), 67-85.
• Hussin, H., Bunyarit, F., & Hussein, R. (2009). Instructional design and e‐learning: Examining learners' perspective in Malaysian institutions of higher learning. Campus-wide information systems, 26(1), 4-19.
• Israel, M. J. (2015). Effectiveness of integrating MOOCs in traditional classrooms for undergraduate students. The International Review of Research in Open and Distributed Learning, 16(5).
• Kakkar, M. (2008). A synthesis of good design practices for stand alone' Global e-learning' for global organisations (Doctoral dissertation, Concordia University).
• Keengwe, J., & Kidd, T. T. (2010). Towards best practices in online learning and teaching in higher education. MERLOT Journal of Online Learning and Teaching, 6(2), 533-541.
• Kisanjara, S., Tossy, T., Sife, A., & Msanjila, S. (2017). An integrated model for measuring the impacts of elearning on students’ achievement in developing countries. International Journal of Education and Development using ICT, 13(3).
• Kehrwald, B. (2008). Understanding social presence in text‐based online learning environments. Distance Education, 29(1), 89-106.
• Kümmel, E., Moskaliuk, J., Cress, U., & Kimmerle, J. (2020). Digital learning environments in higher education: A literature review of the role of individual vs. social settings for measuring learning outcomes. Education Sciences, 10(3), 78.
• Leuven, E., Lindahl, M., Oosterbeek, H., & Webbink, D. (2007). The effect of extra funding for disadvantaged pupils on achievement. The Review of Economics and Statistics, 89(4), 721-736.
• Lin, M. H., & Chen, H. G. (2017). A study of the effects of digital learning on learning motivation and learning outcome. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 3553-3564.
• Lwoga, E. T., & Komba, M. (2015). Antecedents of continued usage intentions of web-based learning management system in Tanzania. Education+ training.
• Mayes, T., & De Freitas, S. (2007). Learning and e-learning: the role of theory. In Rethinking pedagogy for a digital age (pp. 33-45). Routledge.
• Meyer, K. A. (2014). Student engagement in online learning: What works and why. ASHE higher education report, 40(6), 1-114.
• Mirza, A. A., & Al-Abdulkareem, M. (2011). Models of e-learning adopted in the Middle East. Applied computing and informatics, 9(2), 83-93.
• Northey, G., Bucic, T., Chylinski, M., & Govind, R. (2015). Increasing student engagement using asynchronous learning. Journal of Marketing Education, 37(3), 171-180.
• Nortvig, A. M., Petersen, A. K., & Balle, S. H. (2018). A literature review of the factors influencing e-learning and blended learning in relation to learning outcome, student satisfaction and engagement. Electronic Journal of E-learning, 16(1), pp46-55.
• Robinson, C. C., & Hullinger, H. (2008). New benchmarks in higher education: Student engagement in online learning. Journal of Education for Business, 84(2), 101-109.
• Potter, J. (2015). Applying a Hybrid Model: Can It Enhance Student Learning Outcomes?. Journal of Instructional Pedagogies, 17.
• Redmond, P., Abawi, L., Brown, A., Henderson, R., & Heffernan, A. (2018). An online engagement framework for higher education. Online learning, 22(1), 183-204.
• Ryan, S., Kaufman, J., Greenhouse, J., She, R., & Shi, J. (2016). The effectiveness of blended online learning courses at the community college level. Community College Journal of Research and Practice, 40(4), 285-298.
• Sadiq, A. (2020). Effectiveness of Using E-Learning Techniques and Information Systems on Quality in Iraqi Higher Education. Available at SSRN 3641922
• Shehzadi, S., Nisar, Q. A., Hussain, M. S., Basheer, M. F., Hameed, W. U., & Chaudhry, N. I. (2021). The role of digital learning toward students' satisfaction and university brand image at educational institutes of Pakistan: a post-effect of COVID-19. Asian Education and Development Studies, 10(2), 276-294.
• Sosin, K., Blecha, B. J., Agarwal, R., Bartlett, R. L., & Daniel, J. I. (2004). Efficiency in the use of technology in economic education: Some preliminary results. American Economic Review, 94(2), 253-258.
• Ssekakubo, G., Suleman, H., & Marsden, G. (2011, October). Issues of adoption: have e-learning management systems fulfilled their potential in developing countries?. In Proceedings of the South African Institute of Computer Scientists and Information Technologists conference on knowledge, innovation and leadership in a diverse, multidisciplinary environment (pp. 231-238).
• Swan, K., Garrison, D. R., & Richardson, J. C. (2009). A constructivist approach to online learning: The community of inquiry framework. In Information technology and constructivism in higher education: Progressive learning frameworks (pp. 43-57). IGI global.
• Terry, N., Lewer, J. J., & Macy, A. (2003). The efficacy of alternative instruction modes in economics. Available at SSRN 392561.
• Tsinidou, M., Gerogiannis, V., & Fitsilis, P. (2010). Evaluation of the factors that determine quality in higher education: an empirical study. Quality assurance in Education, 18(3), 227-244.
• Vargas, N., & Tian, X. (2013). E-learning: Much more than a matter of technology. International Journal of eEducation, e-Business, e-Management and e-Learning, 3(3), 277.
• Youssef, A. B., & Dahmani, M. (2008). The impact of ICT on student performance in higher education: Direct effects, indirect effects and organisational change. Rev. U. Soc. Conocimiento, 5, 45.
• Yuan, J., & Kim, C. (2014). Guidelines for facilitating the development of learning communities in online courses. Journal of Computer Assisted Learning, 30(3), 220-232.
• Yuan, J., & Kim, C. (2014). Guidelines for facilitating the development of learning communities in online courses. Journal of Computer Assisted Learning, 30(3), 220-232.