Keywords
effectiveness
student's perspective
higher education
COVID-19 pandemic
How to Cite
Abstract
The COVID-19 pandemic situation has impacted the entire education system, especially universities, and brought a new phase in education, “blended learning.” The objective of the research was to study the relationship of eight independent factors: e-learning environment, e-learning facilitation, e-learning materials, e-learning technical support, instructors’ personal attention, interaction with instructors, interaction with peer students, and laboratory learning environment, in the provision of effective blended learning in higher education during COVID-19 pandemic. Additionally, an extended relationship of gender and level of course with the effective blended learning was studied. A descriptive cross-sectional study was conducted with the students of higher education institutions in the Kingdom of Bahrain, and the Kingdom of Saudi Arabia, with a self-administered questionnaire aimed to learn the students’ perception of blended learning. All levels of undergraduate and postgraduate students took part in the study with a sample size of 1229. Ultimately, this study used a Structural Equation Modelling (SEM) approach to find the positive relationship between the effective blended learning and the eight independent variables and two mediating variables in the higher education sector. The study results portrayed a positive relationship between the eight independent variables and blended learning effectiveness in higher education institutions. The findings revealed that there is a difference in the students' perception of gender, level of the course, and the effectiveness of blended learning in the HEIs. The research offers guidance to governing bodies, administrators, and teachers of HEIs in decision-making and improves their actions to provide the best teaching and learning through blended learning. HEIs need to focus on the study results to enhance blended learning effectiveness based on e-learning environment, e-learning facilitation, e-learning materials, e-learning technical support, instructors’ personal attention, interaction with instructors, interaction with peer students, and laboratory learning environment. Also, since there is a significant difference between the gender, level of the course, and blended learning, providing blended learning based on gender and level of the course needs to be concentrated on by the higher education institutions.
References
K. V. Elumalai et al., “Factors Affecting the Quality of E-Learning During the COVID-19 Pandemic From the Perspective of Higher Education Students,” J. Inf. Technol. Educ. Res., vol. 19, no. 1, pp. 731–753, 2020.
M. J. Kintu and C. Zhu, “Student characteristics and learning outcomes in a blended learning environment intervention in a Ugandan university,” Electron. J. e-Learning, vol. 14, no. 3, p. 181‑195, 2016.
M. Yigzaw, Y. Tebekaw, Y. M. Kim, A. Kols, F. Ayalew, and G. Eyassu, “Comparing the effectiveness of a blended learning approach with a conventional learning approach for basic emergency obstetric and newborn care training in Ethiopia,” Midwifery, vol. 78, no. 1, pp. 42–49, 2019.
G. L. Makokha and D. N. Mutisya, “Status of E-learning in public Universities in Kenya,” Int. Rev. Res. Open Distance Learn., vol. 17, no. 3, pp. 341–359, 2016.
D. R. Queiros and M. R. (Ruth) de Villiers, “Online learning in a South African Higher Education Institution: Determining the right connections for the student,” Int. Rev. Res. Open Distance Learn., vol. 17, no. 5, pp. 165–185, 2016.
C. Kulkarni et al., “Peer and self assessment in massive online classes,” ACM Trans. Comput. Interact., vol. 20, no. 6, pp. 1–31, 2013.
U. Klentien and W. Wannasawade, “Development of Blended Learning Model with Virtual Science Laboratory for Secondary Students,” Procedia - Soc. Behav. Sci., vol. 2017, no. 1, pp. 706–711, 2016.
R. O’Reilly, L. M. Ramjan, M. Fatayer, A. Stunden, and L. R. Gregory, “First year undergraduate nursing students’ perceptions of the effectiveness of blended learning approaches for nursing numeracy,” Nurse Educ. Pract., vol. 45, no. 1, p. 102800, 2020.
Y. M. Cheng, “Extending the expectation-confirmation model with quality and flow to explore nurses’ continued blended e-learning intention,” Inf. Technol. People, vol. 27, no. 3, pp. 230–258, 2014.
T. Strike, Higher education strategy and planning : a professional guide. 2018.
T. Strike, “Administrative Planning, Higher Education Institutions,” in Encyclopedia of International Higher Education Systems and Institutions, 2018, pp. 1–6.
P. Ashwin and D. McVitty, “The Meanings of Student Engagement: Implications for Policies and Practices,” in The European Higher Education Area, 2015, pp. 43–359.
B. Little and L. Knihova, “Modern trends in learning architecture,” Ind. Commer. Train., vol. 46, no. 1, pp. 34–38, 2014.
C. F. Goh, C. M. Leong, K. Kasmin, P. K. Hii, and O. K. Tan, “Students’ experiences, learning outcomes and satisfaction in e-learning,” J. E-Learning Knowl. Soc., vol. 13, no. 2, pp. 117–128, 2017.
L. Shahmoradi, V. Changizi, E. Mehraeen, A. Bashiri, B. Jannat, and M. Hosseini, “The challenges of E-learning system: Higher educational institutions perspective.,” J. Educ. Health Promot., vol. 7, no. 1, pp. 1–6, 2018.
Z. Alrefaie, M. Hassanien, and A. Al-Hayani, “Monitoring Online Learning During COVID-19 Pandemic; Suggested Online Learning Portfolio (COVID-19 OLP),” MedEdPublish, vol. 9, no. 1, 2020.
S. Adams Becker, M. Cummins, A. Davis, A. Freeman, C. Hall Giesinger, and V. Ananthanarayanan, “NMC Horizon Report: 2017 Higher Education Edition.,” 2017.
M. J. Martínez-Argüelles and J. M. Batalla-Busquet, “Perceived service quality and student loyalty in an online university,” Int. Rev. Res. Open Distance Learn., vol. 17, no. 4, pp. 264–279, 2016.
J. S. L. Kong, R. C. W. Kwok, and Y. Fang, “The effects of peer intrinsic and extrinsic motivation on MMOG game-based collaborative learning,” Inf. Manag., vol. 49, no. 1, pp. 1–9, 2012.
R. Weinhandl, Z. Lavicza, and T. Houghton, “Designing online learning environments for flipped approaches in professional mathematics teacher development,” J. Inf. Technol. Educ. Res., vol. 19, no. 1, pp. 315–337, 2020.
J. Yu, C. Huang, Z. Han, T. He, and M. Li, “Investigating the influence of interaction on learning persistence in online settings: Moderation or mediation of academic emotions?,” Int. J. Environ. Res. Public Health, vol. 17, no. 1, pp. 1–21, 2020.
S. Binaymin, M. J. Rutter, and S. Smith, “The Moderating Effect of Education and Experience on the Use of Learning Management Systems,” in 8th International Conference on Educational and Information Technology, 2018, p. 8.
Global, “Education during COVID-19; moving towards e-learning,” European Data Portal, 2020.
United Nations, “Policy Brief: Education during COVID-19 and beyond,” 2020.
P. Jones, A. Jones, G. Packham, B. Thomas, and C. Miller, “It’s all in the mix: The evolution of a blended e-learning model for an undergraduate degree,” J. Syst. Inf. Technol., vol. 9, no. 2, pp. 124–142, 2007.
M. Cuadrado-García, M. E. Ruiz-Molina, and J. D. Montoro-Pons, “Are there gender differences in e-learning use and assessment? Evidence from an interuniversity online project in Europe,” in Procedia - Social and Behavioral Sciences, 2010, pp. 367–371.
H. M. Peixoto, M. M. Peixoto, and E. D. Alves, “Learning strategies used by undergraduate and postgraduate students in hybrid courses in the area of health,” Rev. Lat. Am. Enfermagem, vol. 20, no. 3, pp. 551–558, 2012.
R. A. Madani, “Analysis of Educational Quality, a Goal of Education for All Policy,” High. Educ. Stud., vol. 9, no. 1, pp. 100–109, 2019.
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright (c) 2022 Jayendira P Sankar, Kalaichelvi K, Kesavan Vadakalur Elumalai , Alqahtani Mufleh Salem M