[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 12, Issue 4 (12-2023) ::
MEO 2023, 12(4): 71-93 Back to browse issues page
The effect of employees' online perceptions on the results of online learning during the covid-19 pandemic: the role of mediating variables of Course satisfaction and readiness for online learning and the moderating variable of teacher's readiness for online teaching
Alireza Saremi * , Shokrolah Ghahramani
Azad University of Darab
Abstract:   (687 Views)
With the start of the Covid-19 pandemic, holding online courses for education became inevitable, and universities and organizations started offering web-based courses. The aim of the current research is the effect of employees' online perceptions on the results of online learning during the covid-19 pandemic, with the role of mediating variables of satisfaction with online courses and readiness for online learning, and the moderating variable of teacher's readiness to teach online in the prisons organization of southeast Fars province. Using Cochran's formula and random sampling method, the sample members were selected. A standard questionnaire was used to collect data. The type of correlational research and the strategy used is survey. The results of structural equation model analysis in Smart PLS software showed that online learning perception has an effect on online learning readiness, satisfaction with online courses and online learning results. Online learning readiness and satisfaction with online courses have an effect on online learning results. Online learning readiness and online course satisfaction have a mediating role in the relationship between online learning perceptions and online learning outcomes. Finally, the moderating effect of instructor preparation for online teaching was rejected. This research considers the necessity of designing and implementing an online learning system, a system that can meet the educational needs of employees and the goals of the organization by focusing on theory and practice aspects.
 
Article number: 3
Keywords: Employees' online perceptions, Readiness for online learning, Course satisfaction for online learning, Results of online learning, Teacher's readiness for online teaching, Covid-19 pandemic
Full-Text [PDF 1511 kb]   (266 Downloads)    
Type of Study: Research | Subject: managing education in other organizations
Received: 2023/07/13 | Accepted: 2023/10/12 | Published: 2024/03/13
References
1. Adams, D., & Tan, M.H.J. (2020). Sumintono, B. Students' readiness for blended learning in a leading Malaysian private higher education institution. Interact. Technol. Smart Educ, 18, 515-534. [DOI:10.1108/ITSE-03-2020-0032]
2. Baber, H. (2020). Determinants of Students' Perceived Learning Outcome and Satisfaction in Online Learning during the Pandemic of COVID19. Journal of Education and e-Learning Research, 7(3), 285-292. [DOI:10.20448/journal.509.2020.73.285.292]
3. Baviskar, S.N., Hartle, R.T., & Whitney, T. (2009). Essential criteria to characterize constructivist teaching: Derived from a review of the literature and applied to five constructivist-teaching method articles. Int. J. Sci. Educ, 31, 541-550. [DOI:10.1080/09500690701731121]
4. Bingham, J. (1999). Guide to Developing Learning Outcomes. The Learning and Teaching Institute Sheffield Hallam University, Sheffield: Sheffield Hallam University.
5. Cedefop (2022). Defining, writing and applying learning outcomes, A European handbook - second edition. Luxembourg: Publications Office of the European :union:. http://data.europa.eu/doi/10.2801/703079
6. Chin, W. W. (2010). How to write up and report PLS analyses. In V. E. Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and applications in marketing and related fields (pp. 655 - 690). Berlin: Springer. [DOI:10.1007/978-3-540-32827-8_29]
7. Deci, E.L., & Ryan, R.M. (1985). The general causality orientations scale: Self-determination in personality. J. Res. Pers, 19, 109-134. [DOI:10.1016/0092-6566(85)90023-6]
8. Dziuban, C., Moskal, P., Brophy-Ellison, J., & Shea, P. (2007). Student satisfaction with asynchronous learning. Journal of Asynchronous Learning Networks, 11(1), 87-95. [DOI:10.24059/olj.v11i1.1739]
9. Duque, L. C. (2014). A framework for analysing higher education performance: Students' satisfaction, perceived learning outcomes, and dropout intentions. Total Quality Management & Business Excellence, 25(1-2), 1-21. [DOI:10.1080/14783363.2013.807677]
10. Eastin, M. A., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer Mediated Communication, 6(1). [DOI:10.1111/j.1083-6101.2000.tb00110.x]
11. Geng, S., Law, K.M.Y., & Niu, B. (2019). Investigating self-directed learning and technology readiness in blending learning environment. Int. J. Educ. Technol. High. Educ, 16 (17). [DOI:10.1186/s41239-019-0147-0]
12. Gonzalez-Gomez, F., Guardiola, J., Martin Rodríguez, O., & Montero Alonso, M. A. (2012). Gender differences in e-learning satisfaction. Computers & Education, 58(1), 283-290. [DOI:10.1016/j.compedu.2011.08.017]
13. Habibi, A. & Kolahi, B. (2022). Structural equation modeling and factor analysis, Tehran: Jihad University, second edition.( In Persian)
14. Hair, J. F., Ringle, M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver Bullet. Journal of Marketing Theory and Practice, 19(2), 139-151. [DOI:10.2753/MTP1069-6679190202]
15. Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W. & Calantone, R. J. (2014). Common beliefs and reality about partial least squares. Organizational Research Methods, 17(2), 182-209 [DOI:10.1177/1094428114526928]
16. Horzum, M. B., Onder, İ., & Beşoluk, S. (2014). Chronotype and academic achievement among online learning students. Learning and Individual Differences. Advance online publication. doi:10.1016/j.lindif.2013.10.017 [DOI:10.1016/j.lindif.2013.10.017]
17. Horzum, M. B. Demir Kaymak, Z. & Canan Gungoren, O. (2015). Structural Equation Modeling towards Online Learning Readiness, Academic Motivations, and Perceived Learning. Educational Sciences: Theory & Practice, 15(3), 759-770
18. Hung, M. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55, 1080-1090. [DOI:10.1016/j.compedu.2010.05.004]
19. Hussain, G., Sarfraz, M., Shahid, M., Riaz, A., Muavia, M., Saleem Fahed, Y., Azam, F, & Tallal Abdullah, M. (2022). Medical Students' Online Learning Perceptions, Online Learning Readiness, and Learning Outcomes during COVID-19: The Moderating Role of Teacher's Readiness to Teach Online. Int. J. Environ. Res. Public Health, 19, 3520. [DOI:10.3390/ijerph19063520]
20. Ikhsan, R. B., Saraswati, L. A., Muchardie, B. G., & Susilo, A. (2019). The determinants of students' perceived learning outcomes and satisfaction in BINUS online learning. Paper presented at the 5th International Conference on New Media Studies (CONMEDIA). IEEE. [DOI:10.1109/CONMEDIA46929.2019.8981813]
21. Joon Lee, S., Srinivasan, S., Trail, T., Lewis, D. & Lopez, S. (2011). Examining the relationship among student perception of support, course satisfaction, and learning outcomes in online learning. The Internet and Higher Education, 14(3), 158-163. [DOI:10.1016/j.iheduc.2011.04.001]
22. Kamaruzaman, F. M., Sulaiman, N. A., & Shaid, N. A. N. (2021). A Study on Perception of Students' Readiness towards Online Learning during Covid-19 Pandemic. International Journal of Academic Research in Business and Social Sciences, 11(7), 1536-1548. [DOI:10.6007/IJARBSS/v11-i7/10488]
23. Karns, G. L. (2005). An update of marketing student perceptions of learning activities: Structure, preferences and effectiveness. Journal of Higher Education, 27(2), 163-171. [DOI:10.1177/0273475305276641]
24. Keengwe, J., Diteeyont, W., & Lawson-Body, A. (2012). Student and instructor satisfaction with elearning tools in online learning environments, International Journal of Information and Communication Technology Education (IJICTE), 8(1), 76-86. [DOI:10.4018/jicte.2012010108]
25. Kline, R. B. (2012). Principles and Practice of Structural Equation Modeling, 3nd edition, New York: Guilford Press.
26. Kuo, Y. C., Walker, A. E., Belland, B. R., & Schroder, K. E. (2013). A predictive study of student satisfaction in online education programs, The International Review of Research in Open and Distance Learning, 14(1), 16-39. [DOI:10.19173/irrodl.v14i1.1338]
27. Marks, R. B., Sibley, S. D., & Arbaugh, J. B. (2005). A structural equation model of predictors for effective online learning. Journal of Management Education, 29(4), 531-563. [DOI:10.1177/1052562904271199]
28. Martin, F., & Bolliger. D, U. (2022). Developing an online learner satisfaction framework in higher education through a systematic review of research, Int J Educ Technol High Educ, 19(50), 1-21. [DOI:10.1186/s41239-022-00355-5]
29. McVay, M. (2001). How to be a successful distance learning student: Learning on the Internet. New York: Prentice Hall.
30. Nunally, J. (1978). Psychometric theory, 2nd edition. New York: Mc Graw-Hill.
31. Olayemi, M. S., Adamu, H., & Olayemi, K. J. (2021). Perception and Readiness of Students' Towards Online Learning in Nigeria during Covid-19 Pandemic. Library Philosophy and Practice, 5051.
32. Paliwal, M., & Singh, A. (2021). Teacher readiness for online teaching-learning during COVID-19 outbreak: A study of Indian institutions of higher education. Interact. Technol. Smart Educ, 18, 403-421. [DOI:10.1108/ITSE-07-2020-0118]
33. Richardson, J., & Swan, K. (2003). Examing social presence in online courses in relation to students' perceived learning and satisfaction. JALN, 7(1), 68-88. [DOI:10.24059/olj.v7i1.1864]
34. Scherer, R., Howard, S.K., Tondeur, J., & Siddiq, F. (2021). Profiling teachers' readiness for online teaching and learning in higher education: Who's ready? Comput. Human Behav, 118, 106675. [DOI:10.1016/j.chb.2020.106675]
35. Smart, K. L., & Cappel, J. J. (2006). Students' perceptions of online learning: A comparative study. Journal of Information Technology Education, 5, 201-219. [DOI:10.2139/ssrn.3524610]
36. Thongsri, N., Chootong, C., Tripak, O., Piyawanitsatian, P. & Saengae, R. (2021). Predicting the Determinants of Online Learning Adoption during the COVID-19 Outbreak: A Two-Staged Hybrid SEM-Neural Network Approach. Interactve Technoogy and Smart Educaton, 18. [DOI:10.1108/ITSE-08-2020-0165]
37. Wei, H.-C., & Chou, C. (2020). Online learning performance and satisfaction: Do perceptions and readiness matter? Distance Educ, 41, 48-69. [DOI:10.1080/01587919.2020.1724768]
38. Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195. [DOI:10.2307/20650284]
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Saremi A, Ghahramani S. The effect of employees' online perceptions on the results of online learning during the covid-19 pandemic: the role of mediating variables of Course satisfaction and readiness for online learning and the moderating variable of teacher's readiness for online teaching. MEO 2023; 12 (4) : 3
URL: http://journalieaa.ir/article-1-610-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 12, Issue 4 (12-2023) Back to browse issues page
نشریه مدیریت بر آموزش سازمان ها Journal of Managing Education in Organizations

 
 
Persian site map - English site map - Created in 0.05 seconds with 37 queries by YEKTAWEB 4660