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]
|