A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE
Full Text (PDF)
Abstract
Universities benefit from the merging of classroom lecturing and the use of technological resources to provide an innovative environment for their students. E-learning resources facilitate the process of teaching and learning. Although students use these resources widely, their usage behaviours and the factors the dominate the instructor-students learning resources usage still need to be investigated further due to the fast growing technological changes and the advance features of e-learning, which affect the dominant prioritization and the significances of these factors. In order to facilitate this research, a research model was derived from the modified Technology Acceptance Model (TAM) in order to observe the factors that influence the instructors-students utilization of learning resources within universities in the United Arab Emirates (UAE). The research model was assessed based on an analysis of 520 students who participated in the study. Thus, it can be inferred that both peer influence and student’s capability to use technology have no relevant effect on perceived usefulness and students’ usage behaviour. However, instructor contributions, course content and design do indeed have a significant correlation with student usage behaviour. The findings from this research advance the understanding of the factors that have a more dominant influence on instructor-students learning resources usage in the context of UAE universities.
License
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Research Article
EURASIA J Math Sci Tech Ed, Volume 17, Issue 11, November 2021, Article No: em2025
https://doi.org/10.29333/ejmste/11234
Publication date: 23 Sep 2021
Article Views: 2568
Article Downloads: 1706
Open Access Disclosures References How to cite this articleDisclosure
Declaration of Conflict of Interest: No conflict of interest is declared by author(s).
Data sharing statement: Data supporting the findings and conclusions are available upon request from the corresponding author(s).
References
- Abbad, M. M., Morris, D., Al-Ayyoub, A., & Abbad, J. M (2009). Students’ decisions to use an eLearning system: a structural equation modelling analysis. International Journal of Emerging Technologies in Learning, 4(4), 4-13. https://doi.org/10.3991/ijet.v4i4
- Abbad, M., Morris, D., & De Nahlik, C. (2009). Looking under the Bonnet: Factors affecting student adoption of e-learning systems in Jordan. International Review of Research in Open and Distance Learning, 10(2), 1-24. https://doi.org/10.19173/irrodl.v10i2.596
- Abdel-Wahab, A. (2008). Modeling students’ intention to adopt e-learning a case from Egypt. Turkish Online Journal of Distance Education, 9(1), 157-168. https://doi.org/10.1002/j.1681-4835.2008.tb00232.x
- 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. https://doi.org/10.1016/j.chb.2015.11.036
- Abou El-Seoud, M. S., Taj-Eddin, I. A., Seddiek, N., El-Khouly, M. M., & Nosseir, A. (2013). E-learning and students’ motivation: A research study on the effect of e-learning on higher education. International Journal of Emerging Technologies in Learning, 9(4), 20-26 https://doi.org/10.3991/ijet.v9i4.3465
- Abu, F., Rozelan Yunus, A., Abdul Majid, I., Jabar, J., Aris, A., Sakidin, H., & Ahmad, A. (2014). Technology Acceptance (TAM): Empowering smart customer to participate in electricity supply. Journal of Technology Management and Technopreneurship, 2(1), 85-94.
- Ajzen, I., & Fishbein, M. (2005). The influence of attitudes on behavior.
- Al Rabaa’i, A. A. (2016) Extending the Technology Acceptance Model (TAM) to assess students’ behavioural intentions to adopt an e-learning system: The case of Moodle as a learning tool. Journal of Emerging Trends in Engineering and Applied Sciences, 7(1), 13-30.
- Al-Adwan, A. S., & Smedley, J. (2013). Exploring students’ acceptance of e-learning using Technology Acceptance Model in Jordanian universities. International Journal of Education and Development using Information and Communication Technology, 9(2), 4-18.
- Al-Gahtani, A. F. (2011). Evaluating the effectiveness of the e-learning experience in some universities in Saudi Arabia from male students’ perceptions (Doctoral thesis), Durham University.
- Al-Gahtani, S. S. (2008). Testing for the applicability of the TAM Model in the Arabic context: exploring an extended TAM with three moderating factors. Information Resources Management Journal, 21(4), 1-26. https://doi.org/10.4018/irmj.2008100101
- Al-Gahtani, S. S. (2016). Empirical investigation of e-learning acceptance and assimilation: A structural equation model. Applied Computing and Informatics, 12(1), 27-50. https://doi.org/10.1016/j.aci.2014.09.001
- Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007) Information Technology (IT) in Saudi Arabia: culture and the acceptance and use of IT. Information & Management, 44(8), 681-691. https://doi.org/10.1016/j.im.2007.09.002
- AlHamad, A. Q. M. (2020). Acceptance of e-learning among university students in UAE: A practical study. International Journal of Electrical and Computer Engineering (IJECE), 10(4), 3660-3671. https://doi.org/10.11591/ijece.v10i4
- Al-Harbi Al-Siraihi, K. (2011). E-learning in the Saudi tertiary education: Potential and challenges. Applied Computing and Informatics, 9(1), 31-46. https://doi.org/10.1016/j.aci.2010.03.002
- Al-Hawari, M., & Mouakket, S. (2010). The influence of technology acceptance model (TAM) factors on students’ e-satisfaction and e-retention within the context of UAE e-learning. Education, Business and Society: Contemporary Middle Eastern Issues, 3(4), 299-314. https://doi.org/10.1108/17537981011089596
- Almaiah, M. A., & Alismaiel, O. A. (2019). Examination of factors influencing the use of mobile learning system: An empirical study. Education and Information Technologies, 24(1), 885-909. https://doi.org/10.1007/s10639-018-9810-7
- Almaiah, M. A., & Jalil, M. A. (2014). Investigating students’ perceptions on mobile learning services. International Journal of Interactive Mobile Technologies, 8(4), 31-36. https://doi.org/10.3991/ijim.v8i4.3965
- Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and Information Technologies, 25, 5261-5280. https://doi.org/10.1007/s10639-020-10219-y
- Al-Qaysi, N., Mohamad-Nordin, N., & Al-Emran, M. (2018). A systematic review of social media acceptance from the perspective of educational and information systems theories and models. Journal of Educational Computing Research, 57(8), 2085-2109. https://doi.org/10.1177%2F0735633118817879
- Alshammari, S. H., Ali, M. B., & Rosli, M. S. (2016). The influences of technical support, self-efficacy and instructional design on the usage and acceptance of LMS: A comprehensive review. Turkish Online Journal of Educational Technology-TOJET, 15(2), 116-125.
- Arkorful, V., & Abaidoo, N. (2014). The role of e-learning, the advantages and disadvantages of its adoption in higher education. International Journal of Education and Research, 2(12), 397-410.
- Baker, E. W., Al-Gahtani, S. S., & Hubona, G. S. (2010). Cultural impacts on acceptance and adoption of information technology in a developing country. Journal of Global Information Management, 18(3), 35-58. https://doi.org/10.4018/jgim.2010070102
- Barclay, D. C., Higgins, C. A., & Thompson, R. (1995). The partial least squares approach to causal modeling: Personal computer adoption and use asan illustration. Technology Studies, Special Issues on Research Methodology, 2, 282-324.
- Bares, A. (2008). Compensation force (blog). Companies spend an average of $1,202 per employee on training. http://compforce.typepad.com/compensation_force/2008/02/companies-spend.html
- Bokolo Jr, A., Kamaludin, A., Romli, A., Mat Raffei, A. F., A/L Eh Phon, D. N., Abdullah, A., Ming, G. L., Shukor, N. A., Nordin, M. S., & Baba, S. (2020). A managerial perspective on institutions’ administration readiness to diffuse blended learning in higher education: Concept and evidence. Journal of Research on Technology in Education, 52(1), 37-64. https://doi.org/10.1080/15391523.2019.1675203
- Boud, D., Cohen, R., & Sampson, J. (1999). Peer learning and assessment. Assessment & Evaluation in Higher Education, 24, 413-426. https://doi.org/10.1080/0260293990240405
- Calisir, C. A., Gumussoy, A. E., Bayraktaroglu, and Karaali,D ( 2014). Predicting the intention to use a Web-based learning system: Perceived content quality, anxiety, perceived system quality, image, and the technology acceptance model. Human Factors and Ergonomics in Manufacturing & Service Industries, 24(5), 515-531. https://doi.org/10.1002/hfm.20548
- Carswell, A. D., & Venkatesh, V. (2002). Learner outcomes in an asynchronous distance educational environment. International Journal of Human-Computer Studies, 56(5), 475-494. https://doi.org/10.1006/ijhc.2002.1004
- Chen, H., & Li, Y. (2018). A research on factors influencing online education users’ continuance usage intention. Journal of Education and Practice, 9(14), 37-42. https://www.iiste.org/Journals/index.php/JEP/article/download/42383/43649
- Cheng, M. Y. (2011). Antecedents and consequences of e-learning acceptance. Information Systems Journal, 21(3), 269-299. https://doi.org/10.1111/j.1365-2575.2010.00356.x
- Cheng, T. C., Hajiyev, J., & Chia-Rong, S. (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? The General Extended Technology Acceptance Model for E-learning approach. Computer & Education, 111, 128-143. https://doi.org/10.1016/j.compedu.2017.04.010
- Chien, T.-C. (2012). Computer self-efficacy and factors influencing e-learning effectiveness. European Journal of Training and Development, 36(7), 670-686. https://doi.org/10.1108/03090591211255539
- Chin, W. (1998). The partial least squares approach to structural equation modelling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-358). Lawrence Erlbaum Associates.
- Chunjaun, Z., & Zongxiang, M. (2016). A case study of American and Chinese college students’ motivation differences in online learning environment. Journal of Education and Learning, 5(4), 104-112. https://doi.org/10.5539/jel.v5n4p104
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
- Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1002. https://doi.org/10.1287/mnsc.35.8.982
- El Elkaseh, A. M., Wong, K. W., & Fung, Ch. Ch. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: A structural equation modeling analysis. International Journal of Information and Education Technology, 6(3), 192-199. https://doi.org/10.7763/IJIET.2016.V6.683
- El-Seoud, S., Taj-Eddin, I., Seddiek, N., Ghenghesh, P., & El-Khouly, M. (2014). The impact of e-learning on Egyptian higher education and its effect on learner’s motivation: A case study. Computer Science and Information Technology, 2(3), 179-187. https://doi.org/10.13189/csit.2014.02030
- Fathema, N., Shannon, D., & Ross, M. (2015). Expanding The Technology Acceptance Model (TAM) to examine faculty use of learning management systems (LMSs) in higher education institutions. MERLOT Journal of Online Learning and Teaching, 11(2), 210-232.
- Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis. Pearson Prentice Hall.
- Harandi, S. R. (2015) Effects of e-learning on students’ motivation. Procedia - Social and Behavioral Sciences, 181, 423-430. https://doi.org/10.1016/j.sbspro.2015.04.905
- Holden, H. (2011). Understanding the influence of perceived usability and technology self-efficacy on teachers’ technology acceptance. Journal of Research on Technology in Education, 43(4), 343-367. https://doi.org/10.1080/15391523.2011.10782576
- Hoyle, R. H., & Panter, A. T. (1995). Writing about structural equation models. In R. H. Hoyle (Ed.), Structural equation modelling (pp. 158-176). Sage.
- Huang, H. M., & Liaw, S. S. (2005). Exploring users’ attitudes and intentions toward the Web as a survey tool. Computers in Human Behavior, 21(5), 729-743. https://doi.org/10.1016/j.chb.2004.02.020
- Junus, I. S., Santoso, H. B., Yugo K. Isal, R., & Utomo, A. Y. (2015). Usability evaluation of the student centered e-learning environment. International Review of Research in Open and Distance Learning, 16(4), 62-82. https://doi.org/10.19173/irrodl.v16i4.2175
- Juwah, C. (2006). Interactions in online peer learning. In C. Juwah (Ed.), Interactions in online education (pp. 171-190). Routledge. https://doi.org/10.4324/9780203003435
- Keller, J. M., & Suzuki, K. (2004). Learner motivation and e-learning design: A multinational validated process. Journal of Educational Media, 29(3), 229-239. https://doi.org/10.1080/1358165042000283084
- Khor, E. T. (2014). An analysis of ODL student perception and adoption behavior using the technology acceptance model. International Review of Research in Open and Distance Learning, 15(6), 275-288. https://doi.org/10.19173/irrodl.v15i6.1732
- King, W. R., & He, J. (2006). A meta-analysis of the Technology Acceptance Model. Information & Management, 43(6), 740-755. https://doi.org/10.1016/j.im.2006.05.003
- Krejcie, V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308
- Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. Journal of Information Systems and Technology Management, 14(1), 21-38. https://doi.org/10.4301/S1807-17752017000100002
- Lay, J. G., & Chen, Y. W. (2011, October). GIS adoption and diffusion among senior high school geography teachers in Taiwan. In P. Shih (Ed.), ISPRS Workshop Commissions VI/1 – VI/2 E-learning 2011 with ACRS. http://www.isprs.org/proceedings/XXXVIII/6-W27/pdf/P_41_8-16-19.pdf
- Lee, Y. (2006). An empirical investigation into factors influencing the adoption of an e-learning system. Online Information Review, 30(5), 517-541. https://doi.org/10.1108/14684520610706406
- Lee, Y., Kozar, K. A., & Larsen, K. (2003). The Technology Acceptance Model: Past, present, future. Communication of the Associations for Information Systems, 12, 752-780. https://doi.org/10.17705/1CAIS.01250
- Lin, Y.-C., Chen, Y.-C., & Yeh, R. C. (2010). Understanding college students’ continuing intentions to use multimedia E-learning systems. World Transactions on Engineering and Technology Education, 8(4), 488-493.
- Liu, I.-F., Chen, M. C., Sun, Y. S., Wible, D., & Kuo, C.-H. (2010). Extending the TAM model to explore the factors that affect intention to use an online learning community. Computers & Education, 54(2), 600-610. https://doi.org/10.1016/j.compedu.2009.09.009
- Lu, J., Yu, C., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research: Electronic Networking Applications and Policy, 13(3), 206-222. https://doi.org/10.1108/10662240310478222
- Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-374. https://doi.org/10.1016/j.chb.2014.07.044
- Nafsaniath, F., & Shannon. D. (2015). Expanding the Technology Acceptance Model (TAM) to examine faculty use of Learning Management Systems (LMSs) in higher education institutions. MERLOT Journal of Online Learning and Teaching, 11(2), 210-232.
- Nath, R., Bhal, K. T., & Kapoor, G. T. (2014). Factors influencing IT adoption by bank employees: An extended TAM approach. Vikalpa, 38(4), 83-96. https://doi.org/10.1177/0256090920130406
- Oblinger, D. G., & Hawkins, B. L. (2005). The myth about e-learning. Edu cause review.
- Ong, C.-H., & Lai, J. Y. (2006). Gender differences in perceptions and relationships among dominants of e- learning acceptance Computer in Human Resource, 22(5), 816-829. https://doi.org/10.1016/j.chb.2004.03.006
- Paechter, M., Marier, B. & Macher, M (2020) Students’ expectations of, and experiences in e-learning: Their relation to learning achievements and course satisfaction. Computer & Education 54(1) 222-229. https://doi.org/10.1016/j.compedu.2009.08.005
- Pham, L., Limbu, Y. B., Bui, T. K., Nguyen, H. T., & Pham, H. T. (2019). Does e-learning service quality influence e-learning student satisfaction and loyalty? Evidence from Vietnam. International Journal of Educational Technology in Higher Education, 16, 7. https://doi.org/10.1186/s41239-019-0136-3
- Ringle, M., Wende, S., & Becker, J.-M. (2015). SmartPLS 3. Bönningstedt: SmartPLS. Technical Report.
- Roca, J. C., Chiu, C. M., & Jose-Martinez Lopez, F. (2006). Understanding e-Learning continuance intention: An extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683-696. https://doi.org/10.1016/j.ijhcs.2006.01.003
- Rym, B., Bouzaabia, O., & Mélika, B. M. (2013). Determinants of E-learning acceptance: An empirical study in the Tunisian context. American Journal of Industrial and Business Management, 3(3), 307-321. https://doi.org/10.4236/ajibm.2013.33036
- Salajan, F. D., Welch, A. G., Ray, C. M., & Peterson, C. (2015). The role of peer influence and perceived teaching quality in faculty acceptance of web-based learning management systems. International Journal on E-Learning, 14(4), 487-524.
- Salloum, S. (2018). Investigating students’ acceptance of E-learning system in Higher Educational Environments in the UAE: Applying the Extended Technology Acceptance Model (TAM) [MSc dissertation]. The British University in Dubai.
- Salloumi, S., AlHamad, A. Q. M., Al-Emran, M., Abdel Monem, A., & Shaalan, K. (2019). Exploring students’ acceptance of e-learning through the development of a comprehensive technology acceptance model. IEEE Access, 7, 128445-128462. https://doi.org/10.1109/ACCESS.2019.2939467
- Sangrà, A., Vlachopoulos, D., & Cabrera, N. (2012). Building an inclusive definition of e-learning: An approach to the conceptual framework. The International Review of Research in Open and Distributed Learning, 13(2), 145-159. https://doi.org/10.19173/irrodl.v13i2.1161
- Schunk, D. H., Meece, J. L., & Pintrich, P. R. (2014). Motivation in education: Theory, research, and applications (4th ed.). Pearson.
- Shawai, Y. G., & Almaiah, M. A. (2018). Malay language mobile learning system (MLMLS) using NFC technology. International Journal of Education and Management Engineering, 8(2), 1. https://doi.org/10.5815/ijeme.2018.02.01
- Shen, D., Laffey, J., Lin, Y., & Huang, X. (2006). Social influence for perceived usefulness and ease-of-use of course delivery systems. Journal of Interactive Online Learning, 5(3), 270-282. http://www.ncolr.org/jiol/issues/getfile.cfm?volID=5&IssueID=18&ArticleID=91
- Singh, G., O’Donoghue, J., & Worton, H. (2005). A study into the effects of e-learning on higher education. Journal of University Teaching & Learning Practice, 2(1), 3. https://doi.org/10.53761/1.2.1.3
- Sorebo, O., Halvari, H., Gulli, V. F., & Kristiansen, R. (2009). The role of self-determination theory in explaining teachers’ motivation to continue to use elearning technology. Computers & Education, 53(4), 1177-1187. https://doi.org/10.1016/j.compedu.2009.06.001
- Sun, P. C., Tsai, R. J., Finger, G., Chen, Y.-Y., & Yeh, D. (2008). What drives a successful eLearning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202. https://doi.org/10.1016/j.compedu.2006.11.007
- Teo, T., & Zho, M. (2014). Explaining the intention to use technology among university students: A structural equation modeling approach. Journal of Computing in Higher Education, 26(2), 124-142. https://doi.org/10.1007/s12528-014-9080-3
- Thatcher, J. B., & Perrewé, P. L. (2002). An empirical examination of individual traits as antecedents to computer anxiety and computer self-efficacy. MIS Quarterly, 26(4), 381-396. https://doi.org/10.2307/4132314
- Turner, M., Kitchenham, B., Brereton, P., Charter, S., & Budgen, D. (2010). Does the technology acceptance model predict actual use? A systematic literature review. Information and Software Technology, 52(5), 436-479. https://doi.org/10.1016/j.infsof.2009.11.005
- Venkatesh, V. (1999). Creation of favorable user perceptions: exploring the role of intrinsic motivation. Management Information Systems Quarterly, 23(2), 239-260. https://doi.org/10.2307/249753
- Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365. https://doi.org/10.1287/isre.11.4.342.11872
- Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273-315. https://doi.org/10.1111/j.1540-5915.2008.00192.x
- Venkatesh, V., & Davis, F. D. (1999). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481. https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
- Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model four longitudinal field studies. Management Science, 46(2), 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
- Venkatesh, V., Davis, F. D., & Morris, M. G. (2007). Dead or alive? The development, trajectory and future of technology adoption research. Journal of Association for Information Systems, 8(4), 267-286. https://doi.org/10.17705/1jais.00120
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information Technology Toward a unified view. motivation. Management Information Systems Quarterly, 27(3), 426-478. https://doi.org/10.2307/30036540
- Venkatesh, V., Morris, M. G., Davis, M. G., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
- Vonderwell, S., & Zachariah, S. (2005). Factors that influence participation in online learning. Journal of Research on Technology in Education, 38(2), 213-230. https://doi.org/10.1080/15391523.2005.10782457
- Waheed, M., & Jam, A. F. (2010). Teachers’ intention to accept online education: Extended TAM model. Interdisciplinary Journal of Contemporary Research in Business, 2, 330-344.
- Waheed, M., & Kaur, K. (2014). Knowledge quality: A review and a revised conceptual model. Information Development, 32(3), 271-284. https://doi.org/10.1177/0266666914539694
- Waheed, M., Kaur, K., Ul Ain, N., & Hussain, N. (2015). Perceived learning outcomes from Moodle: An empirical study of intrinsic and extrinsic motivating factors. Information Development, 32(4), 1001-1013. https://doi.org/10.1177/0266666915581719
- Yaldirim, S. (2000) Effects of an educational computing course on preservice and inser vice teachers: A discussion and analysis of attitudes and use. Journal of Research on Computing in Education, 32(4), 479-495. https://doi.org/10.1080/08886504.2000.10782293
- Young, J. (2002). Online teaching redefines faculty members’ schedules, duties, and relationships with students. Chronicle of Higher Education.
- Yusuf, N., & Al-Banawi, N. (2013). The impact of changing technology: The case of e-learning. Contemporary Issues in Education Research – Second Quarter, 6(2), 173. https://doi.org/10.19030/cier.v6i2.7726
- Zaharias, P., & Poylymenakou, A. (2009). Developing a usability evaluation method for e-learning applications: Beyond functional usability. International Journal of Human-Computer Interaction, 25(1), 75-98. https://doi.org/10.1080/10447310802546716
- Zainab, B., Awais Bhatti, M., & Alshagawi, M. (2017). Factors affecting e-training adoption: An examination of perceived cost, computer self-efficacy and the technology acceptance model. Behaviour & Information Technology, 36(12), 1261-1273. https://doi.org/10.1080/0144929X.2017.1380703
- Zeitoun, S. (2015). Instructional design in science: Using scenarios in e-learning. International Journal of Humanities Social Sciences and Education, 2(8), 80-89.
- Zemsky, R., & Massy, W. (2004). Thwarted innovation: What happened to e-learning and why. Learning Alliance, University of Pennsylvania. http://www.irhe.upenn.edu/WeatherStation.html
How to cite this article
APA
Shishakly, R. (2021). A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE. Eurasia Journal of Mathematics, Science and Technology Education, 17(11), em2025. https://doi.org/10.29333/ejmste/11234
Vancouver
Shishakly R. A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE. EURASIA J Math Sci Tech Ed. 2021;17(11):em2025. https://doi.org/10.29333/ejmste/11234
AMA
Shishakly R. A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE. EURASIA J Math Sci Tech Ed. 2021;17(11), em2025. https://doi.org/10.29333/ejmste/11234
Chicago
Shishakly, Rima. "A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE". Eurasia Journal of Mathematics, Science and Technology Education 2021 17 no. 11 (2021): em2025. https://doi.org/10.29333/ejmste/11234
Harvard
Shishakly, R. (2021). A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE. Eurasia Journal of Mathematics, Science and Technology Education, 17(11), em2025. https://doi.org/10.29333/ejmste/11234
MLA
Shishakly, Rima "A Further Understanding of the Dominant Factors Affecting E-learning Usage Resources by Students in Universities in the UAE". Eurasia Journal of Mathematics, Science and Technology Education, vol. 17, no. 11, 2021, em2025. https://doi.org/10.29333/ejmste/11234