Interdisciplinary Journal of Virtual Learning in Medical Sciences

Published by: Kowsar

Impact of Personal and Environmental Factors on the Effectiveness in Academic E-Learning Systems; A Case Study: E-Learning System of The University of Sistan and Baluchestan

Fatemeh Saghafi 1 , * , Saeideh Ansari 2 and Seyed Morteza Syedin 2
Authors Information
1 Assistant Professor of Faculty of Management of University of Tehran, IR Iran
2 Master of Science in IT management, Sisten Baluchestan University, IR Iran
Article information
  • Interdisciplinary Journal of Virtual Learning in Medical Sciences: June 2016, 7 (2); e12155
  • Published Online: June 30, 2016
  • Article Type: Research Article
  • Received: September 8, 2015
  • Revised: June 25, 2016
  • Accepted: June 30, 2016
  • DOI: 10.5812/ijvlms.12155

To Cite: Saghafi F, Ansari S, Syedin S M. Impact of Personal and Environmental Factors on the Effectiveness in Academic E-Learning Systems; A Case Study: E-Learning System of The University of Sistan and Baluchestan, Interdiscip J Virtual Learn Med Sci. 2016 ; 7(2):e12155. doi: 10.5812/ijvlms.12155.

Copyright © 2016, Interdisciplinary Journal of Virtual Learning in Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.
1. Introduction
2. Methods
3. Results
4. Discussion and Conclusions
  • 1. Chen HR, Tseng HF. Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Eval Program Plann. 2012; 35(3): 398-406[DOI][PubMed]
  • 2. Sharma K, Pandit P, Pandit P. Critical success factors in crafting strategic architecture for e-learning at HP University. Int J Educ Manag. 2011; 25(5): 423-52
  • 3. Hong K, Cheng JLA, Liau T. Effects of system's and user's characteristics on e-learning use: A study at Universiti Malaysia Sarawak. J Sci Math Educ Southeast Asia. 2005; 28(2): 1
  • 4. Pituch KA, Lee YK. The influence of system characteristics on e-learning use. Comput Educ. 2006; 47(2): 222-44[DOI]
  • 5. Yaghubi NM, Shakeri R. Technology acceptance models; analytical-comparison approach. Res Manag. 2008; 1(2): 205-31
  • 6. Zhang Y, Fang Y, Wei KK, Wang Z. Promoting the intention of students to continue their participation in e‐learning systems. Inf Technol People. 2012; 25(4): 356-75[DOI]
  • 7. Gibson CB, Gibbs JL. Unpacking the Concept of Virtuality: The Effects of Geographic Dispersion, Electronic Dependence, Dynamic Structure, and National Diversity on Team Innovation. Administ Sci Q. 2006; 51(3): 451-95[DOI]
  • 8. Asiri MJ, Mahmud RB, Abu Bakar K, Mohd Ayub AFB. Factors Influencing the Use of Learning Management System in Saudi Arabian Higher Education: A Theoretical Framework. High Educ Stud. 2012; 2(2)[DOI]
  • 9. Pavlic, L. , Pusnik ,M. , Hericko, M. , Sumak, B. . Qualitative analysis: Identification of the factors influencing e-learning system acceptance. Third International Conference on Mobile, Hybrid, and Online Learning. 2011;
  • 10. Sawang S, Newton C, Jamieson K. Increasing learners’ satisfaction/intention to adopt more e‐learning. Educ Train. 2013; 55(1): 83-105[DOI]
  • 11. Al‐hawari MA, Mouakket S. The influence of technology acceptance model (TAM) factors on students' e‐satisfaction and e‐retention within the context of UAE e‐learning. Educ Business Soc Contemporary Middle Eastern Issues. 2010; 3(4): 299-314[DOI]
  • 12. Dasgupta S, Granger M, McGarry N. User acceptance of e-collaboration technology: an extension of the technology acceptance model. Group Decision Negotiat. 2002; 11(2): 87-100[DOI]
  • 13. Padilla-Melendez A, Garrido-Moreno A, Del Aguila-Obra AR. Factors affecting e-collaboration technology use among management students. Comput Educ. 2008; 51(2): 609-23[DOI]
  • 14. Ong CS, Lai JY, Wang YS. Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies. Inf Manag. 2004; 41(6): 795-804[DOI]
  • 15. Lee YH, Hsieh YC, Ma CY. A model of organizational employees’ e-learning systems acceptance. Knowledge Base Systems. 2011; 24(3): 355-66[DOI]
  • 16. Wagner N, Hassanein K, Head M. Computer use by older adults: A multi-disciplinary review. Comput Human Behav. 2010; 26(5): 870-82[DOI]
  • 17. Cheng B, Wang M, Yang SJH, Peng J. Acceptance of competency-based workplace e-learning systems: Effects of individual and peer learning support. Comput Educ. 2011; 57(1): 1317-33[DOI]
  • 18. Chen M, Liao JL. Correlations among Learning Motivation, Life Stress, Learning Satisfaction, and Self-Efficacy for PhD. Students. J Int Manag Stud. 2013; 8(1): 157
  • 19. Salimon MG, Yusoff RZ, Abdullateef AO. The mediating effects of e-satisfaction on the relationship between eBanking adoption and its determinants: A conceptual framework. J Manag Inf System E-Commerce. 2014; 1(1): 95-105
  • 20. Langerak F, Verhoef PC, Verlegh PWJ, Valck K. Satisfaction and participation in virtual communities. NA Adv Consume Res. 2004; 31: 56-7
  • 21. Wu JH, Tennyson RD, Hsia TL. A study of student satisfaction in a blended e-learning system environment. Comput Educ. 2010; 55(1): 155-64[DOI]
  • 22. Hirak R, Peng AC, Carmeli A, Schaubroeck JM. Linking leader inclusiveness to work unit performance: The importance of psychological safety and learning from failures. Leadersh Q. 2012; 23(1): 107-17[DOI]
  • 23. van Gennip NAE, Segers MSR, Tillema HH. Peer assessment as a collaborative learning activity: The role of interpersonal variables and conceptions. Learn Instruct. 2010; 20(4): 280-90[DOI]
  • 24. May DR, Gilson RL, Harter LM. The psychological conditions of meaningfulness, safety and availability and the engagement of the human spirit at work. J Occup Organiz Psychol. 2004; 77(1): 11-37[DOI]
  • 25. de los Ríos Carmenado I, Díaz-Puente JM, Gajardo FG. Behavior competence development through e-learning: experience at the undergraduate level in the context of Aula a Distancia Abierta (ADA) Madrid, Spain. Proc Soc Behav Sci. 2011; 15: 111-9[DOI]
  • 26. Panda BP, Swain DK. Effective Communications through e-Governance and e-Learning. Chinese Librariansh Int Electron J. 2009; (27)
  • 27. Cheng YM. Exploring the roles of interaction and flow in explaining nurses' e-learning acceptance. Nurse Educ Today. 2013; 33(1): 73-80[DOI][PubMed]
  • 28. Human HA. Structural equation modeling using LISREL software (with changes). 2014;
  • 29. Hubona GS. Structural equation modeling (SEM) using SmartPLS software: Analyzing path models using partial least squares (PLS) based SEM. 2009;
  • 30. Ringle CM, Wende S, Will A. Smart PLS 2. 2005;
  • 31. Ringle CM, Wende S, Becker JM. Smart PLS 3. 2015;
  • 32. Templeton GF, Byrd TA. Determinants of the relative advantage of a structured SDM during the adoption stage of implementation. Information Technology and Management. 2003; 4(4): 409-28
  • 33. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis. 1998;
  • 34. Wetzels M, Odekerken-Schröder G, Van Oppen C. Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Q. 2009; : 177-95
  • 35. Omoiee Milan Ghashghagh M, Mehdinezhad V, Yaghoubi N. Assessing Factors Affecting the Tendancy to Use Electronic Learning Systems among Faculty Members. Interdisciplinar J Virtual Learn Med Sci. 2012; 2(3): 28-38
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