Interdisciplinary Journal of Virtual Learning in Medical Sciences

Published by: Kowsar

Prediction of Achievement based on Different Dimensions of E-learning Materials in University of Mysore, India

Razieh Rahmani 1 , * and G. Sheela 2
Authors Information
1 Research Scholar, Department of Education, University of Mysore, India
2 Department of Education, University of Mysore, India
Article information
  • Interdisciplinary Journal of Virtual Learning in Medical Sciences: June 2017, 8 (2); e10651
  • Published Online: June 30, 2017
  • Article Type: Research Article
  • Received: March 9, 2017
  • Revised: April 17, 2017
  • Accepted: May 30, 2017
  • DOI: 10.5812/ijvlms.10651

To Cite: Rahmani R, Sheela G. Prediction of Achievement based on Different Dimensions of E-learning Materials in University of Mysore, India, Interdiscip J Virtual Learn Med Sci. 2017 ; 8(2):e10651. doi: 10.5812/ijvlms.10651.

Copyright © 2017, 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. Background
2. Methods
3. Results
4. Discussion and Conclusion
  • 1. Khan BH. Web-based training: Educational Technology. 2001;
  • 2. Harrison TM, Stephen T. Computer networking and scholarly communication in the twenty-first-century university. 1996;
  • 3. Leidner DE, Fuller M. Improving student learning of conceptual information: GSS supported collaborative learning vs. individual constructive learning. Decision Support Systems. 1997; 20(2): 149-63[DOI]
  • 4. Piccoli G, Ahmad R, Ives B. Web-Based Virtual Learning Environments: A Research Framework and a Preliminary Assessment of Effectiveness in Basic IT Skills Training. MIS Q. 2001; 25(4): 401[DOI]
  • 5. Ehlers UD. Quality in e-learning: use and dissemination of quality approaches in European e-learning: a study by the European Quality Observatory. 2005;
  • 6. Balatsoukas P, Garoufallou E, Asderi S, Siatri R. A survey on the importance of learning object metadata for relevance judgment. Metadata Semantic Res. 2011; : 300-11
  • 7. Ling SW, Yuen MC, Chuah KM. Optimizing Multimedia Learning Objects for Learning in a Procedural-based Course. 2015;
  • 8. Clark RC, Lyons C. Graphics for learning: Proven guidelines for planning, designing, and evaluating visuals in training materials. 2010;
  • 9. Chawla S, Gupta N, Singla RK. LOQES: model for evaluation of learning object. Int J Adv Comput Sci Appl. 2012; 3(7): 73-9
  • 10. Alla MMSO, Faryadi Q. The effect of information quality in e-learning system. Int J Appl. 2013; 3(6)
  • 11. Gibbons AS, Nelson J, Richards R. The nature and origin of instructional objects. The instructional use of learning objects. Bloomington. 2000;
  • 12. Garrison DR. E-learning in the 21st century: A framework for research and practice. 2011;
  • 13. Alonso F, Lopez G, Manrique D, Vines JM. Learning objects, learning objectives and learning design. Innov Educ Teach Int. 2008; 45(4): 389-400[DOI]
  • 14. Bouhnik D, Marcus T. Interaction in distance-learning courses. J Am Soc Inf Sci Technol. 2006; 57(3): 299-305[DOI]
  • 15. Brande S. Learning objects for instruction: Design and evaluation - By Pamela T Northrup. Br J Educ Technol. 2010; 41(6): 977-8[DOI]
  • 16. Polsani PR. Use and abuse of reusable learning objects. J Digital Inf. 2006; 3(4)
  • 17. Lau SH, Woods PC. An investigation of user perceptions and attitudes towards learning objects. Br J Educ Technol. 2008; 39(4): 685-99[DOI]
  • 18. Ozkan S, Koseler R. Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation. Comput Educ. 2009; 53(4): 1285-96[DOI]
  • 19. Liaw SS, Huang HM, Chen GD. Surveying instructor and learner attitudes toward e-learning. Comput Educ. 2007; 49(4): 1066-80[DOI]
  • 20. Clark RC. Developing technical training: A structured approach for developing classroom and computer-based instructional materials. 2011;
  • 21. Jung I. The dimensions of e-learning quality: from the learner’s perspective. Educ Technol Res Dev. 2010; 59(4): 445-64[DOI]
  • 22. Hansson H. E-learning quality. Aspects and criteria for evaluation of e-learning in higher education. 2008;
  • 23. Frydenberg J. Quality Standards in eLearning: A matrix of analysis. Int Rev Res Open Distrib Learn. 2002; 3(2)[DOI]
  • 24. Quality assurance for online courses: From policy to process to improvement. Meeting at the Crossroads. : 435-42
  • 25. Sun PC, Tsai RJ, Finger G, Chen YY, Yeh D. What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Comput Educ. 2008; 50(4): 1183-202[DOI]
  • 26. Howard-Rose D, Harrigan K. CLOE learning impact studies lite: Evaluating learning objects in nine Ontario university courses. Retrieved July. 2003; 3: 2007
  • 27. Mestre LS. Matching up learning styles with learning objects: What's effective? J Lib Administ. 2010; 50(7-8): 808-29
  • 28. Kay RH. Examining Factors That Influence the Effectiveness of Learning Objects in Mathematics Classrooms. Can J Sci Math Technol Educ. 2012; 12(4): 350-66[DOI]
  • 29. Lau SH, Woods PC. Understanding learner acceptance of learning objects: The roles of learning object characteristics and individual differences. Br J Educ Technol. 2009; 40(6): 1059-75[DOI]
  • 30. Lehman RM, Conceicao SCO. Creating a sense of presence in online teaching: How to" be there" for distance learners. 2010; 18
Creative Commons License Except where otherwise noted, this work is licensed under Creative Commons Attribution Non Commercial 4.0 International License .
Readers' Comments