You are here:

Designing a Mobile Training System in Rural Areas with Bayesian Factor Models
ARTICLE

, , Department of Agricultural Extension and Education, Science and Research Branch, Islamic Azad University, Tehran, Iran., Iran (Islamic Republic Of) ; , Mathematical Sciences Department, Shahid Beheshti University,G.C. Evin, 1983963113, Tehran, Iran, Iran (Islamic Republic Of)

International Journal on E-Learning, ISSN 1537-2456 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA

Full Text

Abstract

The facts that the wireless technologies (1) are more convenient; and (2) need less skill than desktop computers, play a crucial role to decrease digital gap in rural areas. This study employed the Bayesian Confirmatory Factor Analysis (CFA) to design a mobile training system in rural areas of Iran. It categorized challenges, potential, and requirements of such mobile training system into 6, 3, and 4 factors, respectively. Namely, it pointed out and, respectively, ranked (1) the system’s challenges as “Human, Phone Company, Organizational, Technical, Expertise, and Security”; (2) “Post harvest, Pre-cultivation, and Crop cultivation & harvesting stages” as the system’s potentials; and (3) “Attitude toward the system, Mobile Skills, Self-directed learning skills, and Opinion about the price” as the system’s requirements.

Citation

Omidi Najafabadi, M., Mirdamadi, S.M. & Payandeh Najafabadi, A.T. (2014). Designing a Mobile Training System in Rural Areas with Bayesian Factor Models. International Journal on E-Learning, 13(1), 23-39. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved August 12, 2024 from .

© 2014 Association for the Advancement of Computing in Education (AACE)

References

View References & Citations Map
  1. Arbaugh, J. B. (2000). Virtual classroom characteristics and student satisfaction with Internet-based MBA courses. Journal of Management Education, 24(1), 32—54.
  2. Agresti, A. (2003). Categorical data analysis. New York: John Wiley and Sons.
  3. Basole, R.C. (2006). Modeling and analysis of complex technology adoption decisions: an investigation in the domain of mobile ICT. (PhD dissertation, Georgia Institute of Technology).
  4. Cantoni, V., Cellario, M. & Porta, M. (2004). Perspective and challenges in e-learning: towards natural interaction paradigms. Journal of Visual Languages and Computing, 15, 335—345.
  5. Chapnick, S. (2000). Are you ready for e-learning? Available at: http://www.astd.org/ASTD/resources/dyor/article_archives.htm
  6. Connetha, M. (2007). Mobile Learning in the Classroom. Research paper on the use and effectiveness of using mobile phones for learning with college students using a commercial m-learning platform. West Chester University. Delivered at SALT Conference in Arlington, VA. August 2007.
  7. Egfar organization website (2009). Available at: http://www.egfar.org/egfar/---/2255_A_ Mind_map_for_ICT_in_Agriculture.p_mind_mapp
  8. Flores, R. C., and Morteo, G. L. (2010). A Framework for Educational Collaborative Activities Based on Mobile Devices: A Support to the Instructional Design. International Journal of Interactive Mobile Technologies, 4(3), pp-9.
  9. Gastaldo, I., Alnerich,G., Diaz,I. Bo, R., & Suarez, J.M.(2005). Analysis of ICT training needs according to gender in primary and secondary school teachers. Available at: www.formatex.org/micte2005/164.pdf
  10. Gilan Telecommunication Company (2009). Cell Phone Subscribers Services Section. Guglielmino, P.J. And Guglielmino, L.M. (2002). Are you learners ready for e-learning? AMA handbook of online learning. New York American Management Association.
  11. Gunawardana, K.D. (2005). An empirical study of potential challenges and benefits of implementing e-learning in Sri-Lanka. Proceedings of the second international conference on e-learning for knowledge-based society. Bangkok-Thailand.
  12. Haney, D. (2002). Assessing organizational readiness for e-learning: 70 questions to ask. Performance improvement, available at: www.ispi.org
  13. Hosmer, D. W. & Lemshow, S. (2000). Applied logistic regression. 2nd ed. New York: John Willey & Sons.
  14. Ismail, I., Johari, S. S. M., and Idrus, R. M. (2010). Acceptance on Mobile Learning via SMS: A Rasch Model Analysis. International Journal of Interactive Mobile Technologies, 4(2).
  15. Johnson, V. E., Albert, J. H., & Albert, J (1999). Ordinal data modeling. New York: Springer. Joreskog, K. G. & Moustaki, I. (2001). Factor Analysis of Ordinal Variables: A Comparison of Three Approaches. Multivariate Behavioral Research, 36(3), pp 347—387.
  16. Joreskog, K. G. & Moustaki, I. (2006). Factor analysis of ordinal variables with full information maximum likelihood. Technical report printed by Athens University of Economics and Business.
  17. Karmakar, C. K., and Wahid, C. M. (2000). Recommendations for Bangladesh towards e-learning readiness. In MMT 2006, Methods, Materials and Tools for Programming
  18. Kaur, J. (2009). ICT and changing roles of teacher. Education New Horizons, 6(22), JanMarch,2009.
  19. Kay, R. H. (1989). Gender differences in computer attitudes, literacy, locus of control and commitment. Journal of Research on Computing in Education, 21, 307—316.
  20. Kim, K.J. (2005). Adult learners’ motivation in self directed learning e-learning. (Ph.D. Dissertation. Indiana University).
  21. Kon, C.L. (2009) Mobile learning: Different technologies Aspects, Designing usable systems, Computer and Internet Technologies. University of Strathclyde.
  22. Koo, A.C. (2008). Factors affecting teachers’ perceived readiness for online collaborative learning: a case study in Malaysia. Journal of Educational Technology and Society, 11(1), 266-278.
  23. Laouris, Y., and Eteokleous, N. (2005). Experiences from the application of knowledgepackets as means for educationally mentally and socially balanced instruction. Presented at 3rd International Conference on Multimedia and Information & Communication Technologies in Education (m-ICTE 2005), Spain, June 8-10.
  24. Leary, J. & Berge, Z. L. (2005). Trends and challenges of e-learning in national and international agricultural development. International Journal of Education and Development Using ICT. 2(2), 51-59.
  25. Lee, S. Y (2007). Structural Equation Modeling: A Bayesian Approach. New York: John Wiley.
  26. Lehmann, E. L. & Casella, G. (1998). Theory of Point Estimation. 2nd ed., New York: Springer-Verlag.
  27. Liu, H. (2005). Discussion about factors affecting e-learning training transfer. Master's thesis. Available at: http://etd.Lib.nsysu.edu.tw
  28. Marshall, J. C. & Bannon, S.H. (1986). Computer attitudes and computer knowledge of students and educators. Association for Education Data Systems Journal, 18, pp 270—286.
  29. Masters, K. (2005) Low-key m-learning: a realistic introduction of m-learning to developing countries. Presented at the Conference of the Hungarian Academy of Sciences:
  30. Piskurich, G. M. (Ed.) (2003). Are your learners ready for e-learning? The AMA handbook of e-learning: Effective design, implementation, and technology solutions. New York: AMACOM, pp 87-98.
  31. Robert, C. (2001). The Bayesian Choice. 2nd ed., New York: Springer-Verlag.
  32. Samak, Z. A. (2006). An exploration of Jordanian English language teachers’ attitudes, skills and access as indicator of ICT integration in Jordan. (PhD dissertation, The Florida State University).
  33. Sharples, M., Taylor, J., and Vavoula, G. (2005). Towards a theory of mobile learning. Available at http://www.mlearn.org.za/CD/papers/Sharples
  34. Shepherd, C. (2001). M is for Maybe. Fastrak Consulting Ltd. Available at http://www.fastra K-consulting.co.uk/tactix/features/mlearning.htm
  35. SORT Website (2008). Student Online Readiness Tool Website. Available at: http://alt.usg .edu/sort/html/tool.html
  36. Sribhadung, R. A. (2006). Mobile devices in e-learning. Third international conference on e-learning for knowledge-based society Bangkok, Thailand. 35, pp 1—5.
  37. Straka, G.A., Kliemann, M., and Stokl, M. (1994). Self-organized job related learning: an empirical study. International self-directed learning symposia. In H.B. Long and Associates, New Ideas about Self Directed Learning. Pp 149-160. Norman, Oklahoma.
  38. Sun, P., Tsai, R., Finger, G., Chen, Y., and Yeh, D. (2008). What drives a successful elearning an empirical investigation of the critical factors influencing learner satisfaction? Computes and education Journal, 4(50), pp 1183-1202.
  39. Thurmond, V. A., Wambach, K., and Connors, H. R. (2002). Evaluation of student satisfaction: determining the impact of a Web-based environment by controlling for
  40. Tyan, K. J. (2003). Diffusion barriers to e-learning in corporate Taiwan: a factor analysis of practitioners’ perspective. (PhD dissertation, Indiana University). Website of the Wikipedia. (Available at: http://en.wikipedia.org/wiki)
  41. Wood, K. (2003). Introduction to Mobile Learning. Available at http://ferl.becta.org.uk/Yunus, M. (2009). Mobile telephony in rural areas. E-agriculture, policy brief-March2009.

These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.

Suggest Corrections to References

Also Read

Related Collections