E-Learning Maturity of Iranian agricultural higher education based on Misra and Dhingra models and its hookup using artificial neural network

Saadi, H.; Mirzaei, Kh.

doi:10.22061/jte.2017.728

Document Type : Original Research Paper

Authors

Agricultural Extension and Education Department, Bu Ali Sina University, Hamedan, Iran

https://doi.org/10.22061/jte.2017.728

Abstract

E-learning is an artistic educational system and a comprehensive solution for those institutions that want to move in the path of technology of the day and change their teaching methods and environments. The purpose of this study is looking for identification and awareness of the current status of e-learning in universities and higher education institutions to draw the desired situation in this field, and at the same time, review the reasons for the lack of development of e-learning in that area. In this article, the maturity six-level model of Misra and Dingra were used (Levels: Closed, Preliminary, Initial presence, Perceived, Institutionalized, Optimized). This research is a survey. The statistical population of the study includes faculty members and postgraduate students in higher education in agriculture in Iran. The sample size is calculated using the Cochran formula and the sample population of the study was selected by random sampling in several steps which is 517 people. In this study, the questionnaire was used in order to collect the required information. The precision of indices and items cited in the questionnaire, or face validity, was confirmed by the specialists and professors. To investigate the reliability and internal consistency of the study instrument, Cronbach's alpha was used. Cronbach's alpha value was 0.86. In order to analyze the collected data Weka software and artificial neural networks were used. In this paper, based on Misra and Dhingra models, the 6 above levels were data analyzed. After analysis by artificial neural networks and communicating between electronic maturity levels, the fourth level or "realized level", with 82.37% accuracy of information, and with the fewest amount of errors (7 %) was more desirable compared to other levels.

Keywords

20.1001.1.20080441.1396.11.4.1.4

Main Subjects

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E-Learning Maturity of Iranian agricultural higher education based on Misra and Dhingra models and its hookup using artificial neural network

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Volume 11, Issue 4 - Serial Number 44
October 2017
Pages 285-300

E-Learning Maturity of Iranian agricultural higher education based on Misra and Dhingra models and its hookup using artificial neural network

References

References

Send comment about this article

Volume 11, Issue 4 - Serial Number 44October 2017Pages 285-300

Volume 11, Issue 4 - Serial Number 44
October 2017
Pages 285-300