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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SAADI HESHMATOLLAH; MIRZAYI KHALIL

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Journal: Technology of Education Journal Year:2017 | Volume:12 | Issue:1 Page(s): 1-16

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Title

E-LEARNING MATURITY OF IRANIAN AGRICULTURAL HIGHER EDUCATION BASED ON MISRA AND DHINGRA MODELS AND ITS HOOKUP USING ARTIFICIAL NEURAL NETWORK

Author(s)

SAADI HESHMATOLLAH | MIRZAYI KHALIL | Issue Writer Certificate

Keywords

E-LEARNINGQ1

ELECTRONIC MATURATIONQ1

WEKA SOFTWAREQ1

HIGHER EDUCATION IN AGRICULTUREQ1

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.

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APA: Copy

SAADI, HESHMATOLLAH, & MIRZAYI, KHALIL. (2017). E-LEARNING MATURITY OF IRANIAN AGRICULTURAL HIGHER EDUCATION BASED ON MISRA AND DHINGRA MODELS AND ITS HOOKUP USING ARTIFICIAL NEURAL NETWORK. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), 12(1 ), 1-16. SID. https://sid.ir/paper/155596/en

Vancouver: Copy

SAADI HESHMATOLLAH, MIRZAYI KHALIL. E-LEARNING MATURITY OF IRANIAN AGRICULTURAL HIGHER EDUCATION BASED ON MISRA AND DHINGRA MODELS AND ITS HOOKUP USING ARTIFICIAL NEURAL NETWORK. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION)[Internet]. 2017;12(1 ):1-16. Available from: https://sid.ir/paper/155596/en

IEEE: Copy

HESHMATOLLAH SAADI, and KHALIL MIRZAYI, “E-LEARNING MATURITY OF IRANIAN AGRICULTURAL HIGHER EDUCATION BASED ON MISRA AND DHINGRA MODELS AND ITS HOOKUP USING ARTIFICIAL NEURAL NETWORK,” JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), vol. 12, no. 1 , pp. 1–16, 2017, [Online]. Available: https://sid.ir/paper/155596/en

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