The study aimed to identify the level of importance of electronic communication among agricultural extension workers in using artificial intelligence (AI) programs and applications in the field of smart agriculture. It also aimed to identify the most frequently used electronic communication means by extension workers in employing AI programs and applications and rank them according to their relative importance; measure the contribution of electronic communication to improving extension workers' efficiency in using AI programs and applications in smart agriculture; identify individual differences in the importance of electronic communication and the use of AI applications according to selected independent variables, namely gender, educational qualification, years of service, training courses, level of Internet use, and willingness to use social networking sites concerning smart-agriculture technologies; and identify the obstacles facing extension workers in using AI applications in smart agriculture. To obtain the study data, a questionnaire consisting of five parts was used. The first part concerned the respondents' personal and occupational information. The second part included a scale measuring the importance of electronic communication among extension workers in using AI programs and applications in smart agriculture. The third part measured the electronic communication means most frequently used by extension workers in employing AI programs and applications. The fourth part measured the contribution of electronic communication to improving extension workers' efficiency in using AI programs and applications in smart agriculture. The fifth part contained 15 items measuring the major obstacles facing extension workers in using AI applications in smart agriculture. After establishing the face validity of the questionnaire, reliability was assessed using Cronbach's alpha, which reached 0.95. The study population consisted of extension workers in the Nineveh Directorate of Agriculture and its 32 agricultural divisions, totaling 256 extension workers. A simple random sample of 128 extension workers, representing approximately 50% of the population, was selected. The data were coded, tabulated, and analyzed using SPSS. The results showed that the level of importance of electronic communication among extension workers in using AI programs and applications in smart agriculture was moderate and tended toward high, with a percentage of 48%. The item "Using electronic platforms belonging to agricultural institutions to obtain information related to AI programs and applications" ranked first, with a mean of 4.34. The contribution of electronic communication to improving extension workers' efficiency in using AI programs and applications in smart agriculture was high, with a percentage of 46%. No significant differences were found in the importance of electronic communication according to gender or training courses, whereas significant differences were reported according to educational qualification, years of occupational service, level of Internet use, and willingness to use social networking sites concerning smart-agriculture technologies. The item "Poor compatibility of some AI applications with the nature and needs of agricultural extension work in Nineveh Governorate" was identified as the most important obstacle. The major recommendation was for the Ministry of Agriculture to establish or develop official agricultural electronic platforms affiliated with agricultural and extension institutions and containing updated information on AI applications and their use in different agricultural fields. The main proposed future study was to investigate the obstacles to using AI applications in agricultural extension work in Nineveh Governorate from the perspective of extension workers.
No takes yet. Share an insight, caveat, or question.
Luma Monther Adress (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: