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Determining the Attitudes of Agricultural Engineer Candidates Towards Digitalization in Agriculture with Factor Analysis: The Case of Tokat Gaziosmanpasa University
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DOI：10.18016/ksutarimdoga.vi.1740494.png)
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Abstract
En 中文
The aim of this research is to determine the attitudes of Tokat Gaziosmanpa & scedil;a University Faculty of Agriculture students towards digitalization in agriculture and to analyze the factors affecting these attitudes. The data of the study were collected from 208 third and fourth-grade students in the 2024-2025 academic year by survey. A Likert-type scale consisting of 23 items was used as a data collection tool, and exploratory factor analysis was applied to the obtained data. As a result of the analysis, the scale was divided into three main dimensions. These are: Perception of the Benefits and Education of Digital Agriculture, Economic and Environmental Benefits of Digital Agriculture and Concerns and Support Needs for Digital Agriculture. While students largely expressed positive opinions on issues such as increasing productivity, reducing costs, and contributing to environmental sustainability in digital agriculture, they also expressed their concerns about risks such as dependence on technology, high investment costs, and the decrease in agricultural employment. The KMO value was calculated as 0.950, and Cronbach's Alpha coefficient as 0.971, and these results showed that the data set was extremely suitable for factor analysis and the scale was highly reliable. The findings reveal that theoretical and applied training on digital agricultural technologies should be increased in agricultural faculties. It is also emphasized that not only technological advantages but also education, support, and adaptation dimensions should be taken into consideration in the digitalization dissemination process. In this context, it is recommended to adopt holistic approaches that include socio-cultural and educational components, not technology-based ones.
Keywords:
Digitalization in agriculture
Use of technology in agriculture
Smart agriculture
Exploratory factor analysis(EFA)
Agricultural engineer candidate
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