Research Paper
Agricultural education
zolfaqar ahmadi; Mosa Azami; atefeh malekian
Abstract
Drone technology as one of the novel tools for precision and smart agriculture, has attracted researchers’ attention in recent years. This study investigated the growth trend and scientific orientations of research related to drone adoption in agriculture, identifying scientific collaboration patterns ...
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Drone technology as one of the novel tools for precision and smart agriculture, has attracted researchers’ attention in recent years. This study investigated the growth trend and scientific orientations of research related to drone adoption in agriculture, identifying scientific collaboration patterns and dominant research themes. This study was conducted using a descriptive-analytical scientometric/bibliometric approach with network analysis (scientific collaboration and keyword co-occurrence). Data were extracted from the Scopus database, and relevant articles published between 2005 and 2025 were collected based on their titles, abstracts, and keywords. After refinement, 712 articles were selected as the final dataset. Analyses were performed using scientometric indicators and VOSviewer software, including an examination of publication trends, geographical distribution, active journals, the network of country collaborations, and the keyword co-occurrence network. The results indicated an increase in scientific output in this field over the last two decades, with a more rapid growth observed after 2016. Geographically, China and the United States held the largest share of scientific production and played central roles in the collaboration network. Keyword analysis also revealed four dominant themes: drone applications in agriculture, remote sensing and data analysis, human/behavioral factors influencing adoption, and economic and regulatory challenges. Overall, the findings suggest that drone adoption in agriculture is a result of the interaction between technological advancements, data infrastructures, policy frameworks, and human factors. These results can be utilized to guide future research and improve decision-making in the development of novel agricultural technologies.
Research Paper
Agricultural education
Fariborz karamifar; Shahpar Geravandi; Yosef Mohamadifar; Samaneh Sanjabi
Abstract
this study adopts an innovative mixed-methods approach to assess the educational needs of agricultural digital marketing professionals by integrating bibliometric analysis and network analysis. In the first stage, a bibliometric analysis was conducted based on Scopus-indexed documents published between ...
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this study adopts an innovative mixed-methods approach to assess the educational needs of agricultural digital marketing professionals by integrating bibliometric analysis and network analysis. In the first stage, a bibliometric analysis was conducted based on Scopus-indexed documents published between 2019 and 2025. The examination of approximately 90 scientific documents and co-occurrence analysis of keywords using VOSviewer revealed the main conceptual clusters and research trends related to the application of artificial intelligence in agricultural digital marketing. This conceptual map provided the basis for the second stage, in which a systemic analysis of skills was carried out. In the next stage, MACTOR analysis was employed to identify relationships of influence, dependency, and strategic importance among the skills. Data for this phase were collected from 48 selected experts using criterion-based sampling. The findings indicated four main dimensions of educational needs: (1) AI literacy and conceptual understanding, (2) interactive and practical chatbot skills, (3) AI-based marketing competencies, and (4) commercialization and value creation. Influence–dependence analysis further showed that “market demand analysis and forecasting” and “consumer behavior analysis” are key driving factors, while skills such as “digital campaign management” serve as intermediary variables linking these drivers to final outcomes such as “customer engagement.” In addition, convergence analysis revealed that “customer data analysis” and “personalized recommendations” exhibit the strongest alignment, highlighting the need for integrated and hybrid training packages.
Research Paper
Agricultural education
SHAHRAM MOGHADDAS FARIMANI
Abstract
The purpose of this study was to investigate the factors affecting the motivation to continue education among male and female students in the secondary agricultural high schools depended to the Ministry of Jihad-e Agriculture. This research was conducted as a quantitative, applied study with a causal-comparative ...
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The purpose of this study was to investigate the factors affecting the motivation to continue education among male and female students in the secondary agricultural high schools depended to the Ministry of Jihad-e Agriculture. This research was conducted as a quantitative, applied study with a causal-comparative approach. The statistical population comprised all tenth-grade students enrolled in the male and female agricultural high schools of the Ministry of Jihad-e Agriculture in the 2024–2025 academic year, totaling 214 students. Using the Cochran formula, a sample of 170 students from high schools in the provinces of Fars, Mazandaran, and Golestan was selected through proportional stratified random sampling. The data collection instrument was a researcher-developed questionnaire containing items designed in accordance with the study objectives and variables, using a five-point Likert scale, and data were collected through face-to-face interviews. The reliability of the instrument was determined by calculating the composite reliability coefficient of 0.87 and Cronbach’s alpha of 0.92 for measuring the factors affecting students’ motivation to continue education. For validity, face validity was established through consultation with experts and faculty members of the Agricultural Education and Extension Institute. The results of the exploratory factor analysis showed that the factors influencing students’ motivation to continue their education in agricultural high schools could be classified into seven factors: interest in agriculture and career advancement, rural background and agricultural family history, compulsion and necessity, welfare facilities and free tuition, ease of access to the high school, influence of others, and recommendations from friends and acquaintances.
Research Paper
Agricultural education
hoda behboudi; seyed mahmood hoseini; seyed jamal Faraj Elah Hosseini
Abstract
Successful knowledge management implementation depends on identifying the key factors that facilitate its adoption and improve organizational effectiveness.However,comprehensive evidence regarding these factors in agricultural service organizations remains limited.Therefore, this study aimed to identify,validateand ...
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Successful knowledge management implementation depends on identifying the key factors that facilitate its adoption and improve organizational effectiveness.However,comprehensive evidence regarding these factors in agricultural service organizations remains limited.Therefore, this study aimed to identify,validateand explain the factors influencing KM implementation in Agricultural Service Centers of Razavi Khorasan ProvinceIran.Thestudy was applied in purpose and employed an exploratory mixed-methods design,integrating qualitative and quantitative approaches.The qualitative phase involved 27purposively selected knowledge management experts from organizations affiliated with the agricultural sector,while the quantitative phase included a census of 147specialists working in Agricultural Service Centers.Data were collected through semi-structured interviews and a researcher-developed questionnaire comprising 96 items measured on a five-point Likert scale.Face validity was confirmed by 16university faculty members,and construct validity(AVE = 0.70)Cronbach's alpha(α = 0.89),and Composite Reliability(CR = 0.80)demonstrated satisfactory validity and reliability.Data were analyzed using Confirmatory Factor Analysis,Partial Least Squares Structural Equation Modelingand the Friedman test.The results indicated that knowledge culture and intellectual capital (β = 0.724),organizational structure and management system(β = 0.751),information technology infrastructure andinformation management(β = 0.731),economic characteristics(β = 0.872),demographic characteristics(β = 0.853),informational and educational characteristics(β = 0.527), competency(β = 0.816),and motivation(β = 0.498)significantly influenced KM implementation.Friedman test results further showed that organizational factors(MR = 2.75),knowledge culture and intellectual capital(MR = 2.09),farmers' informational and educational characteristics(MR = 4.35),and experts' motivation(MR = 3.27)received the highest priorities.These findings highlight the critical role of organizational,environmental,and individual factors in successful KM implementation within Agricultural Service Centers.
Research Paper
Agricultural education
Hamed Izadi; Bahman Khosravipour; Moslem Savari
Abstract
One of the most important factors affecting students' research is their beliefs about their abilities in this field. Research self-efficacy is a significant predictor of research productivity among students and it is confirmed as an important predictor for the stability and academic progress of students. ...
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One of the most important factors affecting students' research is their beliefs about their abilities in this field. Research self-efficacy is a significant predictor of research productivity among students and it is confirmed as an important predictor for the stability and academic progress of students. The present study aimed to investigate the factors affecting research self-efficacy among graduate students of agricultural sciences and natural resources universities of Iran. The statistical population included all postgraduate students of Iranian universities of agricultural sciences and natural resources. The inverse square root method was used to determine the number of statistical samples, and finally 384 students were selected through random sampling.The research instrument was a questionnaire with a five-point Likert-scale questionnaire. Its content validity was confirmed through expert consultation in agricultural extension and education, while its reliability was established via ordinal theta coefficient (θ=0.71-0.80). convergent validity was assessed through factor loadings and the Average Variance Extracted (AVE=0.51-0.68). Collected data were analyzed using descriptive and inferential statistics, including correlation and structural equation modeling with a confirmatory factor analysis approach to extract the measurement model, in SPSS and Amos software. the results obtained from the path analysis structural equation model showed that the variables of research experience, professor-student relationship, motivation for progress, interest, and verbal encouragement have a positive, direct, and significant effect on the research self-efficacy of graduate students, and these five variables in total are able to predict 61 percent of the changes in research self-efficacy.
Research Paper
Agricultural education
Orkideh Heidarnejad; Seyyed Soheil Ghaemmagami
Abstract
The complexities of animal health and food security necessitate a fundamental restructuring of veterinary technician education. This applied qualitative study (2023) developed a competency-based model for professional development, utilizing the Developing a Curriculum (DACUM) approach and the systematic ...
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The complexities of animal health and food security necessitate a fundamental restructuring of veterinary technician education. This applied qualitative study (2023) developed a competency-based model for professional development, utilizing the Developing a Curriculum (DACUM) approach and the systematic Norton model.Research data were collected through triangulation, including document analysis, semi-structured interviews with experts, clinical observation, and rigorous job task analysis. Competency coding was aligned with the International Standard Classification of Occupations (ISCO-08) to enhance global validity and career mobility. Following the five key stages of the Norton model—needs analysis, objective setting, experience design, performance standards, and evaluation—the study categorized the veterinary technician’s role into three primary domains, identifying 24 key tasks and 196 work steps essential for professional competence.Analysis indicates that the absence of standardized criteria significantly increases clinical and sanitary management errors, causes resource wastage, and reduces workforce efficiency. By establishing a framework of essential competencies, this research provides a robust template for curriculum redesign, national skill standardization, and improved credentialing. Implementing this model serves to enhance the quality of veterinary services and offers a scalable framework for professional development in veterinary-related fields.
Research Paper
Agricultural education
SEDIGHEH GHASEMI; Frazad Farbood; Arman bakhshijahromi; Laila sajadifar
Abstract
The Agricultural Virtual Education Network (SHAK), as the official virtual education platform of Iran’s Ministry of Agricultural Jihad, plays a significant role in transferring agricultural knowledge, technologies, and modern skills to farmers and agricultural practitioners. Therefore, evaluating ...
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The Agricultural Virtual Education Network (SHAK), as the official virtual education platform of Iran’s Ministry of Agricultural Jihad, plays a significant role in transferring agricultural knowledge, technologies, and modern skills to farmers and agricultural practitioners. Therefore, evaluating the quality of its educational programs is essential for enhancing their effectiveness. This applied study was conducted using a quantitative survey approach to evaluate the quality of SHAK educational programs in Fars Province and identify the factors influencing their quality. The statistical population consisted of all learners who had successfully completed SHAK training courses in Fars Province during a three-month period (October to December 2025). After removing duplicate records, 300 eligible and unique learners were identified. Given the limited size of the population, a census approach was employed, and the electronic questionnaire was distributed to all 300 learners. Finally, 193 learners voluntarily completed the questionnaire, and their responses were included in the statistical analyses. Data were collected using a researcher-developed questionnaire consisting of eight constructs and 54 items. The items were measured using a five-point Likert scale ranging from 1 (very poor) to 5 (very good). The face validity of the questionnaire was confirmed through expert review, and its reliability was assessed using ordinal alpha and composite reliability coefficients in R software. Data were analyzed using descriptive and inferential statistics, including Pearson’s correlation coefficient and multiple linear regression analysis using the Enter method in SPSS 20.The findings revealed that seven factors, including information resources, learners’ expectations and objectives,
Editor-in-Chief Lecture
Agricultural education
