Agrotechnology Students’ Acceptance on Agriculture Drones Spraying as Practical Tool in Class using the Knowledge, Attitude and Practice (KAP) Model

Agriculture drones are currently becoming a major mechanization for the agricultural industry. Drones have been specifically utilized to improve agricultural activities and hence require a specific skill set to operate effectively and efficiently in the field. Therefore, the future workforce in the agriculture industry is required to learn and accept this new technology. Nonetheless, integrating drone technology into the classroom presents obstacles for students and lecturers as well. Therefore, gaining a deeper comprehension of the numerous facets of drone technology integration in higher education, especially courses related to agrotechnology programs is critical. This quantitative survey used the Knowledge, Attitude, and Practice (KAP) paradigm to investigate agrotechnology students' acceptance of agriculture drones while reducing ambiguity using statistical analysis SPSS 26.0 and employed both descriptive and inferential analysis techniques. The KAP model was employed in a recent survey to ascertain the student's perspective regarding drones within their practical class. In order to gain a deeper understanding of students' knowledge, attitudes, and risk perceptions regarding agriculture drone applications, a closed-ended structured survey was designed. The survey was disseminated to selected University Malaysia Kelantan students specifically further study in agrotechnology and intensive training on handling and practical skill-set of agriculture drone spraying was provided to them. The response from the survey obtained showed that students had a good level of knowledge about the application of agriculture drones (mean score of 4.43), attitude toward the drone application (mean score of 4.56) and practice level of the students showed a mean score of 4.57. The findings from the study revealed that the practical lesson involving agriculture drone spraying had a positive benefit on the agrotechnology student’s skills for their future career endeavor.

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Publication Details

Journal
International Journal of Advanced Research in Food Science and Agriculture Technology
Published
2025-04-05
DOI
https://doi.org/10.37934/fsat.1.1.3144a
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Agrotechnology Students’ Acceptance on Agriculture Drones Spraying as Practical Tool in Class using the Knowledge, Attitude and Practice (KAP) Model

Khairiyah Mat, Muhammad Nurfaiz Abd. Kharim, Maryana Mohamad Nor, Raimi Mohamed Redwan et al.
International Journal of Advanced Research in Food Science and Agriculture Technology
Smart Agriculture and AI
article

Agrotechnology Students’ Acceptance on Agriculture Drones Spraying as Practical Tool in Class using the Knowledge, Attitude and Practice (KAP) Model

Khairiyah Mat, Muhammad Nurfaiz Abd. Kharim, Maryana Mohamad Nor, Raimi Mohamed Redwan, Suhana Zakaria, Mohd Mahmud, Fatimah Kayat, Nor Dini Rusli, Hasnita Che Harun, Ikarastika Rahayu Abdul Wahab, Seri Intan Mokhtar, Ch’ng Huck Ywih, Syed Muhammad Al Amsyar, Tg Halimatun Saadiah Tg Abu Bakar, Norhafizah Md Zain
article en

Abstract

Agriculture drones are currently becoming a major mechanization for the agricultural industry. Drones have been specifically utilized to improve agricultural activities and hence require a specific skill set to operate effectively and efficiently in the field. Therefore, the future workforce in the agriculture industry is required to learn and accept this new technology. Nonetheless, integrating drone technology into the classroom presents obstacles for students and lecturers as well. Therefore, gaining a deeper comprehension of the numerous facets of drone technology integration in higher education, especially courses related to agrotechnology programs is critical. This quantitative survey used the Knowledge, Attitude, and Practice (KAP) paradigm to investigate agrotechnology students' acceptance of agriculture drones while reducing ambiguity using statistical analysis SPSS 26.0 and employed both descriptive and inferential analysis techniques. The KAP model was employed in a recent survey to ascertain the student's perspective regarding drones within their practical class. In order to gain a deeper understanding of students' knowledge, attitudes, and risk perceptions regarding agriculture drone applications, a closed-ended structured survey was designed. The survey was disseminated to selected University Malaysia Kelantan students specifically further study in agrotechnology and intensive training on handling and practical skill-set of agriculture drone spraying was provided to them. The response from the survey obtained showed that students had a good level of knowledge about the application of agriculture drones (mean score of 4.43), attitude toward the drone application (mean score of 4.56) and practice level of the students showed a mean score of 4.57. The findings from the study revealed that the practical lesson involving agriculture drone spraying had a positive benefit on the agrotechnology student’s skills for their future career endeavor.

International Journal of Advanced Research in Food Science and Agriculture TechnologyVol. 1(1)
Universiti Malaysia Kelantan (MY)
Universiti Malaysia Kelantan
Openalex Percentile: Top 95%
Smart Agriculture and AI
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