Examining AI Perceptions and Utilization among Agricultural Educators in Utah
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| Title: | Examining AI Perceptions and Utilization among Agricultural Educators in Utah |
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| Language: | English |
| Authors: | Sidney Pehrson (ORCID |
| Source: | Journal of Agricultural Education. 2025 66(3). |
| Availability: | American Association for Agricultural Education. P.O. Box 7607, Department of Agricultural and Extension Education, Raleigh, NC 27695. Web site: https://jae-online.org/index.php/jae/index |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Artificial Intelligence, Teacher Attitudes, Technology Uses in Education, Agricultural Education, Agriculture Teachers, Barriers, Intention, Faculty Development, Teacher Characteristics |
| Geographic Terms: | Utah |
| DOI: | 10.5032/jae.v66i3.2910 |
| ISSN: | 1042-0541 2162-5212 |
| Abstract: | Artificial Intelligence (AI) has garnered attention as an innovative technology, revolutionizing various components of society, including education. The new technology can potentially improve efficiency and reduce burdens placed on teachers, but AI in educational settings may also have negative consequences. This quantitative survey research study aimed to identify how school based agricultural education (SBAE) teachers are currently using AI and what they already know about it, what beliefs and attitudes they have towards it, and what professional development needs exist. This research was guided by the Technology Acceptance Model (TAM) framework. The population for this study was all SBAE teachers in Utah during the 2023-2024 school year. A total of 70 SBAE teachers participated in the study. Findings suggest that SBAE teachers have mixed feelings about AI. Although some already integrate the technology into their teaching practices, others may have specific barriers keeping them from adopting it. Currently, teachers using AI in the classroom primarily leverage it to save time on administrative tasks and content development. It is worth noting that most of the concerns and specific professional development needs of SBAE teachers relate to students' use of AI and the use of AI around students. It is recommended that state staff provide training related to AI for in-service teachers and that university teacher education programs add curriculum or training related to AI for pre-service teachers. It is also recommended that more research related to AI in agricultural education be conducted. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1480203 |
| Database: | ERIC |
| Abstract: | Artificial Intelligence (AI) has garnered attention as an innovative technology, revolutionizing various components of society, including education. The new technology can potentially improve efficiency and reduce burdens placed on teachers, but AI in educational settings may also have negative consequences. This quantitative survey research study aimed to identify how school based agricultural education (SBAE) teachers are currently using AI and what they already know about it, what beliefs and attitudes they have towards it, and what professional development needs exist. This research was guided by the Technology Acceptance Model (TAM) framework. The population for this study was all SBAE teachers in Utah during the 2023-2024 school year. A total of 70 SBAE teachers participated in the study. Findings suggest that SBAE teachers have mixed feelings about AI. Although some already integrate the technology into their teaching practices, others may have specific barriers keeping them from adopting it. Currently, teachers using AI in the classroom primarily leverage it to save time on administrative tasks and content development. It is worth noting that most of the concerns and specific professional development needs of SBAE teachers relate to students' use of AI and the use of AI around students. It is recommended that state staff provide training related to AI for in-service teachers and that university teacher education programs add curriculum or training related to AI for pre-service teachers. It is also recommended that more research related to AI in agricultural education be conducted. |
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| ISSN: | 1042-0541 2162-5212 |
| DOI: | 10.5032/jae.v66i3.2910 |
