Name
Describing Agricultural Education Professors’ Perceptions of Undergraduate Student Artificial Intelligence Use
Date & Time
Wednesday, June 24, 2026, 5:00 PM - 5:15 PM
Description

Artificial intelligence (AI) could reshape how educators teach and how students learn. The integration of AI into teaching raises questions about academic integrity and core pedagogical values. However, there is a lack of research exploring how agricultural education professors view acceptable use of AI within their courses. This survey study described agricultural education professors’ perceptions and use of AI in undergraduate teaching and learning. Three objectives guided this study: 1) describe perceptions of the effectiveness of AI as a teaching and learning tool, 2) identify the types of AI technologies being used in undergraduate courses, and 3) describe perceptions of acceptable use of AI in teaching and learning. The population was undergraduate agricultural education professors in the United States (N = 139). A 47% response rate (n = 66) was achieved through a Qualtrics email distribution. After data collection, descriptive statistics were calculated for questionnaire items. On a scale of 1 = strongly disagree to 5 = strongly agree, professors agreed AI can support students in developing higher-quality assignments (M = 4.12, SD = 0.81) and improve teaching and learning (M = 4.00, SD = 0.86). The most reported AI tools being used in their courses were ChatGPT (f = 65, 98%) and Grammarly (f = 59, 89%). Professors strongly agreed it is acceptable for students to use AI to brainstorm ideas (M = 4.65, SD = 0.64) and agreed that it is acceptable for students to use AI to help revise their writing (M = 4.42, SD = 0.61). This study indicates professors are allowing AI use in their courses and that they generally believe it is helpful for students. However, what effect does this have on student learning and workforce readiness? Do all AI tools have the same effects on learning? Future research should examine these topics.

Location Name
Clark
Full Address
The Mill at Mississippi State University
600 Russell Street
Starkville, MS 39759
United States
Session Type
Oral Presentation
Presentation Topic(s)
Scholarship
Presentation Track(s)
Afternoon
Schedule Block
Block 5
Authors

Krysti Kelley, Texas Tech University Will Doss, Texas Tech University Clarissa Darby, Texas Tech University