Evaluating the Efficacy of Extension-Based Artificial Insemination Trainings on Knowledge Gain, Satisfaction Level, and Behavioral Intent

Abstract In cattle, artificial insemination (AI) is an effective technique to improve productivity and reproductive efficiency in cattle herds. However, only 11.6 % of the beef females are bred by artificial insemination in the United States. Thus, our goal was to train producers, extension agents, and students on AI techniques and breeding management. The outcomes of a 2-day AI training program (16 hours) on perceived knowledge gain, workshop satisfaction level, and intent to adopt the practices were measured among 82 participants (43 producers, 33 students, and 6 extension agents) using a Likert scale pre- and post-training evaluation. Participants belonged to 18 North Carolina counties and 5 universities. The topics covered are bovine reproductive anatomy and physiology, AI techniques, semen handling, estrous detection, and estrous synchronization protocols. The workshop was composed of lectures and hands-on training. The GLIMMIX procedure of SAS was used to analyze the fixed effects of topic, time (pre- and post-training), and their interaction, and the random effect of participant. Overall, improvements varied across topics within participants (P = 0.0002, topic × time), with the greatest improvement in the hands-on AI technique (Odds ratio: 186, P 0.0001), followed by handling AI equipment and semen (OR: 122, P 0.0001). The lowest improvement was regarding cattle anatomy and physiology (OR: 31, P 0.0001), where participants with no previous biological background still found the amount of information and the nomenclature a little daunting. The participants’ confidence and knowledge about the heat detection principles and applications were significantly enhanced (OR: 41.54, P 0.0001), which shows a critical prerequisite for improving the reproductive management by early estrus detection and timed AI of the animals. An absolute gain was seen in participants’ understanding about the estrus synchronization protocols (OR: 55.12, P 0.0001), which highlights a crucial step in implementing synchronization protocols and timed AI. Overall, there was a high satisfaction rate among participants, where 96.3% being very satisfied with the training quality of the workshop. Among participants, 61% were planning to develop a reproductive management program at their operation, and 23.2% already had an established breeding management program. In addition, 52% were planning to incorporate estrous synchronization and artificial insemination, and 20% were already utilizing the practice. Altogether, these results indicate that AI training effectively increased the participants' knowledge and willingness to implement assisted reproductive technologies in beef and dairy operations, ultimately encouraging the adoption of practices that improve reproductive efficiency, genetic selection, and profitability. These outcomes highlight the significance of extension-based training in bridging the gap between research and field implementation to improve reproductive efficiency and productivity in cattle herds.