Carlos Julián Ramírez Gómez, Holmes Rodriguez Espinosa, Fernando Restrepo Betancur


Background. The current challenges of agrifood chains make it necessary for them to be efficient from the point of view of production. This demands greater attention to the farmer's technological adoption process and to some aspects that may affect it. Objective. In this study a multivariate cluster analysis method was used, with the aim of identifying the influence of a farmer’s profile and their teaching–learning environment on the adoption of technology in avocado farming. Methodology. The investigation was conducted with 94 farmers in two rural municipalities, located in the same rural region. The questionnaire that was used included profile variables, learning styles, farmer learning preferences, and extension agent teaching methods. Results. Three clusters of adopters were formed and the technology adoption index was analyzed in seven categories, including 37 technologies and technological practices. The case study showed that the high adoption cluster included profiles of older farmers with experience and membership to producer organizations; this cluster was also the only group comprising a combination of farmers’ learning styles and preferences. However, the disconnection between an extension agent's teaching methods and the farmers’ learning is evident in all clusters. Implications. Our results provide important evidence regarding the importance of linking the profile, style, and learning preference in contextualized teaching methods, allowing for better development of farmers’ capacities for the adoption of technologies and practices. Conclusions. The analysis of clusters of adopters allowed farmers to be classified into high, medium and low rates of adoption of technology and technological practices. Each cluster presented certain differences in terms of learning styles and preferences, as well as a disconnection in the teaching-learning relationship.


Extension methods; farmer's learning; farmers profile; multivariate analysis; technology adoption

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