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This paper evaluates the utility of the `learning selection' model of the early adoption process, based on a constructivist conceptual framework, to explain farmers' adoption and rejection of two soil-improving technologies – alley farming and the use of Mucuna cover crops. The analysis showed that Mucuna was more successful than alley farming because: (1) early research and extension took farmers' perceptions more into account when changing from recommending Mucuna for soil improvement to weed suppression; (2) it was then introduced into areas where there was a real need for the technology; (3) it gave short-term benefits; and (4) it was more amenable to farmer modification and adaptation. The analysis also provided support for the conclusion reached elsewhere that separate trials are needed to gather biophysical data, where researchers need to keep a high degree of control, as opposed to adoptability trials where farmers must be able to manage the technology as they wish. The paper also used the learning selection model to derive research and extension guidelines. The close match between these guidelines and the literature suggests that a constructivist perspective in general, and the learning selection model in particular, can provide a useful `road map' to plan and carry out research and extension.
Agroforestry Systems – Springer Journals
Published: Dec 1, 2002
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