Adjusting extension models to the way farmers learn

Extension services play a key role in helping developing countries modernize their agriculture and grow. Yet, these services have almost universally performed below expectation. The hypothesis proposed here is that extension systems could perform better if they delivered services structured on the way farmers learn. To inform this hypothesis, we review critically existing extension systems, extract from learning models and empirical studies of adoption regularities about how farmers learn, and propose a set of reforms to existing extension services that match learning channels. Major reforms to extension would select contact farmers as entry points for diffusion according to the specific constraint to be addressed, organize head-to-head trials in farmers’ fields under the jurisdiction of farmers themselves, use private agents in value chains as sources of information, and inform social networks about the existence of innovations using mass media to induce a demand-driven search for information from contact farmers.