Purpose: To develop a transformative learning process around the potential for innovation of technologies such as Conservation Agriculture.
Design/methodology/approach: We applied principles of Transformative Learning and Communicative Action theories to design a learning process structured by the Qualitative Expert Assessment Tool for Conservation Agriculture Adoption in Africa (QAToCA). Elements of the process include: agroecosystem health exploration, stakeholder mapping, innovation timeline, participatory video, the QAToCA exercise, and specifying change promotion. We tested this approach with a group of farmers and experts in Koumbia, Burkina Faso.
Findings: The agroecosystem in Koumbia is under demographic, economic, and climatic pressure. Conservation Agriculture has not been successfully integrated into socio-economic realities or implemented beyond a trial scale. The stakeholder mapping showed that dominant economic players and traditional means of communicating are essential to achieve innovation. Past interventions were not coordinated and focused on technical challenges. The participatory videos were rich in contextual information and created process ownership for research participants. The QAToCA provided a structure for lessons learned and suggestions for change.
Practical implications: The learning process may be applied to initiate innovation initiatives in an efficient manner.
Theoretical implications: The study shows how Transformative Learning and Communicative Action theories can be used for agricultural innovation. It also underlines the need for further work on how to address the implicit superiority of the process initiator and the integration of learning in institutional practice.
Originality: Few studies have attempted to design and test learning processes on agricultural innovation based on theories of learning and Communicative Action. 相似文献
AbstractPurpose: In this article we illustrate the importance of understanding the risk profiles of new technologies, in addition to the changes in productivity, to be able to determine strategies for agricultural development.Design/methodology/approach: The analysis is based on data obtained from a 2002 survey of subsistence farmers in the Kilimanjaro region of Tanzania, and a Just and Pope (1978) framework is used for modeling risk.Findings: We find that even if extension services do not increase the mean production, it may reduce production risk.Practical implication and originality/value: During the past decades, agricultural extension and subsidized conventional inputs such as high-yielding seed varieties, fertilizer and pesticides, have become important components of agricultural aid programs in developing countries. However, outcomes of this type of aid are somewhat ambiguous, and many donor countries have reduced their support in response. For the most part, evaluation of these programs employs total factor productivity analysis to estimate the changes in productivity resulting from investment in aid programs. However, risk-averse, small-scale farmers will consider both the variance in output and the expected mean. They may therefore choose input levels that differ from the optimal input levels of risk-neutral producers, who consider only the expected mean. Programs can therefore have a positive effect because they reduce risk, even if the direct impact on production is limited. 相似文献