Innovation learning platforms have their roots in the agricultural innovation systems (AIS) approach. AIS emphasizes a systems view of agricultural innovations and conceptualizes an innovation system as all individuals and organizations that keep on interacting in producing and using knowledge and the institutional context of knowledge sharing and learning. Research creates knowledge and technology; but innovation process goes further to include putting that knowledge into use.

This booklet grew out of a study on what makes for responsible scaling in the context of agrifood systems, thinking along the same lines as ideas that gave rise to the concept of responsible research and innovation. In our initial exploration, we brought together a number of angles on the topic area (Wigboldus and Leeuwis, 2013; Wigboldus et al. 2016).

The capacity scoring questionnaire is an instrument that can be used when assessing the systems capacities of innovation partnerships or organizations in order to identify strengths and weaknesses and monitor change over time. It thus supports the design and implementation of successful capacity development interventions for agricultural innovation. This questionnaire has been developed in two versions (Version 1 and Version 2) and has been piloted in several countries in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS).

The capacity scoring questionnaire is an instrument that can be used when assessing the systems capacities of innovation partnerships or organizations in order to identify strengths and weaknesses and monitor change over time. It thus supports the design and implementation of successful capacity development interventions for agricultural innovation. This questionnaire has been developed in two versions (Version 1 and Version 2) and has been piloted in several countries in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS).

The Excel workbook contains some preconfigured spreadsheets that can be used for entering data collected through the capacity scoring questionnaire (Version 1 and Version 2), which has been developed in the context of the the CDAIS project, and to perform some basic analysis as well as visualize the data.

Poor farmers seldom benefit from new agricultural technologies. In response, research and extension approaches based on agricultural innovation systems are popular. Often agricultural research organisations are the network brokers, facilitating the emergence of the innovation system. Based on an analysis of the Sustainable Modernization of Traditional Agriculture (MasAgro) initiative in Mexico, this viewpoint suggests that such organisations are more often suitable network brokers when the objective is the development and scaling out of a technology by itself.

In an effort to raise incomes and increase resilience of smallholder farmers and their families in Feed the Future1 (FTF) countries, the United States Agency for International Development (USAID) funded the Developing Local Extension Capacity (DLEC) project. This project is led by Digital Green in partnership with the International Food Policy Research Institute (IFPRI), CARE International (CARE) and multiple resource partners.

This document on Good Practices in Extension Research and Evaluation is developed as a hands on reference manual to help young researchers, research students, and field extension functionaries in choosing the right research methods for conducting quality research and evaluation in extension. This manual has been compiled by the resource persons who participated in the Workshop on ‘Good

This paper describes the research path followed by a team of researchers who had investigated the nitrate problem in a case study area, and who became aware of the low impact of their data on the policy debate and on the practices that – as the research team saw it – had given rise to the problem in the first place. They embarked on a series of interactions first with participatory action researchers from the SLIM project (see Fig.