The UNDP Capacity Assessment Methodology User‘s Guide gives UNDP and other development practitioners a detailed step-by-step guide to conducting a capacity assessment using the UNDP Capacity Assessment Methodology, which consists of the UNDP Capacity Assessment Framework, a three-step process and supporting tools. 

This set of guidance notes is designed to support practitioners and evaluators in conducting retrospective evaluations of a capacity development intervention or portfolio to assess and document results. Users will enhance their understanding of the capacity development process, of what works and what does not work in promoting change and to inform future programs. The standard M&E approach for assessing capacity development results has not been sufficient.

Innovation systems can be defined in a variety of ways: they can be national, regional, sectoral, or technological. They all involve the creation, diffusion, and use of knowledge. Systems consist of components, relationships among these, and their characteristics or attributes. The focus of this paper is on the analytical and methodological issues arising from various system concepts. There are three issues that stand out as problematic. First, what is the appropriate level of analysis for the purpose at hand?

This synthesis report presents the outputs of the workshop organised by CTA at its headquarters in Wageningen, The Netherlands, 15-17 July 2008.  The outputs are presented in two main parts, each corresponding to one of the workshop objectives, and ends with a section on the way forward as suggested by the workshop participants. It also includes a first attempt to come to a consolidated generic framework on AIS performance indicators, based on the outputs of the different working groups.

This review of literature on evaluation methods focuses specifically on approaches and methodologies in evaluation which are relevant for evaluating initiatives in extension or rural advisory services. The context and scope of the review are discussed, followed by sections addressing the purposes, users and uses of evaluation, evaluation standards and criteria, approaches, rigour and attribution.

This report reviews the evidence of impact of capacity strengthening on agricultural research for development (AR4D) in developing countries. The study was commissioned by DFID as part of the documentation process of the project Strengthening Capacity for Agricultural Research for Development in Africa (SCARDA). 

This paper argues that impact assessment research has not made more of a difference because the measurement of the economic impact has poor diagnostic power. In particular it fails to provide research managers with critical institutional lessons concerning ways of improving research and innovation as a process. Paper's contention is that the linear input-output assumptions of economic assessment need to be complemented by an analytical framework that recognizes systems of reflexive, learning interactions and their location in, and relationship with, their institutional context.

This learning module on Applying innovation system concept in agricultural research for development has been prepared to serve as a tool in achieving the objective of strengthening the capacity of project staff and other researchers and actors who are believed to have a key role to play in ushering in market-led agricultural transformation. This includes national, regional, international and private sector agricultural researchers, university lecturers, and others engaged in biophysical as well as social science research.

Many capacity development (CD) programs and processes aim at long‐term sustainable change, which depends on seeing many smaller changes in at times almost invisible fields (rules, incentives, behaviours, power, coordination etc.). Yet, most evaluation processes of CD tend to focus on short‐term outputs focused on clearly visible changes.

Innovation platforms are equitable, dynamic spaces designed to bring heterogeneous actors together to exchange knowledge and take action to solve a common problem. Although innovation platforms are being set up to attain collectively defined development objectives, there are limited methods and tools available using quantitative data to evaluate whether they are effective.