The “E-learning methodologies” guide aims to support professionals involved in the design and development of e-learning projects and products. The guide reviews the basic concepts of e-learning with a focus on adult learning, and introduces the various activities and roles involved in an e-learning project. The guide covers methodologies and tips for creating interactive content and for facilitating online learning, as well as some of the technologies used to create and deliver e-learning.
This paper explores the application of the innovation systems framework to the design and construction of national agricultural innovation indicators. Optimally, these indicators could be used to gauge and benchmark national performance in developing more responsive, dynamic, and innovative agricultural sectors in developing countries.
The paper aims to identify barriers to the development of Learning and Innovation Networks for sustainable agriculture (LINSA). In such networks, social learning processes take place, and knowledge about sustainable agriculture is co-produced by connecting between the different frames and social worlds of the stakeholders with the help of boundary objects. Studying such processes at the interface between different knowledge spheres of research, policy and practice requires a specific methodology.
The Guidance Note on Operationalization provides a brief recap of the conceptual underpinnings and principles of the TAP Common Framework as well as a more detailed guide to operationalization of the proposed dual pathways approach. It offers also a strategy for monitoring and evaluation as well as a toolbox of select tools that may be useful at the different stages of the CD for AIS cycle.
The Conceptual Background provides an in-depth analysis of the conceptual underpinnings and principles of the TAP Common Framework. It is also available in French and Spanish.
The first phase in the development of the Common Framework on Capacity Development for Agricultural Innovation systems (CD for AIS) consisted of the review of the existing literature, building up a repository of relevant documentation on agricultural innovation in general and AIS and CD for AIS. This report summarizes this first phase. In particular, Section 1 covers this brief introduction. Sections two and three focus on the review of relevant literature, presenting the methodology used and the structure of the repository itself.
Experiential learning is prevalent in secondary and university agricultural education programs. An examination of the agricultural education literature showed many inquiries into experiential learning practice but little insight into experiential learning theory. This philosophical manuscript sought to synthesize and summarize what is known about experiential learning theory. The literature characterizes experiential learning as a process or by the context in which it occurs.
This presentation argues the need of green growth in agriculture, analyzes features of the innovation systems and ends with some policies practices. The presentation has been prepared for "Innovation and Modernising the Rural Economy", OECD’s 8th Rural Development Policy Conference, 3-5 October 2012 (Krasnoyarsk, Russian Federation).
African agriculture is currently at a crossroads, at which persistent food shortages are compounded by threats from climate change. But, as this book argues, Africa can feed itself in a generation and help contribute to global food security. To achieve this Africa has to define agriculture as a force in economic growth by: advancing scientific and technological research; investing in infrastructure; fostering higher technical training; and creating regional markets.
In this paper, presented at the 8th European IFSA Symposium ( Workshop 6: "Change in knowledge systems and extension services: Role of the new actors") in 2008, the authors discuss a conceptual framework that understands innovation processes as the outcome of collaborative networks where information is exchanged and learning processes happen. They argue that technical and economic factors used to analyse drivers and barriers alone are not sufficient to understand innovation processes.