An agricultural knowledge-sharing framework for smallholder farmers and agricultural knowledge experts
Abstract
Using Participatory Action Research (PAR) as our research methodology, we selected smallholder farming communities in the districts of Apac, Lira, Kumi and Bukedea with a major goal of developing an ICT based knowledge sharing framework between smallholder farmers and agricultural knowledge experts.
In order to better understand and sufficiently study the engagement between smallholder farmers and agricultural knowledge experts, we built a mobile tool that was used as a medium for exchange of knowledge between the farmers and the knowledge experts.
A combination of data collected from the field using questionnaires, narrative interviews and mobile tool meta data helped us design the knowledge sharing framework which was later implemented and validated for knowledge sharing.
The final framework was achieved by extending a knowledge management framework developed by Heisig (2009). Through our developed framework, we emphasize that successful knowledge sharing is achieved by critically harnessing five (5) enablers to knowledge sharing.
Chapter 1 of this thesis presents a comprehensive background on the growing information needs of smallholder farmers worldwide and in Uganda. It also presents justification for this study, the objectives and research questions that guided the researchers.
Chapter 2 provides a grounded evidence through literature review about previous scholarly works to address the growing information needs of smallholder farmers. Within this chapter, we review a number of knowledge sharing models and frameworks and compare them to one another. We identified existing gaps in the literature reviewed at the end of the chapter.
In Chapter 3, we show in detail how Participatory Action Research (PAR) was used to achieve the study objectives. We divided the study in four major stages i.e. Problem Diagnosis, Solution Design, Solution Implementation and finally Evaluation of the implemented solution.
Chapter 4 covers the data analysis process. We used questionnaires and narrative interviews to collect data from which we drew meanings and conclusions.
Lastly, Chapter 5 presents discussions, recommendations and conclusion of the study.