The Open UniversitySkip to content
 

Reaping the rewards of learning within agricultural knowledge systems: An account of a PhD learning system

Seale, Catherine; Lane, Andy; High, Chris; Macken-Walsh, Aine and Reynolds, Martin (2018). Reaping the rewards of learning within agricultural knowledge systems: An account of a PhD learning system. In: 13th European IFSA symposium - Farming systems: facing uncertainties and enhancing opportunities, 1-5 Jul 2018, Chania. Crete, International Farming Systems Association.

Full text available as:
[img]
Preview
PDF (Version of Record) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (472kB) | Preview
URL: http://www.ifsa2018.gr/en/proceedings/theme_1#th1-...
Google Scholar: Look up in Google Scholar

Abstract

Despite the existence and application of mandatory agri-environmental policy for many decades, significant environmental sustainability problems remain attributable to the agricultural sector. Participatory types of extension practices are believed to have a potential to enable extension organisations to enhance the supports provided to farmers to help meet the requirements and objectives of these policies. To test this proposition, the PhD researcher used a learning systems approach for exploring the interplay between farmer subjectivities, the European Union’s policy of cross compliance and the extension practices of Teagasc, the Irish Agriculture and Food Development Authority.
Three learning sub-systems were employed in the investigation. The first used the principles of Participatory Action Research for revealing stakeholders’ perceptions of Teagasc’s cross compliance extension service. This process resulted in the attainment of rich insights about extension practices, however it also revealed that a significant number of farmers were experiencing socio-cultural difficulties with the application and enforcement of cross compliance. To better understand the implications of these subjectivities, a second sub-system was created to learn about farmers’ experiences of the policy. This process surfaced diverse insights about farmers’ personal experiences of cross compliance. A final sub-system employed systems thinking and practice for appraising the utility of the learning arising from the previous sub-systems for improving interactions between farmers, extension organisations and cross compliance.
The combined findings of the thesis indicate that there is considerable potential for extension organisations to use participatory practices for developing rich understandings of farmers’ preferences for mandatory agri-environmental policy and its related extension practices. However, a limitation in realising participant preferences is that extension organisations appear to have little influence over the application and enforcement of mandatory agri-environmental policy. Overcoming this participatory barrier will require sustained collective learning targeted at understanding how stakeholders can work together to develop agri-environmental policies that are socially, financially and environmentally sustainable.
This paper explores how this ‘sustained collective learning’ may be realised taking a specific account of the learnings developed within and following the completion of the PhD Learning System. The insights elucidated will be of interest to scholars and extension practitioners involved in similar learning endeavours.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 The Authors
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetWalsh Felowship Programme
Not SetNot SetOpen University
Keywords: Knowledge Systems; PhD Learning System; Extension Services; Cross Compliance; Learning; Rewards
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Institute for Innovation Generation in the Life Sciences (Innogen)
Item ID: 55760
Depositing User: Andrew Lane
Date Deposited: 25 Jul 2018 14:11
Last Modified: 03 May 2019 23:36
URI: http://oro.open.ac.uk/id/eprint/55760
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU