Neil Cliffe

Developing the capacity of farmers to understand and apply seasonal climate forecasts through collaborative learning processes

ABSTRACT Purpose: This paper documents and evaluates collaborative learning processes aimed at developing farmer’s knowledge, skills and aspirations to use seasonal climate forecasting (SCF). Methodology: Thirteen workshops conducted in 2012 engaged over 200 stakeholders across Australian sugar production regions. Workshop design promoted participant interaction, stimulated discussion, collected farmer experience of regional climate variability, improved understanding of climate drivers and increased participant skill in interpreting SCF linked to management decisions. Post-workshop surveys collected quantitative and qualitative data for statistical analysis and manual thematic coding. Findings: Over 68% of participants identified improved decision-making and risk reduction as the main benefits of using SCF products. High median self-evaluation ratings for gains in skills, knowledge and understanding of climate forecasts and perceived benefits in using climate forecasts in on-farm decision-making were found across stakeholder groups. No significant differences in self-evaluation rating gains were found between farmers, extension officers and millers, suggesting extension officers are less than optimally informed and skilled to support farmers in understanding and applying SCF. Practical Implications: Developing the capacity of extension officers to understand and interpret SCF may increase adoption of improved climate risk management in farmer networks. Theoretical implications: Collaborative learning activities in the agriculture sector, designed using experiential learning principles and evaluated using a logical framework, provide a robust model for improving the capacity of farmers to manage climate risk. Originality/Value: This paper contributes an example of evaluation of collaborative learning in facilitated agriculture climate risk workshops and discusses the value of learning through small group discussion.

The Development of Virtual World Tools to Enhance Learning and Real World Decision Making in the Australian Sugar Farming Industry

In farming, the outcome of critical decisions to enhance productivity and profitability and so ensure the viability of farming enterprises is often influenced by seasonal conditions and weather events over the growing season. This paper reports on a project that uses cutting-edge advances in digital technologies and their application in learning environments to develop and evaluate a web-based virtual ‘discussion-support’ system for improved climate risk management in Australian sugar farming systems. Customized scripted video clips (machinima) are created in the Second Life virtual world environment. The videos use contextualized settings and lifelike avatar actors to model conversations about climate risk and key farm operational decisions relevant to the real-world lives and practices of sugarcane farmers. The tools generate new cognitive schema for farmers to access and provide stimuli for discussions around how to incorporate an understanding of climate risk into operational decision-making. They also have potential to provide cost-effective agricultural extension which simulates real world face-to-face extension services but is accessible anytime anywhere.