Trialling Second Life machinima to promote discussion and support learning in the Australian sugar industry: Stakeholder responses are encouraging…

CreateWorld 2014, Brisbane

Ms Joanne Doyle

Today’s session…

Australian climate Highest level of year-to-year rainfall variability

globally

Decision-making under uncertainty

Increasing demands on science to provide information for complex decision making to manage climate and related risk

How can science best support complex decision making?

Collaborative Research Network (USQ Project 3)

Investigating the impact of a web-based, ‘discussion-support’, agricultural-climate information system on Australian farmers’ operational decision making to enhance farm management decision-

making around climate risk to support sustainable (resilient)

agricultural systems and rural communities Collaboration: USQ ACSC & ADFI, ANU, UniSA,

CANEGROWERS, Top Dingo

Better support for on-farmdecision-making

Farming systems science

Seasonal forecast modelling

Informed decision making and improved climate risk management

Project objective

Discussion Forum

Targeted climate

information

Interactive predictive models

Virtual scenarios

OUTCOMES

IMPACTImproved climate

knowledgeImproved

decision-makingImproved

climate risk management

SocialEconomic

Environmental

Research impact is…

…the demonstrable contribution that research makes to the economy, society, culture, national security, public policy or services, health, the environment, or quality of life, beyond contributions to academia.

Source: ARC, 2012

Second Life

A virtual world User-created content and virtual marketplace Avatars can be customised and manipulated Machinima can be created

screen capture software (eg FRAPS) to create machinima

recorded soundtracks

Real World Virtual World

Machinima

Avatars

Courtesy: Neil Cliffe

Sweet success in 2013

Evaluation process

Workshop

Evaluations from 13

workshops

(207 participants)

17 semi-structured

Interviews to evaluate

prototype machinima

Deliver 6 workshops with

machinima exposure.

Pre and post workshop surveys

Workshop group output

Semi-structured interviews

2012

2014

2013

Early results

Courtesy: Mr Neil Cliffe, Australian Centre for Sustainable Catchments, University of Southern Queensland

Mean rating of value (1 = low value; 10 = high value): Farmers: 6.9 (N = 7); Extension Officers: 7.2 (N = 6); Canegrowers Org: 6.4 (N = 4)

Quotes: Farmers, Extension Officers &

Industry Organisation

Characters: very accurate; good cross

section; too clean, shiny and young Setting:

looked like a cane farm;standard shed meeting; appropriate for audience

Appeal in conveying messages: good for prompting and helping discussion; good medium to get message across; useful

for other topics; very innovative

Key messages:planning; too basic;

discussion of decisions; seasonal forecasting

and probabilities

First impressions: typical farmer conversation; realistic scenario; choppy graphics; well put

together; starts people thinking about risk; prefer real actors

Key outcomes to date

Machinima: a useful tool to support discussions around climate risk

Audio: scripts appropriately targeted to discussion topics

Visual: avatar ‘look’ was extremely important Technical challenge: seamless link between

climate forecasts and discussions

Looking ahead…Creation of further machinima:Irrigation, Fertiliser, Verandah

Acknowledgement

This project is supported through the Australian Government’s Collaborative Research Networks (CRN) program.

’Digital Futures’ is the CRN research theme for the University of Southern Queensland

Team members: PhD candidate: Neil Cliffe (ACSC, USQ)

Research Fellow: Kate Reardon-Smith (ACSC, USQ)

ACSC (USQ) researchers: Roger Stone, Shahbaz Mushtaq, Torben Marcussen, Tek Maraseni

ADFI (USQ) researchers: Helen Farley, Joanne Doyle, Neil Martin

Research collaborators:Janette Lindesay (ANU), Adam Loch (UniSA), Jeff Coutts (USQ Adjunct)

Research partners:Noel Jacobson and Amanda Hassett (Top Dingo),

Matt Kealley (CANEGROWERS)

Acknowledgement

Thank you