A presentation from the WCCA 2011 event held in Brisbane, Australia.

1. The role of systems analysis in co-learning
Walter Rossing
Wageningen Centre for Agro-ecology and Systems
Analysis (WaCASA), Wageningen University

2. Take home messages
 Systems analysis offers varied career opportunities
 Model to create diversity, not to find the answer
 Projects with impact start from vague deliverables

3. Outline of presentation
 Learning and systems research cycles
 Different types of problems and systems research
 Co-learning and boundary work
 Knowledge for different uses
 Effective co-learning strategies
 Challenges for systems science

4. Learning
 Learning is the process whereby knowledge is created
through the transformation of experience: the learning
cycle (Kolb 1984, Prentice Hall)
 Abstract versus concrete
 Active versus reflective

5. The learning cycle
Action:
Implementing a
‘bright idea’
Plan: Observation:
Which Find out
improvements? consequences
Analysis:
What are
implications?
Kolb 1984, Prentice Hall

6. The learning cycle, supported by the research cycle
Action:
Design / select: Implementing a Describe:
Which? ‘bright idea’
what?
Plan: Observation:
Which Find out
improvements? consequences
Analysis:
Explore: What are Explain:
what if? implications? why?
Models to support the reflective phases
Kolb 1984, Prentice Hall
Giller et al. 2008, Ecol. & Soc.

7. Learning to make decisions: Four types of problems..
Far from
certainty on
required Moderately
Unstructured
and structured problems
problems
available (goals)
knowledge
Moderately Structured
structured problems problems
(means)
Close to
certainty
Close to agreement on
Far from agreement
norms and values at stake
Hisschemöller & Hoppe 2001,
Policy Studies Review Annual

8. ... and the role of science
Far from
certainty on Moderately structured
Unstructured problems
required problems (goals)
and ‘Messy’ problems
Science as problem
available Science as analyst or
recognizer advocate
knowledge
Moderately structured Structured problems
problems (means)
Science as problem
Close to Science as mediator solver
certainty
Close to agreement on
Far from agreement
norms and values at stake
R. Hoppe 2007, WUR-CSIRO Workshop

9. Co-learning as a way to deal with ‘messy’ problems
 A process in which several agents simultaneously try to
adapt to each other's behaviour so as to produce
desirable global system properties
 Co-learning is stimulated by boundary work:
 Social practices to mediate between knowledge and action
 Not fixed, negotiated and re-negotiated
 Often implicit or ambiguous
 Multiple arrangements per institute and per person possible

10. Five boundary arrangements in land use modelling
3 cases 1 case
1 case
No preferred
arrangement in
4 cases the literature
Sterk et al. 2009, Land Use Pol.

11. Outline of presentation
 Learning and systems research cycles
 Different types of problems and systems research
 Co-learning and boundary work
 Knowledge for different uses
 Effective co-learning strategies
 Challenges for systems science

12. Outline of presentation
 Learning and systems research cycles
 Different types of problems and systems research
 Co-learning and boundary work
 Knowledge for different uses
 Effective co-learning strategies
 Challenges for systems science

13. Knowledge: different uses, different requirements
Technically Relevant to Fair, unbiased,
adequate in the decision respectful of all
handling of or policy? stakeholders?
evidence?
Credibility Saliency Legitimacy
Enlightenment:
no clear user
Decision support:
single user
Negotiation support:
multiple users
Adapted from Clark et al. 2011, PNAS

14. Knowledge: different uses, different requirements
Technically Relevant to Fair, unbiased,
adequate in the decision respectful of all
handling of or policy? stakeholders?
evidence?
Credibility Saliency Legitimacy
Enlightenment:
no clear user ***
Decision support:
single user *** ***
Negotiation support:
multiple users *** *** ***
Deviation from
- ++ +++
science tradition
Adapted from Clark et al. 2011, PNAS

15. Effective co-learning strategies
 Meaningful participation during agenda setting and
research
 Arrangements for accountability
 Production of boundary objects, adaptable and robust to
different viewpoints
Carberry et al. 2002
McCown 2002
Sterk et al. 2009 Land Use Pol
Clark et al. 2011 PNAS

16. Participation in agenda setting and research
Goal definition • Credible: ⋎
Formulation of a case-specific
perception of sustainability
• Salient: ?
• Legitimate: ??
Indicator set
Integrative models System definition
Evaluation of the state
Express system performance Definition of actual or
aspired: dimensions and
in terms of indicator set potential agro-ecosystems
thresholds
Sustainability
assessment
Rossing et al. 2007, AGEE

17. Arrange for accountability
E.g. EU project PURE: IPM for
pesticide reduction Innovation system
Suppliers
Retail
Extension
Process NGOs
facilitation:
keeping up
the ambition
through
Reflexive monitoring among involvement Research on both
case study leaders and production and innovation
monitors system

18. Model outputs as boundary objects
Calculated solutions Scenario studies Optimization Pareto based exploration
in white Objective 2
Objective 1
Area of possible
solutions
Groot et al. 2009, JEM

19. Model outputs as boundary objects
Pareto based exploration
Objective 2
Objective 1
Groot et al. 2010, EJA
Groot & Rossing, 2011, MEE

20. Challenges for systems science from boundary work
 Requirements on knowledge
 Credibility: science business-as-usual
 Saliency: specificity versus generality
 Legitimacy: research versus social embedding
 Requirements on organization of research (projects!)
 Accommodating multiple disciplines, stakeholders, levels of
analysis
 Providing governance to balance the above
 Focus on research products that stimulate co-learning

21. Take home messages
From hermitic
A focus on boundary scientist to
objects stimulates political activist
co-learning
 Systems analysis offers varied career opportunities
 Model to create diversity, not to find the answer
 Projects with impact start from vague deliverables
Adaptive (self-reflexive)
project management is
indispensable (and a
research topic in itself!)

22. Thank you for your attention!
© Wageningen UR