A Blend of Planning and Learning: Simplifying a Simulation Model of National Development

Simulation models provide decision support to long-term planning processes. The Bergen Learning Environment for National Development (BLEND) is a game based on a simplified version of Millennium Institute's Threshold 21 model (T21) that sensitizes policy makers in sub-Saharan African nations to the need for simulation-based decision support. The simplification eliminates or aggregates details about individual policy sectors and maintains cross-sector relationships. Validation indicates that the full and the simplified T21 model generate very similar behavior patterns for a wide range of policy scenarios. Pilot tests demonstrate that the simplified T21 model contributes to the learning goals of BLEND. The debriefing employs causal loop diagrams and simulation for structural explanations of the behavior observed during the game. BLEND workshops with repeated runs of the game, full debriefing sessions and different formats of instructional support will contribute further to research on dynamic decision making and learning about tasks with great complexity.

[1]  K̲h̲ālid Saʿīd.  Development planning and policy design : a system dynamics approach , 1994 .

[2]  Cliff Noble,et al.  The Relationship Between Fidelity and Learning in Aviation Training and Assessment , 2002 .

[3]  J. Michael Spector,et al.  Models and simulations for learning in complex domains: using causal loop diagrams for assessment and evaluation , 2001, Comput. Hum. Behav..

[4]  John R. Anderson.  Cognitive Psychology and Its Implications , 1980 .

[5]  B. Brehmer,et al.  Understanding and control of a simple dynamic system , 2003 .

[6]  J Swanson,et al.  Business Dynamics—Systems Thinking and Modeling for a Complex World , 2002, J. Oper. Res. Soc..

[7]  Muhammad Azeem Qureshi,et al.  Challenging trickle‐down approach , 2008 .

[8]  G. Barney.  The Global 2000 Report to the President and the Threshold 21 model: influences of Dana Meadows and system dynamics , 2002 .

[9]  Robert T. Hays,et al.  Simulation Fidelity in Training System Design: Bridging the Gap Between Reality and Training , 1988 .

[10]  Ton de Jong,et al.  Scientific Discovery Learning with Computer Simulations of Conceptual Domains , 1998 .

[11]  J. Sterman.  Business Dynamics , 2000 .

[12]  Hartmut Bossel,et al.  Modeling and simulation , 1994 .

[13]  J. Sterman.  Misperceptions of feedback in dynamic decision making , 1989 .

[14]  J. Sterman,et al.  Understanding public complacency about climate change: adults’ mental models of climate change violate conservation of matter , 2007 .

[15]  Erling Moxnes,et al.  Misperceptions of basic dynamics: the case of renewable resource management , 2004 .

[16]  John D. Sterman,et al.  Learning in and about complex systems , 1994 .

[17]  Matteo Pedercini.  Dynamic Analysis of Millennium Development Goals (MDG) Interventions: The Ghana Case Study , 2009 .

[18]  Matteo Pedercini,et al.  Modeling Resource-Based Growth for Development Policy Analysis , 2009 .

[19]  Brian Dangerfield.  System dynamics advances strategic economic transition planning in a developing nation , 2008 .

[20]  Agata Sawicka,et al.  Simulation-enhanced descriptions of dynamic problems: Initial experimental results , 2008 .

[21]  Ray J. Paul,et al.  On simulation model complexity , 2000, 2000 Winter Simulation Conference Proceedings (Cat. No.00CH37165).

[22]  J. Forrester.  Industrial Dynamics , 1997 .

[23]  Dietrich Doerner,et al.  On the Difficulties People Have in Dealing With Complexity , 1980 .

[24]  Gerald O. Barney,et al.  Dynamic analysis of interventions designed to achieve millennium development goals (MDG): The case of Ghana , 2010 .

[25]  Andreas Größler,et al.  Enhancing Learning Capabilities by Providing Transparency in Business Simulators , 2000 .

[26]  Muhammad Azeem Qureshi,et al.  Human development, public expenditure and economic growth: a system dynamics approach , 2009 .

[27]  Stephen M. Alessi,et al.  Designing Educational Support in System-Dynamics-Based Interactive Learning Environments , 2000 .

[28]  Yaman Barlas,et al.  Model simplification and validation with indirect structure validity tests , 2006 .

[29]  N. C. Boreham.  TRANSFER OF TRAINING IN THE GENERATION OF DIAGNOSTIC HYPOTHESES: THE EFFECT OF LOWERING FIDELITY OF SIMULATION , 1985 .

[30]  Wallace Feurzeig,et al.  Modeling and Simulation in Science and Mathematics Education , 1999, Modeling Dynamic Systems.

[31]  M. Limón.  On the cognitive conflict as an instructional strategy for conceptual change: a critical appraisal , 2001 .

[32]  Yaman Barlas,et al.  Formal aspects of model validity and validation in system dynamics , 1996 .

[33]  Robert T. Hays,et al.  Simulation Fidelity in Training System Design , 1989 .

[34]  Khalid Saeed,et al.  Towards Sustainable Development , 1998 .