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Shrimp Commodity Systems Learning Lab: Guidance Notes
Landel, Robert D.; Soderquist, Chris Technical Note OM-1428 / Published December 6, 2010 / 24 pages.
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Product Overview

This technical note supports the "Shrimp Commodity Systems Learning Lab" (SCSLL) simulation (UVA-OM-1537) used in environmental sustainability or systems thinking courses. It offers detailed guidance for the progression of interactive learning experiences in the SCSLL. Through the simulation, users develop an understanding of the issues facing the shrimp industry system and how policy alternatives could improve the industry's typical boom-and-bust patterns. A teaching note (OM-1428TN) is available.


Learning Objectives

1. Experience the supply, demand and ecological systems issues facing the global shrimp industry, including both wild catch and aquaculture. 2. Provide the application of systems thinking and stock-flow mapping as a means of hypothesizing and expressing underlying system feedback structures. 3. Analyze policy and scenario alternatives that influence system performance including harvest technologies, demand growth, aquaculture effluents, aquaculture and fishery subsidies, good-practice incentives, and various regulations.

  • Videos List

  • Overview

    This technical note supports the "Shrimp Commodity Systems Learning Lab" (SCSLL) simulation (UVA-OM-1537) used in environmental sustainability or systems thinking courses. It offers detailed guidance for the progression of interactive learning experiences in the SCSLL. Through the simulation, users develop an understanding of the issues facing the shrimp industry system and how policy alternatives could improve the industry's typical boom-and-bust patterns. A teaching note (OM-1428TN) is available.

  • Learning Objectives

    Learning Objectives

    1. Experience the supply, demand and ecological systems issues facing the global shrimp industry, including both wild catch and aquaculture. 2. Provide the application of systems thinking and stock-flow mapping as a means of hypothesizing and expressing underlying system feedback structures. 3. Analyze policy and scenario alternatives that influence system performance including harvest technologies, demand growth, aquaculture effluents, aquaculture and fishery subsidies, good-practice incentives, and various regulations.