A comparison of linear and systems thinking approaches for program evaluation illustrated using the Indiana Interdisciplinary GK-12.

Logic models are based on linear relationships between program resources, activities, and outcomes, and have been used widely to support both program development and evaluation. While useful in describing some programs, the linear nature of the logic model makes it difficult to capture the complex relationships within larger, multifaceted programs. Causal loop diagrams based on a systems thinking approach can better capture a multidimensional, layered program model while providing a more complete understanding of the relationship between program elements, which enables evaluators to examine influences and dependencies between and within program components. Few studies describe how to conceptualize and apply systems models for educational program evaluation. The goal of this paper is to use our NSF-funded, Interdisciplinary GK-12 project: Bringing Authentic Problem Solving in STEM to Rural Middle Schools to illustrate a systems thinking approach to model a complex educational program to aid in evaluation. GK-12 pairs eight teachers with eight STEM doctoral fellows per program year to implement curricula in middle schools. We demonstrate how systems thinking provides added value by modeling the participant groups, instruments, outcomes, and other factors in ways that enhance the interpretation of quantitative and qualitative data. Limitations of the model include added complexity. Implications include better understanding of interactions and outcomes and analyses reflecting interacting or conflicting variables.

Toward policies and decision-making for dam removal.

Dam removal has emerged as a critical issue in environmental management. Agencies responsible for dams face a drastic increase in the number of potential dam removals in the near future. Given limited resources, these agencies need to develop ways to decide which dams should be removed and in what order. The underlying science of dam removal is relatively undeveloped and most agencies faced with dam removal lack a coherent purpose for removing dams. These shortcomings can be overcome by the implementation of two policies by agencies faced with dam removal: (1) the development and adoption of a prioritization scheme for what constitutes an important dam removal, and (2) the establishment of minimum levels of analysis prior to decision-making about a dam removal. Federal and state agencies and the scientific community must encourage an initial experimental phase of dam removal during which only a few dams are removed, and these are studied intensively. This will allow for the development of the fundamental scientific understanding needed to support effective decision-making in the future and minimize the risk of disasters arising from poorly thought out dam removal decisions.