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Grazing Cattle

The Connector - Spring 2013 Issue

Systems Thinking Offers a New Approach to Agricultural Education and Research

Benjamin Turner Benjamin Turner

When Benjamin Turner was studying agribusiness as an undergraduate, he struggled with explanations and investigations of agricultural systems that assumed high levels of control. “The approach was very quantitative and reductionist,” says Turner. “The idea was that you could eliminate exogenous variables, get down to the things you can control, and then predict costs, revenue, and the value of the product in the market.”

But there aren’t many meaningful points of control in agricultural systems. “Agriculture is based on soils, plants, animals, and climate,” says Turner, “and you can’t control many variables across those elements.”

Systems Thinking adds a qualitative aspect to the linkages between plants, animals, soils, and the environment

That’s why an Introduction to Systems Thinking course delivered by Michael Goodman of Innovation Associates Organizational Learning at the King Ranch Institute for Ranch Management was so appealing to Turner. “Systems Thinking adds a qualitative aspect to the linkages between plants, animals, soils, and the environment,” says Turner. “Models help us identify the few points of control that actually do exist and have leverage through the system.”

Now a PhD candidate in Biological Science at South Dakota State University, Turner is using Systems Thinking in the classroom and for his dissertation research. “Using Systems Thinking as an educational tool to help students investigate and understand agricultural related problems, like range management and forage supply and demand, is very appealing,” says Turner. “My research builds on that interest by using Systems Thinking to develop a greater awareness of major land use changes in the northern Great Plains, particularly the loss of grassland ecosystems.”

When he was working on his Master’s Degree, Turner used STELLA®, Systems Thinking software from isee systems, to develop a model of cowherd management and replacement decisions. However, forage supply and demand, which is central to those decisions, had not been dynamically modeled. Wanting to know more, Turner was determined to learn if these dynamics could be incorporated into a simplified model.

Forage supplies have to match these demands throughout the year, but forage quantity and quality differs with the seasons, soil quality, precipitation amounts and other variables

“Cattle need to consume about 2% of their own body weight daily for bodily maintenance. Mother cows have to eat even more to support their growing calf and calves also have to consume more if they are to meet performance goals. Forage supplies have to match these demands throughout the year, but forage quantity and quality differs with the seasons, soil quality, precipitation amounts and other variables. If forage demand from animals is not met by standing forage, feed (e.g. harvested hay or purchased feed) must be provided. The model that emerged considered that whole system, but was still quite complex.”

Because it includes numerous linkages, Turner’s animal-forage balance model can take a long time to explain. He knew it would be an overwhelming focus for a guest lecture. Fortunately, he happened upon a YouTube video that demonstrated a STELLA model using Storytelling. “A lightbulb went off,” says Turner. “I thought ‘This is what I need. This is how models should be presented.”

After creating a Story for the forage model, he presented it to a professor who teaches Integrated Ranch Management at South Dakota State University to solicit feedback and ideas for model applications. “He said ‘You should teach my class!” explained Turner. “I told him that I really didn’t feel qualified but with my advisor’s encouragement I offered to guest lecture and the professor agreed.”

Storytelling allows Turner to reveal one piece of the model at a time. “It builds up to the whole system so as not to overwhelm the audience with one view of a huge model.” After attending the lecture, students completed a homework assignment in which they were given a scenario that described how a particular ranch functioned in normal conditions. Students then used the model to determine how the system will change in drought conditions.

Storytelling reveals plant functional-structural groups that influence forage growth Storytelling reveals plant functional-structural groups that influence forage growth

The students in Turner’s guest lecture were all new to Systems Thinking but it was clear that they learned a lot from the model through storytelling. “On a post-course evaluation, students wrote that Systems Thinking helped them understand ranch management in a new way,” says Turner. “One student wrote ‘It’s easier to see the circle of it all” while several others wrote that the model made the material much easier to understand.”

On a post-course evaluation, students wrote that Systems Thinking helped them understand ranch management in a new way

“Thirty-six of the 41 students thought that Systems Thinking, like the STELLA model presented, should at least complement more traditional teaching methods – like PowerPoint presentations,” says Turner. “Over 50% of the class felt that they understood the stocks and flows in the forage system. Thirty-eight of the 41 students in the class felt they understood Systems Thinking and 30 students felt they would be able to build their own simple system dynamics model.”

Turner also learned a lot from his guest lecture. In particular, he learned that one three hour session isn’t enough time to accommodate the level of information he wants to share. Next year, he’ll be teaching a special topics course over a longer period of time and take advantage of the same STELLA model and storytelling to focus on finding system linkages with the greatest leverage. And, faculty at Texas A&M University Kingsville’s King Ranch Institute of Ranch Management have been extremely positive about Turner’s animal-forage model, as they too are interested in modeling as an educational approach.

Outside of the lecture hall, Turner is developing his dissertation and investigating land use changes in the northern Great Plains. “There has been tremendous loss of grass land in this region,” explains Turner. “That’s important because grassland has great economic value to livestock production. The region’s economy also counts on tourism dollars from wildlife viewing and hunting – two activities that depend on grasslands. And open space is important to quality of life. It’s why a lot of people like living here.”

The differentiator of a systems model is not that it might exclude such informative variables, because they rightly include them. The key is that they include the link from exogenous variables to the mental models and values of managers who make decisions

While he certainly isn’t the first biologist to study land use changes in the region, Turner’s system dynamics approach is novel. “There are a lot of models that predict loss of grassland using the same reductionist approach applied to other agricultural issues,” says Turner, “which usually include things like prices and costs, subsidy levels, or land productivity indexes as predictive measures. Although important, these variable don’t make land use decisions, but they do inform management. The differentiator of a systems model is not that it might exclude such informative variables, because they rightly include them. The key is that they include the link from exogenous variables to the mental models and values of managers who make decisions. That’s what my research is including, recognizing those links to better understand the future of grasslands.”

It’s certain that Turner’s dissertation model audience will benefit from his use of storytelling but that’s not the only STELLA feature that helps him apply Systems Thinking to agricultural issues and problems. “A big part of STELLA’s benefit is user-friendliness,” says Turner. “And it allows me to create visually attractive models. It’s a lot easier to engage people in a complex system when things look good.”

Acknowledgements – A special thanks to Dr. Sandy Smart of South Dakota State for allowing me to participate with his class. Also, a special thanks to both Michael Goodman and Corey Peck for their continued support and guidance as I continue my graduate studies using Systems Thinking.

A Virtual Economics System Teaches Students about the Real Economy: Distance Learning with iThink

David Wheat David Wheat

Each semester, David Wheat teaches macroeconomics to 25 undergraduate students. They’re in Virginia. He’s in Bergen, Norway, where he's also teaching system dynamics to 50 graduate students. Distance learning technology enables him to teach in two places at the same time.

Distance learning certainly isn’t new. For years, instructors around the world have been using webinars, videos, Skype, and other technologies to connect with their students. Wheat has been at it for more than a decade, but his approach is a little different. He delivers instruction via MacroLab, a system dynamics (SD) model of the US economy that he created using iThink from isee systems. “MacroLab serves as a virtual text book,” says Wheat. “Each part of the model can be used in conjunction with chapters from a traditional textbook. I don't expect the Virginia undergraduates to become modelers. I want them to use MacroLab as a transparent simulator to see how macroeconomic principles are expressed in relationships between variables that affect one another. For most students, it's also the first time they see how the various macro textbook chapters relate to one another.”

Funding from Virginia Western Community College helped Wheat get started on MacroLab about a dozen years ago. At the time, he was a part-time instructor at the college while running his consulting business full-time. Wheat believed a simulation model of the US economy would be a good tool for the distance learning course his dean had requested. Wheat recalls discussing the idea with Barry Richmond at the 2000 SD conference in Bergen, "With characteristic enthusiasm, Barry gave me a big motivational boost." The model became MacroLab and a central feature in Wheat's PhD thesis when he moved to Norway two years later, and he's been teaching the distance learning course ever since.

when [students] can use feedback loops to explain a macroeconomic trend or interpret economic news in the media, I believe they have moved to a new level of understanding

“I had been using SD in my consulting and teaching for some time but I wanted to get to a higher level of competence,” says Wheat. “So, at the age of 54, I decided to become a student again. That summer before moving to Norway, I attended the 30th reunion of my public policy class at Harvard. My friends were more than a little surprised by my plans." After getting his PhD in system dynamics at the University of Bergen, he joined the faculty as an associate professor. But he continues using MacroLab to teach the online course to students in Virginia. In addition, he goes to Lithuania for a few weeks each spring and uses iThink to teach an SD-based course in applied microeconomics to graduate students at ISM University of Management and Economics.

In the Virginia online course, MacroLab uses iThink’s storytelling feature to enable students to engage in vicarious building of an economic model. As different sectors (e.g., government or the monetary system) are added to the model, students use the simulator to discover how changes in structure cause changes in behavior. For example, they can shock the system and cause a recession, and then compare how the model economy responds under different assumptions about economic policy.

Wheat delivers his course using Blackboard technology. Students log-in to get their assignments and then use the free isee Player to view the model and run simulations without needing their own licensed copy of iThink. Students take weekly online quizzes as they progress through the model, and Wheat asks them to explain specific behavior generated by the model. “Of course, there are different levels of sophistication in explaining the behavior of a complex system, and most of the Virginia students are taking their first course in economics. So expectations must be realistic," Wheat cautions. "But when they can use feedback loops to explain a macroeconomic trend or interpret economic news in the media, I believe they have moved to a new level of understanding. I don't tell the Virginia students they're using SD. As far as they're concerned, this is how you study macroeconomics."

Most who ask for the model aren’t researching the US economy. They use it as an example, to help them develop their own model to better understand some other economy

Even though Wheat’s online economics course never ventures into SD modeling instruction, students must learn the basic concepts of stocks, flows, and feedback. The last question on his final exam asks for a general assessment of the course, and he says students are consistently positive about taking a systems view of the US economy. "It is usually a revelation for them to see how everything fits together," says Wheat. "Some say they 'will never forget the loops' or that they see how feedback loop thinking could be useful in other courses or in their jobs. And, because the model includes a foreign sector, many express a newfound awareness of global interdependence."

Though he’s pleased that MacroLab is helping Virginia students form a deeper understanding of the US economy, Wheat is hopeful that his model can have an even broader impact on economic education. “A few years ago I made a presentation at a conference in London and a link to my work was placed on the conference website,” says Wheat. “Since then, over 100 professors, post-doc researchers, and PhD students around the world have contacted me, requesting a copy of MacroLab. I get emails out of the blue from people saying, ‘I would like to play with your model and maybe use it my course and in my research.' ” Wheat provides the teaching version of MacroLab for free. “Most who ask for the model aren’t researching the US economy,” says Wheat. “They use it as an example, to help them develop their own model to better understand some other economy.”

Storytelling is obviously a useful teaching feature but it’s also valuable for learning about one's own model

Wheat is currently using iThink to help colleagues in Ukraine build SD capacity within the economics department at the National University's Kiev-Mohyla Academy. Funded by the Norwegian Centre for International Cooperation in Education and the Norwegian Foreign Ministry, the three-year project involves student and faculty exchange for teaching and research. While studying in Bergen, PhD students from Kiev are also building MacroLab Ukraine, using Wheat's model to jumpstart their work. Gradually, they will adapt it to their own economy's unique features. This month, Wheat travels to Kiev to give guest lectures. That's after he goes to France to conduct a MacroLab workshop for a non-SD group calling itself "stock-and-flow-consistent economists." He is also developing MacroLab Lithuania, which includes demographic and social sectors in addition to the economic sector.

MacroLab is a big model that uses every feature iThink has to offer, but Wheat believes it's the combination of storytelling and simulator interface that makes the model a strong teaching and learning tool. “With my graduate students in Bergen, I emphasize communication of model insights; you have to be able to explain your work,” says Wheat. “Storytelling is obviously a useful teaching feature but it’s also valuable for learning about one's own model. If you can’t 'tell the story' of your own model, you probably don’t understand how it works.”

University of Bergen Students Win Case Competition with iThink

University of Bergen Students Win Case Competition with iThink

Each year, Education in Bergen (Norway) and Springbrettet, a career organization, invite student teams from area universities to participate in Case Competition--a contest to develop the best solution to a real problem faced by a local company. This year, teams were challenged to solve the logistical and management challenges of relocating Aibel AS, a leading energy service company with 5500 employees.

Teams are given two weeks to define problems, develop solutions, and present their ideas to the judges. This year’s Case Competition award of 20,000 Norwegian kroner (about $3,500) went to a team from the University of Bergen. SD graduate students Aklilu Tadesse and Melak Ayenew and organizational behavior students Hasan Baniamin and Mizanur Rahmand developed an iThink model that specified a problem, simulated a solution, and communicated their thinking.

“I would like to thank you and all my professors for introducing me to such an innovative tool,” Aklilu wrote to David Wheat (read A Virtual Economics System Teaches Students about the Real Economy). “This was entirely the students' initiative and beyond their course requirements," says Wheat. "I wasn’t even aware they were participating in the competition. Aklilu and Melak applied their SD skills and experience with iThink very effectively. Pål [Davidsen], Erling [Moxnes], and I are proud of their initiative and their success.” From Ethiopia, the two SD students are in the international master's degree program run by the System Dynamics Group in Bergen.

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