When my colleagues explained to me what this blog was for, I was really pleased to hear that it would be a forum where a modeling novice could gain some orientation and learn shortcuts that weren’t available, or at least not easy to find, when I was just learning. Modeling, at least the computational side of it, is still in many ways a rarefied specialization in the social sciences, and reliable guideposts are few.
The concept of modeling itself is vast and vague. For some, images of flow-charts and mental maps come to mind. For others, it could mean miniature trains or linear regressions. There are many different ideas about what models are or what they are used for. It doesn’t help that there are two very different career paths that are both called “modeling” (from what I can tell, the crossover rate has been pretty limited).
When someone new begins to dig into the pursuit of modeling, they’re likely to come up against that stumbling block to end all stumbling blocks: MATHEMATICS. Differential equations. Graph theory. Markov chains. Point processes. And coupled to this is an array of seemingly unrelated computer programming languages and development environments with documentation that is not always easy to navigate. If you don’t come from a mathematics or computer science background, it can be difficult to know where to begin. But more importantly, it may not be clear what modeling is actually for or why anyone would ever want to do it.
Enter the Coursera course “Model Thinking”, taught by Michigan’s Scott E. Page. In the first lectures, the reasons why anyone would want to learn about models are laid out in plain English. From the course website:
1. To be an intelligent citizen of the world
2. To be a clearer thinker
3. To understand and use data
4. To better decide, strategize, and design
Page tells us that, in the era of Big Data, the ability to identify key components and apply knowledge are crucial. Data by itself, no matter what quantity, is useless without the ability to harness its informational potential through identifying patterns and understanding processes. Models, it is argued, are just the kinds of tools we need to use data wisely.
It should be stated up front that this is not a course designed to teach you to how to program. There are lots of different courses, tutorials, and other materials on programming which are available, and this site is doing its part to help provide some direction. Instead, Page offers valuable tools for thinking about complex problems using the power of models.
In some ways, it’s like a best-of album: all your favorites are there. Segregation. The Prisoner’s Dilemma. Forest Fires. The Game of Life. These models are used to demonstrate principal concepts in modeling and complex systems, such as aggregation, tipping points, bounded rationality, and path dependence. Real-world case studies are used to show how models like these can illuminate core dynamics in what are otherwise very complex and intractable systems, such as banking networks, electoral politics, or counterterrorism.
The course doesn’t deal outside of mathematics entirely, but introduces the necessary concepts in a fairly straightforward and basic way. The online format suits this well: if you’re not familiar with a concept, you can simply pause the video and Google it.
If you’ve taken a few MOOCs, you know that production counts for a lot, but sometimes it can be distracting. A voice-over with someone’s lecture slides is bound to put you to sleep; too many animations or an overdone background or wardrobe can draw your attention from the lesson. Most of these videos begin with Page in front of a blank background, waist up and gesturing, with key words being displayed at the bottom of the screen. This usually transitions into a demonstration with simple but effective graphics and live-drawn overlays for emphasis (see here). This approach seems to balance the issue of too little/too much production. The weekly quizzes are thoughtful but not overwhelming. I found them particularly good for someone new to MOOCs. In addition, if you’re watching the videos on the Coursera site, many of the lectures will stop part way through and ask a multiple-choice question to make sure you’re paying attention. This does a reasonably good job of reinforcing the lesson.
For someone who does modeling on a regular basis, the course is great for clarifying and compartmentalizing different ideas which you may already be using but don’t know much about their background or how to interface them other other concepts. For someone who is new, it has the potential to shed light on some of the reasons models are used and give some direction in terms of how to use models in your life.
The next session begins on February 3rd and runs for 10 weeks, with a recommended workload of 4 to 8 hours per week. The signup page at Coursera can be found here.
Image “5th Floor Lecture Hall.jpg” courtesy of Xbxg32000 @ Wikimedia Commons