John Sweller Interview 3: What’s the difference between the goal-free effect and minimally guided instruction?

This is part of a series of blogs detailing a discussion that I had with John Sweller in mid 2017. See all parts of this series on this page

OL: What are some of the fundamental differences between goal-free activities and minimally guided instruction?

JS: One of the reasons we switched from goal-free problems to worked examples is that goal-free problems work really well, but in a very limited number of areas. They don’t work well in all areas. The areas they work well in are areas where if you tell people: ‘Calculate the values of as many variables as you can’, there are only a very limited number, maybe 3, 4, 5 variables, that you can calculate. In other words, if you really know what you’re doing you can calculate everything very very quickly. The other areas, like in some areas of mathematics but also areas in other disciplines, if you tell people: ‘Do as much as you can’, they’ll be going from now to infinity! There are literally an infinite number of things you can do. So you just cannot do that. An example I use is to ask people to consider something like simple algebra. Give someone an algebra equation and say ‘manipulate this algebra equation in as many ways as you can’. There’s an infinite number of ways.

OL: You end up with the ‘x’ on one side by itself in only a small number of these combinations.

JS: Exactly. We’ve never run a goal-free problem using that sort of material. In most geometry areas it tends to be limited. It works in some areas of physics. Especially in physics, word problems like calculating velocity of something, acceleration, or time. If you tell someone: “calculate everything”, they’ll run out of things to calculate very, very quickly. They can do it and, all of a sudden, they find: ‘Oh  right, I’ve just calculated what this question was asking’. I’m thinking of the experiment you proposed a little while ago (see this post). But in other areas you can’t use it. Worked examples on the other hand, work everywhere. All the way from limited mathematics areas to…

OL: Shakespeare?

JS:  Shakespeare, yeah. That’s why we put the emphasis on worked examples rather than goal-free problem solving.

OL: Is there a key difference between—I understand what you’re saying in terms of how the goal-free effect is limited in its scope—but is there a fundamental difference between that and minimally guided instruction?

JS: Probably not. There is no instruction other than “calculate whatever you can”, but the reason it works is the reason I just outlined. There may not be any instruction, but there’s not much you can do anyway.

OL: Yeah okay. It’s within a kind of bounded region of exploration.

JS: It’s very very bounded, and generally speaking, if it’s using motion equations you just look at your 3 or 4 equations, you’ve got an unknown in each one of them and you just say, “Ok. I’ll try this, I’ll try this, I’ll try this.” And at the end of the day, not only that but everything you try will teach you something that you need to learn. For any of these equations, you have to be really good at it.  You have to be able to calculate any unknown at any time. You can always be given a problem which will require you to calculate this unknown and then the next one this other unknown, etc, etc.

OL: Got it. What I’m taking away from that is: Goal-free kind of approaches and minimally guided approaches can both be effective within a bounded set of examples if also students record what they’re doing in a clear way and then reflect upon it.

JS: Students need to reflect on it and can I reiterate strongly that the reason worked examples work is because you’re asking them to reflect on it. In effect you’re saying: “Study the worked example”. That’s another way of saying: “Here’s a problem solution, reflect on it.” Okay, “You didn’t calculate it yourself but it doesn’t matter”.

OL: It doesn’t matter who did it, as long as they’re reflecting afterwards?

John Sweller: Yeah.

Next post:

4. Biologically primary and biologically secondary knowledge

All posts in this series:

  1. Worked Examples – What’s the role of students recording their thinking?
  2. Can we teach problem solving?
  3. What’s the difference between the goal-free effect and minimally guided instruction?
  4. Biologically primary and biologically secondary knowledge
  5. Motivation, what’s CLT got to do with it?
  6. Productive Failure – Kapur (What does Sweller think about it?)
  7. How do we measure cognitive load?
  8. Can we teach collaboration?
  9. CLT – misconceptions and future directions