## The goal of productive failure is not to get the correct answer faster and more easily via shallower learning

Saturday, June 24th, 2023

Generally, teaching looks something like:

1. Explain how to do something (lecture)
2. Show students what it looks like in action (demonstration)
3. Fix their off-target attempts, to help them minimize “failure,” and reward them for their successes (feedback)

This sequence tends to emphasize getting to the correct answer as expeditiously as possible.

[…]

A pair of researchers (Kapur & Bielaczyc, 2011) conducted a study of “productive failure” to see if early floundering would lead to better learning than the traditional teaching approach (“direct instruction”).

[…]

The direct instruction class began learning about average speed with a lecture.

The teacher explained the concepts, worked through some examples, encouraged questions, and had students solve practice problems.

Then they reviewed the problems and discussed the solutions.

For homework, they were assigned similar problems in their workbook.

[…]

The productive failure class was split up into small groups, and each was tasked with solving two complex problems…

They were given these problems with no teacher support or guidance, but simply allowed two class periods to try to solve each problem (4 classes total).

There was also no homework, though they did receive extra problems to work on individually when the group problems were complete (2 class periods).

After 6 sessions of working on their own, the class spent their final class session sharing their solutions and strategies with the teacher and each other.

Only then did the teacher finally explain how to solve these problems the “correct” way, and help the students go through their previous work, fix their mistakes, and ensure they could arrive at the correct answer.

Ultimately, the productive failure group spent 7 class sessions working on calculating average speed, just like the direct instruction group. But they spent most of these classes floundering on their own, and doing many things wrong. It was only during the 7th and final class that they learned the correct way to approach these problems.

[…]

As you can probably imagine, the direct instruction group did waaaay better than the productive failure group in the early stages of learning.

The direct instruction group averaged a score of 91.4% on their homework.

Meanwhile, the productive failure group performed miserably on their unguided attempts to solve the complex problems. Only 2 out of the 12 groups (16%) arrived at the correct solutions. And when they had to work on the problems individually, their average score of 11.5% was even worse.

But a very different picture emerges when you look at the groups’ performance on the post-test.

On the final test, the performance between the two groups flipped, and the productive failure group outscored the direct instruction group by a significant margin.

On the simple problems, the productive failure group earned an average score of 84.8% (vs. 75.3% for the direct instruction group).

And on the complex problem, the productive failure group earned an average score of 59.7% (vs. 42.4% for the direct instruction group).

[…]

However, in much the way that spaced, random, and variable practice lead to worse performance in the short term, but better performance in the long term, it seems that the goal of productive failure is not to get the correct answer faster and more easily via shallower learning (“unproductive success”), but instead, to cultivate a deeper understanding of the fundamental principles and various ways of arriving at a solution even at the expense of short-term performance.

1. Felix says:

Zero surprise.

A core to my own method of working is that, given a problem, the thing to do is to thrash around (not knowing the “right” solution) way, way longer than justified. The idea is to not pollute your mind with the “right” way to solve the problem. Instead, try to accidentally come up with a better solution than the “right” solution. True, that rarely happens, but:

1) I come out knowing the landscape around the “right” solution. In the future that can be handy.

2) Sometimes, a sub-optimal solution is, in fact, better than the “right” solution for the particular problem at hand.

3) It’s remarkably satisfying to discover, yourself, the “right” solution.

4) It’s way more fun.

Honestly, #4 is the real reason for using this method.