Computers are dumb – make smarter e-Learning

Computers are dumb, which can make your e-Learning dumb. What can you do about it?

Be Less Helpful

Over the weekend, I watched this video of a great presentation by Dan Meyer on how to Be Less Helpful to students.

It’s an hour long, and is well worth the viewing, even if you aren’t really interested in math education.   Amongst his many good points, there were a couple that stood out for me:

  • Students need to know how to approach and problem solve messy problems
  • Good questions should have information missing, so students can learn to figure out what else they need to know
  • Intuition can be an excellent tool in the problem-solving toolbox, if you can learn how use it well
  • These problems don’t necessarily have a single, tidy, correct answer.

That all sounds well and good and constructivist, and is in the neighborhood of all sorts of instructional design ideas that I’ve considered and espoused for years  (Problem-based LearningAuthentic Tasks, etc.), but my summary of this really doesn’t do it justice.

It was actually pretty revelatory to me — one of view shifts that picks your head up and sets it back down at a 45 degree angle, and you don’t see things the same afterwards. Lest you think I’m overselling it, set aside time to watch the presentation.  There’s also a very good explanation of his approach to these questions on his blog here: http://blog.mrmeyer.com/?p=1928

Basically, the revelation that I had was — I like right answers.  I really like tidy right answers.  I usually don’t ask learners questions that I don’t have a “right” answer or answers for. Even when the task is “authentic” and “embedded in context” I want there to be a right answer.  And this is wrong.

Because what Dan Meyer is teaching his students is how to approach problems that don’t have right answers, which is the way that most of the problems in the real world work.  His students are learning to be okay with that, and how to ask good questions, and how approach those problems.

How does this relate to computers being dumb?

Dan Meyer does a good job of recognizing why this approach is challenging to implement in his instructor-led math classes.

And it occurred to me that if it was challenging in an instructor-led environment, it was nearly impossible in a computer-based one.

Because computers are dumb.

At best, interactions in e-Learning usually consist of recognizing a right answer (or answers).  So instead of generating answers or even recalling answers, e-Learning users recognize right answers.

That’s because computers are the enemies of ambiguity (note: I’m not talking about instructor-led webinars or the like, but traditional single-user e-Learning). Instead of recognizing chewy, messy ambiguity, computers recognize Right Answers and Wrong Answers.

Even dressed up multiple choice questions are still multiple choice questions.

The other day, I was creating a quick e-Learning tutorial, and the right answer for a question was $1,244.  If I wanted the computer to be at all flexible about what the user could type in, I had to also tell the computer (in tedious detail) that 1,244 / 1244 / 1,244.00 / 1244.00 / $1244 / $1244.00 & $1,244.00 were also acceptable answers.

See? Computers are dumb.

I know that technically, it’s the software that’s dumb, and maybe if you are funded by Massive Educational Foundation and have access to some pretty impressive technology resources, you can explore things like natural language recognition (so e-Learning students could type complex essay question answers) but that’s not a practical solution for most e-Learning projects.  Even more so if you are constrained by “rapid” e-Learning tools.

So, what do you do to reconcile the fact that while there can be tremendous value in ambiguious, messy problems, computers don’t even like figuring what decimal place the learner might be rounding to?

We can dress is up in all sorts of different ways, but in the end it’s *very* difficult to insert any ambiguity into the process.

So, what can we do about it?

So, if you you don’t have access to programming resources to make interesting complicated learning games, here are a five suggestions to at least increase the level of ambiguity in your e-Learning:

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1 )  Have lots of options.  Lots and lots:

This is a pretty blunt force solution, but it means that your learners may need to employ other strategies to get answers than just browsing through until they recognize things that seem familiar or right.  It also disguises the “rightest” answers (learners have years of experience answering these kinds of questions, and know tricks for guessing and short-cutting the process).

Ways to enhance this:

  • Use same lengthy set of answers for multiple scenarios – this helps turns off learners’ “guessing” behaviors
  • Layer sets of questions (e.g. follow “What’s the Problem?” with “What clarifying questions could you ask?”)
  • Use a relevant document as the answers (e.g. “Which section/paragraph of the ethics manual addresses this issue?”)

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2)  Don’t use wrong answers

The standard format for a multiple choice question that has three wrong answers and one right answer:

You have an angry customer demanding that reverse a charge on her account, but you don’t have the authority to do so.
What do you say?
  1. “I’m sorry ma’am, but that’s the policy.”
  2. “Only a manager can do that.”
  3. “Ma’am, I understand why you would be upset about an incorrect charge.”
  4. “Of course, we’ll take care of that right away!”

We’ve all taken those quizzes, right? The ones where you are pretty sure you can answer all the questions with common sense, without looking at any of the materials.

You have an angry customer demanding that reverse a charge on her account, but you don’t have the authority to do so.
What do you say?
  1. “I can’t reverse that charge myself, ma’am, but I will find out what I need to do to help you with this.”
  2. “I’m sure there’s a way we can help you.  I just need some additional information.”
  3. “Ma’am, I understand why you would be upset about an incorrect charge.”
  4. “How frustrating that must have been for you!  We’ll take care of that right away!”

Now, to answer the question correctly, you might need to know that the training was about using validation to defuse anger.

Ways to enhance this:

  • Use “None of the above”:
You have an angry customer demanding that reverse a charge on her account, but you don’t have the authority to do so.
What do you say?
  1. “I can’t reverse that charge myself, ma’am, but I will find out what I need to do to help you with this.”
  2. “I’m sure there’s a way we can help you.  I just need some additional information.”
  3. “Ma’am, I understand why you would be upset about an incorrect charge.”
  4. “How frustrating that must have been for you!  We’ll take care of that right away!”
  5. None of the above

“None of the above” doesn’t take the number of possible answers from 4 to 5.  It takes the number of possible answer from 4 to an infinite number of options (This is something I learned from the estimable Will Thalheimer — you can get more wisdom on designing good questions, and other things learning-related at his site).

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3)  Use Self-Evaluation

Your learners are infinitely smarter and more subtle than any computer.  Let them be the judge of their own performance:

So how do you know if they got the right answer?  The same way you know somebody didn’t guess on a multiple choice questions: You Don’t.  And that’s okay, because you have to trust your learners sometime.

Ways to enhance this:

  • Have them compare their answers to a “right” answer, or even better, multiple “right answers.”
  • Don’t give them a right answer, but ask complex questions, and create discussion areas to address them (here’s an example of good questions — sorry about the font size)

Okay, so far, these are all things that can be implemented in any reasonable rapid e-Learning tool, without much programming assistance. But let’s say you do have some programming resources available.  That opens up your options considerably, but here are a just few things you might want to consider:

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4) Points-based answers

Since we are trying to get away from Right and Wrong, if you use points as the feedback for answers, you can answers that are a little bit right or wrong, a lot wrong or right, or completely neutral.  You can also have answers that are right in some ways (lowering the customer’s frustration level), but very wrong in other ways (wrong procedure eventually backfires and angers customer even more).

Ways to enhance this:

  • You can also base your outcomes on points, and have excellent, good, mediocre and bad outcomes based on points or points plus other variables (you made all the right procedural choices, but the customer is still unhappy and takes her business elsewhere).
  • This gets you a little closer to games, which can have marvelous complexity and ambiguity.

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5)  One more thing

So there are a number of ways to insert ambiguity into e-Learning, but here’s the thing — these all kind of suck.  Seriously, they are, at best, kludgey workarounds for the dumbness of computers.  Many of these still have elements of recognition rather than recall or generation, and none of them get anywhere close to having the kind of complexity that Dan Meyer was talking about.

So if computers can’t really provide the kind of ambiguity and complexity that we’d like to see, what can?

Other people.

Don’t just have your learners interact with the computer — have them interact with other people.  There are lots of ways to do this kind of Social Learning, and I’m not going to get into here, as this post is already long enough, and there are lots of smart people working on this elsewhere.

So, how do you put ambiguity and/or complexity into your e-Learning? Do you have ways to make computers not-so-dumb?

(You might notice that branching scenarios are not on this list.  While they are the most common format for simulations, they are also essentially multiple-choice questions, so I didn’t choose to include them here.)