. What is it?
Is it fair to ask questions about new topics without presenting some relevant information first? It’s an instructional design method I’ve always liked, so it was good to see that the research backs up the instinct. But it’s also one that has got me into heated discussions with subject matter experts. Before we look at the pros and cons, what is generation?
The act of trying to answer a question or attempting to solve a problem rather than being presented with the information or solution
When we have to struggle with a question about something new, we tend to think of terms of reference that could be relevant. That helps us make connections with prior knowledge and deepens learning. But that’s just one form of generation. It also refers to everything from simple fill-in-the-blank and open input questions to essay writing. In other words, any kind of question that requires you to come up with the answer yourself rather than choose from a list of possible right answers. Why does this style of question lead to stronger memories and better retrieval? It’s about desirable difficulty which I mentioned further up.
The more effort you have to expend to retrieve knowledge or a skill, the more the practice of retrieval will entrench it
How does Duolingo do this?
It does it in stages. When you start a new topic you get no background information, no learning objectives, just a topic name like “Food”.
The first question is always a graphical multiple choice question – so far they’ve all been nouns. So although you don’t know the vocabulary, even a small child can recognise the right answer.
Not all vocabulary is easy to represent visually – pronouns, some verbs etc. Instead, new structures are introduced with multiple choice answers, so you can make an educated guess. You also have the option to tap for a definition and explanation.
You have to type the answer in, either from what you heard or what you read. These questions have no support, so the stakes are higher. If you get any question wrong in Duolingo you lose a life. It’s a very gamified learning experience, but we’ll look at that in another post.
Beyond the core language learning system, there are other features which encourage higher levels of learning and application. These include chatbots and social learning communities.
There are several characters represented as chatbots in typical situations like restaurants, shops etc. This is your chance to practise using actual phrases in
response to “real” native speakers. It’s naturally more challenging, but it works
really well. They’ve put a lot of thought into how the conversations flow and I never once felt frustrated that my answer wasn’t recognised (unless it was
complete rubbish). You also get additional points for coming up with more elaborate answers. I haven’t tried out the community groups yet, but it’s great to see they offer ongoing options to raise your mastery levels in each language.
How could you use this in e-learning?
Earlier I mentioned the pros and cons of elaboration in e-learning and how they can get instructional designers into trouble. The first problem comes when people feel it’s unfair. It’s about high stakes vs low stakes testing. If you’re expecting people to answer questions they’ve never encountered before, it needs to be clear that it’s ok to get it wrong. If it’s a compliance course, people are likely to be on edge about getting questions wrong.
When we use this approach we need to make it clear which questions contribute to completing a course and which don’t.
The other challenge comes when we deviate from multiple choice questions. Any time we ask people to type in answers to questions online we create the potential for user frustration. If someone types in a correct answer that we didn’t think of, or they made a small typo, they’ll get upset when the software tells them they’re wrong. In Duolingo every feedback box gives the option to report any problems back to Duolingo which is a good way of putting power back in the hands of the user (and picking up on any errors). I tend to shy away from using open input questions, unless it’s for reflective purposes, because of the trouble I’ve caused myself in the past. You’d think that with advances in predictive text and natural language processing, today’s authoring tools could auto-suggest all
the most likely answers, rather than rely on the poor old instructional designer to come up with them and enter them manually. If such a tool exists I haven’t heard about it yet – feel free to enlighten me in the comments!
So what about chatbots?
Surely simulating conversations in safe online environments must have a wide range of applications? Are there any
authoring tools that have incorporated this as a feature? I know the latest version of Evolve is heading in this direction, but it’s not actually interactive or branching yet. Building interactive chat sequences isn’t really that hard. I’ve been playing with a tool called Tars that makes it easy to create branching chat
sequences. Here’s an example we built to capture leads on a client’s website . It wouldn’t be difficult to do something similar for a branching scenario. If there isn’t a tool that does this already, expect something on the market soon.