When we design learning activities (per the activity-based learning model), ideally we’re looking to create an integration of a number of constraints around that assignment. I was looking to enumerate them, and (of course) I tried diagramming it. Thought I’d share the first draft, and I welcome feedback!
The goal is an assignment that includes the right type of processing. This must align with what they need to be able to do after the learning experience. Whether at work or in a subsequent class. Of course, that’s factored into the objective for this learning activity (which is part of an overall sequence of learning).
Another constraint is making sure the setting is a context that helps establish the breadth of transfer. The choice should be sufficiently different from contexts seen in examples and other practices to facilitate abstracting the essential elements. And, of course, it’s ideally in the form of a story that the learner’s actions are contributing to (read: resolve). The right level of exaggeration could play an (unrepresented) role in that story.
We also need the challenge in the activity to be in the right range of difficulty for the learner. This is the integration of flow and learning to create meaningful engagement. And we want to include ways in which learners typically go wrong (read: misconceptions). Learners need to be able to make the mistakes here so we’re trapping and addressing them in the learning situation, not when it could matter.
Finally, we want to make sure there’s enough variation across tasks. While some similarities benefit for both consistency and addressing the objective, variety can maintain interest. We need to strike that balance. Similarly, look at the overall workload: how much are we expecting, and is that appropriate given the other constraints outside this learning goal.
I think you can see that successfully integrating these is non-trivial, and I haven’t even gotten into how to evaluate this, particularly to make it a part of an overall assessment. Yet, we know that multiple constraints help make the design easier (at least until you constrain yourself to an empty solution set ;). This is probably still a mix of art and science, but by being explicit you’re less likely to miss an element.
We want to align activities with the desired outcome, in the full context. So, what am I missing? Does this make sense?
Hi Clark, interesting post!
We’ve been discussing this issue in the tiny instructional design team at organization where I work. I have a tendency to leap right to “let’s let them try the full task,” but that runs the risk of overwhelming the learner. In his book, Practice Perfect, Doug Lemov points out that we want learners to practice success more often than failure, because although the saying is that “practice makes perfect,” it in fact does not. Rather, practice makes *permanent*, so practicing failure too often runs the risk of “burning in” the wrong way to do things, which we definitely do not want. That suggests constraining the early challenges more than the later ones, so that learners are more likely to be successful at each stage as they build up their skills.
At this year’s ATD conference I attended a session about using the Hero’s Journey as a storytelling guide for training purposes, and noticed that a middle stage in the journey (called “Ordeal, death, and rebirth” in the presentation I attended) involved death and rebirth, and so did a later stage (titled “Resurrection” in the ATD presentation). I asked about it and the presenter used the movie Rocky as an example. The earlier stage is when Rocky is preparing for the big fight and his confidence is flagging; he has to recommit to his training routine. Through hard work, he is “reborn” (i.e., regains his confidence), symbolized in the movie by his running to the top of the stairs, hands in the air in triumph. The “resurrection” at the later stage of the journey is when he’s in the ring, and Apollo Creed knocks him to the mat. This is the “death.” He has to muster all of his strength to get back on his feet and finish the fight. That he does so is his “resurrection.” So the first death and rebirth is in a situation where something important is on the line, but less important than what’s at stake in the later “resurrection” situation.
So this suggests that in drama, there are escalating levels, just like in video games, and perhaps this is a good way to look at learning challenges as well. Start with smaller or simpler challenges, maybe with conditions constrained so much as to be unrealistically ideal, and then let the learner “level up” as he or she takes on challenges that remove constraints by adding additional (realistic) complications to the challenge, until finally, the learner is able to solve fully-realistic challenges with very few constraints. By leveling through graduated challenges this way, we might increase the odds that learners practice success at each stage more often than failure.
We implemented this in a limited way in a recent hazardous waste course we built. Learners are first asked to accumulate flammable liquid waste into an accumulation container. There are many sub-tasks they must complete to solve this task correctly, but overall it is not too complicated. After they finish this, we ask them to do it again, but this time their waste fills the accumulation container, which adds a whole set of additional tasks they need to master, including capping off the full canister and labeling and starting a new one.
Another kind of constraint might be on when or how the learner is allowed to move on from one level of challenge to the next. Lemov points out that we often stop training when learners achieve competency, but that the value of practice actually increases after that. Imagine if we threw pitches to a little league player only until he or she successfully hit the ball one time! That wouldn’t be nearly enough to get that player to be a really great batter. Once the kid hits the ball successfully, then we can practice success! We should throw many more pitches so the batter can learn what success feels like, and can can become truly expert at hitting the ball in response to a wide variety of different kinds of pitches. Lemov points out that it is usually more beneficial to be able do the most important 20% of things really well, than to be able to do more things merely competently.
Anyway, figuring out how to graduate the challenges, when to let learners proceed from one level to the next, and when to declare they have mastered the tasks is, as you say, non-trivial.
Ray, yes, the old “practice ’til they get it right” instead of “practice ’til they can’t get it wrong”. Sigh. And agreed re: scaffolding and increasing challenge. The narrative tension, ramping up with either different contexts and/or more complexities to address. Testing and tuning should be considered in the schedule, but too few do. “If we build it, it is good” is implicitly the mantra, wrong as that is. Thanks for the thoughtful response!