The most common mistake I see in implementing the Depth and Complexity thinking tools (and one I made myself) is to rely on a graphic organizer like this:
Here are three problems with this worksheet:
1. Too many prompts!
In this case, there are so many prompts of depth, that students will rush through to complete it all, leading to (ironically!) shallow thinking. This worksheet becomes a checklist rather than a tool for deep-thinking. After all, how can a kid possibly go deep with nine different tools at once?
2. No directions!
In this worksheet, there’s just a prompt sitting there by itself: “rules”. What are students supposed to do with the prompts? How should they be thinking about “rules”? If you don’t make this clear, many students will default to the lowest level of thinking. They’ll just list three rules, three details, three patterns, and so on. Listing three rules is not very deep thinking.
3. No connection to content.
Students should use prompts that best connect to the content, not a generic “use as many as we can” worksheet. If you’re cooking, you don’t always use all of your spices, right? When using the prompts of depth and complexity, consider which prompts will draw out the most interesting thinking about the content.
How To Do It better
- Pick the perfect prompts for the task. Sometimes it might be two or three, but never nine or ten! If I’m studying Rosa Parks, I’ll probably pick ethics, rules, and multiple perspectives. Sure, I could use all the prompts (they all “work”), but these three set the stage for a specific task I have in mind. You might pick three different prompts to focus on – but do pick that focus with purpose.
- Always pair Depth and Complexity prompts with a thinking skill. Use Bloom’s Taxonomy to help you rise above the “find three examples” level of thinking. Never let the prompt sit by itself or kids will default to “listing”.
- Think about your learning goal. Is it for students to fill in a worksheet? That’s neither deep nor complex. Instead, consider how to set the stage for slow, deep learning, using the prompts as a tool to get there.
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