Deep Learning in a Digital World of Possibilities
It seems like every day a new app or platform is clamoring for teachers’ attention and claiming that it will revolutionize learning by engaging students and improving educational outcomes. But the reality is that the track record of edtech is not necessarily a source of pride. Instead, a lot of money has been spent and a lot of time devoted to products that did not, in fact, improve learning outcomes. So how can we help edtech to reach its full potential? I am glad you asked. I am of the opinion that in order to maximize the impact of edtech, we need to redefine deep learing in a digital world full of possibilities.
While there have likely been many factors contributing to the current state of affairs, an important one is that most edtech tools have not focused on deeper learning. The fact is that it is pretty simple to design edtech that tests students’ recall of material: pretty much anyone can create multiple choice questions on a digital platform. But rote memorization and spitting back facts are not the route to deep learning. Instead, the next generation of edtech needs to focus on deeper learning to be truly impactful.
How can this be done? There are a variety of models for what constitutes deeper learning that edtech designers can consult. One classic source is Bloom’s taxonomy, especially the revised version. The tendency to emphasize the lowest levels of the pyramid needs to be avoided. While it is normally easier and cheaper to design digital tools that test students’ ability to remember information simply, this is not deep learning.
Instead, edtech can focus on the top of the pyramid and promote instructional materials that encourage students to evaluate and create. This kind of work cannot be assessed by a machine. Quality instruction still requires human involvement, and it will have a price tag that reflects it. But it is an essential element in deeper learning.
Bloom’s taxonomy is not the only game in town. Many educators prefer to use the Depth of Knowledge wheel instead. But for our purposes, these two taxonomies are similar in that too many edtech tools focus on DoK’s level one, simple recall. Instead, the next generation of edtech needs to aim for level four and emphasize extended thinking.
One advantage of the DoK approach is that it instantly provides designers with the verbs that they need to use to assess these deeper levels of learning. Edtech tools should ask students to design, critique, analyze, create, and prove. Again, this type of work can not be assessed with a simple algorithm.
Whether one prefers Bloom’s or DoK, the end result is the same: deeper learning requires edtech to embrace higher-order thinking skills.