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ust as advances in technology enabled the growth of science, the extremely rapid growth of technology we’re experiencing today is impacting our perspectives, tools, and priorities now. But beyond some mild clamor for a focus on “STEM,” there have been only minor changes in how we think of content–this is spite of extraordinary changes in how students connect, access data, and function on a daily basis.

What kind of changes might we expect in a perfect-but-still-classroom-and-content-based world? What might students learn in the future? Of course any response at all is pure speculation, but if we draw an arc from classical approaches to the Dewey approach to what might be next–factoring in technology change, social values, and criticisms of the current model–we may get a pretty decent answer. This assumes, of course a few things (all of which may be untrue): 1. We’ll still teach content 2. That content will be a mix of skills and knowledge 3. Said skills and knowledge will be thematically arranged into “content areas”

The Content Of The Future: 8 Content Areas For Tomorrow’s Students 1. Literacy Big Idea: Reading and writing in physical & digital spaces Examples of traditional ideas and academic content areas included: Grammar, Word Parts, Greek & Latin Roots, The Writing Process, Fluency; all traditional content areas 2. Patterns Big Idea: How and why patterns emerge everywhere under careful study Examples of traditional ideas and academic content areas include: Grammar, Literature, Math, Geometry, Music, Art, Social Studies, Astronomy 3. Systems Big Idea: The universe—and every single thing in it–is made of systems, and systems are made of parts. Examples of traditional ideas and academic content areas include: Grammar, Law, Medicine, Science, Math, Music, Art, Social Studies, History, Anthropology, Engineering, Biology; all traditional content areas by definition (they’re systems, yes?) 4. Design Big Idea: Marrying creative and analytical thought Examples of traditional ideas and academic content areas include: Literature, Creativity, Art, Music, Engineering, Geometry 5. Citizenship Big Idea: Responding to interdependence Examples of traditional ideas and academic content areas include: Literature, Social Studies, History; Civics, Government, Theology 6. Data Big Idea: Recognizing & using information in traditional & non-traditional forms Examples of traditional ideas and academic content areas include: Math, Geometry, Science, Engineering, Biology; 7. Research Big Idea: Identifying, evaluating, and synthesizing diverse ideas Examples of traditional ideas and academic content areas include: English, Math, Science; Humanities 8. Philosophy Big Idea: The nuance of thought Examples of traditional ideas and academic content areas include: Ethics, Literature/Poetry, Art, Music; Humanities

uch tactile features can help build muscle memory and improve accuracy — skills lost in the rush to touch screens, said Scott MacKenzie, a professor of electrical engineering and computer science at York University in Toronto who specializes in human-computer interaction. Many people who type on flat glass screens must keep their eyes focused on the surface to hit the correct key, he said. “It’s not just that visual attention is needed,” he added, “but a lot of visual attention.”

Let’s look more closely at what is happening, conceptually, when we make an analogy. “The essential requirement for analogical thinking,” Holyoak and Thagard write, “is the ability to look at specific situations and [] pull out abstract patterns that may also be found in superficially different situations.” That’s important, so I’ll say it again in a slightly different way: A useful analogy reveals the deep commonalities beneath superficial differences.

What does this allow us to do? The scientists Kevin Dunbar studied used analogies, first, to formulate hypotheses that they could then test. Their thought process went something like this: If we know that X does Y when Z, is it possible that A does Y when Z, too? Let’s find out. That’s often how innovations get their start, in the lab and elsewhere: by taking a familiar starting point and using it as a launch pad to explore new territory.

The appearance in the transcript of words indicating uncertainty, such as “maybe,” “I don’t know,” and “I don’t understand,” was often followed by an attempt to draw an analogy—to compare the ambiguous situation to a situation with which the scientists were familiar.

Eight of the top 10 computer science departments now use Python to teach coding, as well as 27 of the top 39 schools

Java is frequently used in high school advanced courses, so the transition to Java in college is a natural one for students

mary and secondary school pupils in

Teaching programming skills to children is seen as a long-term solution to the “skills gap” between the number of technology jobs and the people qualified to fill them

Our new curriculum teaches children computer science, information technology and digital literacy: teaching them how to code,and how to create their own programs; not just how to work a computer, but how a computer works and how to make it work for you.”