by Terry Heick
This post has been republished from a previous version and is actually intended to supplement the “Cycle of Learning Innovation,” which means this is less about analysis and context and more about the examples. First, some quick clarification so that we have a common language.
In short, by “disruption,” we are referring to something that causes the kind of impact that leads to change. To push it further, one definition of disruption might be a bottom-up cause that substantially affects the ecology it is a part of (e.g., perception, market advantages, resource needs, usage patterns, etc.), forcing redistribution (e.g., market, demographic spread, revenue, credibility, knowledge) of something else we collectively value.
Or put even more simply, “a bottom-up cause that substantially affects the ecology it is a part of, forcing reconfiguration of that system, and recreation and redistribution of currencies within that system.”
The Innovator’s Dilemma
This leads to the “innovator’s dilemma,” described in The Economist as “the difficult choice an established company faces when it has to choose between holding onto an existing market by doing the same thing a bit better, or capturing new markets by embracing new technologies and adopting new business models.”
The article goes on to point out some examples of this kind of dilemma, and how certain businesses responded.
“IBM dealt with this dilemma by launching a new business unit to make PCs, while continuing to make mainframe computers. Netflix took a more radical move, switching away from its old business model (sending out rental DVDs by post) to a new one (streaming on-demand video to its customers).
Disruptive innovations usually find their first customers at the bottom of the market: as unproven, often unpolished, products, they cannot command a high price. Incumbents are often complacent, slow to recognize the threat that their inferior competitors pose. But as successive refinements improve them to the point that they start to steal customers, they may end up reshaping entire industries: classified ads (Craigslist), long distance calls (Skype), record stores (iTunes), research libraries (Google), local stores (eBay), taxis (Uber) and newspapers (Twitter).”
What are some examples of disruptions in the classroom, then? Not necessarily initially innovations, but factors (value neutral–neither good nor bad in and of themselves) that can lead to innovation?
I’ve listed some examples of disruption in education below and ranked them (though obviously the ranking is entirely subjective and only useful as a crude reference point to start your own thinking).
For the first example, I explain in greater detail how the technology impacted modern knowledge to me. Obviously, I can’t do that for all 30 examples for this article would be 10,000 words long. The big idea is thinking about how technology is changing teaching and learning, so for the rest, I only listed the impacting factor.
30 Examples Of How Technology Is Changing What Students Need To Know
1. Voice Search
The ubiquity of search and its impact on curriculum knowledge demands. This includes voice search like Siri, Amazon’s Alexa, and Google Home
The nature of the disruption: It was argued for years that modern search engines made traditional ways of teaching and learning obsolete. Memorization and strict ‘knowledge’ were deemed less important because those ideas were a Google Search away.
Of course, that wasn’t true then, and it isn’t true now. There are things human beings need to know regardless of how efficient search is, how good predictive search and autocomplete gets, or how smart search algorithms get in identifying and retrieving what you’re looking for before you even know you’re looking for it.
While voice activated technology control found early traction with Apple’s Siri, what she was able to do was—and is—relatively limited. Amazon’s Alexa and Google Home aren’t hugely better in terms of what they are able to do, but while ‘old search’ required your phone and an often clunky web browser, voice search 2.0 is independent of your phone. It’s sitting on the kitchen table while you cook, ready to tell you the weather forecast tomorrow, play a song—even order pizza if you burn the food.
The point? We are getting closer and closer to having the ‘brain’ of every encyclopedia and book and song and poem and speech and play and political policy ever created a spoken sentence away.
While knowledge will always matter, more than ever inquiry matters: the ability of the technology user to ask the right question at the right time, and evaluate the credibility of the information that ‘new and simple’ search returns.
2. Planned obsolescence of mobile technology
3. 1:1 as the new standard
4. Extraordinary cost of college
5. Change in cultural perception of identity–gender, technology, science, faith, sexuality, etc.
6. Change in credibility of a high school diploma or college degree
7. Increasingly formal use of social media by education institutions
8. Maker Movement
9. General insecurity or misunderstanding about how to meaningfully integrate technology in the classroom
10. Relative ‘normalizing’ of computer coding
11. Falling cost of mobile devices, which impacts what’s affordable, who shows up to school with what on their own, school budgets, etc.
12. The increasing potential to ‘start a business’ that is entirely social and digital (which impacts the idea of a ‘job,’ which itself impacts the knowledge demands for ‘careers,’ which impacts curriculum design and academic standards, etc.)
13. Adaptive learning platforms and learning algorithms
14. Rapid change in the demands for media forms
15. Increased velocity of information
16. Social media as social justice platform
17. Ease of publishing (e.g., blogs, social media, podcasting) to promote conversation and thinking around what’s possible in education
18. The general success of Google as a platform model (Classroom, Music, YouTube, Search, Chromebooks, Chrome OS, etc.)
19. Narrowed (overly-narrow?) metrics of “school success” which causes parents to question how learning effectiveness is measured (see also #20).
20. The relative shrinking marketshare of iPads, as well as some very visible failure of iPad rollouts
21. Education documentaries on Netflix (such as “Waiting for Superman”), which brings the “Ed reform” conversation to a broader audience
22. 3D Printing (this one should be higher–likely will be in five years–but we’re just not there yet)
23. New demands for digital citizenship
24. District-level BYOD programs
25. The adoption of blended learning approaches through learning management systems
26. Highly variable quality of “learning apps,” which causes some app developers to “backwards plan” from the what a teacher or school will find credible; it also which causes some teachers to change their definition of what “effective” means, while others respond by calling for standards on measuring that effectiveness.
27. The growing ‘quality’ of robotics, VR, and AR in the classroom
28. Social credibility of alternative school models (Walden, Montessori, Homeschooling, etc.)
29. MOOCs, nanodegrees, etc.
30. Relative crudeness of most school and district IT performance (Wi-Fi, bandwidth, district filters, repairs, regulations, workflow, etc.) which can reduce the demand for innovative technology by teachers already hesitant to adopt meaningful education technology
31. The difference between the success of a school and the success of its most needful students
30 Examples Of Disruption In The Classroom; image attribution flickeringbrad