Choose your own (data powered) Adventure
You’re old if you remember Choose your own Adventure books. Every few pages had a decision that magically transported one across the span of the book, either winging the reader’s way to victory or certain death. The snakes-and-ladders mechanism behind the books was a fascinating way to actively involve a passive reader in their experience of reading.
That mechanism hasn’t gone the way of the famed books in the internet era; content companies like Netflix have dabbled with the idea of actively letting users make decisions with mixed results. The active aspect in the 2-way content participation mechanism is still being worked out, but the passive aspect is more alive with possibility and results than ever. It’s no secret that Netflix uses data from passive user interactions to provide a better user experience: every time you pause, rate, complete or binge a show - Netflix records and uses that data to give you more of what you want. On a single person level this may come across as overkill, but at scale it amounts to millions of dollars in retained revenue.
Coming back to my youth, I found the one-size-fits-all model in education to be a misfiring and often inappropriate way of educating a vast swathe of unique little humans. I, particularly, wasn’t interested in history (there’s no future in history) nor has the knowledge that reduction happens at the Cathode had any effect whatsoever on my career as a technologist. Humans present a myriad different data points by which we can more effectively cater to their unique conditions:
Firstly, by understanding a child’s aptitude, altitude and attitude we can immediately provide for a much more unique journey through education. Case in point: my incredibly bright daughter often forgets her homework at school - it’s not because she’s thick, it’s because she has an attitude problem. There is a fantastic service at her school which understands my daughter’s needs and recommends a follow on school for her, but in the face of so much potential data, this doesn’t seem adequate enough.
Secondly, once users are assessed and their skills ascertained, they can decide how they want to proceed. This use of assessment as a way of decision making fosters that active participation in learning. Say, for example, I was learning how to be more empathetic: I could watch some content and at a specific juncture I could decide how to respond to a particular situation. That response is an assessment of how I’ve learned the skill through a decision tree which could then lead to the next scenario or point of learning. If I make the wrong decision, I am taken back to the point I was learning so that I may participate in it again. At the same time, data about my usage is recorded: What did I enjoy watching? Where did I stumble? What did I go back to?
All of this could make for a more efficient and effective learning journey as a human. In the face of a technology revolution led by the likes of ChatGPT, humans need to foster their humanity and uniqueness now more than ever. What better way to do that than to provide them with the skills and unique education that they need in order to achieve it?
