In the last post, I juxtaposed my past as a dedicated English teacher with the last decades’ amazing changes in technology. The reason for pairing these two is that while technologies have transformed nearly every aspect of our lives, its impact on helping develop better writers has been negligible. This post therefore sets the scene for how these two worlds can finally sync up.
FANGST
Wall Street has an acronym for the powerhouses of the new digital era: FANG, which stands for Facebook, Amazon, Netflix and Google. Interesting, isn’t it: the bite that this nomenclature suggests? Thinking about technology’s encroachment into human experience, I tend to include Siri (with her personal assistant peers) and Tesla because of the new era of artificial intelligence they present. There’s more to think about regarding these companies and their impact on human existence, but the rapid and fundamental changes they bring to daily life understandably raise our collective level of “FANGST” (technology induced angst).
As different as they are, these FANGST technologies (Facebook, Amazon, Netflix, Google, Siri and Tesla) have two main things in common. First, they provide services in such powerful ways that they seem to verge on magic. This magic comes from Big Data and the algorithmic machine learning that happens behind the scenes. The second aspect in common is that such rapid change always stirs anxiety. It was true for the Luddites two hundred years ago and our elders last century when electricity, the horseless carriage and flying machines redefined human life.
Besides the shared anxiety that comes with such rapid changes, our current variation has its own bitter-sweet flavour: sweet in that we all easily gain more of what we want (anywhere, anytime), but bitter when we’re reminded by the media buzz that such Artificial Intelligence, personal assistants and automations will replace lots of our jobs. In the area of technology and student writing, the media buzz has taken a particular slant…
Fear and Grading in the age of FANGST
Because overall results in student writing have shown a flat line and backward trend, one aspect that’s getting a lot of attention in Australia is the use of computer software to evaluate student writing. For decades, researchers and software companies have explored this area from many perspectives, including computer science, linguistics and writing theory. The research and approaches go by many names and often become highly charged. For example, in our current debate, it’s no surprise that what researchers refer to as the science of Natural Language Processing (NLP), the media whips up hysteria suggesting it’s an invasion of “Robo-Graders” ready to undermine the value of teachers and dilute the art of writing. Like all technologies, using software to analyse writing is neither inherently good nor bad. It’s all about what the software is truly capable of analysing and how this approach is used. This is true about the many technologies we’ve already built into our lives…
Our Friendly Assistants
Each of us have already made peace with many of the assistants new technologies provide. We choose when we want software to help and when we don’t. We also choose the kind of help we want from software. For example, we’d rather have software do the mind-numbing aspects, those that are not intrinsically motivating or are prone to our human error. We’re also pretty happy when software suggests possibilities based on crunching data that we know is there, but can’t see or access.
Do we want to drive into a new city without GPS? Do we want to plan a trip without the Web? Do we want to chat with friends using Morse code? Do we want students to write essays using stone tablets and chisels? And if we recognise that students become better writers by writing more and more often, do we want teachers to read thousands more assignments? How is this fair when their colleagues don’t? Of course we want some technologies to help us. So let’s begin with a commitment to be reasonable and use what works to further the goals we have.
Which is the topic of the next post: Letting Software Do What Software Can