A recent article about the use of Googles Cloud Vision API and a series of interactions on our collective Tweeting has provoked some thinking about how technology is potentially going to change the way we carry out learning and assessment even more radically that we think.
The article in Forbes magazine describes how the Googles Cloud Vision tool was tasked with analysing over a quarter of a billion images published by online news outlets from all countries around the world to see what kind of narrative developed. It documented and collated data on faces, people, places, OCR, to name a few, at unprecedented levels and to a degree that would simply not be possible by humans alone. This deep learning analytics process has brought a new visual aspect to the process of analysis and which is different from the normal data based approach.
This story, combined with our conversation this week on the alternative uses of MOOC’s other than for their primary intended purpose (I have a significant bunch of learners on my open course that I am sure are using it to practice their creative English writing skill) leads me to believe that a future in which high functioning learning analytics combined with new forms of continuous, iterative (and perhaps even micro-iterative) assessment could provide us with the ability to use single learning artifacts for multiple purposes and possibly even in combination with ones that have no currently viable connection. It may develop in to a matrix of knowledge and assessment that is so hugely complex that AI’s would simply have to manage all the connections. The plus side though, is that it could result in the creation of specializations and competencies even more vastly different from that which we have today or has been previously posited through the use of technology before.
Engineering and social sciences combinations, geology and human resources, economics and space travel, who knows. The possibilities are probably limitless..