When publishing around the World wide web, content material creators have considerable insight into what readers are performing, whether or not it’s where they’ve come from, just how much they consume and no matter whether they share content on social media. This real-time feedback has permitted publishers to tailor content material particularly towards the needs of their audience.
Suffice to say, with all the trusty paper back book, this kind of feedback is not offered, and it creates a little of a black box, whereby the only real feedback authors and publishers get is by means of points like reviews, awards and sales figures.
With books entering a digital age having said that, they bring with them the possibility of richer feedback for readers, teachers, authors and publishers alike. I spoke recently with Alfred Essa, Vice President, Analytics and R&D, at McGraw-Hill Education ahead of his presentation at the Predictive Analytics Innovation Summit, and he explained how data is driving innovation, both at his company and in education more generally.
Transforming The Understanding Experience
They are attempting to move away from the traditional, one size fits all way of understanding that doesn’t really reflect a more complex reality. Because, not only do people learn at different speeds, but they often arrive from different start points and with different backgrounds.
The use of digital books and adaptive finding out allows for a a great deal more tailored and customizable learning experience, as teachers now have access to data on what exactly students are consuming, and how they’re coping together with the concepts they’re trying to learn. Armed with this data, teachers can see if a student, or the class as a whole, is not grasping certain ideas or topics. This insight allows teachers to adjust their lessons accordingly and help at-risk students from falling behind or dropping out
What’s more, the process is not simply one of providing data to teachers. Machine studying algorithms create predictive learning paths for students while they are studying. As students go through a course with adaptive understanding software, these algorithms can serve up additional content for the student to study if reinforcement is needed, or allow the student to move ahead if the subject matter has already been mastered.
One example of this is McGraw-Hill Education’s ALEKS, a web-based, artificially intelligent assessment and mastering system, which uses graph theory to break up a domain into concepts. The edges of the network might then be used as a bridge to another domain. For instance, if algebra has 500 concepts, a student might be tested when he or she begins mastering, pinpointing exactly what a student knows and doesn’t know, and then creating an appropriate path through the domain that is selected based upon the start point
Education As A Service
It’s a process that has been seen in a growing number of industries. For instance, heavy equipment manufacturer John Deere is now more of a service provider than a manufacturer. Its latest models come equipped with all sorts of sensors and monitors to allow farmers to optimize the farming process, with an array of data helping them to function more productively. The company has gone as far as to predict that within a few year’s time, they will employ more software engineers than mechanical engineers.
Central to this move towards education as a service is the data ecosystem that underpins everything. McGraw-Hill Education is a strong supporter of IMSGlobal, which aims to develop common standards that educational providers can use to develop products and services that operate effectively together.
“The key to creating effective, scalable ecosystems, in education or any other industry, is having open standards,” commented Essa. “Our success won’t be predicated on closed systems, but instead, we are focused on building open, interoperable ones, which will allow a multitude of tools, technologies and platforms from various companies and organizations to work together.”
This shift is likely to underpin changes in the business model of publishing. While traditionally authors would be paid a one-time fee when customers purchase their book, there are signs that this model demands to change. The current breed of digital books is considerably more fluid, with content material updated based upon real-time feedback from readers. What’s more, publishers are including more open educational content in their materials, with pooled analytics provided to add further value.
How this will manifest itself in terms of business models is still largely to be decided, but this kind of open data philosophy has some fascinating implications for the industry, and for mastering as a whole.