Will E-learning Platforms change Education?

Last Updated on December 5, 2017 by Karl Thompson

Big data enthusiasts argue that the greater data collection and analysis potential provided by e-learning platforms such as Khan Academy and Udacity provide much more immediate feedback to students about how they learn, and they thus predict a future in which schools and private data companies will work together in a new educational ecosystem…

This is a continuation of my summary of  Meyer-Schonberger and Cukier’s in their (2017) ‘Big Data: The Essential Guide to Work, Life and Learning in the Age of Insight.

You might like to read this previous post first – How will Big Data Change Education? (according to the above authors).

The advantages of e-learning platforms over traditional education

Khan Academy is well-known for its online videos, but just as important to its success is the software which collects data about how students learn, as well as what they are learning.

To date, Khan Academy has data on over a billion completed exercises, which includes information on not only what videos students watch and what tests scores they achieve, but also on the length and number of times they engage with each aspect of the course, and the time of day they did their work. This enables data analysts to deduce (probabilistically) how students learn most effectively, and to provide feedback as to how they might improve their learning.

The Kahn Academy is just one online learning platform, along with a whole range of MOOCs offered through Udacity, Coursera and edX, as well as SPOOCs (small, private online courses) which are collecting huge volumes of data on student learning. The volume of data is unprecedented in human history, and Cukier suggests that this could change the whole ecosystem of learning, incorporating third parties who do the data analysis and with the role of instructors (‘teachers’) changing providing advice on which learning pathways students should adopt.

At least some of the Khan Academy Data on learning is available to third parties to analyse for free, and information personal to students is presented to them in the form a dashboard, which allows for real-time feedback to take place.

Cukier contrasts the above, emerging ecosystem of online learning, to the present ‘backward’ way in which data is collected and managed in the current education system as backward (he actually uses the term ‘agrarian’ to describe the process) – in which students are subjected to a few SATs tests at predetermined stages, and this score is ‘born by them’ until the next test, which makes labelling by teachers more likely.

In addition to this, the school day and year are run in a 19th century style, pigeon holed into year groups, pre-determined classes, students exposed to the same material, and with digital devices often banned from classes. All of this means data cannot be harnessed and analysed.

Where does this leave existing institutions of learning?

Schools and universities are well poised to harvest huge amounts of data on students, simply because they have 1000s, or 10s of 1000s of students enrolled.

To date, however, these traditional education institutions have shown a very limited ability to collect, let alone analyse and use big data to better inform how students learn.

The coming change will affect universities first – these have mature students, and this audience is more than capable of digesting insights about how to learn more effectively… the big universities where fees are expensive and students don’t get much back in return are poised for disruption by innovators…

Some of the very top universities seem to have got the importance of BIg Data – MIT identified EdX as a crucial part of its forward strategy in 2013 for example, but some of the universities lower down the pecking order may find it difficult to compete.

The response of some forward looking schools is to embrace elearning – recognising the importance of getting and utilising more data on how students learn – Khan Academy is partnered with a number of schools, for example Peninsula Bridge, a summer school for middle schoolers from poor communities in the Bay area. – Cukier cites an example of one girl who managed to improve her maths due to this (again, evidence cited is almost non existent here!)

The chapter concludes with imaging a future in which schools are just part of a broader ecosystem of learning – which includes a much more prominent role for private companies and where data plays a more central role in learning.

Comments

There are number of factors which may contribute to schools’ inability to harness big data:

  1. Time limitations – as Frank Furedi argues in ‘Wasted’, the function of schools have expanded so that they are now expected to do more than just educate kids – thus an ever larger proportion of schools’ budgets are taken up with other aspects of child development; combined with meddling by successive governments introducing new policies every few years, schools are caught in the trap of having to devote their resources to adapting to external stimuli rather than being able to innovate.
  2. Financial limitations/ equality issues – correct me if I’m wrong, but any online course tailored to GCSEs or A-levels is going to cost money, and this might be prohibitively expensive!
  3. The negative teacher experience of governance by ‘small data’ – there is a staggering amount of small data already collected and teachers are governed by this – it might actually be this experience of being governed by data that makes teachers reluctant to collect even more data – no one wants to be disempowered!
  4. Child privacy rights – there is the not insignificant issue of letting big ICT education companies have access to our children’s learning data!

 

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Discover more from ReviseSociology

Subscribe now to keep reading and get access to the full archive.

Continue reading