Technology isn’t seen as a panacea for the education sector’s problems. The disconnect between the needs of employers and the type of graduates universities are producing won’t be solved through technology, nor will the numerous pressures on lecturers or the shaky finances of some of our tertiary institutions.

But technology does promise to make education more accessible and effective. Why should Amazon or Facebook know more about what motivates you, and deliver you more effective tools, than the people and institutions who are trying to prepare you for a productive life and career?

The tech touted to shake up tertiary education five years ago was the MOOC (massive open online course), which promised to open up free online courses to anyone, anywhere. It did just that – Stanford University alone has enrolled 10 million students from around the world in its online courses on everything from philosophy to engineering. The University of Auckland and Victoria University are among those offering MOOCs here.

Many in tertiary education saw the arrival of MOOCs as either undermining existing university courses by reducing valuable interaction between students and teachers, or as a potential cash cow for underfunded universities.

MOOCs turned out to be neither. Their innovative use of technology has lifted the game of institutions, transforming course materials, online platforms and assessment processes. The data yielded from interactive online platforms has informed course design and assessment.

But while they have allowed institutions to reach international students and grown their global brand awareness, they have been no silver bullet for reducing institutions’ costs or increasing revenue.

A similar mix of trepidation and hype greets the application of artificial intelligence (AI) to the education sector. Using machine learning and with access to increasing amounts of data generated by students’ digital activity, a new suite of algorithms promises to offer educational insights at a personal level that could improve outcomes for teachers, students and institutions alike.

Sarah’s ‘personalised learning’

They call it ‘personalised learning’ and for Sarah, a typical first year Bachelor of Commerce undergraduate student at university it could, in the near future, look something like this: instead of having to turn up to the usual lectures and complete course assignments by pre-assigned due dates, Sarah’s content, timing and intensity of course work is tailored to her individual needs, based on her survey results and monitoring of studying habits.
Sarah skips the lectures entirely in favour of online videos and online peer group discussion. Her learning app has detected that she is struggling to complete a module on accounting, so it prompts her to message her tutor and fellow students for additional help.
Instead of arbitrary test dates, she chooses when to complete them. Sarah pays a lower tuition fee than some of her fellow students, because she has opted for online coaching and digital learning materials only.

Aspects of this are already done at tertiary level, but the mix of processes, platforms and methodologies underpinning it all are not yet standardised for best results. That’s why the tech sector is taking a keen interest, with the likes of Microsoft developing personalised learning tools.

A data-driven approach

Facebook founder Mark Zuckerberg and his wife Priscilla Chan have poured hundreds of millions of dollars via their charitable foundation into developing the Personalised Learning Platform, to pursue that ‘student-of-one’ pathway allowing technology and algorithms to, as Zuckerberg puts it, “customise instruction to meet the student’s individual needs and interests”.

It isn’t a Facebook project, but it draws from the social media giant’s modus operandi of figuring out what makes us tick and delivering content and interactions tailored to our needs, which Facebook’s algorithms understand better than we do ourselves.
An increasingly data driven approach to personalised learning is a chilling prospect for many in the education sector. But as with the arrival of the MOOC, AI could improve on a one-size-fits-all system increasingly less well suited to the realities of the market, rather than up-end tertiary education completely.

At a more functional level, AI is expected to bring the convenience of digital assistants to the learning environment. AUT students in 2016 developed NINA, a chatbot that works with Facebook’s Messenger service to offer access to many of their university’s own services. With NINA, you could renew a library book, enroll in a course or order lunch through the chatbot, rather than navigating numerous websites and log-in systems.

Others are applying the digital assistant to learning itself. Jaipuna, a New Zealand-based tutoring business, has created Amy, an AI maths tutor for high school students. Amy learns your skill level and gives feedback on mistakes to make learning maths easier.

It is too much to expect the AI-driven benefits we enjoy in our everyday lives to bypass the education sector. The challenge ahead is to do so in a way that brings the best out of teachers and students alike and gives our tertiary institutions a renewed sense of relevance and responsiveness.


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