How people keep learning – the role of intrinsic and extrinsic motivators and when behavioural economists need to come in

AI Singapore has a strong focus on learning and growth. We want our internal engineers and apprentices to develop and improve their craft. This means we don’t only think about how to build machine learning systems. We also spend time thinking about how to engineer productive learning environments for our people. The following are a few thoughts about a key feature of any learning environment – sustained motivation

Daphne Koller is a Stanford Professor who founded Coursera, a platform that offers Massive Open Online Courses. In a lecture she gave at Carnegie Mellon university, she joked that many people in the audience must have started a course on Coursera. Whether or not they had finished the course, however, was another matter. In response, the audience laughed sheepishly.

 

Daphne’s contemporary, Peter Norvig, who founded the a similar MOOC platform Udacity, has also shared how he experimented with different course delivery styles meant to slow down how fast students were dropping out of courses. They sent email reminders to students. They built features to facilitate more peer-to-peer interactions so students felt a sense of community. These measures did appear to work, and indeed Daphne and Peter’s experiences show that any discussion around learning is incomplete without a discussion around how to engineer and sustain motivation.

In my own experience, motivation falls along a spectrum ranging from intrinsic to extrinsic. At the intrinsic end, internal emotions like curiosity or an appetite for learning something can be enough to drive someone to start learning something new. Learning might look like playing with Raspberry Pis over a weekend of signing up for an online course with friends. At the opposite end, external motivators, like a problem at work or a company mandate, are what pushes a student to hone a new skill. These people may then petition their boss to send them for a training course or attend a conference. In these two instances, the motivators are strong, and so learning is largely effective. In fact, there is sometimes double effectiveness if there is a tangible outcome at the end, for example switching careers, making new friends, or reaching a new work milestone.

The question is what to do about the masses of people who fall in the middle of these two extremes. These are people who might hear rumblings like “the jobs landscape is changing” and “upskilling is important in a modern world”. Yet, because there isn’t a concrete push or pull factor, they fall through the cracks. They may sign up for a Coursera account, attend a few courses, then drop out. They may even complete the courses and videos, but miss out on a crucial next step – applying what they have learnt to a real-world problem.

It is in this middle space that behavioural economists come in with their tools: “nudges” and default options that push people towards desired behaviour, or competitions and points systems to keep people motivated. These measures work, and although it’s tempting to think that people who rely on these are more “weak-willed”, the fact is that even the strongly motivated sometimes also need these interventions to keep them on track.

I would suggest though, that having a strong intrinsic/extrinsic motivator needs to exist first. Get that right, and the need for a lot of the behavioural checkpoints like assignment deadlines and automated email reminders falls away.  

Community Lead | AI Singapore

Share the post!

Facebook
Twitter
LinkedIn
Reddit
Telegram
WhatsApp
Email
Print

Related Posts

Leave a Reply

Please Login to comment
  Subscribe  
Notify of
Do NOT follow this link or you will be banned from the site!