Learning to learn could be built into online courses

Why do some of us learn easily and quickly, while others struggle, left behind plodding along? Part of the answer, at least in the online learning space, is that learning is a real skill in and of itself, and some people are more skilled at it than others. And the good news for the plodders is that it is a skill that can be readily grasped when we break it down.

I’ve analysed the data from over 100,000 learners on the University of Melbourne’s various MOOCs or massive open online courses – every click, tap, swipe they make, every document they consult and every word they write in chat forums and exercises. What emerged was a remarkably consistent pattern of which learning behaviours work and which don’t.

It means that it should be possible to design online learning systems that not only teach skills and knowledge, but also at the same time teach students how best to learn.

Passive learning

Overall, the analysis suggests that learners with lower levels of learning expertise are likely to be passive in their behaviour. That is, they receive input, limit their interaction to consuming content supplied by the teacher and are unengaged with their peers, taking responsibility only for themselves. They seek guidance only from authoritative figures about what to read or think and adhere to contexts and perspectives similar to their own.

They regard learning as the mastery of reasonably static, generalisable knowledge, easily transferred in books or by lectures. Expert learners, by contrast, are likely to scan different sources of information, seeking out a range of potential sources of learning in the environment.

They regard valuable knowledge as somewhat volatile, context dependent, widely distributed, and including tacit understandings, as well as generalisable understandings. They actively seek out the views of others and conduct dialogues with peers in which they collaborate, mentor and even teach their fellow students.

Taking risks

They actively review and consider the perspective of others, and are critically aware. They are prepared to reject anything they see as unhelpful, and are independent-minded enough to take the social risk of expressing a contrary view. They produce learning artefacts, try out new ideas and skills, potentially risking public failure and embarrassment, and they share learning activities and resources with others.

They interact with feedback to exhaust its value for learning and provide feedback themselves to peers and evaluate peer performances.

The study found that 90% of learners from any MOOC could be reliably grouped along this curve of learning skill by analysing their behaviours in the log stream of online courses.

I found that an individual’s position on the learning skill progression was a good predictor of grade outcomes in the MOOC. In essence, this progression describes the differences between learners more or less skilled in learning in MOOCs and supports the view that learning is itself a learnable and transferable skill. It means that people can get better at learning if they know how to go about learning to learn.

Indeed, it is possible that the progression captures something about learning skill in general, and that it can easily be adapted to any learning by anybody at any level. By analysing the progression of learners I was able to identify five distinct levels of learning:

• • Level 1: Reader – MOOC as a textbook
  
• • Level 2: Consumer of Instruction – MOOC as a tutor
  
• • Level 3: Self-regulated producer of learning – MOOC as a tutor with a user support group
  
• • Level 4: Collaborative learner – MOOC as a collaborative learning environment
• • Level 5: Reciprocal teacher – MOOC as a reciprocal, distributed learning environment.

The rocket fuel of learning

For me the most exciting aspect of the research is the potential for putting it to work.

Since the analyses are based on learning progressions along which individuals develop, and not just an end result, assessments of expertise in learning can be fed back to every participant in even the most massive of MOOCs.

That feedback could show every learner the level of expertise in learning they are at, together with hints, encouragement, suggestions and resources to help them move to the next level of learning expertise. And feedback, learning science suggests, can be the rocket fuel of learning.

With this possibility in mind, the algorithms underpinning the assessment of learner position on the progression in MOOCs are being further developed for use in the Melbourne MOOC programme in ways not previously attempted.

Early results suggest that these progression-based analyses do indeed have practical utility in providing formative feedback as well as informing course developers and learning designers about ‘what works’.

By showing that learning is a skill within large-scale digitally mediated programmes, the research will help to develop both the quality of programmes and the capacity of learners to make the most of them.

In a society categorised by fast-moving technology, business disruption and multiple career changes, knowing how best to learn will be a critical skill.

Sandra Milligan is associate professor at the University of Melbourne, Australia. This article was first published in Pursuit.