Learning Paths: Less Netflix, more Google
A few months ago I wrote a post on the role of Discovery in MOOCs, a perennial topic of interest as MOOC platforms are a bit of a jungle — incredible variety but no obvious path between them. Coursera have now introduced Learning Paths to their platform, with this they aim to bring their product closer to the goals of professional learners by steering those who know what they want, through the requisite courses and in the absence of a career goal they aim to provide a path to mastering a subject.
What is a Learning Path? Learning Paths, as the name suggests, provide a structured series of MOOCS through a subject or towards a profession. Coursera have been working towards this for a while with a well publicised intellectual journey:
- Coursera’s major learner survey ‘Who’s benefiting from MOOCs and Why’ distinguished broadly between three types of learner, those seeking to advance in their career, those seeking a new job and a third driven just by curiosity. The first question on the learning path asks you to sort yourself into one of these three
- Coursera created ‘skill search’ the aim was to catalogue which skills and concepts were being taught within each MOOC and then allow users to search for it — this was the critical precursor. Not only did skill searches allow better discovery (rather than having to infer from the title and course description) they allowed Coursera to structure learning across different MOOCs
- With the skill search in place and the three user profiles demarcated, Coursera created learning paths that create a series of courses among MOOCs of different providers to achieve an end goal e.g. ‘Data Scientist’ or to learn ‘Economics’
Why did Coursera do this? Coursera have been open in their goal of moving to a focus on professional learners because these learners had disposable income and had an unmet need in learning new skills and subjects to advance, change job or pursue their intellectual curiosity. By having a large portfolio of courses (including in-depth Specializations) Coursera already catered to their immediate need, but in order to raise further revenue Coursera needed move to retain these users.
To do this, Coursera needed to switch their customer relationship from a product provider (the course or Specialization) to a service — the learner’s indispensable aid to career progression or their dream job. Some of this is meeting unmet demand and some is supply driven demand.
- The first part is simply discovery, by providing a map of how to master say Economics, Coursera are providing a meta layer between courses by different providers that learners would otherwise have had to deduce themselves. Simply doing the work on their behalf ought to increase uptake
- The second part is fulfilling a goal the learner may not have known they had. Learners may have an interest in Statistics and can then be ushered into the Learning Path for Data Analyst
- Unmet demand — for those that do know what they want, MOOCs provide a bewildering array of options — where to start among so many beginner courses? What to do after that course? Even if a learner has completed a Specialization they may be at a loss to know how to progress
The latter point is a particular issue for MOOCs, as specialist platforms emerge, MOOCs are at a risk of losing out on the most valuable customers. Treehouse for coding, Datacamp for Data Science with new specialists popping up. The problem was that what MOOC platforms gained in breadth, they lost in curation. Specialists own their curriculum and provide carefully tailored routes to the learner goals.
Learning Paths are an obvious way to navigate this, providing a more direct solution to the problem of the career (or curiosity) driven learner. Coursera may well have already beta tested their particular choice of course, ensuring entry courses had lower dropout rates to ease learners in, examining how successful learners had already navigated Coursera’s portfolio while understanding where courses overlapped too much.
Coursera should also be able to go further — marketing techniques, interventions to nudge, incentives to course providers. They could also go into a personalised level, knowing someone had struggled with maths on a previous course they could swap in introductory maths before the Data Analyst track.
LinkedIn are similarly finding ways to surface discovery but by relating the user to extrinsic factors such as comparing a user’s profile with say a job advert and then tell them where they come up short — or nudging a coder to learn the most in-demand skill in the market.
In either case, both are attempting, as Google are, to drive demand of their service by meeting a user’s goal and intentions even if perhaps the user doesn’t yet know it themselves. Learning Paths, job profile data are the first step towards a much more personalised discover service.