There are some very interesting education experiments in progress. I have written about an opportunity in augmented education, post-graduate classes that provide tactical and responsive professional skill development. In higher education, companies like Coursera, Udacity, and EdX are taking on the much broader challenges of improving access, cost, and quality (and the holy grail of trying to address them all at once) of university courses. But what do we lose when classes are on a la carte offer? And where does the (blurry) line between education and learning fall anyway?
As new educational models gain traction, I think we will need a learning marketplace to make sense of the new channels for learning in the context of the new learning objectives (i.e., beyond degrees) that they open up. Specifically, we will need metrics to evaluate and compare the different types of classes on offer. We will also need a way to help people construct learning paths that make sense in addressing their individual objectives. And, eventually, we’ll need a more nuanced way to measure what people have learned, and more broadly, what they know.
For some time, higher education has been relatively one-size-fits-all: people enrolled at institutions that measured progress through prescriptive curricula (defined majors) and formulaic requirements (distribution of credit hours), and those institutions provided certification at structured milestones (tests, graduation).
In this context, the currency of higher education has been reputation; this has been the best indication of how effective learning institutions are at educating. Reputation has, in turn, often corresponded to selectivity. Many of the US News criteria get at how good the admitted students are (e.g., acceptance rate, SAT percentiles, 6-year graduation rate) more accurately than the effectiveness of the classes they’ll take. This has remained a reasonable proxy because, upon graduation, the graduates continue achieving at more of less the same levels as they always have.
But reputation represents the whole experience—the interaction with peers, the extracurricular opportunities, the grassy quads. If you are taking a few online courses offered by Stanford instead, what do you lose? And in any case, if the defining feature of massive open online courses is that anyone can take any class, selectivity goes away as a metric.
So what are some practical substitutes for reputation in determining the effectiveness of new learning opportunities, particularly those related to augmented education and professional learning? A few concept/elements come to mind:
Job placement – If you take a class or series of classes and then get a (better) job as a result (i.e., because an employer is sufficiently confident that you know the things that you should know), that’s pretty good evidence that you’ve learned something. One school that has used job placement as a measure of quality is Western Governors University, an online non-profit university started in the late 90s based on the principle of competency-based education: your progress is measured not in credit hours, but Competency Units based on assessments that are administered along the way. The school emphasizes job placement and shuts down programs when employer demand dwindles. General Assembly is also pursuing placement opportunities for students that complete their certificate programs.
Ratings and reviews – Ratings and reviews already work for restaurants, shopping, and various service providers. Many MBA programs aggregate and publish data from course and professor evaluations to help other students make selection decisions; scores are used to set up a marketplace where highest-ranked courses cost the most bidding points.
In addition to indicating overall quality (instructor expertise, teaching ability, pedagogical approach), peer reviews could be the best available measure of relevance in areas going through rapid change; student feedback could suggest that the context of the topic has changed even before the instructors themselves become aware of it. And the profile of the reviewer is also useful data: Was the class most useful to practitioners or managers? Experts? People with non-technical backgrounds?
Portfolios –Student output and application is one of the best ways to demonstrate what’s been learned as well as to expose student talent. Do those completing a particular course produce intellectual property that is intelligent, creative, analytical, etc.? Sites like Behance and dribbble are emerging to serve as public portfolios for creative disciplines, and Quora and personal blogs showcase other kinds of personal aptitude. Especially as more and more interviews are asking for examples of work upfront (but let’s please not call them applijects), what’s the way to standardize and showcase work product in such a way that others can form conclusions?
Then, what about determining what to learn? Beyond satisfying curiosity, how do we understand what we don’t yet know?
Jeff Jarvis has offered up one of the most compelling views of how the function of a school (or, more broadly, provider of education) might evolve. He suggests that educating may become about “prescribing and agreeing to students’ desired outcomes,” with the school curating, creating, and recommending tools to address the gaps.
This framework makes a lot of sense in the context of augmented education; increasingly, no two professional paths will develop in exactly the same way so we have to set our own curricula. What if the learning marketplace, then, provided not only a means of assessing quality, but also a way to plot out what we need to learn and how best to do it?
Curation – The marketplace should surface and organize the best resources to gain knowledge by topic or function or discipline. It will have to address questions of scope: Do conferences count as resources? Slideshare decks? TED talks?
Recommendation – The marketplace should provide suggestions as individuals start to define their learning paths. If a person starts building a curriculum to shore up on social media, she should also get recommendations for resources about, say, content strategies, as well as some sense for the profiles of other people who have considered or used various resources.
Tracking – Finally, the marketplace should keep some record of the learning investments people have made, a sort of digital transcript of the knowledge they should be accountable to. It may have to determine how to validate what people report, or even provide some translation or evaluation across sources.
Current experiments in education are starting to prove out whether education can be provided in non-traditional formats and by non-traditional instructors. If successful, there will be new opportunities to make learning effective as modular, self-directed, and practical pursuits.