Learner, Know Thyself

As “Big Data” loom larger and larger, the value of owning your own data likewise increases. Learners need to have access to all of their prior educational data, just as much as patients need access to all of their prior medical records, especially as they move between multiple providers and change over time. Instead of locking up valuable information in the hands of individual organizations with their own proprietary or idiosyncratic institutional habits, this lets the learner share their data for new educational providers to analyze.

Putting data back in the learners’ hands also empowers them to act as their own student-advocates, not just recognizing patterns in when they are learning more effectively (or less), but having the evidence to support their position. With accurate self-assessment and self-regulated learning becoming increasingly important goals in education these days, having students take literal ownership of their own learning and assessment data can help them make progress toward those goals.

Beating cheating

Between cheating to learn and learning to cheat, current discourse on academic dishonesty upends the “if you can’t beat ’em, join ’em” approach.

From Peter Nonacs, UCLA professor teaching Behavioral Ecology:

Tests are really just measures of how the Education Game is proceeding. Professors test to measure their success at teaching, and students take tests in order to get a good grade.  Might these goals be maximized simultaneously? What if I let the students write their own rules for the test-taking game?  Allow them to do everything we would normally call cheating?

And in a new MOOC titled “Understanding Cheating in Online Courses,” taught by Bernard Bull at Concordia University Wisconsin:

The start of the course will cover the basic vocabulary and different types of cheating. The course will then move into discussing the differences between online and face-to-face learning, and the philosophy and psychology behind academic integrity. One unit will examine the best practices to minimize cheating.

Cheating crops up whenever there is a mismatch between effort and reward, something which happens often in our current educational system. Assigning unequal rewards to equal efforts biases attention toward the inflated reward, motivating cheating. Assigning equal rewards to unequal efforts favors the lesser effort, enabling cheating. The greater the disparities, the greater the likelihood of cheating.

Thus, one potential avenue for reducing cheating would be to better align the reward to the effort, to link the evaluation of outputs more closely to the actual inputs. High-stakes tests separate them by exaggerating the influence of a single, limited snapshot. In contrast, continuous, passive assessment brings them closer by examining a much broader range of work over time, collected in authentic learning contexts rather than artificial testing situations. Education then becomes a series of honest learning experiences, rather than an arbitrary system to game.

In an era where students learn what gets assessed, the answer may be to assess everything.

Unpacking degrees

Chris Dillow questions the purpose and value of a university degree (linked from Observational Epidemiology):

What is university for? I ask this old question because the utilitarian answer which was especially popular in the New Labour years – that the economy needs more graduates – might be becoming less plausible. A new paper by Paul Beaudry and colleagues says (pdf) there has been a “great reversal” in the demand for high cognitive skills in the US since around 2000, and the BLS forecasts that the fastest-growing occupations between now and 2020 will be mostly traditionally non-graduate ones, such as care assistants, fast food workers and truck drivers; Allister Heath thinks a similar thing might be true for the UK.

Nevertheless,we should ask: what function would universities serve in an economy where demand for higher cognitive skills is declining? There are many possibilities:

– A signaling device. A degree tells prospective employers that its holder is intelligent, hard-working and moderately conventional – all attractive qualities.

– Network effects. University teaches you to associate with the sort of people who might have good jobs in future, and might give you the contacts to get such jobs later.

– A lottery ticket.A degree doesn’t guarantee getting a good job. But without one, you have no chance.

– Flexibility. A graduate can stack shelves, and might be more attractive as a shelf-stacker than a non-graduate. Beaudry and colleagues decribe how the falling demand for graduates has caused graduates to displace non-graduates in less skilled jobs.

– Maturation & hidden unemployment. 21-year-olds are more employable than 18-year-olds, simply because they are three years less foolish. In this sense, university lets people pass time without showing up in the unemployment data.

– Consumption benefits. University is a less unpleasant way of spending three years than work. And it can provide a stock of consumption capital which improves the quality of our future leisure. By far the most important thing I learnt at Oxford was a love of Hank Williams and Leonard Cohen.

As the signaling function of the degree falls, we should consider how the signaling power of certificates, competencies, and other innovations may rise to overtake it. With specific knowledge and skills unbundled from each other, these markers may be more responsive to actual demand. More specific assessment metrics can help stakeholders better evaluate different programs of study, while more flexible learning paths can help students more efficiently pursue the knowledge and skills that will be most valuable to them.