Tag: learning

Credentials and standardisation

Someone pinch me, because I must be dreaming. It’s 2018, right? So why are we still seeing this kind of article about Open Badges and digital credentials?

“We do have a little bit of a Wild West situation right now with alternative credentials,” said Alana Dunagan, a senior research fellow at the nonprofit Clayton Christensen Institute, which researches education innovation. The U.S. higher education system “doesn’t do a good job of separating the wheat from the chaff.”

You’d think by now we’d realise that we have a huge opportunity to do something different here and not just replicate the existing system. Let’s credential stuff that matters rather than some ridiculous notion of ’employability skills’. Open Badges and digital credentials shouldn’t be just another stick to beat educational institutions.

Nor do they need to be ‘standardised’. Another person’s ‘wild west’ is another person’s landscape of huge opportunity. We not living in a world of 1950s career pathways.

“Everybody is scrambling to create microcredentials or badges,” Cheney said. “This has never been a precise marketplace, and we’re just speeding up that imprecision.”

Arizona State University, for example, is rapidly increasing the number of online courses in its continuing and professional education division, which confers both badges and certificates. According to staff, the division offers 200 courses and programs in a slew of categories, including art, history, education, health and law, and plans to provide more than 500 by next year.

My eyes are rolling out of my head at this point. Thankfully, I’ve already written about misguided notions around ‘quality’ and ‘rigour’, as well thinking through in a bit more detail what earning a ‘credential’ actually means.

Source: The Hechinger Report

How do people learn?

I was looking forward to digging into a new book from the US National Academies Press, which is freely downloadable in return for a (fake?) email address:

There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy.

In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom.

Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments.

How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.

Thankfully, Stephen Downes has created a slide-based overview of the key points for easier consumption!

How People Learn from Stephen Downes

It would have been great if he’d used different images rather than the same one on every slide, but it’s still helpful.
 
Source: National Academies / OLDaily

Why badge endorsement is a game-changer

Since starting work with Moodle, I’ve been advocating for upgrading its Open Badges implementation to v2.0. It’s on the horizon, thankfully. The reason I’m particularly interested in this is endorsement, the value of which is explained in a post by Don Presant:

What’s so exciting about Endorsement, you may ask. Well, for one thing, it promises to resolve recurring questions about the “credibility of badges” by providing third party validation that can be formal (like accreditation) or informal (“fits our purpose”). Endorsement can also strengthen collaboration, increase portability and encourage the development of meaningful badge ecosystems.

I’ve known Don for a number of years and have been consistently impressed by combination of idealism and pragmatism. He provides a version of Open Badge Factory in Canada called ‘CanCred’ and, under these auspices, is working on a project around a Humanitarian Passport.

Endorsement of organisations is now being embedded into the DNA of HPass, the international humanitarian skills recognition network now in piloting, scheduled for public launch in early 2019. Organisations who can demonstrate audited compliance with the HPass Standards for Learning or Assessment Providers will become “HPass Approved” on the system, a form of accreditation that will be signposted with Endorsement metadata baked into their badges and a distinctive visual quality mark they can display on their badge images. This is an example of a formal “accreditation-like” endorsement, but HPass badges can also be endorsed informally by peer organisations.

The ultimate aim of alternative credentialing such as Open Badges is recognition, and I think that the ability to endorse badges is a big step forward towards that.

Source: Open Badge Factory

The Digital Knowledge Loop

I’ve featured the work of Albert Wenger a few times before on Thought Shrapnel. He maintains a blog called Continuations and is writing a book called World After Capital.

In this post, he expands on a point he makes in his book around the ‘Digital Feedback Loop’ which, Wenger says, has three components:

  1. Economic freedom. We must let everyone meet their basic needs without being forced into the Job Loop. With economic freedom, we can embrace automation and enable everyone to participate in and benefit from the Digital Knowledge Loop.
  2. Informational freedom. We must remove barriers from the Digital Knowledge Loop that artificially limit learning from existing knowledge, creating new knowledge based on what we learn and sharing this new knowledge. At the same time must build systems that support the operation of critical inquiry in the Digital Knowledge Loop.
  3. Psychological freedom. We must free ourselves from scarcity thinking and its associated fears and other emotional reactions that impede our participation in the Digital Knowledge Loop. Much of the peril of the Digital Knowledge Loop arises directly from a lack of psychological freedom.

Wenger is a venture capitalist, albeit a seemingly-enlightened one. Interestingly, he’s approaching the post-scarcity world through the lens of knowledge, economics, and society. As educators, I think we need to be thinking about similar things.

In fact, this reminds me of some work Martin Weller at the Open University has done around a pedagogy of abundance. After reviewing the effect of the ‘abundance’ model in the digital marketplace, looks at what that means for education. He concludes:

The issue for educators is twofold I would suggest: firstly how can they best take
advantage of abundance in their own teaching practice, and secondly how do we best equip learners to make use of it? It is this second challenge that is perhaps the most significant. There is often consideration given to  transferable or key skills in
education (eg Dearing 1997), but these have not been revisited to take into account
the significant change that abundant and free content offers to learners… Coping with abundance then is a key issue for higher education, and one which as yet, it has not made explicit steps to meet, but as with many industries, adopting a  response which attempts to reinstate scarcity would seem to be a doomed enterprise.

Yesterday, during a break in our MoodleNet workshop with Outlandish, we were talking about the The Up Series of documentaries that showed just how much of a conveyer belt there is for children born into British society. I think part of the problem around that is we’re locked into outdated models, as Wenger and Weller point out in their respective work.

My children, for example, with a few minor updates, are experiencing the very same state education I received a quarter of a century ago. The world has moved on, yet the mindset of scarcity remains. They’re not going to have a job for life. They don’t need to selfishly hold onto their ‘intellectual property’. And they certainly don’t need to learn how to sit still within a behaviourist classroom.

Source: Continuations

The rise and rise of e-sports

I wouldn’t even have bothered clicking on this article if it weren’t for one simple fact: my son can’t get enough of this guy’s YouTube channel.

If you haven’t heard of Ninja, ask the nearest 12-year-old. He shot to fame in March after he and Drake played Fortnite, the video game phenomenon in which 100 players are dropped onto an island and battle to be the last one standing while building forts that are used to both attack and hide from opponents. At its peak, Ninja and Drake’s game, which also featured rapper Travis Scott and Pittsburgh Steelers receiver JuJu Smith-Schuster, pulled in 630,000 concurrent viewers on Twitch, Amazon’s livestreaming platform, shattering the previous record of 388,000. Since then, Ninja has achieved what no other gamer has before: mainstream fame. With 11 million Twitch followers and climbing, he commands an audience few can dream of. In April, he logged the most social media interactions in the entire sports world, beating out the likes of Cristiano Ronaldo, Shaquille O’Neal and Neymar.

This article in ESPN is testament to the work that Ninja (a.k.a. Tyler Blevins) has done in crafting a brand and putting in the hours for over a decade. It sounds gruelling:

Tyler can’t join us until he wraps up his six-hour stream. In the basement, past a well-stocked bar, a pool table and a dartboard, next to a foosball table, he sits on this sunny August day in a T-shirt and plaid pajama pants at the most famous space in their house, his gaming setup. It doesn’t look like much — a couple of screens, a fridge full of Red Bull, a mess of wires — but from this modest corner he makes millions by captivating millions.

[…]

In college, Jess [his wife] started streaming to better understand why Tyler would go hours without replying to her texts. A day in, she realized how consuming it was. “It’s physically exhausting but also mentally because you’re sitting there constantly interacting,” Tyler says. “I’m engaging a lot more senses than if I were just gaming by myself. We’re not sitting there doing nothing. I don’t think anyone gets that.”

The reason for sharing this here is because I’m going to use this as an example of deliberate practice.

How does he stay so good? Pro tip: Don’t just play, practice. Ninja competes in about 50 games a day, and he analyzes each and every one. He never gets tired of it, and every loss hits him hard. Hypercompetitive, he makes sure he walks away with at least one win each day. (He averages about 15 and once got 29 in a single day.)

“When I die, I get so upset,” he says. “You can play every single day, you’re not practicing. You die, and oh well, you go onto the next game. When you’re practicing, you’re taking every single match seriously, so you don’t have an excuse when you die. You’re like, ‘I should have rotated here, I should have pushed there, I should have backed off.’ A lot of people don’t do that.”

The article is worth a read, for several reasons. It shows why e-sports are going to be even bigger than regular sports for my children’s generation. It demonstrates how to get to the top in anything you have to put in the time and effort. And, perhaps, above all, it shows that, just as I’ve found, growing up spending time in front of screens can be pretty lucrative.

Source: ESPN

Fluency without conceptual understanding

I’ve been following Dan Meyer’s work on-and-off for over a decade now. He’s a Maths teacher by trade, but now working as Chief Academic Officer at Desmos after gaining his PhD from Stanford. He’s a smart guy, and a great blogger.

Dan’s particularly interested in how kids learn Maths (or ‘Math’ because he’s American) and is always particularly concerned to disprove/squash approaches that don’t work:

In the wake of Barbara Oakley’s op-ed in the New York Times arguing that we overemphasize conceptual understanding in math class, it’s become clear to me that our national conversation about math instruction is missing at least one crucial element: nobody knows what anybody means by “conceptual understanding.”

It’s worth reading the whole post (and the comment section), but I just wanted to pull out a couple of things which I think are useful:

A student who has procedural fluency but lacks conceptual understanding …

  • Can accurately subtract 2018-1999 using a standard algorithm, but doesn’t recognize that counting up would be more efficient.
  • Can accurately compute the area of a triangle, but doesn’t recognize how its formula was derived or how it can be extended to other shapes. (eg. trapezoids, parallelograms, etc.)
  • Can accurately calculate the discriminant of y = x2 + 2 to determine that it doesn’t have any real roots, but couldn’t draw a quick sketch of the parabola to figure that out more efficiently.

I find this all the time with my own kids, and also when I was teaching. For example, I knew that the students in my Year 7 History class could draw a line graph in Maths, but they didn’t seem to be able to do it in my classroom for some reason. In other words, they were ‘procedurally fluent’ in a particular domain.

Children are very good at giving the impression to adults that they understand and can do what they’re being told to do. Poke a little, and you come to realise that they don’t really understand what’s going on. That’s particularly true in History, where it’s easy to regurgitate facts and dates, without any empathy or historical understanding.

Another thing that Dan points out which I think we should all take to heart is that we should learn a bit of humility. He criticises both Barbara Oakley (op-ed in The New York Times) and Paul Morgan (author of an article with which he disagrees for not having what Nassim Nicholas Taleb would call ‘skin in the game‘:

If you’re going to engage with the ideas of a complex field, engage with its best. That’s good practice for all of us and it’s especially good practice for people who are commenting from outside the field like Oakley (trained in engineering) and Morgan (trained in education policy).

Everyone’s got opinions. The important thing is to listen to those who are talking sense.

Source: dy/dan

Intimate data analytics in education

The ever-relevant and compulsively-readable Ben Williamson turns his attention to ‘precision education’ in his latest post. It would seem that now that the phrase ‘personalised learning’ has jumped the proverbial shark, people are doubling down on the rather dangerous assumption that we just need more data to provide better learning experiences.

In some ways, precision education looks a lot like a raft of other personalized learning practices and platform developments that have taken shape over the past few years. Driven by developments in learning analytics and adaptive learning technologies, personalized learning has become the dominant focus of the educational technology industry and the main priority for philanthropic funders such as Bill Gates and Mark Zuckerberg.

[…]

A particularly important aspect of precision education as it is being advocated by others, however, is its scientific basis. Whereas most personalized learning platforms tend to focus on analysing student progress and outcomes, precision education requires much more intimate data to be collected from students. Precision education represents a shift from the collection of assessment-type data about educational outcomes, to the generation of data about the intimate interior details of students’ genetic make-up, their psychological characteristics, and their neural functioning.

As Williamson points out, the collection of ‘intimate data’ is particularly concerning, particularly in the wake of the Cambridge Analytica revelations.

Many people will find the ideas behind precision education seriously concerning. For a start, there appear to be some alarming symmetries between the logics of targeted learning and targeted advertising that have generated heated public and media attention already in 2018. Data protection and privacy are obvious risks when data are collected about people’s private, intimate and interior lives, bodies and brains. The ethical stakes in using genetics, neural information and psychological profiles to target students with differentiated learning inputs are significant.

There’s a very definite worldview which presupposes that we just need to throw more technology at a problem until it goes away. That may be true in some situations, but at what cost? And to what extent is the outcome an artefact of the constraints of the technologies? Hopefully my own kids will be finished school before this kind of nonsense becomes mainstream. I do, however, worry about my grandchildren.

The technical machinery alone required for precision education would be vast. It would have to include neurotechnologies for gathering brain data, such as neuroheadsets for EEG monitoring. It would require new kinds of tests, such as those of personality and noncognitive skills, as well as real-time analytics programs of the kind promoted by personalized-learning enthusiasts. Gathering intimate data might also require genetics testing technologies, and perhaps wearable-enhanced learning devices for capturing real-time data from students’ bodies as proxy psychometric measures of their responses to learning inputs and materials.

Thankfully, Williamson cites the work of academics who are proposing a different way forward. Something that respects the social aspect of learning rather than a reductionist view that focuses on inputs and outputs.

One productive way forward might be to approach precision education from a ‘biosocial’ perspective. As Deborah Youdell  argues, learning may be best understood as the result of ‘social and biological entanglements.’ She advocates collaborative, inter-disciplinary research across social and biological sciences to understand learning processes as the dynamic outcomes of biological, genetic and neural factors combined with socially and culturally embedded interactions and meaning-making processes. A variety of biological and neuroscientific ideas are being developed in education, too, making policy and practice more bio-inspired.

The trouble is, of course, is that it’s not enough for academics to write papers about things. Or even journalists to write newspaper articles. Even with all of the firestorm over Facebook recently, people are still using the platform. If the advocates of ‘precision education’  have their way, I wonder who will actually create something meaningful that opposes their technocratic worldview?

Source: Code Acts in Education

Sounds and smells can help reinforce learning while you sleep

Apparently, the idea of learning while you sleep is actually bollocks, at least the way we have come to believe it works:

It wasn’t until the 1950s that researchers discovered the touted effects of hypnopaedia were actually not due to sleep at all. Instead these contraptions were actually awakening people. The debunkers could tell by using a relatively established technique called electroencephalography (EEG), which records the brain’s electrical signals through electrodes placed on the scalp. Using EEG on their participants, researchers could tell that the sleep-learners were actually awake (something we still do in research today), and this all but ended research into sleep as a cognitive tool. 50 years later, we now know it is possible to alter memory during sleep, just in a different way than previously expected.

However, and fascinatingly, sounds (not words) and smells can reinforce learning:

In 2007, the neuroscientist Björn Rasch at Lübeck University and colleagues reported that smells, which were associated with previously learned material, could be used to cue the sleeping brain. The study authors had taught participants the locations of objects on a grid, just like in the game Concentration, and exposed them to the odour of roses as they did so. Next, participants slept in the lab, and the experimenters waited until the deepest stage of sleep (slow-wave sleep) to once again expose them to the odour. Then when they were awake, the participants were significantly better at remembering where the objects were located. This worked only if they had been exposed to the rose odour during learning, and had smelled it during slow-wave sleep. If they were exposed to the odour only while awake or during REM sleep, the cue didn’t work.

Pretty awesome. There are some things still to research:

Outstanding questions that we have yet to address include: does this work for foreign-language learning (ie, grammar learning), or just learning foreign vocabulary? Could it be used to help maintain memory performance in an ageing population? Does reactivating some memories mean that others are wiped away even more quickly?

Worth trying!

Source: Aeon