Category: Education systems (page 1 of 2)

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

Charity is no substitute for justice

The always-brilliant Audrey Watters eviscerates the latest project from a white, male billionaire to ‘fix education’. Citing Amazon CEO Jeff Bezos’ plan to open a series of “Montessori-inspired preschools in underserved communities” where “the child will be the customer”, Audrey comments:

The assurance that “the child will be the customer” underscores the belief – shared by many in and out of education reform and education technology – that education is simply a transaction: an individual’s decision-making in a “marketplace of ideas.” (There is no community, no public responsibility, no larger civic impulse for early childhood education here. It’s all about privateschools offering private, individual benefits.)

As I’ve said on many occasions, everyone wakes up with cool ideas to change the world. The difference is that you or I would have to run it through many, many filters to get the funding to implement it. Those filters , hopefully, kill 99% of batshit-crazy ideas. Billionaires, in the other hand, can just speak and fund things into existence, no matter how damaging and I’ll thought-out the ideas behind them happen to be.

[Teaching] is a field in which a third of employeesalready qualify for government assistance. And now Jeff Bezos, a man whose own workers also rely on these same low-income programs, wants to step in – not as a taxpayer, oh no, but as a philanthropist. Honestly, he could have a more positive impact here by just giving those workers a raise. (Or, you know, by paying taxes.)

This is the thing. We can do more and better together than we can do apart. The ideas of the many, honed over years, lead to better outcomes than the few thinking alone.

For all the flaws in the public school system, it’s important to remember: there is no accountability in billionaires’ educational philanthropy.

And, as W. B. Yeats famously never said, charity is no substitute for justice.

Whatever your moral and political views, accountability is something that cuts across the divide. I should imagine there are some reading this who send their kids to private schools and don’t particularly see the problem with this. Isn’t it just another example of competition within ‘the market’?

The trouble with that kind of thinking, at least from my perspective, is twofold. First, it assumes that education is a private instead of a public good. Second, that it’s OK to withhold money from society and then use that to subsidise the education of the already-privileged.

Source: Hack Education

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

Higher Education and blockchain

I’ve said it before, and I’ll say it again: the most useful applications of blockchain technologies are incredibly boring. That goes in education, too.

This post by Chris Fellingham considers blockchain in the context of Higher Education, and in particular credentialing:

The short pitch is that as jobs and education go digital, we need digital credentials for our education and those need to be trustworthy and automisable. Decentralised trust systems may well be the future but I don’t see that it solves a core problem. Namely that the main premium market for Higher Education Edtech is geared twards graduates in developed countries and that market — does not have a problem of trust in its credentials — it has a problem of credibility in its courses. People don’t know what it means to have done a MOOC/Specialization/MicroMasters in X which undermines the market system for it. Shoring up the credential is a second order problem to proving the intrinsic value of the course itself.

“Decentralised trust systems” is what blockchain aficionados refer to, but what they actually mean is removing trust from the equation. So, in hiring decisions, for example, trust is removed from the equation in favour of cryptographic proof.

Fellingham mentions someone called ‘Smolenski’ who, after a little bit of digging, must be Natalie Smolenski, who works for Learning Machine. That organisation is a driving force, with MIT, behind the Blockcerts standard for blockchain-based digital credentialing.

Smolenski however, is a believer, and in numerous elegant essays has argued blockchain is the latest paradigm shift in trust-based technologies. The thesis puts trust based technologies as a central driver of human development. Kinship was the first ‘trust technology’, followed by language and cultural development. Things really got going with organised religion which was the early modern driver — enabling proto-legal systems and financial systems to emerge. Total strangers could now conduct economic transactions by putting their trust in local laws (a mutually understand system for transactions) in the knowledge that it would be enforced by a trusted third party — the state. Out of this emerged market economies and currencies.

Like Fellingham, I’m not particularly enamoured with this teleological ‘grand narrative’ approach to history, of which blockchain believers do tend to be overly-fond. I’m pretty sure that human history hasn’t been ‘building’ in any way towards anything, particularly something that involves less trust between human beings.

Blockchain at this moment is a kind of religion. It’s based on a hope of things to come:

Blockchain — be it in credential or currency form …could well be a major — if not paradigmatic technology — but it has its own logic and fundamentally suits those who use it best — much as social networks turned out to be fertile grounds for fake news. For that reason alone, we should be far more cautious about a shift to blockchain in Higher Education — lest like fake news — it takes an imperfect system and makes it worse.

Indeed. Who on earth would want wants to hard code the way things are right now in Higher Education? If your answer is ‘blockchain-based credentials’, then I’m not sure you really understand what the question is.

Source: Chris Fellingham (via Stephen Downes)

On ‘academic innovation’

Rolin Moe is in a good position to talk on the topic of ‘academic innovation’. In fact, it’s literally in his job title: ‘Assistant professor and Director of the Institute for Academic Innovation at Seattle Pacific University”.

Moe warns, however, that it’s not necessarily a great idea to create a new discipline out of academic innovation. Until fairly recently, being ‘innovative’ was a negative slur, something that could get you in some serious trouble if you were found guilty.

[T]he historical usage of innovation is not as a foundational platform but a superficial label; yet in 2018 the governing bodies of societal institutions wield “innovation” in setting forth policy, administration and funding. Innovation, a term we all know but do not have a conceptual framework for, is driving change and growth in education. As regularly used without context, innovation is positioned as the future out-of-the-box solution for the problems of the present.

This makes the term a conduit of power relationships despite many proponents of innovation serving as vocal advocates for diversity, equity and inclusion in higher education. Thinking about revenue shortfalls in a time of national economic prosperity, the extraction of arts and humanities programs at a time when industry demands critical thinking from graduates, and the positioning of online learning as a democratizing tool when research shows the greatest benefit is to populations of existing privilege, the solutions offered under the innovation mantle have at best affected symptoms, at worst perpetuated causes.

Words and terms, of course, change over time. But, as Moe points out, if we’re to update the definition of innovation, we need a common understanding of what it means.

Coalescing around a common understanding is vital for the growth of “academic innovation,” but the history of innovation makes this concept problematic. Some have argued that innovation binds together disciplines such as learning technologies, leadership and change, and industrial/organizational psychology.

However, this cohesion assumes a “shared language of inquiry,” which does not currently exist. Today’s shared language around innovation is emotive rather than procedural; we use innovation to highlight the desired positive results of our efforts rather than to identify anything specific about our effort (products, processes or policies). The predominant use of innovation is to highlight the value and future-readiness of whatever the speaker supports, which is why opposite sides of issues in education (see school choice, personalized learning, etc.) use innovation in promoting their ideologies.

It seems to me that the neoliberal agenda has invaded education, as it does with any uncommodified available space, and introduced the language of the market. So we get educators using the language of Silicon Valley and attempting to ‘disrupt’ their institution.

If the goal of academic innovation is to be creative and flexible in the development, discovery and engagement of knowledge about the future of education, the foundation for knowledge accumulation and development needs to be innovative in and of itself. That must start with an operational definition of academic innovation, differentiating what innovation means to education from what it means to entrepreneurial spaces or sociological efforts.

That definition must address the negotiated history of the term, from the earliest application of the concept in government-funded research spurred by education policy during the 1960s, through overlooked innovation authors like Freeman and Thorstein Veblen. Negotiating the future we want with the history we have is vital in order to determine the best structure to support the development of an inventive network for creating research-backed, criticism-engaged and outside-the-box approaches to the future of education. The energy behind what we today call academic innovation needs to be put toward problematizing and unraveling the causes of the obstacles facing the practice of educating people of competence and character, rather than focusing on the promotion of near-future technologies and their effect on symptomatic issues.

While I’m sympathetic to the idea that educational institutions can be ‘stodgy’ places that can often need a good kick up the behind, I’m not entirely sure that academic innovation as a discipline will do anything other than legitimise the capitalist takeover of a public good.

Source: Inside Higher Ed (via Aaron Davis)

Getting on the edtech bus

As many people will be aware, the Open University (OU) is going through a pretty turbulent time in its history. As befitting the nature of the institution, a lot of conversations about its future are happening in public spaces.

Martin Weller, a professor at the university, has been vocal. In this post, a response to a keynote from Tony Bates, he offers a way forward.

I would like to… propose a new role: Sensible Ed Tech Advisor. Job role is as follows:

  • Ability to offer practical advice on adoption of ed tech that will benefit learners
  • Strong BS detector for ed tech hype
  • Interpreter of developing trends for particular context
  • Understanding of the intersection of tech and academic culture
  • Communicating benefits of any particular tech in terms that are valuable to educators and learners
  • Appreciation of ethical and social impact of ed tech

(Lest that sound like I’m creating a job description for myself, I didn’t add “interest in ice hockey” at the end, so you can tell that it isn’t)

Weller notes that Bates mentioned in his his post-keynote write-up that the OU has a “fixation on print as the ‘core’ medium/technology”. He doesn’t think that’s correct.

I’m interested in this, because the view of an institution is formed not only by the people inside it, but by the press and those who have an opinion and an audience. Weller accuses Bates of being woefully out of date. I think he’s correct to call him out on it, as I’ve witnessed recently a whole host of middle-aged white guys lazily referencing things in presentations they haven’t bothered to research very well.

 It is certainly true that some disciplines do have a print preference, and Tony is correct to say that often a print mentality is transferred to online. But what this outdated view (it was probably true 10-15 years ago) suggests is a ‘get digital or else’ mentality. Rather, I would argue, we need to acknowledge the very good digital foundation we have, but find ways to innovate on top of this.

If you are fighting an imaginary analogue beast, then this becomes difficult. For instance, Tony does rightly highlight how we don’t make enough use of social media to support students, but then ignores that there are pockets of very good practice, for example the OU PG Education account and the use of social media in the Cisco courses. Rolling these out across the university is not simple, but it is the type of project that we know how to realise. But by framing the problem as one of wholesale structural, cultural change starting from a zero base, it makes achieving practical, implementable projects difficult. You can’t do that small(ish) thing until we’ve done these twenty big things.

We seem to be living at a time when those who were massive, uncritical boosters of technology in education (and society in general) are realising the errors of their ways. I actually wouldn’t count Weller as an uncritical booster, but I welcome the fact that he is self-deprecating enough to include himself in that crowd.

I would also suggest that the sort of “get on the ed tech bus or else” argument that Tony puts forward is outdated, and ineffective (I’ve been guilty of it myself in the past). And as Audrey Watters highlights tirelessly, an unsceptical approach to ed tech is problematic for many reasons. Far more useful is to focus on specific problems staff have, or things they want to realise, than suggest they just ‘don’t get it’. Having an appreciation for this intersection between ed tech (coming from outside the institution and discipline often) and the internal values and culture is also an essential ingredient in implementing any technology successfully.

This is a particularly interesting time in the history of technology in education and society. I’m glad that conversations like this are happening in the open.

Source: Martin Weller

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

The four things you need to become an intellectual

I came across this, I think, via one of the aggregation sites I skim. It’s a letter in the form of an article by Paul J. Griffiths, who is a Professor of Catholic Theology at Duke Divinity School. In it, he replies to a student who has asked how to become an intellectual.

Griffiths breaks it down into four requirements, and then at the end gives a warning.

The first requirement is that you find something to think about. This may be easy to arrive at, or almost impossibly difficult. It’s something like falling in love. There’s an infinite number of topics you might think about, just as there’s an almost infinite number of people you might fall in love with. But in neither case is the choice made by consulting all possibilities and choosing among them. You can only love what you see, and what you see is given, in large part, by location and chance.

There’s a tension here, isn’t there? Given the almost infinite multiplicity of things it’s possible to spend life thinking about and concentrating upon, how does one choose between them? Griffiths mentions the role of location and chance, but I’d also through in tendencies. If you notice yourself liking a particular style of art, captivated by a certain style of writing, or enthralled by a way of approaching the world, this may be a clue that you should investigate it further.

The second requirement is time: You need a life in which you can spend a minimum of three uninterrupted hours every day, excepting sabbaths and occasional vacations, on your intellectual work. Those hours need to be free from distractions: no telephone calls, no email, no texts, no visits. Just you. Just thinking and whatever serves as a direct aid to and support of thinking (reading, writing, experiment, etc.). Nothing else. You need this because intellectual work is, typically, cumulative and has momentum. It doesn’t leap from one eureka moment to the next, even though there may be such moments in your life if you’re fortunate. No, it builds slowly from one day to the next, one month to the next. Whatever it is you’re thinking about will demand of you that you think about it a lot and for a long time, and you won’t be able to do that if you’re distracted from moment to moment, or if you allow long gaps between one session of work and the next. Undistracted time is the space in which intellectual work is done: It’s the space for that work in the same way that the factory floor is the space for the assembly line.

This chimes with a quotation from Mark Manson I referenced yesterday, in which he talks about the joy you feel and meaning you experience when you’ve spent decades dedicated to one thing in particular. You have to carve out time for that, whether through your occupation, or through putting aside leisure time to pursue it.

The third requirement is training. Once you know what you want to think about, you need to learn whatever skills are necessary for good thinking about it, and whatever body of knowledge is requisite for such thinking. These days we tend to think of this as requiring university studies.

[…]

The most essential skill is surprisingly hard to come by. That skill is attention. Intellectuals always think about something, and that means they need to know how to attend to what they’re thinking about. Attention can be thought of as a long, slow, surprised gaze at whatever it is.

[…]

The long, slow, surprised gaze requires cultivation. We’re quickly and easily habituated, with the result that once we’ve seen something a few times it comes to seem unsurprising, and if it’s neither threatening nor useful it rapidly becomes invisible. There are many reasons for this (the necessities of survival; the fact of the Fall), but whatever a full account of those might be (“full account” being itself a matter for thinking about), their result is that we can’t easily attend.

This section was difficult to quote as it weaves in specific details from the original student’s letter, but the gist is that people assume that universities are good places for intellectual pursuits. Griffiths responds that this may or may not be the case, and, in fact, is less likely to be true as the 21st century progresses.

Instead, we need to cultivate attention, which he describes as being almost like a muscle. Griffiths suggests “intentionally engaging in repetitive activity” such as “practicing a musical instrument, attending Mass daily, meditating on the rhythms of your breath, taking the same walk every day (Kant in Königsberg)” to “foster attentiveness”.

[The] fourth requirement is interlocutors. You can’t develop the needed skills or appropriate the needed body of knowledge without them. You can’t do it by yourself. Solitude and loneliness, yes, very well; but that solitude must grow out of and continually be nourished by conversation with others who’ve thought and are thinking about what you’re thinking about. Those are your interlocutors. They may be dead, in which case they’ll be available to you in their postmortem traces: written texts, recordings, reports by others, and so on. Or they may be living, in which case you may benefit from face-to-face interactions, whether public or private. But in either case, you need them. You can neither decide what to think about nor learn to think about it well without getting the right training, and the best training is to be had by apprenticeship: Observe the work—or the traces of the work—of those who’ve done what you’d like to do; try to discriminate good instances of such work from less good; and then be formed by imitation.

I talked in my thesis about the impossibility of being ‘literate’ unless you’ve got a community in which to engage in literate practices. The same is true of intellectual activity: you can’t be an intellectual in a vacuum.

As a society, we worship at the altar of the lone genius but, in fact, that idea is fundamentally flawed. Progress and breakthroughs come through discussion and collaboration, not sitting in a darkened room by yourself with a wet tea-towel over your head, thinking very hard.

Interestingly, and importantly, Griffiths points out to the student to whom he’s replying that the life of an intellectual might seem attractive, but that it’s a long, hard road.

And lastly: Don’t do any of the things I’ve recommended unless it seems to you that you must. The world doesn’t need many intellectuals. Most people have neither the talent nor the taste for intellectual work, and most that is admirable and good about human life (love, self-sacrifice, justice, passion, martyrdom, hope) has little or nothing to do with what intellectuals do. Intellectual skill, and even intellectual greatness, is as likely to be accompanied by moral vice as moral virtue. And the world—certainly the American world—has little interest in and few rewards for intellectuals. The life of an intellectual is lonely, hard, and usually penurious; don’t undertake it if you hope for better than that. Don’t undertake it if you think the intellectual vocation the most important there is: It isn’t. Don’t undertake it if you have the least tincture in you of contempt or pity for those without intellectual talents: You shouldn’t. Don’t undertake it if you think it will make you a better person: It won’t. Undertake it if, and only if, nothing else seems possible.

A long read, but a rewarding one.

Source: First Things

Teaching kids about computers and coding

Not only is Hacker News a great place to find the latest news about tech-related stuff, it’s also got some interesting ‘Ask HN’ threads sourcing recommendations from the community.

This particular one starts with a user posing the question:

Ask HN: How do you teach you kids about computers and coding?

Please share what tools & approaches you use – it may Scratch, Python, any kids specific like Linux distros, Raspberry Pi or recent products like Lego Boost… Or your experiences with them.. thanks.

Like sites such as Reddit and Stack Overflow, responses are voted up based on their usefulness. The most-upvoted response was this one:

My daughter is almost 5 and she picked up Scratch Jr in ten minutes. I am writing my suggestions mostly from the context of a younger child.

I approached it this way, I bought a book on Scratch Jr so I could get up to speed on it. I walked her through a few of the basics, and then I just let her take over after that.

One other programming related activity we have done is the Learning Resources Code & Go Robot Mouse Activity. She has a lot of fun with this as you have a small mouse you program with simple directions to navigate a maze to find the cheese. It uses a set of cards to help then grasp the steps needed. I switch to not using the cards after a while. We now just step the mouse through the maze manually adding steps as we go.

One other activity to consider is the robot turtles board game. This teaches some basic logic concepts needed in programming.

For an older child, I did help my nephew to learn programming in Python when he was a freshman in high school. I took the approach of having him type in games from the free Python book. I have always though this was a good approach for older kids to get the familiar with the syntax.

Something else I would consider would be a robot that can be programmer with Scratch. While I have not done this yet, I think for kid seeing the physical results of programming via a robot is a powerful way to capture interest.

But I think my favourite response is this one:

What age range are we talking about? For most kids aged 6-12 writing code is too abstract to start with. For my kids, I started making really simple projects with a Makey Makey. After that, I taught them the basics with Scratch, since there are tons of fun tutorials for kids. Right now, I’m building a Raspberry Pi-powered robot with my 10yo (basically it’s a poor man’s Lego Mindstorm).

The key is fun. The focus is much more on ‘building something together’ than ‘I’ll learn you how to code’. I’m pretty sure that if I were to press them into learning how to code it will only put them off. Sometimes we go for weeks without building on the robot, and all of the sudden she will ask me to work on it with her again.

My son is sailing through his Computer Science classes at school because of some webmaking and ‘coding’ stuff we did when he was younger. He’s seldom interested, however, if I want to break out the Raspberry Pi and have a play.

At the end of the day, it’s meeting them where they’re at. If they show an interest, run with it!

Source: Hacker News