ENTRIES TAGGED "learning"
Use teaching stacks to drive growth.
Elliott Hauser is CEO of Trinket, a startup focused on creating open sourced teaching materials. He is also a Python instructor at UNC Chapel Hill.
Well-developed tools for teaching are crucial to the spread of open source software and programming languages. Stacks like those used by the Young Coders Tutorial and Mozilla Software Carpentry are having national and international impact by enabling more people to teach more often.
The spread of tech depends on teaching
Software won’t replace teachers. But teachers need great software for teaching. The success and growth of technical communities are largely dependent on the availability of teaching stacks appropriate to teaching their technologies. Resources like try git or interactivepython.org not only help students on their own but also equip instructors to teach these topics without also having to discover the best tools for doing so. In that way, they play the same function as open source Web stacks: getting us up and running quickly with time-tested and community-backed tools. Thank goodness I don’t need to write a database just to write a website; I can use open source software instead. As an instructor teaching others to code websites, what’s the equivalent tool set? That’s what I mean by Teaching Stack: a collection of open tools that help individual instructors teach technology at scale.
Elements of a great teaching stack
Here are some of the major components of a teaching stack for a hands-on technology course:
Can Elixir bring functional programming to a much wider audience?
I was delighted to talk with Dave Thomas, co-founder of the The Pragmatic Programmers and author of their in-progress Programming Elixir. I’m writing Introducing Elixir for O’Reilly, and we both seem to be enjoying the progress of the language. Read more…
Simon St. Laurent and Jose Valim explore a new functional programming language
I was delighted to sit down with Jose Valim, the creator of Elixir, earlier this month at Erlang Factory. He and Dave Thomas had just given a brave keynote exploring the barriers that keep people from taking advantage of Erlang’s many superpowers, challenging the audience with reminders that a programming environment must have reach as well as power to change the world.
Elixir itself is a bold effort to bring Erlang’s strengths to a broader group of developers, adding new strengths, notably metaprogramming, along the way.
Whether you’re interested in Elixir itself or just in the challenges of creating a new combination in a world filled with past experiments, it’s well worth listening to Jose Valim.
- We’ve had functional programming since 1959 – why the burst of interest now? [2:10]
- Moving from Ruby to Erlang “making Rails thread-safe, that was my personal pain-point” [3:13]
- “Every time I got to study more about the VM, the tooling and everything it provides, my mind gets blown.” [6:12]
- Why Elixir started, and how it’s changed as Jose learned more. [10:08]
- Integrating new Erlang features (R17 maps) into Elixir. [15:43]
- When can you use Elixir in production? [18:07]
I’m looking forward to seeing a lot more Elixir, even as I need to catch up on updating Introducing Elixir. I’m not sure it will conquer the world immediately, but it will certainly leave its mark.
CSS already making Web code more approachable
Last week, I wrote about the need to make programming, at least much programming, more accessible. I was thinking in terms of business processes, so spreadsheets and flow-based programming sprang to mind. Today, though, Jeremy Keith reminds me that on the Web, we already have much of that world in Cascading Style Sheets (CSS).
There are a lot of really powerful programmatic concepts that we could add to CSS, all of which would certainly make it a more powerful language. But I think that power would come at an expense.
Right now, CSS is a relatively-straightforward language.
I suspect some readers are scratching their heads, wondering why CSS is even being considered a language, much less why adding programming features to it would be a bad thing. If you think of CSS as a simple object-manipulation language, though, it fits pretty neatly into the sweet spot I described last week.
Teaching Future Coders
Ever since PyCon 2013, the interest in the Young Coders class has been intensifying. Practically every Python conference since then has asked about doing one, and several have run their own. Classes outside of conferences have sprung up, as well, from one time workshops to after school clubs.
As more classes happen, more people have been asking about running their own. These classes do take quite a bit of effort to set up, but the payoff is enormous. Also, once you do one, doing subsequent ones gets easier and easier.
A few iterations make even functional programming digestible
Programming gets easier and easier as you do more of it. Languages and logic become familiar, in ways that extend from looking up less and less all the way to muscle memory in your typing. The first few iterations in a new language are often difficult, as everything seems odd. Shifting not just to new languages but to new approaches makes practice even more important.
One of my worst features has been that I never liked to practice. I understood rehearsing, working together in a group, but practicing? Exercises, especially for the sake of exercise, were never my thing. That character flaw has hobbled my writing. I can come up with examples for books, focusing tightly on an issue I’m explaining. But then, really? I have to ask readers to go solve a particular (already solved) problem?
I’m not alone in this—too many writers have inflicted that attitude on their readers. Exploring sample code is not the same as writing your own code. Miguel de Icaza points out that:
When you finish a chapter in a modern computing book, there are no exercises to try. When you finish it, your choices are to either take a break by checking some blogs or keep marching in a quest to collect more facts on the next chapter.
During this process, while you amass a bunch of information, at some neurological level, you have not really mastered the subject, nor gained the skills that you wanted.
We can fix this.
If we want kids to aspire to become scientists and technologists, celebrate academic achievement like athletics and celebrity.
There are few ways to better judge a nation’s character than to look at how its children are educated. What values do their parents, teachers and mentors demonstrate? What accomplishments are celebrated? In a world where championship sports teams are idolized and superstar athletes are feted by the media, it was gratifying to see science, students and teachers get their moment in the sun at the White House last week.
“…one of the things that I’m concerned about is that, as a culture, we’re great consumers of technology, but we’re not always properly respecting the people who are in the labs and behind the scenes creating the stuff that we now take for granted,” said President Barack Obama, “and we’ve got to give the millions of Americans who work in science and technology not only the kind of respect they deserve but also new ways to engage young people.”
An increasingly fierce global competition for talent and natural resources has put a premium on developing scientists and engineers in the nation’s schools. (On that count, last week, the President announced a plan to promote careers in the sciences and expand federal and private-sector initiatives to encourage students to study STEM.
“America has always been about discovery, and invention, and engineering, and science and evidence,” said the President, last week. “That’s who we are. That’s in our DNA. That’s how this country became the greatest economic power in the history of the world. That’s how we’re able to provide so many contributions to people all around the world with our scientific and medical and technological discoveries.”
If data scientists aren't skeptical about how they use and analyze data, who will be?
A couple of months ago, I wrote that “big data” is heading toward the trough of a hype curve as a result of oversized hype and promises. That’s certainly true. I see more expressions of skepticism about the value of data every day. Some of the skepticism is a reaction against the hype; a lot of it arises from ignorance, and it has the same smell as the rich history of science denial from the tobacco industry (and probably much earlier) onward.
But there’s another thread of data skepticism that’s profoundly important. On her MathBabe blog, Cathy O’Neil has written several articles about lying with data — about intentionally developing models that don’t work because it’s possible to make more money from a bad model than a good one. (If you remember Mel Brooks’ classic “The Producers,” it’s the same idea.) In a slightly different vein, Cathy argues that making machine learning simple for non-experts might not be in our best interests; it’s easy to start believing answers because the computer told you so, without understanding why those answers might not correspond with reality. Read more…
Cody Lindley on finding your way through a popular and powerful language
- Don’t be down on jQuery users (at 2:03)
- Are buffers between your code and browser APIs necessary? (at 9:17)
- Running browser tests on the DOM (at 11:08)
- Needing more focused in-depth documentation (at 12:57)
His closing – “we need to do a better job communicating with the bulk of developers out there” – sounded just right to me.
You can view the entire conversation in the following video:
Steve Vinoski on when to make the leap to functional programming.
Functional programming has a long and distinguished heritage of great work — that was only used by a small group of programmers. In a world dominated by individual computers running single processors, the extra cost of thinking functionally limited its appeal. Lately, as more projects require distributed systems that must always be available, functional programming approaches suddenly look a lot more appealing.
Steve Vinoski, an architect at Basho Technologies, has been working with distributed systems and complex projects for a long time, first as a tentative explorer and then leaping across to Erlang when it seemed right. Seventeen years as a columnist on C, C++, and functional languages have given him a unique viewpoint on how developers and companies are deciding whether and how to take the plunge.
Highlights from our recent interview include: