When you’re just learning to sketch, you use graphite. Why? It’s cheap, great at training you to recognize different shades, and most of all, it’s erasable. When you’re learning, you’re going to make mistakes, and un-making them is an important part of the game. Same goes for electronics, of course, so when you’re teaching someone to solder, don’t neglect teaching them to desolder.
We could argue all day about the best ways of pressing the molten-metal undo button, but the truth is that it’s horses for courses. I’ve had really good luck with solder braid and maybe a little heat gun to pull up reluctant SOIC surface-mount chips, but nothing beats a solder sucker for clearing out a few through-holes. (I haven’t tried the questionable, but time-tested practice of blasting the joint with compressed air.)
For bulk part removal, all you really have to do is heat the board up, and there’s plenty of ways to do that, ranging from fancy to foolish. Low-temperature alloys help out in really tough cases. And for removing rows of pinheaders, it can help to add more solder along the row until it’s one molten blob, and then tap the PCB and watch the part — and hot liquid metal! — just drop out.
But the bigger point is that an important step in learning a new technique is learning to undo your mistakes. It makes it all a lot less intimidating when you know that you can just pull out the solder braid and call “do-over”. And don’t forget the flux.
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In my work for Hackaday over the years I have been privileged to interact with some of the most creative people I have ever met, I have travelled far more than I ever did when I toiled unseen in an office in Oxford, and I have been lucky enough to hang out in our community’s spaces, camps, and dives across Europe.
Among the huge diversity of skills and ideas though, it’s striking how many of us share similar experiences and histories that have caused us to find our people in rooms full of tools and 3D printers. One of these things I found surprising because I thought I was the only one; I never fit in with the other kids at school, I found much of the teaching incomprehensible and had to figure things out for myself. As an exercise recently I did a straw poll among some of my friends, and found that a significant majority had a similar experience. Clearly something must have gone badly wrong in the way we were being taught that so many of us could have been let down by our schooling, and maybe to understand the needs of our community it’s time to understand why.
Learning a new language is hard work, but they say that the best way to learn something is to teach it. [Angeliki Beyko] is learning Greek, and what better way to teach than to build a vocabulary flash-card game from Arduinos, color screens, 1602 text screens, and arcade buttons? After the break, we have a video from the creator talking about how to play, the hardware she chose, and what to expect in the next version.
Pegboard holds most of the hardware except the color screens, which are finicky when it comes to their power source. The project is like someone raided our collective junk drawers and picked out the coolest bits to make a game. Around the perimeter are over one hundred NeoPixels to display the game progress and draw people like a midway game. Once invested, you select a category on the four colored arcade buttons by looking at the adjacent LCD screens’ titles. An onboard MP3 shield reads a pseudo-random Greek word and displays it on the top-right 1602 screen in English phonetics. After that, it is multiple choice with your options displaying in full-color on four TFT monitors. A correct choice awards you a point and moves to the next word, but any excuse to mash on arcade buttons is good enough for us.
[Angeliki] does something we see more often than before, she’s covering what she learned, struggled with, would do differently, and how she wants to improve. We think this is a vital sign that the hacker community is showcasing what we already knew; hackers love to share their knowledge and improve themselves.
Gears are fairly straightforward way to couple rotational motion, and the physics topics required to understand them are encountered in an entry level physics classroom, not a university degree. But to really dig down to the root of how gears transfer motion may be somewhat more complex than it seems. [Bartosz Ciechanowski] put together an astonishingly good interactive teaching tool on gears, covering the fundamentals of motion up through multi-stage gear trains.
The post starts at the beginning – not “how to calculate a gear ratio” – but how does rotational motion work at all. The illustrations help give the reader an intuitive sense for how the rate of rotation is measured and what that measurement actually represents in the real world. From there [Bartosz] builds up to describing how two discs touching edge to edge transfer motion and the relationship of their size on that process. After explaining torque he has the fundamentals in place to describe why gears have teeth, and why they work at all.
Well written explanatory copy aside, the real joy in this post is the interactivity. Each concept is illustrated, and each illustration is interactive. Images are accompanied by a slider which lets you adjust what’s shown, either changing the speed of a rotating gear or advancing the motion of two teeth interlocking. We found that being able to move through time this way really helped form an intuitive understanding of the concepts being discussed. This feels like the dream of interactive multimedia textbooks come to life.
Sign language can like any language be difficult to learn if you’re not immersed in it, or at least learning from someone who is fluent. It’s not easy to know when you’re making minor mistakes or missing nuances. It’s a medium with its own unique issues when learning, so if you want to learn and don’t have access to someone who knows the language you might want to reach for the next best thing: a machine that can teach you.
This project comes from three of [Bruce Land]’s senior electrical and computer engineering students, [Alicia], [Raul], and [Kerry], as part of their final design class at Cornell University. Someone who wishes to learn the sign language alphabet slips on a glove outfitted with position sensors for each finger. A computer inside the device shows each letter’s proper sign on a screen, and then checks the sensors from the glove to ensure that the hand is in the proper position. Two letters include making a gesture as well, and the device is able to track this by use of a gyroscope and compass to ensure that the letter has been properly signed. It appears to only cover the alphabet and not a wider vocabulary, but as a proof of concept it is very effective.
The students show that it is entirely possible to learn the alphabet reliably using the machine as a teaching tool. This type of technology could be useful for other applications as well, such as gesture recognition for a human interface device. If you want to see more of these interesting and well-referenced senior design builds we’ve featured quite a few, from polygraph machines to a sonar system for a bicycle.
We are big fans of tools in the browser for education. You have a consistent environment maintained by someone else, you don’t have to install anything, and you can work from any computer you happen to find yourself. The HDLBits site has a great set of Verilog “exams” that would be a big help to anyone trying to learn or brush up on their Verilog skills.
The site offers a range of topics that go from the silly (output a constant 1 or 0) to full-blown state machines and testbenches. The site isn’t tutorial in nature, instead it offers a problem, an optional hint, and an editing window with some code already in place. You add your code and hit submit. Behind the scenes, the site runs Intel Quartus and Modelsim to test your work. It will either show you the results or tell you that you failed.
Connecting computers to human brains is currently limited to the scope of science fiction and a few cutting-edge laboratories. Tapping into some nerves farther from our central wetware is possible and [Peter Buczkowski] shows us his stylish machine for implanting a pattern into our brains without actively having to memorize anything.
His Medium Machine leverages a TENS unit to activate forearm muscles in a pattern programmed into an Arduino. Users place their forearm across two aluminum electrodes mounted on a tasteful wooden platform and extend a single finger over a button. Electrical impulses trigger the muscles which press the button. That’s all. After repeating the pattern a few times, the users should be able to recite it back on command even if they aren’t aware of what it means. If this sounds like some [Johnny Mnemonic] memory cache, you are absolutely correct. This project draws inspiration from the [William Gibson] novel which became a [Keanu Reeves] movie.