"education" entries

Four short links: 9 November 2015

Four short links: 9 November 2015

Smart Sensors, Learning Autopilot, Higher Education, and 3D Soccer

  1. Low-Power Deep Learning — it’s a media release for proprietary tech, but interesting that people are working on low-power deep learning neural nets. As Pete Warden noted, this kind of research will be at the center of smart sensors. (via Pete Warden)
  2. Tesla’s Self-Improving Autopilot — it learns when you “rescue” (aka take control back from autopilot), so it’s getting better day by day. Musk said that Model S owners could add ~1 million miles of new data every day, which is helping the company create “high-precision maps.” Navteq, Google Maps, Waze … new map data is still valuable.
  3. The Digital Revolution in Higher Education Has Already Happened (Clay Shirky) — and no-one noticed. I read half of this before going “holy crap this is good, who wrote it?” I’m a Shirky junkie (I bet his laundry lists cite Habermas and the Peace of Westphalia). At the current rate of growth, half the country’s undergraduates will have at least one online class on their transcripts by the end of the decade. This is the new normal. But, As long as we discuss online education as a pedagogic revolution rather than an organizational one, we aren’t even having the right kind of conversation. The dramatic adoption of online education is not mainly a change in the content of classes. It’s a change in the institutional form of college, a demand for more flexibility by students who have to manage the increasingly complicated triangle of work, family, and school.
  4. System Automatically Converts 2-D to 3-D (MIT) — hilarious strategy! They constrained their domain: broadcast soccer games. The MIT and QCRI researchers essentially ran this process in reverse. They set the very realistic Microsoft soccer game “FIFA13” to play over and over again, and used Microsoft’s video-game analysis tool PIX to continuously store screen shots of the action. For each screen shot, they also extracted the corresponding 3-D map. […] For every frame of 2-D video of an actual soccer game, the system looks for the 10 or so screen shots in the database that best correspond to it. Then it decomposes all those images, looking for the best matches between smaller regions of the video feed and smaller regions of the screen shots. Once it’s found those matches, it superimposes the depth information from the screen shots on the corresponding sections of the video feed. Finally, it stitches the pieces back together. Brute-forcing soccer. Ok, perhaps “hilarious” for a certain type of person. I am that person.
Four short links: 28 September 2015

Four short links: 28 September 2015

Coordinated Disclosure Kit, Coding Contests, Growth Strategies, and Ad Buck Passing

  1. Coordinated Disclosure Toolkita generic copy of the resources used by Portcullis Computer Security to manage our Advisory Process.
  2. Competitive Coding (Bloomberg) — ignore the lazy author’s patronising tone; the bit that caught my eye was: He first began freaking people out in second grade, at age 8, when he took second place in a major Belarusian coding competition. To put this achievement in perspective, the score was high enough for Korotkevich to be granted automatic enrollment in a top technical university without needing to pass any other entrance exams. That is how you value STEM education: let people test out of it if they don’t need it!
  3. Here’s What a Growth Strategy Looks Like (First Round) — User acquisition doesn’t really make sense unless you already have healthy retention [of diversity-in-tech pipeline conversations].
  4. How We Pass The Buck (Anil Dash) — The thing is, technology is not neutral, algorithms are built with values, and the default choices in our software determine huge swaths of our culture. We delegate ethical decisions as consumers and citizens to people who make software, but almost no computer science program teaches ethics, and almost no major technology company has a chief ethicist.

Are there some students who can’t learn how to code?

Change tactics or give up: It's a crossroads many teachers face when students don't understand the code.

I can never forget an evening late into a semester of my Introduction to Python course, during which I asked my students a question about user-defined classes. Here’s the code I had put on the board:

As new information for this particular lesson, I informed them that every time a new MyClass instance is created, the __init__() method is called implicitly. In other words, the code above calls __init__() twice, and in executing the code in __init__(), the variable MyClass.var is being incremented — so this is also happening twice.

So, I asked them: after the above code is executed, what is the value of MyClass.var?

The hand of this class’ most enthusiastic student shot into the air.

“One!” He answered proudly. And for a moment my mouth stood open. Read more…

Comments: 12
Four short links: 27 July 2015

Four short links: 27 July 2015

Google’s Borg, Georgia v. Malamud, SLAM-aware system, and SmartGPA

  1. Large-scale Cluster Management at Google with BorgGoogle’s Borg system is a cluster manager that runs hundreds of thousands of jobs, from many thousands of different applications, across a number of clusters, each with up to tens of thousands of machines. […] We present a summary of the Borg system architecture and features, important design decisions, a quantitative analysis of some of its policy decisions, and a qualitative examination of lessons learned from a decade of operational experience with it.
  2. Georgia Sues Carl Malamud (TechDirt) — for copyright infringement… for publishing an official annotated copy of the state's laws. […] the state points directly to the annotated version as the official laws of the state.
  3. Monocular SLAM Supported Object Recognition (PDF) — a monocular SLAM-aware object recognition system that is able to achieve considerably stronger recognition performance, as compared to classical object recognition systems that function on a frame-by-frame basis. (via Improving Object Recognition for Robots)
  4. SmartGPA: How Smartphones Can Assess and Predict Academic Performance of College Students (PDF) — We show that there are a number of important behavioral factors automatically inferred from smartphones that significantly correlate with term and cumulative GPA, including time series analysis of activity, conversational interaction, mobility, class attendance, studying, and partying.
Comment: 1

4 ways the Raspberry Pi is being used in education

Get inspired to create, teach, and learn with the Raspberry Pi.


The Raspberry Pi is a small computer that can be used for a variety of projects, and has been heralded as a great boon to education due to its flexibility and simplicity. While PcPro magazine noted in January of 2014 that Pi’s were “gathering dust” in classrooms, production has not ceased. The usage map is pretty impressive and the Raspberry Pi 2 was recently released.

In February of this year, the Raspberry Pi Foundation announced that they’re starting a mentoring program for people 16-21 years old. Here are four other ways that the Pi is being used in education and growing the tech community.

Read more…

Comments: 2
Four short links: 7 July 2015

Four short links: 7 July 2015

SCIP Berkeley Style, Regular Failures, Web Material Design, and Javascript Breakouts

  1. CS 61AS — Berkeley self-directed Structure and Interpretation of Computer Programs course.
  2. Harbingers of Failure (PDF) — We show that some customers, whom we call ‘Harbingers’ of failure, systematically purchase new products that flop. Their early adoption of a new product is a strong signal that a product will fail – the more they buy, the less likely the product will succeed. Firms can identify these customers either through past purchases of new products that failed, or through past purchases of existing products that few other customers purchase.
  3. Google Material Design LiteA library of Material Design components in CSS, JS, and HTML.
  4. Breakoutsvarious implementations of the classic game Breakout in numerous different [Javascript] engines.
Four short links: 4 June 2015

Four short links: 4 June 2015

DARPA Robotics Challenge, Math Instruction, Microservices Construction, and Crypto Hardware Sans Spooks

  1. Pocket Guide to DARPA Robotics Challenge Finals (Robohub) — The robots will start in a vehicle, drive to a simulated disaster building, and then they’ll have to open doors, walk on rubble, and use tools. Finally, they’ll have to climb a flight of stairs. The fastest team with the same amount of points for completing tasks will win. The main issues teams will face are communications with their robot and battery life: “Even the best batteries are still roughly 10 times less energy-dense than the kinds of fuels we all use to get around,” said Pratt.
  2. Dan Meyer’s Dissertation — Dan came up with a way to make math class social and the vocabulary sticky.
  3. Monolith First — echoes the idea that platforms should come from successful apps (the way AWS emerged from operating the Amazon store) rather than be designed before use.
  4. Building a More Assured Hardware Security Module (PDF) — proposal for An open source reference design for HSMs; Scalable, first cut in an FPGA and CPU, later allow higher speed options; Composable, e.g. “Give me a key store and signer suitable for DNSsec”; Reasonable assurance by being open, diverse design team, and an increasingly assured tool-chain. See cryptech.is for more info.
Four short links: 15 May 2015

Four short links: 15 May 2015

Army Cloud, Google Curriculum, Immutable Infrastructure, and Task Queues

  1. Army Cloud Computing Strategy (PDF) — aka: “what we hope to do without having done, to use what we’re doing to them.”
  2. Guide to Technical Development (Google) — This guide is a suggested path for university students to develop their technical skills academically and non-academically through self-paced, hands-on learning.
  3. Immutable Infrastructure is the Future (Michael DeHaan) — The future of configuration management systems is in deploying cloud infrastructure that will later run immutable systems via an API level.
  4. machineryan asynchronous task queue/job queue based on distributed message passing.
Four short links: 20 April 2015

Four short links: 20 April 2015

Edtech Advice, MEMS Sensors, Security in Go, and Building Teams

  1. Ed Tech Developer’s Guide (PDF) — U.S. government’s largely reasonable advice for educational technology startups. Nonetheless, take with a healthy dose of The Audrey Test.
  2. The Crazy-Tiny Next Generation of Computers — 1 cubic millimeter-sized sensors are coming. The only sound you might hear is a prolonged groan. That’s because these computers are just one cubic millimeter in size, and once they hit the floor, they’re gone. “We just lose them,” Dutta says. “It’s worse than jewelry.”
  3. Looking for Security Trouble Spots in Go — brief summary of the known security issues in and around Go code.
  4. The New Science of Building Great Teams (Sandy Pentland) — fascinating discussion of MIT’s Human Dynamics lab’s research into how great teams function. The data also reveal, at a higher level, that successful teams share several defining characteristics: 1. Everyone on the team talks and listens in roughly equal measure, keeping contributions short and sweet. 2. Members face one another, and their conversations and gestures are energetic. 3. Members connect directly with one another—not just with the team leader. 4. Members carry on back-channel or side conversations within the team. 5. Members periodically break, go exploring outside the team, and bring information back.
Four short links: 2 March 2015

Four short links: 2 March 2015

Onboarding UX, Productivity Vision, Bad ML, and Lifelong Learning

  1. User Onboarding Teardowns — the UX of new users. (via Andy Baio)
  2. Microsoft’s Productivity Vision — always-on thinged-up Internet everywhere, with predictions and magic by the dozen.
  3. Machine Learning Done WrongWhen dealing with small amounts of data, it’s reasonable to try as many algorithms as possible and to pick the best one since the cost of experimentation is low. But as we hit “big data,” it pays off to analyze the data upfront and then design the modeling pipeline (pre-processing, modeling, optimization algorithm, evaluation, productionization) accordingly.
  4. Ten Simple Rules for Lifelong Learning According to Richard Hamming (PLoScompBio) — Exponential growth of the amount of knowledge is a central feature of the modern era. As Hamming points out, since the time of Isaac Newton (1642/3-1726/7), the total amount of knowledge (including but not limited to technical fields) has doubled about every 17 years. At the same time, the half-life of technical knowledge has been estimated to be about 15 years. If the total amount of knowledge available today is x, then in 15 years the total amount of knowledge can be expected to be nearly 2x, while the amount of knowledge that has become obsolete will be about 0.5x. This means that the total amount of knowledge thought to be valid has increased from x to nearly 1.5x. Taken together, this means that if your daughter or son was born when you were 34 years old, the amount of knowledge she or he will be faced with on entering university at age 17 will be more than twice the amount you faced when you started college.