The Economist ran one of their occasional EdTech updates: to titles that caught my eye:
- Summary bit: Together, technology and teachers can revamp schools
- copy of this article here
- And Technology is transforming what happens when a child goes to school
- copy of this article here
Two popular recent articles on applications of machine learning:
- Million-Dollar Prize Hints at How Machine Learning May Someday Spot Cancer (Will Knight, May 9, 2017)
- a copy of this article is here
- Machine-learning promises to shake up large swathes of finance (The Economist, May 28, 2017)
- a copy of the article is here
Often, in the context of large scale testing programs, “critical thinking assessment” is represented more by “information synthesis“, “reading comprehension“, “problem solving” or other exercises that require an examinee to make a claim and cite evidence and reasoning to support it.
In some contexts this is also called “Argumentative Writing” — much as the “analyze and argument” question on the GMAT was once a common “analytical writing” task, but only one program that comes to mind — the CAE’s Collegiate Learning Exam Plus (or Minus or Pro of whatever the marketing types want to call it this year) — does or did (at one point) break out “problem solving” and “analytic reasoning & evaluation” as dimensions on a rubric for a performance task, although they may have moved toward generalize “analysis and problem solving” dimension in current exams.
In any event, the big news today is that I have discovered EXACTLY the self-paced, student-centric, topic-organized critical thinking product and platform I have long envisioned that would replace the beloved “SRA Reading Cards” of my youth. A group in Chicago has created a modern, digital version of this tool — organized as a set of subject mater-organized topics, grade / difficulty sequenced, that (hopefully) are as interesting and “teachful” as the SRA reading card stories and articles were. Only here, students WRITE about what they read, not just answer MCQs. And they are taught to cite evidence, make claims, explain reasoning — even identify counter-arguments! Great stuff.
Read more about them at ThinkCERCA.com.
Google posted information about TensorFlow — the release of as open source of a key bunch of machine learning tools on their Google research blog here.
Given the great piles of multi-dimensional tables (or arrays) of data machine learning typically involves, and (at least for us primitive users) the tremendous shovel work involved in massaging and pushing around these giant piles of data file (and sorting out the arcane naming schemes devised to try to help with this problem is almost a worse problem itself),
the appellation of “Tensor Flow” as a tool to help with this is at first blush very promising. That is, rather than just a library of mathmatical algorithm implementations, I am expecting something that can help make the machine learning work itself more manageable.
I suspect that just figuring out what this is will cost me a few days… but I have much to learn.
I was very impressed with how quick and easy it was to create a web site with “twitter bootstrap.js” — but only today did a fellow grad student teach me another benefit: support for multi-language web sites. [I found tutorials at https://www.youtube.com/user/wiredwiki very useful, and the one below basically had my site up and running in less than its the running time (it is well over an hour and designed for non-technical novices). The others from this teacher were on individual bootstrap 3 features, rather than the one-stop-shop provided below.]
And Wencheng Hu, an experienced translator and web developer, provided me the key solution element: a complete BootStrap 3 solution for language labels and names, etc. — documented here at http://usrz.github.io/bootstrap-languages/ complete with flags icons (in three sizes) for the 43 languages it supports!
How well this works for a “web app” or even a “blog” on an ongoing basis, i am not sure. probably a blog should just be done as separate blogs for a variety of reasons, but swapping out labels and UI elements in an application is often useful (if, for a variety of reasons, painful). My 8-language support for my “language learning” apps on iOS taught me a lot about the challenges of making an app work for 8 different audiences…
I am very interested to see the final details of my implementation for my new web site. I will post the implementation particulars, as one-page bootstrap web sites are a very handy and useful tool for SMEs, and this neat trick certainly works quite well for a small number of languages. Further, popular and inexpensive hosting services support the necessary tools with ease and by default, by and large, so the follow up post should be quite short. And soon!
After this post, I have continued to get more input and find more articles.
Here are two:
- http://www.rspective.com/blog/berlin-startups-tech-stack, which contains these nice diagrams:
And lots of other interesting graphs…
In the article noted above, I linked here for graphs like this one (where venture funded startups are rated on an “okay”, “good” and “great” scale (grade inflation?) using blue / red / yellow) as reflected in Angle.co standings.
Here are just three (of many many) samples:
And lastly, I saw this piece has is called:
Which web technology should I use?
A handy guide for non-technical founders
Interesting at least as far as learning how some folks see the world, including very rough shorthand impressions of the “pros and cons” of using different tool sets. The primary starting point advocated is ‘do something fast and cheap to prove your concept and that you are willing to throw away” — not something I’ve ever been a big fan of (since using a technology I know best is usually fastest, and building “throw away” code is a bad habit I never developed) but might be right for some people / situations (e.g. when using mid-level or junior people who only write throw-away code…).
Perhaps we are nearly at the point where saying “distributed systems” is as redundant as “software program” always has been, but for the moment I want to consider how a specific issue is heightened by the nature of modern, asynchronous systems, and that issue is “fault tolerance” generally as well as “cascading failures” specifically.
More and more such issues arise — and I was please to read a particularly lucid explanation of a popular and important design pattern used in many solutions: the Circuit Breaker pattern. On Martin Fowler’s blog — haha. I was kind of surprised by that — but only because I don’t google interesting problems in architecture and design nearly as often as I’d like.
I can’t add any value to what he’s written here, so instead i will just quote briefly:
The basic idea behind the circuit breaker is very simple. You wrap a protected function call in a circuit breaker object, which monitors for failures. Once the failures reach a certain threshold, the circuit breaker trips, and all further calls to the circuit breaker return with an error, without the protected call being made at all. Usually you’ll also want some kind of monitor alert if the circuit breaker trips.
There are added bits about adding a capability to attempt automatic reset (at some specified interval) and discussions of other real-world refinements (e.g. different thresholds for different sorts of errors), but a hallmark of this sort of writing is that, at least for most of its intended audience, a simple example provided in detail, and pointers to additional kinds of flourishes and add-ons, is really all that is needed.
Check it out! And if you googled this topic, doubtless you have read or seen something about NetFlix’ Hystrix, which says on that getHub landing page:
Hystrix is a latency and fault tolerance library designed to isolate points of access to remote systems, services and 3rd party libraries, stop cascading failure and enable resilience in complex distributed systems where failure is inevitable.
It is a java implementation; there are other articles linked here and links to alternative Circuit-breaker patterns in Ruby, Java, Grails Plugin, C#, AspectJ, and Scala listed at the bottom of the Fowler blog post.