Showing posts with label big. Show all posts
Showing posts with label big. Show all posts

Thursday, October 13, 2016

Aneesh Chopra and Big Data Resources

Much to my familys annoyance I listen to A LOT of podcasts. We have two pre-teen girls and they mostly want to listen to "Call me Maybe" right now rather that chit chat.


Heavy in rotation for the past two weeks has been the Entrepreneurial Thought Leaders Podcast from Stanford University.

This talk by Aneesh Chopra, the United States Chief Technology Officer, is a great overview of some of the ways the US government is trying to keep up with technological changes. I was lucky enough to hear him speak at one of the UVA Tapestry Workshops a few years back when he was still serving as Secretary of Technology here in Virginia. He is always very interesting and I end up walking away with a huge list of thing to look up.

In this talk he includes several sources particularly relevant to teaching the CS Principles Data topic.

  • http://www.data.gov/ - free clearing house of data collected by the government. In the talk he mentions several entrepreneurs using this data to start companies.
  • Healthcare - there is some good discussion here on privacy and how large data sets can be used to help develop treatments. This was one of the topics my students really responded to this year.
  • Education - This gives a great example of high school students using data to save money for their school district by looking at electricity usage.
There is a lot more, these were the highlights. The advantage is Stanford breaks the podcast down into small snippets of video making it very usable in a classroom.

While I am on the subject, if you have the chance to get to one of the Tapestry Workshops you need to go. Great information on expanding computer science to a broader group of students. They have expanded to several universities - so there is sure to be one near you. (I am speaking at UVA briefly this Thursday, but dont let that scare you away, the rest of the presenters are amazing.)
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Tuesday, August 2, 2016

Big Data Research

When I start off with a new topic in class I like to gather as much information as possible. Most of it will never make it to the notes of activities the kids see, but I find the more stuff floating around the ol noggin the better I do with teaching the topic.

Data in particular is difficult. I majored in math - which was great for the theoretical underpinnings of mathematics (totally practical on a daily basis). The field of Operational Research was brand new when I was going through college, so again, not a huge foundation for this whole data thing.

Some of the resources I have been using, in no particular order:

  • Computer Science Illuminated - this is my go to book for the CS Principles course. Great place to start.
  • Code - great book
  • List of Publicly available Data Sets
  • Big Data at CSAIL - MIT 
  • Ted Talk - Human Face on Big Data
    • http://humanfaceofbigdata.com/
  • Census Bureau API
  • CEISE- live data sets
  • Exploring Data
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Monday, May 30, 2016

Big Ideas Roundup

My AP CS Principles classes are finishing up Unit 1: Computers in Society.

So far we have covered hardware, from the basics of the CPU to the machine instruction cycle. They have learned binary and hexadecimal and are finishing up

Along the way they have worked together, written, and yet not written a single line of code.

IBM Wild Ducks


Odd for a programming class?

Turns out, what I originally did to keep myself from creating "just another coding class" ended up being a good decision. I have students ranging from absolute beginners to kids that have taken APCS or IBCS.

And anyone that has taught computer science knows that can be a recipe for disaster. The more experienced kids show off, intimidating the newbies, especially those that do not self identify as "good at computers". Most of this material is new to all of the kids, so no one has an advantage, other than working hard.

This also establishes that in this room, everyone has an opinion that counts, we work together and respect where we are int eh learning process.

So today we are finishing up Unit 1. My goal is to summarize what we have done and to start to look at the big ideas (Creativity, Abstraction, Data, Algorithms, Programming, Internet, Impact).


  • Fast Start: Based on everything we have talked about, what do you think computer science is? How would you explain it to someone else?
  • Finish working on their computer history projects
  • Watch this video from IBM: http://www-03.ibm.com/ibm/history/ibm100/us/en/
  • Whole Group Discussion - what is computer science
  • Poster - do a mind map with computer science  in the middle and the seven big ideas around the outside.
  • Test Review (still gotta grade, you know)



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Saturday, February 6, 2016

Random Numbers make Big Hair



Random numbers are one of those core topics in teaching computer science. We experience them all the time, but most folks really dont know anything about how they happen or what they are used for.

Often games are the most obvious way of teaching about random numbers. It is a quick and easy way to introduce the topic. However there is a downside in relying too much on games. Not all students, especially females, are naturally interested in gaming. Traditionally it is perceived to be a very male centered activity and  only using gaming to teach runs the risk of turning off a large chunk of our students.

This months Wired Magazine had a quick article on how the animators at Pixar created the hair in Brave. It gives and interesting discussion of how geometry and computer science come together in animation. The article is nice and short and would make a good discussion board prompt on random numbers.

I do use games throughout my courses, but I try to balance them with other types of programs. We use a lot of media computation based problems also, and when I do games I try to wither offer a social component or an alternative assignment.

A side note - overall this was one of the better issues for high school kids. Pretty readable overall, and less questionable content than some.


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