Hatched by Google Creative Lab creative technologist Jason Striegel, designer Jeff Baxter, and a small team in New York, Coder offers a stepping stone for people interested in building for the web by converting cheap Raspberry Pi mini-computers into personal web servers through a stripped-back web-based development environment.
Google’s pitching Coder at an education audience, a potential sweet spot for Raspberry Pi given its $35 price tag and one Google has focused on previously, gifting 15,000 of the devices to UK schools earlier this year. Raspberry Pi supporters in the UK have also been urging schools to use the devices to spur interest in coding, hacking and building.
I’ve spent many years referencing Wikipedia’s list of cognitive biases whenever I have a hunch that a certain type of thinking is an official bias but I can’t recall the name or details. It’s been an invaluable reference for helping me identify the hidden flaws in my own thinking. Nothing else I’ve come across seems to be both as comprehensive and as succinct.
However, honestly, the Wikipedia page is a bit of a tangled mess. Despite trying to absorb the information of this page many times over the years, very little of it seems to stick. I often scan it and feel like I’m not able to find the bias I’m looking for, and then quickly forget what I’ve learned. I think this has to do with how the page has organically evolved over the years. Today, it groups 175 biases into vague categories (decision-making biases, social biases, memory errors, etc) that don’t really feel mutually exclusive to me, and then lists them alphabetically within categories. There are duplicates a-plenty, and many similar biases with different names, scattered willy-nilly.
I’ve taken some time over the last four weeks (I’m on paternity leave) to try to more deeply absorb and understand this list, and to try to come up with a simpler, clearer organizing structure to hang these biases off of. Reading deeply about various biases has given my brain something to chew on while I bounce little Louie to sleep.
Despite the phenomenal rise in computing over the last 50 years, the birth of the internet, and our ever increasing reliance on technology, women are still not engaging with computer science at the same rate as men.
The report shows that in 2016 only a minority of schools (29%) entered pupils for GCSE computing – despite it being a foundation subject on the national curriculum. The figure is even lower at A-level, with only 24% of schools entering their students for the qualification.
Things don’t fair any better in further education either, with the Digest of Education statistics revealing the percentage of females who took an undergraduate degree in computer science in 1970-71 was 14%. This rose to 37% in 1983-84 but gradually declined to 18% in 2010-11.
The group will serve as an opportunity to connect and engage with researchers and domain experts to drive awareness of Microsoft Research and Windows Azure for Research. We’d like for you to be part of the community and discussions.
What is the Windows Azure for Research initiative?