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Bill Gates did it, will.i.am did it, Mayor Bloomberg did it and even the POTUS did it. Shouldn't you? An hour of Code for *you* the Busy Development Professionals

Tanya Gupta's picture

Computer Science Education Week has already kicked off (December 5 - 11, 2016) and it is a pretty big deal. One hour of code for everyone (no experience needed) is a part of that. The focus is on getting children involved. But what about busy professionals? Can it be useful for them, too? We think the answer to that is yes. This blog will teach you to code in Google Apps Script (GAS for short) in sixty minutes or less. There are two main reasons we chose GAS.

One, GAS is an easy to use scripting language that can help you write programs to solve common coding problems. We chose GAS because it is very easy to get started and offers some great features for saving your files in the cloud and working with different kinds of files. You need to be able to use Google Drive to write basic scripts in GAS.

Secondly, as our regular readers may know, this is the seventh blog of the technology aided gut (TAG) checks series. So far in this series, we have focused on the tools and techniques of a just-in-time learning strategy, and how to use TAG checks to make conclusions about data. In this blog we wanted to focus on some basic programming that will help illustrate how powerful (and easy!) just a little code education can be. GAS is perfect for this purpose.

N.B. You can do some pretty nifty stuff in GAS and here is the result of more professional code we have written entirely in GAS. This is an Add-On for Google Docs to create word clouds

Now -- all you need is a gmail account to get started.

(͡• ͜ʖ ͡•) GET SET AND START YOUR CLOCK
MINUTE TO MINUTE
While logged into Gmail, go to https://drive.google.com/. If this is your first time, you will see something like this:


 

Think you know who the manager's favorite is? You may be right: Technology Aided Gut Checks

Tanya Gupta's picture

Welcome to the sixth blog of the technology aided gut (TAG) checks series. So far in this series, we have focused on the tools and techniques of a just-in-time learning strategy. We will now switch gears and show how, with very little effort, we can use TAG checks to make simple yet (occasionally) profound conclusions about data - big and small.

As we delve into the details of TAG checks in the next several blogs, we will be using web programming tools and techniques to gather, process and analyze data. While we will try to be as comprehensive as possible in our explanations, it may not be always as detailed as we would like it to be. This forum, after all, is a blog and not a training tutorial. We hope by applying the just-in-time learning strategy that we have discussed so far in the series, you will be able to supplement what we miss in our explanations. Our goal for the overall series has been to empower you. We hope the first part of the series has made you an empowered self-learner.

The second part of the series will make you an empowered and savvy data consumer, a development professional who can confidently rely on the story the data tells to accomplish her tasks.

For the readers who are just joining in, we suggest that you become somewhat familiar with the just-in-time learning strategy by skimming the series so far.

Netflixing learning: How to select a good learning video?

Tanya Gupta's picture

Welcome to the fifth blog of the technology aided gut (TAG) checks series where we use a just-in-time learning strategy to help you learn to do TAG checks on your data.  Our last post talked about web videos as a learning tool. We shared five questions one should ask before choosing a video source over text, audio or other media. Once you have decided that video is the most suitable format for your particular learning task - the next question is finding the right video for you to watch. This is the focus of this blog. When it comes to learning videos, one size does not fit all. A highly rated learning video on YouTube may not necessarily suit your needs. The two key determinants of a good match are the type of learning you need to do and your familiarity with the subject matter.
 

What and How-To learning types

When it comes to learning something, most belong to the What category or the How-To category.

Ask before you watch: How to get the most out of learning videos

Tanya Gupta's picture
Welcome to the fourth blog of the technology aided gut (TAG) checks series. In our last post we showed you how to be reasonably confident that the information you find from an online resource is accurate, especially when you do not have the subject matter expertise to ascertain its correctness. In the next two blogs, we will take a closer look at educationational videos - arguably the “hottest” format for knowledge exchange.
 
This is a pragmatic blog for providing technical knowledge to adult professionals. So we are not going to address big questions like: The debate rages on while the trillion dollar online education industry blossoms.
 
No matter which side of the aisle you are on in this big debate, if you are in the need to learn something useful (quickly) and you are choosing a web source to learn from- remember these five critical factors - and then decide whether to use a video or some other source. These factors may not guarantee the success of a learning session but ignoring them will most likely ensure the session’s failure.

Just-in (New Year’s resolution)-time learning

Abir Qasem's picture

Mediated Reality running on Apple iPhoneHello readers,
 
In this season of making resolutions (and hopefully sticking to a few of them) we invite you to join us for a year long skills transfer discussion/blog series on technology aided gut (TAG) checks.
 
TAG is a term we have coined to describe the use of simple web programming tools and techniques to do basic gut checks on data - big and small. TAG does not replace data science, rather it complements it. TAG empowers you - the development professionals - who rely on the story the data tells to accomplish your tasks. It does so by giving a you good enough idea about the data before you delve into the sophisticated data science methods (here is a good look at the last 50 years of data science from Stanford’s Dr. Donoho). In many cases it actually allows you to add your own insights to the story the data tells. As the series progresses we will talk a lot about TAGs.  For the eager-minded here’s an example of TAG usage in US politics.
 
In this series, we will use a just-in-time learning strategy to help you learn to do TAG checks on your data.  Just in time learning, as the name implies, is all about providing only the right amount of information at the right time. It is the minimum, essential information needed to help a learner progress to the next step. If the learner has a specific learning objective, just-in-time learning can be extremely efficient and highly effective. A good example of just in time information is the voice command a GPS gives you right before a turn. Contrast this with the use of maps before the days of GPS. You were given way more information than you needed and in a format that is not conducive to processing when you are driving.

MOOCs and e-learning for higher education in developing countries: the case of Tajikistan

Saori Imaizumi's picture
There has been a lot of talk and research on massive open online courses (MOOCs) and their potential impact, but is it really applicable to developing countries? How can universities take advantage of online content? And what kind of regulations and quality assurance mechanisms do we need? 

Last year, as a part of the “Tajikistan: Higher Education Sector Study,” I led a team to conduct pilot activities to assess the feasibility of using MOOCs and other e-learning content in higher education institutions (HEIs) in Tajikistan.

Recently the Government of Tajikistan has decided to discontinue existing correspondence-based programs for part-time students and shift to a “distance learning” system using computers and Internet technology. Thus, this study was conducted to assess the possibility of using information and communication technologies (ICT) to improve access, quality and relevance of higher education in Tajikistan. In addition, the study supported a mini-project to pilot a number of ICT-based solution models to tackle challenges identified in the country’s National Education Development Strategy.

Recently, we interviewed pilot participants about their experience participating in MOOCs, e-learning and distance education, and then produced a series of short video clips. These videos showcase the impact of potential use of online learning and distance education for improving access, quality and relevance of education as well as reduction of the gender gap. One of the female students in the video mentioned that distance education allows her to continue studying after having kids.

Here is the overview video that we produced:
 
ICT for Higher Education? The Case of Tajikistan

The Things We Do: How Crowd Science Can Help Eliminate Biases

Roxanne Bauer's picture

There is a new and exciting field emerging that combines the insight of analytics and psychology; it’s known as crowd science.  Already, it’s a fairly pervasive industry, involving not just data scientists but also behavioral economists, marketers, and entrepreneurs.
 
Crowd science analyzes data (through mining, algorithms, statistical modeling, and others) and then applies psychological or behavioral theories to make sense of the analyses. It is sometimes referred to as the “guinea pig” economy because it utilizes consumer tests— often without the consumer realizing it— to obtain its data and, therefore, insight.
 
One of the most popular forms of crowd science is A/B testing whereby website visitors are shown different interfaces or versions of the same site. The way in which each visitor navigates through the site is then tracked to determine which version is more appealing or effective. One reason A/B testing is so helpful is that it divides users into a control group and a treatment group, allowing the engineers of the experiment to determine not just what the issues are but how to solve them. It also allows decision-makers to test for biases in project design and implementation.