Should My Kid Learn to Code

Posted by Maggie Johnson, Director of Education and University Relations, Google

(Cross-posted on the Google for Education Blog)

Over the last few years, successful marketing campaigns such as Hour of Code and Made with Code have helped K12 students become increasingly aware of the power and relevance of computer programming across all fields. In addition, there has been growth in developer bootcamps, online “learn to code” programs (code.org, CS First, Khan Academy, Codecademy, Blockly Games, etc.), and non-profits focused specifically on girls and underrepresented minorities (URMs) (Technovation, Girls who Code, Black Girls Code, #YesWeCode, etc.).

This is good news, as we need many more computing professionals than are currently graduating from Computer Science (CS) and Information Technology (IT) programs. There is evidence that students are starting to respond positively too, given undergraduate departments are experiencing capacity issues in accommodating all the students who want to study CS.

Most educators agree that basic application and internet skills (typing, word processing, spreadsheets, web literacy and safety, etc.) are fundamental, and thus, “digital literacy” is a part of K12 curriculum. But is coding now a fundamental literacy, like reading or writing, that all K12 students need to learn as well?

In order to gain a deeper understanding of the devices and applications they use everyday, it’s important for all students to try coding. In doing so, this also has the positive effect of inspiring more potential future programmers. Furthermore, there are a set of relevant skills, often consolidated as “computational thinking”, that are becoming more important for all students, given the growth in the use of computers, algorithms and data in many fields. These include:

• Abstraction, which is the replacement of a complex real-world situation with a simple model within which we can solve problems. CS is the science of abstraction: creating the right model for a problem, representing it in a computer, and then devising appropriate automated techniques to solve the problem within the model. A spreadsheet is an abstraction of an accountant’s worksheet; a word processor is an abstraction of a typewriter; a game like Civilization is an abstraction of history.
• An algorithm is a procedure for solving a problem in a finite number of steps that can involve repetition of operations, or branching to one set of operations or another based on a condition. Being able to represent a problem-solving process as an algorithm is becoming increasingly important in any field that uses computing as a primary tool (business, economics, statistics, medicine, engineering, etc.). Success in these fields requires algorithm design skills.
• As computers become essential in a particular field, more domain-specific data is collected, analyzed and used to make decisions. Students need to understand how to find the data; how to collect it appropriately and with respect to privacy considerations; how much data is needed for a particular problem; how to remove noise from data; what techniques are most appropriate for analysis; how to use an analysis to make a decision; etc. Such data skills are already required in many fields.

These computational thinking skills are becoming more important as computers, algorithms and data become ubiquitous. Coding will also become more common, particularly with the growth in the use of visual programming languages, like Blockly, that remove the need to learn programming language syntax, and via custom blocks, can be used as an abstraction for many different applications.

One way to represent these different skill sets and the students who need them is as follows:

All students need digital literacy, many need computational thinking depending on their career choice, and some will actually do the software development in high-tech companies, IT departments, or other specialized areas. I don’t believe all kids should learn to code seriously, but all kids should try it via programs like code.org, CS First or Khan Academy. This gives students a good introduction to computational thinking and coding, and provides them with a basis for making an informed decision on whether CS or IT is something they wish to pursue as a career.

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Computers start to learn like us

Its always nice to see an article on A.I. in the local newspaper, The New Zealand Herald. So the article titled Autocorrect fails could be distant mammary as computers start to learn like us, by Sarah Knapton made for an interesting read. Heres a quote: "Most mobile phone users have suffered the indignity of an embarrassing autocorrect mistake, but smartphones may soon be smart enough to understand what we are trying to say." Scientists claim that for the first time, they have programmed a machine to learn in the same way as humans. I recommend the full article.

from The Universal Machine http://universal-machine.blogspot.com/

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What we can learn about effective meaningful and diverse organizations

Posted by Beryl Nelson, Software Engineering Manager

By becoming more conscious of our own stereotypes and biases, and making use of the insights revealed by the research on bias and stereotype threat, unconscious decision making, and cognitive illusions, each of us can bring more to our work and create diverse, innovative, and meaningful organizations.

Since 2009, I’ve been reading literature about the challenges and successes in making diverse teams effective, and speaking about this research. My goal is to help everyone understand more about unconscious decision-making and other barriers to inclusion, and through knowledge, combat these effects.

A short summary:

• A team that is heterogeneous in meaningful ways is good for innovation, and good for business.
• There are many challenges to making such teams effective, such as unconscious decision making, stereotype threat, and other cognitive illusions.
• There is repeatable quantitative research which shows ways to combat some of these effects.
• The barriers to effectiveness may seem overwhelming, but there is hope! Meaningful change is possible, and some examples of successful change are cited below.

In a bit more detail:

1. Diversity is good for innovation and business. There is a correlation between financial success and the diversity of leadership teams, as shown in research by Catalyst, McKinsey and Cedric Herring. Further, research shows a strong correlation between having women on teams and innovation; concluding that there is a strong correlation between the presence of women and the social skills required to get ideas percolating into the open.
2. We all make decisions unconsciously, influenced by our implicit associations. As an example of these effects, a large proportion of CEOs are taller than the average population and height is strongly correlated with financial and career success. It’s long been argued that women and underrepresented minorities are not represented in CEO leadership because there aren’t enough qualified individuals in the labor pool. This “pipeline issue” argument can’t be made for short and average-height people, however. Simple, repeatable tests measure, via response time and error rate, the implicit associations we have between concepts. These associations are created as an adaptive response, but we must understand our own implicit biases in order to make better decisions.
3. Stereotype threat plays a role in preventing people from being fully effective. The low representation of women and minorities in Science has long been the source of a troubling question: is this an indication of a difference in innate ability (see Ben Barre’s response to Lawrence Summers’ remarks), or the result of some other effect? Claude Steele and his colleagues elegantly showed that two groups of people can have similar or opposite reactions, depending on the way a situation is presented. These and other experiments show that stereotype threat can compromise the performance of the subject of a stereotype, if he or she knows about the stereotype and cares about it.
4. Change is possible. The above and other challenges may make it seem nearly impossible to create a diverse and highly functioning organization, but dramatic change can be made. Take, for example, the discovery of biased decision making and effective changes made via the use of data in the MIT Science Faculty Study, or the amazing changes at Harvey Mudd college, which not only increased participation of women as Computer Science majors from 12% to 40% in five years, but also increased the total number of CS majors from 25 to 30 per year to 70 CS graduates in the class of 2014.

If you’re interested in learning more, watch the video about the data on diversity below. You can read the full research in the November issue of Communications of the Association of Computing Machinery. You can read even more using the full bibliography.

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Syrias children learn to code with the Raspberry Pi

Three years ago, when I was looking for an example of social unrest to highlight the use of social media as a communication tool for protestors in my book, I chose the then new uprising in Syria. Im horrified the conflict still continues. However, I just came across a surprisingly good piece of news from that awful conflict; the use of the Raspberry Pi to teach Syrian refugees in Lebanon to code. Read the full article in the Guardian to learn more.

from The Universal Machine http://universal-machine.blogspot.com/

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Summer Games Learn to Program

Posted by Jennifer Vaden Barth, Executive Assistant

Looking for ways to engage your kids in constructive, meaningful learning? We’ve just launched Blockly Games, our next extension of Blockly, a web­-based graphical programming environment. As part of the generation of new programming environments that provide a more accessible introduction to coding, Blockly Games allows users to create and run programs by arranging blocks with a simple click, drag and drop.

Blockly Games requires little or no typing, which facilitates young or novice programmers to learn core coding principles in an intuitive way. By minimizing the use of syntax, users are able to focus on the logic and concepts used by computer scientists, progressing at their own pace as they venture through mazes and more advanced arenas.

Blockly was featured during the 2013 Computer Science Education week where people of all ages tried programming for the first time. Blockly is universally accessible with translations for a number of languages, including German, Vietnamese, Russian and even Klingon.

We encourage you and your child to explore Blockly Games, where novice programmers of any age begin to learn together. With Blockly Games, the whole family can learn and master basic computer science concepts.

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