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"The groundwork for machine learning was laid down in the middle of last century. But increasingly powerful computers - harnessed to algorithms refined over the past decade - are driving an explosion of applications in everything from medical physics to materials, as Marric Stephens discovers When your bank calls to ask about a suspiciously large purchase made on your credit card at a strange time, it's unlikely that a kindly member of staff has personally been combing through your account. Instead, it's more likely that a machine has learned what sort of behaviours to associate with criminal activity - and that it's spotted something unexpected on your statement. Silently and efficiently, the bank's computer has been using algorithms to watch over your account for signs of theft. Monitoring credit cards in this way is an example of "machine learning" - the process by which a computer system, trained on a given set of examples, develops the ability to perform a task flexibly and autonomously. As a subset of the more general field of artificial intelligence (AI), machine-learning techniques can be applied wherever there are large and complex data sets that can be mined for associations between inputs and outputs. In the case of your bank, the algorithm will have analysed a vast pool of both legitimate and illegitimate transactions to produce an output ("suspected fraud") from a given input ("high-value order placed at 3 a.m."). But machine learning isn't just used in finance. It's being applied in many other fields too, from healthcare and transport to the criminal-justice system. Indeed, Ge Wang - a biomedical engineer from the Rensselaer Polytechnic Institute in the US who is one of those pioneering its use in medical imaging - believes that when it comes to machine learning, we're on the cusp of a revolution."

"In India, 41km of highway road was constructed every day for the year of 2016. In the Indian government budget, it estimated the cost just for 2016 to be 19 billion USD. It would be financing any shortfall through tax-free government bonds. Computational thinking would have played an instrumental role in deciding on where the road would go through with taking into account the key hubs and may have saved the government millions, if not billions of dollars. Jeanette Wing (2012) defines computational thinking as the thought process involved in formulating a problem and expressing its solution in a way that a computer-human or machine can effectively carry out. It is the process of abstraction by; choosing the right abstractions, operating in terms of multiple layers of abstraction simulations and defining the relationships between layers guided by efficiency, correctness, and flexibility. Computational thinking can best be related to as writing software or instructionals. Every action or non-action is accounted for in the way computational artifacts are constructed. Computational thinking is great for working out a solution but there is an argument that computational thinking does not put enough emphasis on the problem itself. Design thinking, on the other hand, attempts to understand the intent or problem before looking at any solution - computational or otherwise. Design thinking attempts to identify why the problem exists in the first place before solving it. IDEO defines design thinking as the application of empathy and experimentation to arrive at innovation solutions through making decisions based on stakeholder input and evidence based research. Using the Indian roading example, a design thinker would ask, what is the intent of building the roads in the first place?"

"Facebook-Style Learning Site Gets $15 Million"

"Think Tank: Flip-thinking - the new buzz word sweeping the US "

Lecture first via online video, then set the work in class. Teacher in a better position to assist and enable learning than lecturing in class and setting homework

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"Money is a necessary tool, but like any other, it can easily lead its untrained users into uncomfortable - perhaps even painful - situations. So why, then is, financial literacy an educational requirement in less than half of the states in the U.S.? Students deserve to approach life armed with the knowledge they need to understand money matters. The following resources can give you insight into how to bring financial literacy into your classroom."