Tuesday 24 September 2013

Scratch Magic - Drawings Fractals using scratch

SCRATCH

Create stories, games, and animations
Share with others around the world

With Scratch, you can program your own interactive stories, games, and animations — and share your creations with others in the online community.
Scratch helps young people learn to think creatively, reason systematically, and work collaboratively — essential skills for life in the 21st century.
Scratch is a project of the Lifelong Kindergarten Group at the MIT Media Lab. It is provided free of charge.

 For More Details Visit : Scratch Website

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WE SCRATCHED  Our Head a lot and started from the SCRATCH and we SCRATCHED the beauty of Mathematics and Fractals in SCRATCH

The below given fractals are Drawn with Different version of scratch called SCRIBBLE.You can try the same with different flavors ( BYOB, SCRATCH, etc.. )

CODE be released soon !.....

A fractal is a mathematical set that has a fractal dimension that usually exceeds its topological dimension[1] and may fall between the integers.[2] Fractals are typically self-similar patterns, where self-similar means they are "the same from near as from far".[3] Fractals may be exactly the same at every scale,they may be nearly the same at different scales. The definition of fractal goes beyond self-similarity per se to exclude trivial self-similarity and include the idea of a detailed pattern repeating itself.

For More information Visit : Fractals












Friday 20 September 2013

Joy of Computing with Spreadsheet




Computational Thinking with Spreadsheet

Computers are incredibly fast, accurate, and stupid. Human beings are incredibly slow, inaccurate, and brilliant. Together they are powerful beyond imagination.”
                                                                                                (Albert Einstein)
"It is not the strongest of the species that survive, nor the most intelligent, but the one most responsive to change.                                                       (Charles Darwin.)

 


Computational Thinking is the type of thinking a person does when making use of human intelligence and computer intelligence to solve problems and accomplish tasks . This term was coined by Jeannette M. Wing, President's Professor of Computer Science,  Carnegie Mellon University, USA.  With a funding from Microft, Professor Jeannette even established a centre for  ‘Computational thinking’ in the University. Many people consider, Carnegie Mellon  as the Mecca of computer science and computational thinking. 


At Carnegie Mellon, computational thinking pervades every department. Professors in Computer science department interacts with almost every other discipline on campus. Computational biology, computational chemistry, computational design, computational finance, computational linguistics, computational logic, computational mechanics, computational neuroscience, computational physics, and computational and statistical learning are just a few examples of such interdisciplinary fields of study. Uundergraduate computer science curriculum and their  outreach programs teach students how to think like a computer scientist. Their message is that computer science is not just about programming, but about thinking.

 

According to Jeannette Wing, Computational thinking will be a fundamental skill used by everyone in the world in 21st century: Therefore, in addition to traditional ‘Reading, Writing, and Arithmetic’, current educational system must be prepared to add computational thinking’ to every child's analytical ability.  


So what is Computational Thinking? Well,  it is a collection of diverse skills to do with problem solving that result from studying the nature of computation. It includes some obviously important skills that most subjects help develop, like creativity, ability to explain and team work. It also consists of some very specific problem solving skills such as the ability to think logically, algorithmically and recursively. Computational Science is unique in the way it brings all these diverse skills together.

Computational thinking has the following characteristics [ ]:

Conceptualizing, not programming. Computer science is not computer  programming. Thinking like a computer scientist means more than being able to program a computer. It requires thinking at multiple levels of abstraction;

A way that humans, not computers, think. Computational thinking is a way humans solve problems; it is not trying to get humans to think like computers. Computers are dull and boring; humans are clever and imaginative. We humans make computers exciting. Equipped with computing devices, we use our cleverness to tackle problems we would have dared to take on before the age of computing and build systems with functionality limited only by our imaginations;



Complements and combines mathematical and engineering thinking.  Computer science inherently draws on mathematical thinking, given that, like all sciences, its formal foundations rest on mathematics. Computer science inherently draws on engineering thinking, given that we build systems that interact with the real world. The constraints of the underlying computing device force computer scientists to think computationally, not just mathematically. Being free to build virtual worlds enables us to engineer systems beyond the physical world;



Ideas, not artifacts. It’s not just the software and hardware artifacts we produce that will be physically present everywhere and touch our lives all the time, it will be the computational concepts we use to approach and solve problems, manage our daily lives, and communicate and interact with other people; and



For everyone, everywhere. Computational thinking will be a reality when it is so integral to human endeavors it disappears as an explicit philosophy.

It is more of Mathematical Modelling and Computer Simulation

The most important underlying idea in computational thinking is developing models and simulations of problems that one is trying to study and solve. We are all familiar with the idea of developing mental models—we form mental representations of a problem and often we "play the mental images" in our heads, doing a mental simulation.

    A math model of a "real world" problem is usually complex. A computer program to solve this problem can be thought of as a computer model (a physics model, a math model) for this problem.

Computer models have some of the characteristics of mental modeling as well as some of the characteristics of math modeling and the types of modeling done in other disciplines. If a problem lends itself to computer modeling, then the computer may well be able to carry out the steps (procedures, symbol manipulations) needed to solve the problem.

   Thus, computational thinking, integrating human thinking with the capabilities of computers, provides a powerful new way to solve problems. The computer aspects of computational thinking require one to know capabilities and limitations of computers and how one communicates with (interacts with) a computer system. From an educational point of view, a key aspect of studying any discipline now includes:

1.     Learning some of the capabilities and limitations of computers as an aid to representing and solving the problems of the discipline.

2.     Learning how to actually make use of these computer capabilities.

3.     Learning how to think about problems in the discipline both from a traditional point of view  and from a point of view of possible uses of computers to help solve the problem.

According to David Moursund who wrote more than fifty books on “computers in education”, (available to download from http://iae-pedia.org/ David_Moursund_Books)  there are three types of brains in representing and solving math problems: 


1.     Human brain (a "meat" brain).

2.     Paper & pencil (reading and writing) brain.

3.     Information and Communication Technology (ICT) brain. 


      It was a huge leap forward (a major paradigm shift) when people developed reading and writing as an aid to their meat brain. We are now involved in another huge step forward (a major paradigm shift) as we develop and learn to make effective  ICT brain.

Our educational system is certainly making some progress in helping students to make effective use of the ICT brain and to integrate use of all three types of brains. However, the progress of thoroughly integrating use of the ICT brain in with use of one's meat brain and with paper & pencil brain has been modest. Meanwhile, the ICT brain's capabilities have continued to grow very rapidly.

A number of the articles point to new directions to better prepare students for their futures in our rapidly changing world.

The purpose of this book is to help develop computational thinking using Electronic Spreadsheets. Spreadsheets are readily accessible and the interface is quite intuitive. Logical, algorithmic and recursive thinking which are essential ingredients for Computational thinking is introduced through the use of fractal geometry. Fractal geometry inherently is recursive in nature and its implementation in excel without the need of using any program help  novice students to get a firm grip on the concept of recursion. Further,  beautiful pictures created by the recursive algorithm is so captivating that the readers are likely to try more and more complex fractals.


Another important aspect of the book is that many problems and concepts  in probability theory is explored using spreadsheet simulation. Random number generation from various distributions allows many abstract and difficult concepts to be explored and verified.Calculus is another area where many students find difficult to understand. Again Spreadsheet can be easily employed to explore and verify concepts. 


We are living at a time of a rapid technological change. The rate of change is increasing. Such change brings with it both threats and opportunities. Students can shape their informal and formal education to diminish the threats and increase the opportunities.  Gaining a competitive advantage is one of the underlying themes of the book. Computer technology empowers and enables its users. This means that in any academic area of study, a student can gain a competitive advantage by developing a higher level of “traditional” expertise in the area and by developing an increased level of expertise in using computers in the areas.