Bebras India Computational Thinking Challenge 2020
1st - 13th February, 2021
Student participation: 103,114 in age groups 8-18 in 7 languages across 19 states.
Results will be declared by 15 March, 2021.
Bebras India Computational Thinking Challenge 2019!
Participation: 178,239 students!
The 2019 Bebras India Challenge was held from 18th – 30th November for age groups 8-18 in English, Gujarati, Marathi, Tamil, and Telugu. 178,239 students participated from 649 schools in 15 states in the challenge.
Bebras (www.bebras.org) is an international student Computational Thinking Challenge organised in over 60 countries and designed to get students all over the world excited about computing. The challenge is a great way to learn about computational thinking and problem solving skills.
The Bebras challenges are made of a set of short problems called Bebras tasks. The tasks are fun, engaging and based on problems that Computer Scientists enjoy solving. The tasks require logical thinking and can be solved without prior knowledge of computational thinking. The aim is to solve as many as you can in the allotted time.
Bebras India Challenge is organized by ACM India’s CSpathshala initiative (www.cspathshala.org). ACM India/CSpathshala’s goal is to make it possible so that every child in India learns Computational Thinking.
The 2018 Bebras India Challenge was held from 19th – 30th November for age groups 8-18. It was offered in English, Gujarati, Marathi, and Telugu. 137,081 students from 380 schools across 12 states participated in 2018 Bebras India Challenge.
Bebras Tasks (Also featured in Sakal Newspaper in Education: NIE)
Kittu, our beaver, loves to travel to different countries on her adventures solving puzzles and making new friends too. Kittu always examines all the available information before reaching any conclusion. Kittu wants you to join her in this journey across the world and help solve the Bebras Tasks.
Exciting Football Game
Kittu goes to watch a football match between Pune Paltan and Dabang Delhi teams ...
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What is Computational Thinking?
Computational Thinking is the process of formulating a problem, finding a solution to the problem and expressing it in such a way that humans or machines can understand the solution. It involves the use of problem solving methods to decompose the problem into smaller manageable subproblems, identifying the right abstractions so as to deal with scale and complexity, finding existing patterns or models that can be adapted, building an algorithm to solve the problem and in case of multiple solutions, analysing the solutions on multiple parameters to identify the one that best meets the given situation.
Algorithms underlie the most basic tasks everyone performs, from following a simple cooking recipe to providing complicated driving directions. There is a general misconception that algorithms are used only to solve mathematical problems and are not applicable in other disciplines, whereas there are enough examples from daily lives that require us to use algorithms. For example, the steps involved in brushing teeth, getting ready for school, steps performed during a lab experiment etc. Understanding and articulating algorithms as a sequence of precise steps helps us think logically.
Students can be exposed to the CT concept of abstraction by creating models in physics (such as a model of the solar system). Abstraction helps students learn to strip away complexity and unnecessary detail to focus only on the important parts of the problem. Maps, building plans etc. are very good examples of abstraction.
The primary goal of teaching CT is to develop the ability to solve problems. Experts feel that this does not require the use of computers and can be taught as a series of interesting, engaging and fun activities. This avoids confusing Computer Science with programming or learning application software, makes the activities available to those children who do not have access to computers, and overcomes the hurdle of having to learn to program before being able to explore ideas and articulating solutions as algorithms. Students soon realize that they are capable of finding solutions to problems on their own, rather than being given a solution to apply to the problem. For example, children can play the game of Tic-Tac-Toe and then develop the rules of the game and winning strategies from observation.