We will see how this relates to a computational thinking framework
of algorithmic thinking, evaluation, decomposition, abstraction and generalisation (Selby and Woollard 2013).
The focus
of algorithmic thinking is the algorithm or problem - solving strategy, whereas, the focus of coding is the translation of the algorithm into a language that a computer can execute, a process called implementation.
In today's Q&A, we get a K - 12 overview
of algorithmic thinking from educators Greg Breese (Head of Mathematics at Glen Waverley Secondary College, Victoria) and David Shigrov (Year 7 and 8 STEM teacher at Seymour College, Adelaide, and President of the Mathematical Association of South Australia).
It might also be worth considering the paralleled step - by - step nature
of algorithmic thinking that could lend itself to reduced anxiety in learning.
Thought about more specifically, this strategy can be seen as an example
of algorithmic thinking.
Not exact matches
You can
think of algorithmic trading like the trading bots that now make up 90 %
of trades on the stock market, buying and selling much faster than humanly possible.
If you
think of this neural net as a sequence
of steps, where you're processing information at each step and feeding it to the next one, then one
of the goals from the
algorithmic standpoint is to reduce that to the smallest number
of steps yet get the same results.
They can also work to identify the series
of steps used when given both the input and the output, another essential skill for
algorithmic thinking.
GB:
Algorithmic thinking skills support the development
of general reasoning, problem - solving and communication skills by giving students the skills to fluently interpret and design structured procedures and rule systems.
With
algorithmic thinking, it means younger students have more time to develop effective habits in their processing
of tasks and problem solving.
The point
of this is the need for teachers to demonstrate the
algorithmic thinking process to students and when a hurdle or challenge is encountered, further demonstration
of how this is incorporated into the process.
David Shigrov says
algorithmic thinking has the potential to take primary teachers out
of their comfort zone.
Report writing through the appropriate steps in an investigation
of scientific experiment, or procedural writing through the same or other elements
of English are just a few
of the means in which this (
algorithmic)
thinking can be accessed, utilised and put into practice.
Algorithmic thinking has the potential
of doing this.
Students demonstrate
algorithmic thinking whenever they create or use a well - defined series
of steps to achieve a desired outcome.
Computational
thinking: A problem - solving process that includes, but is not limited to, the following characteristics: formulating problems in a way that enables us to use a computer and other tools to solve them; logically organizing and analyzing data; representing data through abstractions such as models and simulations; automating solutions through
algorithmic thinking (a series
of ordered steps); identifying, analyzing and implementing possible solutions with the goal
of achieving the most efficient and effective combination
of steps and resources; and generalizing and transferring this problem - solving process to a wide variety
of problems.
By varying the format and types
of numbers involved (Q5 - 12), students spent much longer
thinking about the concepts involved in multiplying fractions and less time executing a simple
algorithmic process without
thinking.
If you reach a certain
algorithmic threshold, and Facebook
thinks you're overly annoying other Facebook users or spamming (even though all the groups allow such promo posts), you will be banned from posting in groups for a certain amount
of time.
VII recently interviewed the team at Tweedy, Browne Co. about their value investing strategy, how to find potential opportunities, and their
thoughts on the impact
of passive investment strategies and
algorithmic trading today.
«I hope that the present foray into
algorithmic game theory will encourage our community to continue to
think explicitly about assumptions and goals for crowdsales as we experiment with and build upon the trustless, cryptoeconomic power
of smart contracts.»