Hour of Code: Build your own animal classifier! Lesson Plan

Overview

In this code activity, students are introduced to branching, one of the critical decision-making constructs in computer programming, often implemented as an if statement. If statements determine whether a condition being tested is True or False, and will execute different statements on that basis.

The theme of this activity is Taxonomy - the process of classifying species in Biology according to their key features. The classification of a species is often phrased in terms of whether a feature is present or not present -a dichotomous (or binary True/False) comparison.

In this activity, students will use the programming language Python to build a simple biological specifies classifier based on the physical features and characteristics of different species.


Learning Objectives

Students will:

  • write programs using the Python programming language
  • recognise that breaking down a problem into smaller steps (decomposition) makes it easier to solve problems
  • recognise that steps in algorithms need to accurate and precise
  • debug algorithms
  • recognise that problems can have multiple solutions
  • get input from the user
  • use variables to store data
  • manipulate strings
  • utilise branching (if, if-else, and if-elif-else) in programs

Extended Activities

Classifying living things with computer science (unplugged activity)

In this unplugged activity from the Australian Computing Academy, students design an algorithm to classify living things and create a visual representation in the form of a decision tree. This activity would work well as an introduction to the topic, and prepares students for the project at the end of the coding activity.


How does programming help scientists?

Biologists, like all scientists, use data they collect from experiments and observations to test ideas and learn new things about the world. As more data becomes available, analysing that data so that you can draw conclusions about it becomes more difficult to do manually.

Being able to write computer programs to access, manipulate and process data allows you to test your ideas against larger amounts of data. This allows for simulations to be built, new questions and hypotheses to be developed, and for new solutions and products to be designed. Many scientists now spend more time analysing their data than they do conducting their experiments. To do this efficiently, they need to work out how to represent their data so they can write code to analyse it. Some good examples from biology include how geneticists are able to analyse DNA by representing it as text strings, and being able to determine how diseases can spread throughout a population so they can design a suitable strategy for preventing further outbreaks.

What other examples of ways in which programming is transforming the work of scientists can students think of or find?

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