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Resources tagged with STEM - Data Handling similar to Terrariums:

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There are 13 results

Broad Topics > STEM mapping > STEM - Data Handling

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Terrariums

Age 11 to 14 Challenge Level:

Build a mini eco-system, and collect and interpret data on how well the plants grow under different conditions.

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Bird Watch

Age 7 to 14 Challenge Level:

Do you know which birds are regular visitors where you live?

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Avalanche!

Age 7 to 14 Challenge Level:

Investigate how avalanches occur and how they can be controlled

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Reaction Timer

Age 11 to 14 Challenge Level:

This problem offers you two ways to test reactions - use them to investigate your ideas about speeds of reaction.

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Observing the Sun and the Moon

Age 7 to 14 Challenge Level:

How does the time of dawn and dusk vary? What about the Moon, how does that change from night to night? Is the Sun always the same? Gather data to help you explore these questions.

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Investigating Epidemics

Age 11 to 16 Challenge Level:

Simple models which help us to investigate how epidemics grow and die out.

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How Do You React?

Age 14 to 16 Challenge Level:

To investigate the relationship between the distance the ruler drops and the time taken, we need to do some mathematical modelling...

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Helicopters

Age 7 to 16 Challenge Level:

Design and test a paper helicopter. What is the best design?

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Counting Dolphins

Age 14 to 16 Challenge Level:

How would you go about estimating populations of dolphins?

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Troublesome Triangles

Age 7 to 14 Challenge Level:

Many natural systems appear to be in equilibrium until suddenly a critical point is reached, setting up a mudslide or an avalanche or an earthquake. In this project, students will use a simple. . . .

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Flip Your Mat!

Age 7 to 14 Challenge Level:

What shape and size of drinks mat is best for flipping and catching?

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Using the Haemocytometer

Age 14 to 16 Challenge Level:

Practise your skills of proportional reasoning with this interactive haemocytometer.

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Solving the Genome Puzzle

Age 14 to 18

The human genome is represented by a string of around 3 billion letters. To deal with such large numbers, genome sequencing relies on clever algorithms. This article investigates.