Mathematics and Computational Thinking in Science

Mathematics and Computational Thinking in Science

Assessment

Interactive Video

Mathematics, Physics, Chemistry, Biology, Science, Computers

9th - 12th Grade

Hard

Created by

Emma Peterson

FREE Resource

Paul Andersen discusses the importance of mathematics and computational thinking in science and engineering. He explains how mathematics is foundational to scientific disciplines and highlights the role of computation in modern science. The video covers examples like Einstein's E=mc^2 and Maxwell's equations, illustrating the integration of math in scientific theories. Andersen introduces computational thinking, emphasizing its significance in modeling and simulations. He also discusses the impact of big data and the need for students to engage with data from an early age. The video concludes with teaching strategies for integrating math and computation in education.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main idea conveyed by John Lewis von Neumann's quote about mathematics?

Mathematics is inherently complex.

Mathematics simplifies the complexity of life.

Mathematics is unrelated to science.

Mathematics is only for mathematicians.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which formula is used to explain the relationship between mass and energy?

P=IV

F=ma

V=IR

E=mc²

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What do Maxwell's equations explain besides electromagnetism?

Fluid dynamics

Quantum mechanics

Optics and electrical circuits

Thermodynamics

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Who coined the term 'computational thinking'?

Seymour Papert

Isaac Newton

Alan Turing

Albert Einstein

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of using simulation software like NetLogo?

To perform physical experiments

To simulate complex systems quickly

To replace all scientific research

To teach basic arithmetic

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is an example of big data in genomics?

Studying weather patterns

Sequencing DNA of various species

Analyzing stock market trends

Mapping ocean currents

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is it important for students to work with data from an early age?

To memorize scientific facts

To focus solely on theoretical knowledge

To avoid using technology

To develop computational skills

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