Measurement Tools and Units
The system of measurement that is universally used by the scientific world.
What is the metric system?
The definition of a bias.
What is a mistake in research that creates incorrect data.
True or False: You don't need to research before designing.
What is false?
The importance of asking questions and defining problems.
What is leading to descriptions and explanations of how the natural and designed world works and which can be empirically tested?
The definition of criteria.
What are the requirements or checklist for the qualities you want in your creation?
The standard measure of length.
What are meters?
The bias that comes mainly from incorrect data.
What is research bias?
What is the first step of the engineering design process?
What is identifying the criteria and constraint?
The importance of developing and using models.
What are visual representations of ideas?
The definition of constraints.
What are the limits to producing the creation?
The standard measure of liquid volume.
What are liters?
The bias that mainly comes from incorrect measurements.
What is measurement/information bias?
The design you test.
What is a prototype?
The importance of planning and carrying out investigations.
What is the best way to gather data?
The criteria in this problem:
I want to sew a bag with an $80 budget that has lots of pockets, durable zippers, and pretty fabric by the end of the summer.
What are lots of pockets, durable zippers, and pretty fabric?
The standard measure of mass.
What are grams?
The bias that stems from only informing others of studies/projects that go successfully.
What is publication bias?
Another word for improve.
What is optimize?
The importance of analyzing and interpreting data.
What is finding the meaning of the data you found?
The constraints in this problem:
I want to sew a bag with an $80 budget that has lots of pockets, durable zippers, and pretty fabric by the end of the summer.
What is money and time?
The order of the measurement prefixes from smallest to largest.
Pico, Nano, Micro, Milli, Centi, Deci, Kilo, Mega
The bias that happens because of what the researcher believes/thinks.
What is personal bias?
Why you need to test your prototype.
What is accuracy and optimization?
The importance of using mathematics and computational thinking.
What is representing quantitative data?
The reason you need criteria and constraints.
What is knowing what to do and what the limits are?