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comet_blooms_taxonomy_few_shot.txt
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comet_blooms_taxonomy_few_shot.txt
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Generate questions in each level of Bloom’s taxonomy.
Passage: "In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor. Since an algorithm's running time may vary among different inputs of the same size, one commonly considers the worst-case time complexity, which is the maximum amount of time required for inputs of a given size. Less common, and usually specified explicitly, is the average-case complexity, which is the average of the time taken on inputs of a given size (this makes sense because there are only a finite number of possible inputs of a given size). In both cases, the time complexity is generally expressed as a function of the size of the input."
Remembering = What does time complexity measure?
Understanding = How is time complexity estimated?
Applying = How would you determine the worst-case time complexity of an algorithm?
Analyzing = What is the difference between the worst-case and average-case time complexity?
Evaluating = Is time complexity a reliable measure of an algorithm's performance?
Creating = How can you modify an algorithm to reduce its time complexity?
Passage: "Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The 'signal' at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs."
Remembering =
Generate questions in each level of Bloom’s taxonomy.
Passage: "In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor. Since an algorithm's running time may vary among different inputs of the same size, one commonly considers the worst-case time complexity, which is the maximum amount of time required for inputs of a given size. Less common, and usually specified explicitly, is the average-case complexity, which is the average of the time taken on inputs of a given size (this makes sense because there are only a finite number of possible inputs of a given size). In both cases, the time complexity is generally expressed as a function of the size of the input."
Remembering = What does time complexity measure?
Understanding = How is time complexity estimated?
Applying = How would you determine the worst-case time complexity of an algorithm?
Analyzing = What is the difference between the worst-case and average-case time complexity?
Evaluating = Is time complexity a reliable measure of an algorithm's performance?
Creating = How can you modify an algorithm to reduce its time complexity?
Passage: "Comets: Mysterious Visitors from Space
What Are Comets?
Comets are fascinating celestial objects that travel through space. They are often referred to as "dirty snowballs" or "icy dirtballs" because they are composed of a mixture of ice, dust, and rock.
Where Do Comets Come From?
Comets mainly come from two regions in space:
1. Oort Cloud: This is a distant, spherical cloud of icy objects that surrounds our solar system. Comets from the Oort Cloud can take thousands or even millions of years to reach the inner solar system.
2. Kuiper Belt: This is another region beyond the orbit of Neptune that contains icy bodies, including comets. Some comets originate from the Kuiper Belt and have shorter orbits.
The Parts of a Comet
Comets have three main parts:
1. Nucleus: This is the solid core of the comet, made up of ice and rock. It can be several kilometers in size.
2. Coma: As a comet approaches the Sun, heat causes the nucleus to release gas and dust. This forms a glowing cloud around the nucleus called the coma.
3. Tail: The solar wind and radiation from the Sun push the gas and dust away from the nucleus, creating a bright tail that always points away from the Sun. The tail can be visible from Earth and can stretch for millions of kilometers.
Famous Comets
- Halley's Comet: One of the most famous comets, it returns to the inner solar system roughly every 76 years.
- Hale-Bopp: This comet was exceptionally bright and visible from Earth in 1997.
- Comet NEOWISE: Discovered in 2020, this comet put on a beautiful display in the night sky.
Why Study Comets?
Scientists study comets to learn more about the early solar system and the building blocks of planets. Comets may contain clues about the origins of water and organic molecules on Earth.
Viewing Comets
You can sometimes see comets with the naked eye, especially during their closest approach to the Sun. Keep an eye on astronomy websites and news to learn about upcoming comet sightings.
Fun Fact
Comets are often named after their discoverers, making them a part of scientific history.
Comets are mysterious and captivating objects in the night sky. Exploring their origins and behaviors can teach us a lot about the vast universe beyond our planet."
Remembering =Generate questions in each level of Bloom’s taxonomy.
Passage: "In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor. Since an algorithm's running time may vary among different inputs of the same size, one commonly considers the worst-case time complexity, which is the maximum amount of time required for inputs of a given size. Less common, and usually specified explicitly, is the average-case complexity, which is the average of the time taken on inputs of a given size (this makes sense because there are only a finite number of possible inputs of a given size). In both cases, the time complexity is generally expressed as a function of the size of the input."
Remembering = What does time complexity measure?
Understanding = How is time complexity estimated?
Applying = How would you determine the worst-case time complexity of an algorithm?
Analyzing = What is the difference between the worst-case and average-case time complexity?
Evaluating = Is time complexity a reliable measure of an algorithm's performance?
Creating = How can you modify an algorithm to reduce its time complexity?
Passage: "Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons. An artificial neuron receives signals then processes them and can signal neurons connected to it. The 'signal' at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs."
Remembering =
Generate questions in each level of Bloom’s taxonomy.
Passage: "In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by the algorithm, supposing that each elementary operation takes a fixed amount of time to perform. Thus, the amount of time taken and the number of elementary operations performed by the algorithm are taken to be related by a constant factor. Since an algorithm's running time may vary among different inputs of the same size, one commonly considers the worst-case time complexity, which is the maximum amount of time required for inputs of a given size. Less common, and usually specified explicitly, is the average-case complexity, which is the average of the time taken on inputs of a given size (this makes sense because there are only a finite number of possible inputs of a given size). In both cases, the time complexity is generally expressed as a function of the size of the input."
Remembering = What does time complexity measure?
Understanding = How is time complexity estimated?
Applying = How would you determine the worst-case time complexity of an algorithm?
Analyzing = What is the difference between the worst-case and average-case time complexity?
Evaluating = Is time complexity a reliable measure of an algorithm's performance?
Creating = How can you modify an algorithm to reduce its time complexity?
Passage: "Comets: Mysterious Visitors from Space
What Are Comets?
Comets are fascinating celestial objects that travel through space. They are often referred to as "dirty snowballs" or "icy dirtballs" because they are composed of a mixture of ice, dust, and rock.
Where Do Comets Come From?
Comets mainly come from two regions in space:
1. Oort Cloud: This is a distant, spherical cloud of icy objects that surrounds our solar system. Comets from the Oort Cloud can take thousands or even millions of years to reach the inner solar system.
2. Kuiper Belt: This is another region beyond the orbit of Neptune that contains icy bodies, including comets. Some comets originate from the Kuiper Belt and have shorter orbits.
The Parts of a Comet
Comets have three main parts:
1. Nucleus: This is the solid core of the comet, made up of ice and rock. It can be several kilometers in size.
2. Coma: As a comet approaches the Sun, heat causes the nucleus to release gas and dust. This forms a glowing cloud around the nucleus called the coma.
3. Tail: The solar wind and radiation from the Sun push the gas and dust away from the nucleus, creating a bright tail that always points away from the Sun. The tail can be visible from Earth and can stretch for millions of kilometers.
Famous Comets
- Halley's Comet: One of the most famous comets, it returns to the inner solar system roughly every 76 years.
- Hale-Bopp: This comet was exceptionally bright and visible from Earth in 1997.
- Comet NEOWISE: Discovered in 2020, this comet put on a beautiful display in the night sky.
Why Study Comets?
Scientists study comets to learn more about the early solar system and the building blocks of planets. Comets may contain clues about the origins of water and organic molecules on Earth.
Viewing Comets
You can sometimes see comets with the naked eye, especially during their closest approach to the Sun. Keep an eye on astronomy websites and news to learn about upcoming comet sightings.
Fun Fact
Comets are often named after their discoverers, making them a part of scientific history.
Comets are mysterious and captivating objects in the night sky. Exploring their origins and behaviors can teach us a lot about the vast universe beyond our planet."
Remembering =