Code.org - Unit 6 Review
Quiz
•
Computers
•
9th - 12th Grade
•
Practice Problem
•
Easy
Used 593+ times
FREE Resource
About this resource
This quiz focuses on fundamental computer science concepts related to algorithms and computational thinking, specifically covering algorithmic problem-solving, search algorithms, computational efficiency, and parallel computing. The content is appropriate for grades 9-12, as it requires students to understand abstract computational concepts, analyze algorithmic complexity using mathematical notation (polynomial vs. exponential time), and distinguish between theoretical computer science principles like decidability and heuristic approaches. Students need a solid foundation in mathematical reasoning to grasp efficiency classifications (n², n³ versus 2ⁿ, 3ⁿ), logical thinking to understand the step-by-step nature of algorithms, and the ability to compare and contrast different computational approaches like linear versus binary search methods. The quiz also requires comprehension of advanced concepts such as undecidable problems and the trade-offs between sequential and parallel computing architectures. This quiz was created by a classroom teacher who designed it for students studying computer science in grades 9-12. This assessment serves as an excellent review tool for Unit 6 of a comprehensive computer science curriculum, helping students consolidate their understanding of core algorithmic concepts before moving to more advanced topics. Teachers can deploy this quiz as a formative assessment to identify knowledge gaps, use it as homework to reinforce classroom learning, or implement it as a warm-up activity to activate prior knowledge before introducing new computational concepts. The question format makes it ideal for both individual practice and collaborative review sessions where students can discuss the reasoning behind correct answers. This quiz aligns with Computer Science Principles standards including CSP-AAP-2.O (explaining how the use of procedural abstraction manages complexity), CSP-AAP-4.A (representing algorithms using pseudocode), and CSP-CSN-1.E (explaining how parallel and distributed computing leverage multiple computers), supporting students' development of computational thinking skills essential for advanced computer science coursework.
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15 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A general description of a task that can (or cannot) be solved with an algorithm
Problem
Algorithm
Sequencing
Iteration
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A finite set of instructions that accomplish a task.
Problem
Algorithm
Sequencing
Iteration
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
_________ is an informal language that helps programmers develop algorithms, literally means “fake code.” Its like writing code for yourself before writing it in proper program language format.
Problem
Algorithm
Pseudocode
Iteration
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A search algorithm which checks each element of a list, in order, until the desired value is found or all elements in the list have been checked.
Linear Search
Binary Search
Pseudocode
Iteration
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A search algorithm that starts at the middle of a sorted set of numbers and removes half of the data; this process repeats until the desired value is found or all elements have been eliminated.
Linear Search
Binary Search
Pseudocode
Iteration
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
A measure of how many steps are needed to complete an algorithm.
Problem
Algorithm
Pseudocode
Efficiency
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Any algorithm whose efficiency includes an n2, n3, n4 … is called ___________.
Problem
Polynomial
Pseudocode
Efficiency
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