WGU D684 Objective Assessment &
Pre-Assessment: The Complete
Questions & Answers Exam Prep
Guide (2025–2026)
What does computational thinking involve?
Solving problems using logical steps and systematic approaches.
Rationale: Computational thinking focuses on breaking down complex
problems, recognizing patterns, abstracting relevant information, and
designing step-by-step algorithms—not just memorizing syntax or writing
code.
What are the four pillars of computational thinking?
Decomposition, pattern recognition, abstraction, and algorithm design.
Rationale: These four pillars form the foundation of computational thinking.
Decomposition breaks problems down, pattern recognition identifies
similarities, abstraction filters out unnecessary details, and algorithm design
creates step-by-step solutions.
What is decomposition in computational thinking?
Breaking a complex problem down into smaller, more manageable parts.
,Rationale: Decomposition makes large problems easier to solve by dividing
them into subproblems that can be addressed individually, similar to how a
large project is divided into tasks.
What is pattern recognition in computational thinking?
Identifying similarities, trends, or regularities within data or between
different problems.
Rationale: Recognizing patterns allows problem-solvers to apply known
solutions to new problems and make predictions based on observed
regularities.
What is abstraction in computational thinking?
Removing unnecessary details and focusing only on essential information.
Rationale: Abstraction filters out irrelevant details so that only the
information essential for solving a particular problem remains, making the
problem more manageable.
What is algorithm design in computational thinking?
Creating a step-by-step procedure to solve a problem.
Rationale: Algorithm design involves developing precise, ordered
instructions that, when followed, produce a solution to a problem.
Which step of Pólya's problem-solving method involves coming up
with possible strategies?
Devising a plan.
Rationale: After understanding the problem, the next step is to devise a
plan—strategizing possible approaches before executing any solution.
, What is an algorithm?
A step-by-step set of instructions designed to perform a specific task or
solve a problem.
Rationale: Algorithms are fundamental to computer science and can be
expressed in various forms, including natural language, pseudocode,
flowcharts, or programming languages.
Which search algorithm checks each element in a list one by one until
the desired element is found?
Sequential search (linear search).
Rationale: Sequential search works on both sorted and unsorted data but
has O(n) time complexity, meaning it may need to check every element.
What is binary search?
A search algorithm that finds the position of a target value within a sorted
array by repeatedly dividing the search interval in half.
Rationale: Binary search is efficient with O(log n) time complexity, but it
requires the data to be sorted beforehand.
Which sorting algorithm builds the final sorted array one item at a
time?
Insertion sort.
Rationale: Insertion sort builds the sorted array by repeatedly taking the
next element and inserting it into its correct position among the already-
sorted elements.
What is a bubble sort?
Pre-Assessment: The Complete
Questions & Answers Exam Prep
Guide (2025–2026)
What does computational thinking involve?
Solving problems using logical steps and systematic approaches.
Rationale: Computational thinking focuses on breaking down complex
problems, recognizing patterns, abstracting relevant information, and
designing step-by-step algorithms—not just memorizing syntax or writing
code.
What are the four pillars of computational thinking?
Decomposition, pattern recognition, abstraction, and algorithm design.
Rationale: These four pillars form the foundation of computational thinking.
Decomposition breaks problems down, pattern recognition identifies
similarities, abstraction filters out unnecessary details, and algorithm design
creates step-by-step solutions.
What is decomposition in computational thinking?
Breaking a complex problem down into smaller, more manageable parts.
,Rationale: Decomposition makes large problems easier to solve by dividing
them into subproblems that can be addressed individually, similar to how a
large project is divided into tasks.
What is pattern recognition in computational thinking?
Identifying similarities, trends, or regularities within data or between
different problems.
Rationale: Recognizing patterns allows problem-solvers to apply known
solutions to new problems and make predictions based on observed
regularities.
What is abstraction in computational thinking?
Removing unnecessary details and focusing only on essential information.
Rationale: Abstraction filters out irrelevant details so that only the
information essential for solving a particular problem remains, making the
problem more manageable.
What is algorithm design in computational thinking?
Creating a step-by-step procedure to solve a problem.
Rationale: Algorithm design involves developing precise, ordered
instructions that, when followed, produce a solution to a problem.
Which step of Pólya's problem-solving method involves coming up
with possible strategies?
Devising a plan.
Rationale: After understanding the problem, the next step is to devise a
plan—strategizing possible approaches before executing any solution.
, What is an algorithm?
A step-by-step set of instructions designed to perform a specific task or
solve a problem.
Rationale: Algorithms are fundamental to computer science and can be
expressed in various forms, including natural language, pseudocode,
flowcharts, or programming languages.
Which search algorithm checks each element in a list one by one until
the desired element is found?
Sequential search (linear search).
Rationale: Sequential search works on both sorted and unsorted data but
has O(n) time complexity, meaning it may need to check every element.
What is binary search?
A search algorithm that finds the position of a target value within a sorted
array by repeatedly dividing the search interval in half.
Rationale: Binary search is efficient with O(log n) time complexity, but it
requires the data to be sorted beforehand.
Which sorting algorithm builds the final sorted array one item at a
time?
Insertion sort.
Rationale: Insertion sort builds the sorted array by repeatedly taking the
next element and inserting it into its correct position among the already-
sorted elements.
What is a bubble sort?
