WGU D685 – Practical Applications of Prompt Engineering | Objective
Assessment (OA) V1 and V2 | Questions and Answers | 2026 Update |
100% Correct.
WGU D685 – Practical Applications of Prompt Engineering
FULL 70-Question Timed Mock OA
Domain 1: Prompt Engineering Fundamentals
1. What is the primary goal of prompt engineering?
A. Reduce AI response time
B. Control AI model architecture
C. Guide AI outputs to meet user intent
D. Increase model creativity
Answer: C
2. Which prompt element defines the role the AI should assume?
A. Context
B. Persona
C. Constraints
D. Output format
Answer: B
3. Why are vague prompts problematic?
A. They increase processing cost
B. They reduce determinism and accuracy
C. They exceed token limits
D. They prevent formatting
Answer: B
4. Which is an example of a zero-shot prompt?
A. Providing three examples before asking
B. Asking a question without examples
C. Using prompt chaining
D. Reusing a template
,Answer: B
5. Which prompt BEST demonstrates specificity?
A. “Explain finance.”
B. “Explain accounting.”
C. “Explain accrual accounting for a small nonprofit.”
D. “Accounting basics.”
Answer: C
Domain 2: Prompt Structure & Components
6. What is the purpose of constraints in a prompt?
A. Increase creativity
B. Limit and guide output
C. Change the AI model
D. Increase randomness
Answer: B
7. Which constraint controls output length?
A. Persona
B. Token limit
C. Temperature
D. Context window
Answer: B
8. Which instruction improves output consistency?
A. “Be creative”
B. “Answer freely”
C. “Use bullet points and headings”
D. “Respond naturally”
Answer: C
9. What does “context” provide in a prompt?
A. Randomness
B. Background information
C. Output formatting
D. Ethical compliance
,Answer: B
10. Which prompt element defines HOW results are displayed?
A. Persona
B. Output format
C. Temperature
D. Context
Answer: B
Domain 3: Few-Shot & Example-Based Prompting
11. What is few-shot prompting?
A. Using minimal tokens
B. Providing examples to guide output
C. Limiting creativity
D. Removing constraints
Answer: B
12. Few-shot prompting is MOST useful when:
A. Tasks are ambiguous
B. Creativity is required
C. Output must follow a pattern
D. Speed is critical
Answer: C
13. What risk can poorly chosen examples introduce?
A. Token overflow
B. Bias or incorrect patterns
C. Reduced speed
D. Shorter responses
Answer: B
14. Which task benefits MOST from few-shot prompting?
A. Brainstorming ideas
B. Structured data extraction
C. Creative storytelling
D. Open discussion
, Answer: B
15. Few-shot prompting primarily improves:
A. Creativity
B. Accuracy and consistency
C. Token efficiency
D. Model size
Answer: B
Domain 4: Iterative Prompting & Refinement
16. What is iterative prompting?
A. Using the same prompt repeatedly
B. Refining prompts through feedback
C. Increasing temperature
D. Removing constraints
Answer: B
17. An AI response is too broad. What should be adjusted FIRST?
A. Temperature
B. Persona
C. Prompt specificity
D. Output format
Answer: C
18. What does prompt chaining involve?
A. Combining multiple models
B. Linking prompts sequentially
C. Increasing context length
D. Removing examples
Answer: B
19. Why is prompt refinement important?
A. Reduces token usage
B. Improves alignment with goals
C. Changes model behavior
D. Increases randomness
Assessment (OA) V1 and V2 | Questions and Answers | 2026 Update |
100% Correct.
WGU D685 – Practical Applications of Prompt Engineering
FULL 70-Question Timed Mock OA
Domain 1: Prompt Engineering Fundamentals
1. What is the primary goal of prompt engineering?
A. Reduce AI response time
B. Control AI model architecture
C. Guide AI outputs to meet user intent
D. Increase model creativity
Answer: C
2. Which prompt element defines the role the AI should assume?
A. Context
B. Persona
C. Constraints
D. Output format
Answer: B
3. Why are vague prompts problematic?
A. They increase processing cost
B. They reduce determinism and accuracy
C. They exceed token limits
D. They prevent formatting
Answer: B
4. Which is an example of a zero-shot prompt?
A. Providing three examples before asking
B. Asking a question without examples
C. Using prompt chaining
D. Reusing a template
,Answer: B
5. Which prompt BEST demonstrates specificity?
A. “Explain finance.”
B. “Explain accounting.”
C. “Explain accrual accounting for a small nonprofit.”
D. “Accounting basics.”
Answer: C
Domain 2: Prompt Structure & Components
6. What is the purpose of constraints in a prompt?
A. Increase creativity
B. Limit and guide output
C. Change the AI model
D. Increase randomness
Answer: B
7. Which constraint controls output length?
A. Persona
B. Token limit
C. Temperature
D. Context window
Answer: B
8. Which instruction improves output consistency?
A. “Be creative”
B. “Answer freely”
C. “Use bullet points and headings”
D. “Respond naturally”
Answer: C
9. What does “context” provide in a prompt?
A. Randomness
B. Background information
C. Output formatting
D. Ethical compliance
,Answer: B
10. Which prompt element defines HOW results are displayed?
A. Persona
B. Output format
C. Temperature
D. Context
Answer: B
Domain 3: Few-Shot & Example-Based Prompting
11. What is few-shot prompting?
A. Using minimal tokens
B. Providing examples to guide output
C. Limiting creativity
D. Removing constraints
Answer: B
12. Few-shot prompting is MOST useful when:
A. Tasks are ambiguous
B. Creativity is required
C. Output must follow a pattern
D. Speed is critical
Answer: C
13. What risk can poorly chosen examples introduce?
A. Token overflow
B. Bias or incorrect patterns
C. Reduced speed
D. Shorter responses
Answer: B
14. Which task benefits MOST from few-shot prompting?
A. Brainstorming ideas
B. Structured data extraction
C. Creative storytelling
D. Open discussion
, Answer: B
15. Few-shot prompting primarily improves:
A. Creativity
B. Accuracy and consistency
C. Token efficiency
D. Model size
Answer: B
Domain 4: Iterative Prompting & Refinement
16. What is iterative prompting?
A. Using the same prompt repeatedly
B. Refining prompts through feedback
C. Increasing temperature
D. Removing constraints
Answer: B
17. An AI response is too broad. What should be adjusted FIRST?
A. Temperature
B. Persona
C. Prompt specificity
D. Output format
Answer: C
18. What does prompt chaining involve?
A. Combining multiple models
B. Linking prompts sequentially
C. Increasing context length
D. Removing examples
Answer: B
19. Why is prompt refinement important?
A. Reduces token usage
B. Improves alignment with goals
C. Changes model behavior
D. Increases randomness
