WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Question 1
Which component of the CO-STAR framework specifies the format in
which the AI should output its response (e.g., bullet points, table,
JSON)?
A) Context
B) Objective
C) Style
D) Response
Correct Answer: D
Rationale: The "Response" component in the CO-STAR framework
dictates the output format, ensuring the AI delivers the information in
the exact structure required by the user.
Question 2
When an LLM provides factually incorrect information presented with
high confidence, this phenomenon is best described as:
A) Overfitting
B) Hallucination
C) Token truncation
D) Prompt leakage
Correct Answer: B
Rationale: A hallucination occurs when a language model generates
plausible-sounding but completely incorrect or fabricated facts without
realizing it is wrong.
,WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Question 3
What is the primary advantage of using "Few-Shot" prompting over
"Zero-Shot" prompting?
A) It reduces the total token count used in the API call.
B) It entirely eliminates model hallucinations.
C) It provides concrete input-output examples that guide the model on
pattern, tone, and format.
D) It forces the model to bypass its safety guardrails.
Correct Answer: C
Rationale: Few-shot prompting includes examples of desired behavior
within the prompt, helping the model understand expectations through
pattern matching.
Question 4
Which prompt engineering technique explicitly instructs the model to
break down a complex problem into intermediate reasoning steps
before arriving at the final answer?
A) Role prompting
B) Chain-of-Thought (CoT) prompting
C) Negative constraints
D) Zero-shot classification
Correct Answer: B
,WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Rationale: Chain-of-Thought prompting encourages step-by-step logical
decomposition, significantly improving accuracy on math, logic, and
multi-step reasoning tasks.
Question 5
In the CO-STAR framework, what does the letter 'A' stand for?
A) Accuracy
B) Algorithm
C) Audience
D) Action
Correct Answer: C
Rationale: In CO-STAR, 'A' stands for Audience (who the response is
written for, e.g., beginners, executives, children).
Question 6
You notice an LLM is ignoring a negative constraint (e.g., "Do not use
bullet points"). What is the most effective prompt engineering fix?
A) Move the negative constraint to the very beginning or end of the
prompt and emphasize it in uppercase.
B) Increase the temperature setting to 2.0.
C) Remove all other instructions so the model only focuses on the
negative rule.
D) Switch from a few-shot prompt to a zero-shot prompt.
Correct Answer: A
, WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Rationale: LLMs sometimes pay more attention to primacy and recency
effects (the beginning and end of prompts). Reinforcing constraints with
emphasis or repositioning them helps compliance.
Question 7
What is the primary purpose of assigning a specific "Persona" or role to
an LLM in a prompt?
A) To encrypt the prompt data.
B) To narrow down the model's perspective, tone, and domain expertise
to match the target context.
C) To prevent the model from generating tokens outside the English
language.
D) To reduce subscription costs.
Correct Answer: B
Rationale: Persona prompting frames the model's behavioral
parameters, aligning its vocabulary, depth of knowledge, and tone with
a specific professional role.
Question 8
Which parameter in LLM settings typically controls the randomness and
creativity of the generated output?
A) Context Window
B) Temperature
C) Token Limit
D) Top-K
questions and well detailed answers
Question 1
Which component of the CO-STAR framework specifies the format in
which the AI should output its response (e.g., bullet points, table,
JSON)?
A) Context
B) Objective
C) Style
D) Response
Correct Answer: D
Rationale: The "Response" component in the CO-STAR framework
dictates the output format, ensuring the AI delivers the information in
the exact structure required by the user.
Question 2
When an LLM provides factually incorrect information presented with
high confidence, this phenomenon is best described as:
A) Overfitting
B) Hallucination
C) Token truncation
D) Prompt leakage
Correct Answer: B
Rationale: A hallucination occurs when a language model generates
plausible-sounding but completely incorrect or fabricated facts without
realizing it is wrong.
,WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Question 3
What is the primary advantage of using "Few-Shot" prompting over
"Zero-Shot" prompting?
A) It reduces the total token count used in the API call.
B) It entirely eliminates model hallucinations.
C) It provides concrete input-output examples that guide the model on
pattern, tone, and format.
D) It forces the model to bypass its safety guardrails.
Correct Answer: C
Rationale: Few-shot prompting includes examples of desired behavior
within the prompt, helping the model understand expectations through
pattern matching.
Question 4
Which prompt engineering technique explicitly instructs the model to
break down a complex problem into intermediate reasoning steps
before arriving at the final answer?
A) Role prompting
B) Chain-of-Thought (CoT) prompting
C) Negative constraints
D) Zero-shot classification
Correct Answer: B
,WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Rationale: Chain-of-Thought prompting encourages step-by-step logical
decomposition, significantly improving accuracy on math, logic, and
multi-step reasoning tasks.
Question 5
In the CO-STAR framework, what does the letter 'A' stand for?
A) Accuracy
B) Algorithm
C) Audience
D) Action
Correct Answer: C
Rationale: In CO-STAR, 'A' stands for Audience (who the response is
written for, e.g., beginners, executives, children).
Question 6
You notice an LLM is ignoring a negative constraint (e.g., "Do not use
bullet points"). What is the most effective prompt engineering fix?
A) Move the negative constraint to the very beginning or end of the
prompt and emphasize it in uppercase.
B) Increase the temperature setting to 2.0.
C) Remove all other instructions so the model only focuses on the
negative rule.
D) Switch from a few-shot prompt to a zero-shot prompt.
Correct Answer: A
, WGU D685 Practical Applications of Prompt OA actual 2026 Exam
questions and well detailed answers
Rationale: LLMs sometimes pay more attention to primacy and recency
effects (the beginning and end of prompts). Reinforcing constraints with
emphasis or repositioning them helps compliance.
Question 7
What is the primary purpose of assigning a specific "Persona" or role to
an LLM in a prompt?
A) To encrypt the prompt data.
B) To narrow down the model's perspective, tone, and domain expertise
to match the target context.
C) To prevent the model from generating tokens outside the English
language.
D) To reduce subscription costs.
Correct Answer: B
Rationale: Persona prompting frames the model's behavioral
parameters, aligning its vocabulary, depth of knowledge, and tone with
a specific professional role.
Question 8
Which parameter in LLM settings typically controls the randomness and
creativity of the generated output?
A) Context Window
B) Temperature
C) Token Limit
D) Top-K
