WGU D685 PRACTICAL APPLICATIONS OF PROMPT
ENGINEERING
OBJECTIVE ASSESSMENT (OA) 2026 PRACTICE EXAM
100 Multiple-Choice Questions with Answers and Rationales
Currently Up
Question 1
What is the primary goal of prompt engineering in generative AI?
A. To write longer and more complex prompts
B. To maximize the likelihood of a desired model output
C. To reduce the number of model parameters
D. To train the model from scratch with new data
Correct Answer: B
Rationale: Prompt engineering focuses on designing inputs that guide a generative AI model
to produce accurate, relevant, and useful outputs without modifying the model's underlying
weights. The goal is to craft prompts that elicit the best possible response from the existing
model.
Question 2
Which of the following is an example of a zero-shot prompt?
A. "Translate 'Hello' to Spanish." (without examples)
B. "Here is an example: 'Cat -> Gato'. Now translate 'Dog'."
C. "Classify this sentiment as positive or negative after reading 5 examples."
D. "Generate a story based on the following three examples of fairy tales."
Correct Answer: A
Rationale: Zero-shot prompting means the model receives no examples within the prompt; it
must rely solely on its pre-trained knowledge to perform the task. Options B, C, and D all
provide examples, making them one-shot or few-shot prompts.
,Question 3
A user provides no examples and simply asks an AI model to classify customer feedback as
positive, neutral, or negative. Which prompting approach is being used?
A. Few-shot prompting
B. One-shot prompting
C. Chain-of-thought prompting
D. Zero-shot prompting
Correct Answer: D
Rationale: Zero-shot prompting involves giving the model a task without any examples. The
model must use its pre-existing knowledge to perform the classification. Few-shot and one-
shot prompting include examples, while chain-of-thought involves step-by-step reasoning.
Question 4
What is the primary purpose of "few-shot" prompting?
A. To provide the AI with a large dataset to train on before generating a response
B. To instruct the AI to generate a specific number of responses for a single prompt
C. To give the AI a few examples of the desired input-output format within the prompt
D. To reduce the computational cost of generating a response
Correct Answer: C
Rationale: Few-shot prompting includes a small number of examples that demonstrate the
task, helping the AI understand the pattern and format required without needing extensive
fine-tuning. The examples guide the model toward the desired output structure.
Question 5
A user wants an AI system to generate a professional email requesting a project deadline
extension while maintaining a respectful and persuasive tone. Which prompting technique
would most likely improve the quality of the response?
A. Using vague instructions without specifying tone or audience
B. Providing clear context, audience, and desired tone within the prompt
C. Asking multiple unrelated questions in a single prompt
D. Omitting the purpose of the email entirely
Correct Answer: B
Rationale: AI systems perform better when prompts provide context, audience information,
,goals, and tone requirements. Specificity improves relevance and quality. Vague or unfocused
prompts lead to generic or irrelevant outputs.
Question 6
A prompt asks an AI model to summarize a research article in exactly three concise bullet
points. Which characteristic of prompt engineering is being demonstrated?
A. Prompt ambiguity
B. Open-ended prompting
C. Use of output constraints and formatting instructions
D. Hallucination reduction through fact checking
Correct Answer: C
Rationale: Output constraints specify the desired format, length, and structure, helping the
model produce more targeted responses. Explicit formatting instructions guide the model
toward a predictable and structured output.
Question 7
What is the most effective way to mitigate a large language model's tendency to generate
"hallucinations" when asked to summarize a provided document?
A. Ask the model to generate the summary in a bulleted list format
B. Instruct the model to only use information explicitly present in the provided document
C. Add a system prompt that encourages creativity
D. Increase the temperature parameter to add variability
Correct Answer: B
Rationale: Explicitly instructing the model to restrict its response to information contained
within the provided document is the most effective way to reduce hallucinations. Bulleted lists
affect format but do not address factual accuracy, and increasing temperature typically
increases variability and potential hallucinations.
Question 8
What is an AI hallucination?
A. A language model generating plausible but false or misleading information
B. An AI system refusing to make predictions on unfamiliar input
, C. The model correctly identifying patterns in data
D. An AI system exceeding its training data capabilities
Correct Answer: A
Rationale: A hallucination occurs when an AI model generates information that appears
plausible and coherent but is factually incorrect or entirely fabricated. This is a known
limitation of large language models.
Question 9
Which key benefit is associated with artificial intelligence?
A. Implementing common sense reasoning
B. Predicting outcomes beyond training data reliably
C. Performing independent human-like reasoning
D. Processing data in real time
Correct Answer: D
Rationale: AI systems excel at processing large volumes of data rapidly and in real-time,
enabling immediate insights and responses. While AI can simulate aspects of reasoning, it
does not truly implement common sense, predict reliably beyond its training data, or perform
independent reasoning in the human sense.
Question 10
What is a "system prompt" in a conversational LLM?
A. A prompt written by the user after the model responds
B. Initial instructions defining model behavior, role, or constraints
C. A prompt that is ignored by the model
D. A technical error message displayed by the system
Correct Answer: B
Rationale: System prompts are initial instructions that define the model's behavior, role, or
constraints for the entire conversation. They set the context and parameters within which the
model operates.
Question 11
Which prompting technique involves breaking down a complex problem into a series of
intermediate steps?
ENGINEERING
OBJECTIVE ASSESSMENT (OA) 2026 PRACTICE EXAM
100 Multiple-Choice Questions with Answers and Rationales
Currently Up
Question 1
What is the primary goal of prompt engineering in generative AI?
A. To write longer and more complex prompts
B. To maximize the likelihood of a desired model output
C. To reduce the number of model parameters
D. To train the model from scratch with new data
Correct Answer: B
Rationale: Prompt engineering focuses on designing inputs that guide a generative AI model
to produce accurate, relevant, and useful outputs without modifying the model's underlying
weights. The goal is to craft prompts that elicit the best possible response from the existing
model.
Question 2
Which of the following is an example of a zero-shot prompt?
A. "Translate 'Hello' to Spanish." (without examples)
B. "Here is an example: 'Cat -> Gato'. Now translate 'Dog'."
C. "Classify this sentiment as positive or negative after reading 5 examples."
D. "Generate a story based on the following three examples of fairy tales."
Correct Answer: A
Rationale: Zero-shot prompting means the model receives no examples within the prompt; it
must rely solely on its pre-trained knowledge to perform the task. Options B, C, and D all
provide examples, making them one-shot or few-shot prompts.
,Question 3
A user provides no examples and simply asks an AI model to classify customer feedback as
positive, neutral, or negative. Which prompting approach is being used?
A. Few-shot prompting
B. One-shot prompting
C. Chain-of-thought prompting
D. Zero-shot prompting
Correct Answer: D
Rationale: Zero-shot prompting involves giving the model a task without any examples. The
model must use its pre-existing knowledge to perform the classification. Few-shot and one-
shot prompting include examples, while chain-of-thought involves step-by-step reasoning.
Question 4
What is the primary purpose of "few-shot" prompting?
A. To provide the AI with a large dataset to train on before generating a response
B. To instruct the AI to generate a specific number of responses for a single prompt
C. To give the AI a few examples of the desired input-output format within the prompt
D. To reduce the computational cost of generating a response
Correct Answer: C
Rationale: Few-shot prompting includes a small number of examples that demonstrate the
task, helping the AI understand the pattern and format required without needing extensive
fine-tuning. The examples guide the model toward the desired output structure.
Question 5
A user wants an AI system to generate a professional email requesting a project deadline
extension while maintaining a respectful and persuasive tone. Which prompting technique
would most likely improve the quality of the response?
A. Using vague instructions without specifying tone or audience
B. Providing clear context, audience, and desired tone within the prompt
C. Asking multiple unrelated questions in a single prompt
D. Omitting the purpose of the email entirely
Correct Answer: B
Rationale: AI systems perform better when prompts provide context, audience information,
,goals, and tone requirements. Specificity improves relevance and quality. Vague or unfocused
prompts lead to generic or irrelevant outputs.
Question 6
A prompt asks an AI model to summarize a research article in exactly three concise bullet
points. Which characteristic of prompt engineering is being demonstrated?
A. Prompt ambiguity
B. Open-ended prompting
C. Use of output constraints and formatting instructions
D. Hallucination reduction through fact checking
Correct Answer: C
Rationale: Output constraints specify the desired format, length, and structure, helping the
model produce more targeted responses. Explicit formatting instructions guide the model
toward a predictable and structured output.
Question 7
What is the most effective way to mitigate a large language model's tendency to generate
"hallucinations" when asked to summarize a provided document?
A. Ask the model to generate the summary in a bulleted list format
B. Instruct the model to only use information explicitly present in the provided document
C. Add a system prompt that encourages creativity
D. Increase the temperature parameter to add variability
Correct Answer: B
Rationale: Explicitly instructing the model to restrict its response to information contained
within the provided document is the most effective way to reduce hallucinations. Bulleted lists
affect format but do not address factual accuracy, and increasing temperature typically
increases variability and potential hallucinations.
Question 8
What is an AI hallucination?
A. A language model generating plausible but false or misleading information
B. An AI system refusing to make predictions on unfamiliar input
, C. The model correctly identifying patterns in data
D. An AI system exceeding its training data capabilities
Correct Answer: A
Rationale: A hallucination occurs when an AI model generates information that appears
plausible and coherent but is factually incorrect or entirely fabricated. This is a known
limitation of large language models.
Question 9
Which key benefit is associated with artificial intelligence?
A. Implementing common sense reasoning
B. Predicting outcomes beyond training data reliably
C. Performing independent human-like reasoning
D. Processing data in real time
Correct Answer: D
Rationale: AI systems excel at processing large volumes of data rapidly and in real-time,
enabling immediate insights and responses. While AI can simulate aspects of reasoning, it
does not truly implement common sense, predict reliably beyond its training data, or perform
independent reasoning in the human sense.
Question 10
What is a "system prompt" in a conversational LLM?
A. A prompt written by the user after the model responds
B. Initial instructions defining model behavior, role, or constraints
C. A prompt that is ignored by the model
D. A technical error message displayed by the system
Correct Answer: B
Rationale: System prompts are initial instructions that define the model's behavior, role, or
constraints for the entire conversation. They set the context and parameters within which the
model operates.
Question 11
Which prompting technique involves breaking down a complex problem into a series of
intermediate steps?
