WGU D685 OA Final Exam Test Bank 2026/2027 –
Practical Applications of Prompt Engineering –
Objective Assessment Complete Questions & Detailed
Verified Answers
300 QUESTIONS
TABLE OF CONTENTS
# TOPIC
1 Fundamentals of Prompt Engineering
2 Prompt Patterns & Techniques
3 Evaluation & Iteration
4 Model Behavior & Limitations
5 Ethics & Safety
6 Practical Applications
7 Advanced Techniques
8 Tooling & Integration
,Q1
What is prompt engineering?
A) The process of designing hardware for AI models
B) The practice of designing inputs to guide AI models toward desired outputs CORRECT
C) A method for training large language models from scratch
D) A technique for compressing model weights
Rationale
Prompt engineering focuses on crafting effective prompts to elicit accurate, relevant responses from AI
systems.
Q2
Which of the following is a key component of a well-structured prompt?
A) Random punctuation
B) Clear instructions and context CORRECT
C) Excessive jargon
D) Ambiguous language
Rationale
Clear instructions and sufficient context help the model understand the task and produce desired
outputs.
Q3
What is a token in the context of large language models?
A) A unit of currency for API usage
B) A piece of text (word, subword, or character) that the model processes CORRECT
C) A security credential
D) A type of neural network layer
2
,Rationale
Models break text into tokens; token limits affect how much input/output can be processed.
Q4
What does the context window refer to?
A) The graphical user interface of an AI application
B) The maximum amount of text (in tokens) a model can consider at once CORRECT
C) The time it takes for a model to respond
D) The number of users a model can serve
Rationale
Context window limits how much prior conversation and input the model can use.
Q5
Which model type is designed to generate text based on prompts?
A) Discriminative model
B) Generative model CORRECT
C) Regression model
D) Clustering model
Rationale
Generative models (e.g., GPT) produce new text in response to prompts.
Q6
What is zero-shot prompting?
A) Providing no instructions at all
3
, B) Asking the model to perform a task without any examples CORRECT
C) Training the model on zero data
D) Using a model with zero parameters
Rationale
Zero-shot relies on the model’s pre-trained knowledge to perform a new task without demonstrations.
Q7
What is few-shot prompting?
A) Using a model with few parameters
B) Providing a small number of examples in the prompt to guide the model CORRECT
C) Asking the model to generate few words
D) Limiting the output length
Rationale
Few-shot prompting includes example inputs/outputs to help the model infer the desired pattern.
Q8
What is the primary purpose of a system prompt?
A) To provide examples for few-shot learning
B) To set the model’s overall behavior, role, and constraints CORRECT
C) To encrypt the conversation
D) To reduce token usage
Rationale
System prompts define the AI’s persona, tone, and boundaries before user interaction.
4
Practical Applications of Prompt Engineering –
Objective Assessment Complete Questions & Detailed
Verified Answers
300 QUESTIONS
TABLE OF CONTENTS
# TOPIC
1 Fundamentals of Prompt Engineering
2 Prompt Patterns & Techniques
3 Evaluation & Iteration
4 Model Behavior & Limitations
5 Ethics & Safety
6 Practical Applications
7 Advanced Techniques
8 Tooling & Integration
,Q1
What is prompt engineering?
A) The process of designing hardware for AI models
B) The practice of designing inputs to guide AI models toward desired outputs CORRECT
C) A method for training large language models from scratch
D) A technique for compressing model weights
Rationale
Prompt engineering focuses on crafting effective prompts to elicit accurate, relevant responses from AI
systems.
Q2
Which of the following is a key component of a well-structured prompt?
A) Random punctuation
B) Clear instructions and context CORRECT
C) Excessive jargon
D) Ambiguous language
Rationale
Clear instructions and sufficient context help the model understand the task and produce desired
outputs.
Q3
What is a token in the context of large language models?
A) A unit of currency for API usage
B) A piece of text (word, subword, or character) that the model processes CORRECT
C) A security credential
D) A type of neural network layer
2
,Rationale
Models break text into tokens; token limits affect how much input/output can be processed.
Q4
What does the context window refer to?
A) The graphical user interface of an AI application
B) The maximum amount of text (in tokens) a model can consider at once CORRECT
C) The time it takes for a model to respond
D) The number of users a model can serve
Rationale
Context window limits how much prior conversation and input the model can use.
Q5
Which model type is designed to generate text based on prompts?
A) Discriminative model
B) Generative model CORRECT
C) Regression model
D) Clustering model
Rationale
Generative models (e.g., GPT) produce new text in response to prompts.
Q6
What is zero-shot prompting?
A) Providing no instructions at all
3
, B) Asking the model to perform a task without any examples CORRECT
C) Training the model on zero data
D) Using a model with zero parameters
Rationale
Zero-shot relies on the model’s pre-trained knowledge to perform a new task without demonstrations.
Q7
What is few-shot prompting?
A) Using a model with few parameters
B) Providing a small number of examples in the prompt to guide the model CORRECT
C) Asking the model to generate few words
D) Limiting the output length
Rationale
Few-shot prompting includes example inputs/outputs to help the model infer the desired pattern.
Q8
What is the primary purpose of a system prompt?
A) To provide examples for few-shot learning
B) To set the model’s overall behavior, role, and constraints CORRECT
C) To encrypt the conversation
D) To reduce token usage
Rationale
System prompts define the AI’s persona, tone, and boundaries before user interaction.
4
