AI-300 Practice Question: Generative AI Quality Assurance And Observability
You are evaluating an LLM application using Prompt Flow. You want to measure the 'Groundedness' of the model response relative to the retrieved context. Which evaluator should you configure?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Groundedness evaluator
The Groundedness evaluator in Prompt Flow checks if the response is supported by the context provided.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Relevance evaluator
Why it's wrong here
Relevance measures how well the response addresses the prompt.
- ✓
Groundedness evaluator
Why this is correct
Groundedness specifically measures factual consistency with source context.
- ✗
Coherence evaluator
Why it's wrong here
Coherence measures how well the response flows logically.
- ✗
Fluency evaluator
Why it's wrong here
Fluency measures grammatical correctness.
About these practice questions
This AI-300 question is part of Courseiva's 204-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-300 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-300 exam.