AI-300 Practice Question: Generative AI Quality Assurance And Observability
You are building a RAG application and notice that the model sometimes hallucinates information not present in the retrieved documents. Which evaluation metric should you prioritize to mitigate this?
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
Groundedness specifically assesses whether the generated response is derived from the retrieved documents.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Groundedness
Why this is correct
Groundedness verifies the response is based on the source context.
- ✗
Relevance
Why it's wrong here
Relevance checks if the question is answered, not the factual basis.
- ✗
Performance
Why it's wrong here
Performance relates to speed, not accuracy.
- ✗
Fluency
Why it's wrong here
Fluency does not check for external truth.
About these practice questions
One of 204 original AI-300 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. 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.