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Artificial Intelligence Final Year Topic: Design and Evaluation of Question Generation Source Fidelity

This Artificial Intelligence final year project examines creating practice questions that remain answerable from a supplied passage through a bounded AI prototype with an explicit baseline and evaluation dataset.

Why choose this project topic?

A study of creating practice questions that remain answerable from a supplied passage gives this topic a concrete purpose beyond simply adding an AI model. Comparing answerability, ambiguity and source coverage helps a student demonstrate capability, inspect failure cases and explain where human review or a simpler method remains necessary.

How effectively can question generation source fidelity support creating practice questions that remain answerable from a supplied passage, evaluated using answerability, ambiguity and source coverage?

Choose a feasible licensed or synthetic dataset and available compute budget, then agree a narrow evaluation for creating practice questions that remain answerable from a supplied passage with your supervisor.

Proposed project objectives

  1. 01Define the task, evidence and evaluation assumptions for creating practice questions that remain answerable from a supplied passage.
  2. 02Use original teaching passages, generate bounded question types and have reviewers check answerability, ambiguity and unsupported premises.
  3. 03Measure answerability, ambiguity and source coverage against a stated baseline and analyse failure cases.

A suggested research approach

Use original teaching passages, generate bounded question types and have reviewers check answerability, ambiguity and unsupported premises. Check dataset permissions and keep evaluation examples separate from model development. Record model versions, prompts or training settings, then compare answerability, ambiguity and source coverage using repeatable runs and retain incorrect outputs for a transparent limitations discussion.

What you will need

  • Original teaching passages
  • Question review rubric
  • Permitted generation model

Keep your project scope clear

Generated questions need review and should not be presented as validated examination items. Generated project writing does not include a trained or deployed AI application.

Artificial Intelligence project chapter outline

Use this outline as a starting point. You can edit the chapter titles to match your department’s format during setup.

  1. Chapter 1Introduction
  2. Chapter 2Literature Review
  3. Chapter 3System Analysis and Design
  4. Chapter 4System Implementation and Testing
  5. Chapter 5Summary, Conclusion and Recommendations

Turn this topic into your own final year project.

Your title, department, research question and outline are ready. Add your institution, personalise the details and continue to your project workspace.

Generate the Complete Project Generation uses your word balance. Review the draft and supply your own verified research findings.