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System Overview

Abstract​

Auto Suggestion Quiz is a web-based learning application designed to help students practice making correct decisions when working with AI-generated code suggestions. Instead of simply generating quizzes from static question banks, the system presents students with multiple code options (including AI-generated suggestions) and asks them to evaluate, select, and justify the most correct solution. The platform adapts the difficulty and topic selection based on the student’s performance, reinforcing both technical understanding and critical thinking. Users receive immediate feedback, explanations, and performance tracking over time. The primary goal of Auto Suggestion Quiz is to improve students’ ability to recognize correct code, avoid common AI-generated mistakes, and build stronger confidence in real-world programming and debugging scenarios.

Purpose​

The purpose of Auto Suggestion Quiz is to support students learning programming by providing structured practice in evaluating code suggestions generated by AI tools. As AI assistants become more common in academic and professional environments, students must learn how to validate and select correct solutions rather than relying on AI output without verification.

This system is designed to strengthen students’ decision-making skills, code comprehension, and debugging mindset through repeated practice and explanation-based feedback.

Goals and Objectives​

Auto Suggestion Quiz is designed to achieve the following objectives:

  • Encourage critical thinking when reviewing AI-generated code suggestions.
  • Improve student accuracy in selecting correct code solutions.
  • Reduce student reliance on blindly copying AI-generated answers.
  • Provide adaptive practice that adjusts difficulty based on performance.
  • Provide clear explanations and feedback to reinforce learning.
  • Track student progress across topics and quiz attempts over time.

Target Users​

The system is intended for the following user groups:

Students​

  • Students learning introductory and intermediate programming concepts.
  • Students practicing for coding interviews or technical assessments.
  • Students who frequently use AI tools (ChatGPT, Copilot, etc.) for coding.

Instructors (Optional / Future Support)​

  • Professors or teaching assistants who may assign quizzes.
  • Instructors who may want to review aggregated student progress.

High-Level System Description​

Auto Suggestion Quiz is a browser-based application where users practice answering programming questions by selecting the most correct solution from multiple options. The options may include AI-generated code suggestions as well as known correct solutions.

The system emphasizes reasoning and decision-making. Users are not only asked to select an answer but also receive feedback explaining why the correct option is correct and why the incorrect options are wrong. Over time, the system adapts to the user’s skill level and provides performance tracking across topics.

Key Features​

The system includes the following key features:

  • Multiple-choice code selection quizzes

    • Users select the best solution from several code options.

  • AI-suggestion evaluation

    • The quiz experience is designed to simulate real-world AI-assisted coding decisions.

  • Adaptive difficulty

    • Question difficulty adjusts based on user performance.

  • Immediate feedback

    • Users receive results and explanations after answering questions.

  • Topic-based practice

    • Users can practice specific programming topics.

  • Progress tracking

    • Users can view performance history and improvement over time.

  • User authentication

    • Users can register, log in, and save progress.

Scope​

In Scope​

The following items are included in the system scope:

  • User registration, login, and authentication.
  • Quiz topic selection and difficulty selection.
  • Presenting code-based quiz questions with multiple options.
  • Adaptive difficulty adjustments based on quiz results.
  • Automatic grading for selection-based questions.
  • Feedback and explanations for quiz answers.
  • Storing quiz attempts and performance history.

Out of Scope​

The following items are not included in the current project scope:

  • Fully open-ended code writing and execution inside the platform.
  • Full integration with external Learning Management Systems (Canvas, Blackboard, etc.).
  • Real-time multiplayer features or competitive leaderboards.
  • AI model training or fine-tuning as part of the platform.
  • Advanced instructor dashboards (may be considered future work).

Assumptions​

The system is built under the following assumptions:

  • Users have access to a modern web browser and stable internet.
  • Users have at least basic programming knowledge depending on quiz difficulty.
  • AI-generated code suggestions may contain errors, making evaluation necessary.
  • Students benefit from repeated practice with explanations and feedback.

Constraints​

The system must operate under the following constraints:

  • The system must be accessible via standard web browsers.
  • The system must store user data securely and protect privacy.
  • The system should provide fast response times for quizzes and grading.
  • The system should be scalable to support multiple users.
  • The system must remain simple enough for beginner students to use.

Success Metrics​

The system will be considered successful if:

  • Users improve accuracy over time across quiz topics.
  • Users demonstrate reduced repeated mistakes across similar question types.
  • Users report increased confidence in evaluating AI-generated code suggestions.
  • The system reliably stores quiz history and provides meaningful feedback.
  • The application remains stable and usable during normal student usage.
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Last updated by Han Wang