QUS-5: Adaptive Learning Algorithms Implementation

[IvanoskiHarmonia]

Feature Overview

Summary

Develop adaptive learning algorithms to personalize quiz difficulty based on user performance.

Rationale

• Motivation: To offer a tailored learning experience that adapts to the user's skill level.
• Functionality: Dynamic adjustment of quiz difficulty based on how well the user is performing.
• Impact: Involves developing new algorithms, updating quiz generation logic, and potentially modifying the database schema.

Acceptance Criteria

• Implementation of adaptive algorithms to adjust question difficulty.
• Seamless integration with existing quiz structures.
• Effective calibration of difficulty levels based on user responses.

Acceptance Test Cases:

• Test Case 1: If a user consistently answers correctly, then subsequent questions become more challenging.
• Test Case 2: If a user struggles with certain topics, then the difficulty level is adjusted accordingly.

Additional Information

Consider the balance in difficulty levels to avoid extreme fluctuations that could discourage users.