Designing a Knowledge Point System for Online Quiz Platforms: Structure, API, and Smart Recommendations

Building a Hierarchical Knowledge Point Structure

To ensure better organization and maintainability of an online quiz system, it's essential to establish a clear hierarchical structure for knowledge points. A tree-like structure helps represent parent-child relationships between topics. For example, mathematics can be divided into 'Basic Math', 'Algebra', and 'Geometry', each containing specific sub-topics.

From a data management perspective, using a relational database to store the structure is recommended. A basic knowledge point table should include the following fields:

CREATE TABLE knowledge_points (
  id INT AUTO_INCREMENT PRIMARY KEY,
  name VARCHAR(255) NOT NULL,
  parent_id INT DEFAULT 0
);

The parent_id field links each knowledge point to its parent, enabling the creation of a hierarchical system.

Designing Question Structure and Answer APIs

The answer interface should support retrieving and validating questions based on knowledge point IDs. Every question must be linked to a knowledge point for efficient categorization. The structure of the question table may look like this:

CREATE TABLE questions (
  id INT AUTO_INCREMENT PRIMARY KEY,
  content TEXT NOT NULL,
  options TEXT NOT NULL,
  correct_answer VARCHAR(10) NOT NULL,
  knowledge_point_id INT NOT NULL
);

The API can then accept a knowledge point ID to fetch related questions from the database:

// Example: Retrieve questions under a specific knowledge point
function getQuestionsByKnowledgePoint($kp_id) {
  $sql = "SELECT * FROM questions WHERE knowledge_point_id = ?";
  // Execute query
}

Implementing Knowledge Navigation and Question Selection

To improve usability, a navigation interface displaying the knowledge point hierarchy is beneficial. Users can browse or expand each topic layer to access the related questions easily.

// Recursive function to build a tree of knowledge points
function buildTree($data, $parentId = 0) {
  $tree = [];
  foreach ($data as $item) {
    if ($item['parent_id'] == $parentId) {
      $children = buildTree($data, $item['id']);
      if ($children) {
        $item['children'] = $children;
      }
      $tree[] = $item;
    }
  }
  return $tree;
}

The front-end can render this tree structure and dynamically load questions based on the selected node.

Integrating Smart Recommendation Features

Smart recommendations significantly enhance the user experience. By analyzing a user’s previous performance and selected knowledge areas, the system can suggest relevant or frequently mistaken questions for reinforcement.

Common recommendation approaches include:

• Collaborative Filtering: Suggest questions based on the behavior of similar users
• Content-Based Filtering: Recommend questions related to user’s preferred or weak areas

Here is a basic idea of how a recommendation function could be implemented:

function recommendQuestions($user_id) {
  // Analyze user's incorrect answers and frequently accessed knowledge points
  // Recommend new questions based on this analysis
  // Return recommendation list
}

Conclusion

A robust knowledge point system forms the backbone of a well-structured online quiz platform. From organizing knowledge points to linking them with questions, implementing a navigable interface, and offering smart recommendations, every component plays a crucial role in delivering a personalized and effective learning experience. Proper system design not only enhances engagement but also boosts educational outcomes.