如何设计一个支持在线答题中的学习过程监控和学习行为建模的系统

import datetime
import pymongo

# 连接数据库
client = pymongo.MongoClient("mongodb://localhost:27017/")
db = client["learning_monitoring"]
collection = db["answer_data"]

# 记录学生答题信息
def record_answer_data(user_id, question_id, answer, is_correct):
    data = {
        "user_id": user_id,
        "question_id": question_id,
        "answer": answer,
        "is_correct": is_correct,
        "timestamp": datetime.datetime.now()
    }
    collection.insert_one(data)

from sklearn.cluster import KMeans

# 加载学生答题数据
def load_answer_data(user_id):
    data = collection.find({"user_id": user_id})
    return [d["is_correct"] for d in data]

# 建立学生的学习行为模型
def build_behavior_model(user_id):
    answer_data = load_answer_data(user_id)
    model = KMeans(n_clusters=2)
    model.fit(answer_data)
    return model

# 输出学习行为模型
def print_behavior_model(model):
    print("Cluster centers:", model.cluster_centers_)
    print("Labels:", model.labels_)