How to implement the answering statistics function in online answering questions

How to implement the answer statistics function in online answering requires specific code examples

In an online answer system, the answer statistics function is very important for understanding students’ answering and evaluation Teaching effect is very important. This article will introduce how to implement the answer statistics function in online question answering through programming, and provide some specific code examples.

1. Requirements for answering statistics

The answering statistics function in the online answering system should at least include the following requirements:

1. Statistics on the overall situation: including the total number of people, answers Basic statistical information such as the number of people and the total number of answers.
2. Statistics on personal answer status: You can view the answer status of each student, including the number of questions answered correctly, the number of questions answered incorrectly, etc.
3. Statistics on questions: You can view statistical information such as the correct answer rate and incorrect answer rate for each question.
4. Answer analysis: You can analyze the answer data and provide some indicators, such as difficulty coefficient, discrimination, etc.

2. Use a database to store answer data

When implementing the answer statistics function, it is best to use a database to store answer data. You can use a relational database such as MySQL or a non-relational database such as MongoDB.

First, create a student table and a question table. The student table contains at least student ID, name and other fields, and the question table contains at least question ID, question content, answer and other fields.

Then, create an answer sheet to store students’ answer data. The answer table contains at least answer ID, student ID, question ID, answer and other fields.

3. Statistics of the overall situation

The overall statistics of the situation can be achieved by querying the data in the database. First calculate the total number of people, that is, the number of records in the student table. Then calculate the number of answerers, that is, the number of unique student IDs in the answer sheet. Finally, calculate the total number of answers, that is, the number of records in the answer sheet.

The specific code examples are as follows:

import pymysql

# 连接数据库
conn = pymysql.connect(host='localhost', user='root', password='123456', database='online_test')
cursor = conn.cursor()

# 统计总人数
cursor.execute("SELECT COUNT(*) FROM student")
total_students = cursor.fetchone()[0]

# 统计答题人数
cursor.execute("SELECT DISTINCT student_id FROM answer")
total_answered_students = cursor.fetchone()[0]

# 统计答题总量
cursor.execute("SELECT COUNT(*) FROM answer")
total_answers = cursor.fetchone()[0]

# 打印统计结果
print("总人数:", total_students)
print("答题人数:", total_answered_students)
print("答题总量:", total_answers)

# 关闭数据库连接
cursor.close()
conn.close()

4. Statistics of individual responses

Statistics of individual responses can be achieved by querying the record of the specified student ID in the answer table. You can count the number of questions the student answered correctly, the number of questions he answered incorrectly, etc.

The specific code examples are as follows:

import pymysql

# 连接数据库
conn = pymysql.connect(host='localhost', user='root', password='123456', database='online_test')
cursor = conn.cursor()

# 输入学生ID
student_id = input("请输入学生ID: ")

# 统计答对题目数量
cursor.execute("SELECT COUNT(*) FROM answer WHERE student_id=%s AND answer=correct_answer", student_id)
correct_answers = cursor.fetchone()[0]

# 统计答错题目数量
cursor.execute("SELECT COUNT(*) FROM answer WHERE student_id=%s AND answer!=correct_answer", student_id)
incorrect_answers = cursor.fetchone()[0]

# 打印统计结果
print("答对题目数量:", correct_answers)
print("答错题目数量:", incorrect_answers)

# 关闭数据库连接
cursor.close()
conn.close()

5. Statistical question status

Statistics on the question status can be achieved by querying the record of the specified question ID in the answer table. The correct answer rate, incorrect answer rate, etc. of the question can be counted.

The specific code examples are as follows:

import pymysql

# 连接数据库
conn = pymysql.connect(host='localhost', user='root', password='123456', database='online_test')
cursor = conn.cursor()

# 输入题目ID
question_id = input("请输入题目ID: ")

# 统计答对率
cursor.execute("SELECT COUNT(*) FROM answer WHERE question_id=%s AND answer=correct_answer", question_id)
correct_count = cursor.fetchone()[0]

# 统计答错率
cursor.execute("SELECT COUNT(*) FROM answer WHERE question_id=%s AND answer!=correct_answer", question_id)
incorrect_count = cursor.fetchone()[0]

# 统计总回答次数
total_count = correct_count + incorrect_count

# 计算答对率和答错率
correct_rate = correct_count / total_count
incorrect_rate = incorrect_count / total_count

# 打印统计结果
print("答对率:", correct_rate)
print("答错率:", incorrect_rate)

# 关闭数据库连接
cursor.close()
conn.close()

6. Answer analysis

Answer analysis can evaluate students' answer performance through various indicators. For example, the difficulty coefficient and discrimination index of each question can be calculated.

Difficulty coefficient (Difficulty) refers to the proportion of students who answered the question, which can be calculated by counting the questions.

Discrimination refers to the difference between the proportion of high-scoring students who answered the question and the proportion of low-scoring students who answered the question. Discrimination can be calculated by calculating the proportion of high-scoring students who answered the questions correctly and the proportion of low-scoring students who answered the questions correctly.

The specific code examples are as follows:

import pymysql

# 连接数据库
conn = pymysql.connect(host='localhost', user='root', password='123456', database='online_test')
cursor = conn.cursor()

# 输入题目ID
question_id = input("请输入题目ID: ")

# 计算难度系数
cursor.execute("SELECT COUNT(*) FROM answer WHERE question_id=%s", question_id)
total_count = cursor.fetchone()[0]
cursor.execute("SELECT COUNT(*) FROM answer WHERE question_id=%s AND answer=correct_answer", question_id)
correct_count = cursor.fetchone()[0]
difficulty = correct_count / total_count

# 计算区分度
cursor.execute("SELECT COUNT(*) FROM answer WHERE question_id=%s AND answer=correct_answer AND student_score>=90", question_id)
high_score_correct_count = cursor.fetchone()[0]
cursor.execute("SELECT COUNT(*) FROM answer WHERE question_id=%s AND answer=correct_answer AND student_score<60", question_id)
low_score_correct_count = cursor.fetchone()[0]
discrimination = high_score_correct_count / total_count - low_score_correct_count / total_count

# 打印统计结果
print("难度系数:", difficulty)
print("区分度:", discrimination)

# 关闭数据库连接
cursor.close()
conn.close()

The above is the code example to implement the answer statistics function in online answering. By querying and counting the data in the database, students' answers and statistical information on the questions can be obtained, which is helpful to understand students' learning situations and evaluate teaching effects. Please make appropriate modifications and expansions according to the actual situation.

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