How to implement automatic question generation and automatic question selection functions in online answering questions

How to realize the automatic question generation and automatic question selection functions in online answering questions

Introduction:
With the development of the Internet, online answering systems have become an important part of education and training One of the most commonly used tools. However, in the face of a huge question bank and a large number of students, the workload of manually setting and selecting questions is quite large. In order to improve efficiency and accuracy, we need to implement automatic question generation and automatic question selection functions in online answering questions.

1. Implementation of automatic question generation function
Automatic question generation refers to automatically generating questions through the software system based on the questions and rules in the question bank. The specific implementation steps are as follows:

1. Automatic generation of mathematical questions
   Mathematical questions usually involve formulas, operators, variables, etc. We can realize the function of automatically generating mathematical questions through programming languages. For example, using the Python language, you can generate math problems by referencing functions that comply with rules, such as generating addition, subtraction, multiplication, and division problems.

import random

def generate_addition_question():
    a = random.randint(1, 100)
    b = random.randint(1, 100)
    return f"{a} + {b} = ..."

def generate_subtraction_question():
    a = random.randint(1, 100)
    b = random.randint(1, a)
    return f"{a} - {b} = ..."

def generate_multiplication_question():
    a = random.randint(1, 10)
    b = random.randint(1, 10)
    return f"{a} × {b} = ..."

def generate_division_question():
    a = random.randint(1, 100)
    b = random.randint(1, 10)
    c = a * b
    return f"{c} ÷ {b} = ..."

The above code example is an implementation method for generating four arithmetic operations questions.

2. Automatic generation of non-mathematical questions
   For non-mathematical questions, natural language processing (NLP) technology can be used to generate them. For example, we can use semantic analysis algorithms and rules to generate options for multiple-choice questions.
3. Definition of question rules
   The rules of the question include question type, difficulty, knowledge points, etc. By defining question rules, you can control the scope and content of question generation.
4. Establishment of question bank
   Building a question bank is the basis for automatic question generation. The question bank can be classified and organized according to various question types and knowledge points, so that the software system can quickly filter and generate according to user needs.

2. Implementation of automatic topic selection function
Automatic topic selection refers to automatically matching appropriate topics through the software system based on factors such as students' learning status, ability level, and personalized needs. The specific implementation steps are as follows:

1. Obtaining student information
   Through the student’s login information and learning records, the student’s learning status, ability level, learning preferences and other information can be obtained.
2. Establishment of student model
   According to student information, a student model can be established, including learning curve, knowledge point mastery, error type analysis, etc.
3. Matching of questions and student models
   Match the questions with the student model, and select appropriate questions based on factors such as the student's learning situation and ability level. The appropriateness of the question can be assessed by calculating the difficulty coefficient of the question and the match between the student's ability.
4. Question Recommendation and Feedback
   Generate a list of question recommendations based on the matching results, and provide feedback based on students' choices and answers to help students better master knowledge.

Conclusion:
By realizing the automatic question generation and automatic question selection functions, the efficiency and accuracy of the online answering system can be greatly improved, providing students with a personalized and efficient learning experience. Of course, realizing these functions also requires the support of more professional technologies and algorithms, as well as the continuous updating and maintenance of the question bank.

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