CoT Method for SAT-Level English Question Maker

 

CoT Method for SAT-Level English Question Maker

Problem Statement (Primary Prompt):
Generate an SAT-level English question.

Steps:

1. Define the Skill to Be Tested
2. Create the Question Prompt
3. Generate Answer Choices
4. Designate the Correct Answer
5. Add Explanation or Rationale

Assumptions:

• The questions are for SAT-level English.
• Each question will test only one skill.

Calculations:

• Use curriculum guidelines or SAT standards for the skill being tested.
• Use Natural Language Processing (NLP) tools for generating choices and explanations.

Conclusions:

• The final SAT-level English question, including the prompt, choices, correct answer, and explanation.

Step-by-Step Implementation in Python

Step 1: Define the Skill to Be Tested

For this prototype, let's focus on Reading Comprehension.

Step 2: Create the Question Prompt

We will generate a reading comprehension question based on a short passage.

Step 3: Generate Answer Choices

We will create multiple-choice options for the question.

Step 4: Designate the Correct Answer

Identify the correct answer from the generated choices.

Step 5: Add Explanation or Rationale

Provide a rationale for the correct answer.

Let's implement this in Python:

import pandas as pd
import random

# Define the skill to be tested
skill = "Reading Comprehension"

# Sample passage
passage = """
In recent years, researchers have discovered a significant link between physical exercise and improved mental health. 
Regular physical activity has been shown to reduce symptoms of anxiety and depression, enhance mood, and improve overall cognitive function.
"""

# Create the question prompt
question_prompt = "Based on the passage, which of the following statements best summarizes the main point?"

# Generate answer choices
answer_choices = [
    "A) Physical exercise has no impact on mental health.",
    "B) Regular physical activity can improve mental health.",
    "C) Mental health is solely dependent on diet.",
    "D) Cognitive function is not influenced by physical activity."
]

# Designate the correct answer
correct_answer = "B) Regular physical activity can improve mental health."

# Add explanation or rationale
explanation = "The passage highlights the benefits of physical exercise on mental health, including reducing anxiety and depression and improving cognitive function."

# Create a DataFrame to represent the CoT Method template
data = {
    "Skill": [skill],
    "Passage": [passage],
    "Question Prompt": [question_prompt],
    "Answer Choices": [", ".join(answer_choices)],
    "Correct Answer": [correct_answer],
    "Explanation": [explanation]
}

df = pd.DataFrame(data)

# Save to an Excel file
output_path = "SAT_Level_English_Question.xlsx"
df.to_excel(output_path, index=False)

# Display the DataFrame
print(df)

Output

The output will be an Excel file named SAT_Level_English_Question.xlsx containing the generated SAT-level English question along with the passage, answer choices, the correct answer, and the explanation.

You can download the generated Excel file here.

Summary

This prototype demonstrates the process of generating an SAT-level English question using the CoT Method. By following the structured steps, we ensure that the question aligns with the desired standards and effectively tests a specific skill. This approach can be automated further and expanded to include various skills and question types.