To implement a system that only accepts open-ended questions like "What would make your life easier?" in a coding environment, you can use a combination of regular expressions, natural language processing (NLP), and form validation techniques. Below is a conceptual example using JavaScript, with some Python examples for more advanced processing:

1. Basic Validation with JavaScript

This is a simple implementation that checks if the question starts with "What," "How," or "Why," and doesn't contain keywords like "which," "select," or "choose."

function validateQuestion(question) {
    // Convert the question to lowercase for uniformity
    question = question.toLowerCase();

    // Define regex patterns for open-ended question starters
    const openEndedPattern = /^(what|how|why)/;
    // Define regex patterns to avoid closed-ended questions
    const closedEndedKeywords = /(which|select|choose|is|are|do|does|would)/;

    // Check if the question starts with an open-ended word and doesn't contain closed-ended keywords
    if (openEndedPattern.test(question) && !closedEndedKeywords.test(question)) {
        return true; // Question is valid
    } else {
        return false; // Question is invalid
    }
}

// Example usage
const question = "What would make your life easier?";
if (validateQuestion(question)) {
    console.log("Valid question");
} else {
    console.log("Invalid question, please rephrase.");
}

2. Enhanced Validation with NLP (Python Example)

For more complex validation, you can use Python with an NLP library like spaCy to analyze the structure of the sentence. This example checks if the question is open-ended by analyzing the first word and ensuring it's not a binary or multiple-choice question.

import spacy

# Load the spaCy model for English
nlp = spacy.load("en_core_web_sm")

def is_open_ended_question(question):
    # Process the question with spaCy
    doc = nlp(question.lower())

    # Check if the first word is an open-ended question starter
    open_ended_starters = {"what", "how", "why"}
    first_word = doc[0].text

    # Simple check based on first word
    if first_word in open_ended_starters:
        # Additional checks for closed-ended patterns
        if any(keyword in question for keyword in ["which", "select", "choose", "is", "are", "do", "does", "would"]):
            return False
        return True

    return False

# Example usage
question = "What would make your life easier?"
if is_open_ended_question(question):
    print("Valid question")
else:
    print("Invalid question, please rephrase.")

3. Integration into a Web Form

You can integrate the above JavaScript function into a web form to validate the input before submission. Here’s a basic HTML example:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Question Validator</title>
    <script>
        function validateQuestionForm() {
            const question = document.getElementById("questionInput").value;
            if (validateQuestion(question)) {
                alert("Valid question submitted!");
                return true;
            } else {
                alert("Invalid question. Please rephrase to be more open-ended.");
                return false;
            }
        }

        function validateQuestion(question) {
            question = question.toLowerCase();
            const openEndedPattern = /^(what|how|why)/;
            const closedEndedKeywords = /(which|select|choose|is|are|do|does|would)/;
            return openEndedPattern.test(question) && !closedEndedKeywords.test(question);
        }
    </script>
</head>
<body>
    <form onsubmit="return validateQuestionForm()">
        <label for="questionInput">Enter your question:</label><br>
        <input type="text" id="questionInput" name="questionInput"><br><br>
        <input type="submit" value="Submit">
    </form>
</body>
</html>

4. Advanced Implementation

If you want to perform more advanced checks, such as using machine learning models to classify the question type, you could:

This setup allows you to ensure that only questions prompting subjective, open-ended responses are accepted, enhancing the quality of the feedback or data you collect.