AI in Education

# Simple adaptive learning system that adjusts difficulty

class AdaptiveLearningSystem:
    def __init__(self, student_name):
        self.student = student_name
        self.difficulty = 1      # 1=easy, 2=medium, 3=hard
        self.correct = 0
        self.total = 0
        self.streak = 0
    
    def questions_by_difficulty(self):
        """Return questions for current difficulty level."""
        bank = {
            1: [  # Easy
                ("What is 2 + 2?", "4"),
                ("What is 5 - 3?", "2"),
                ("What is 3 * 2?", "6"),
            ],
            2: [  # Medium
                ("What is 15 * 8?", "120"),
                ("What is 144 / 12?", "12"),
                ("What is 17 + 28?", "45"),
            ],
            3: [  # Hard
                ("What is 23 * 47?", "1081"),
                ("What is 512 / 16?", "32"),
                ("What is 99 * 101?", "9999"),
            ],
        }
        return bank.get(self.difficulty, bank[1])
    
    def answer_question(self, question, correct_answer, student_answer):
        """Process a student's answer and adapt difficulty."""
        self.total += 1
        is_correct = student_answer.strip() == correct_answer
        
        if is_correct:
            self.correct += 1
            self.streak += 1
            # Increase difficulty after 3 correct in a row
            if self.streak >= 3 and self.difficulty < 3:
                self.difficulty += 1
                self.streak = 0
                return True, "Great work! Moving to harder questions."
            return True, "Correct!"
        else:
            self.streak = 0
            # Decrease difficulty after 2 wrong answers
            if self.total >= 2 and (self.correct / self.total) < 0.5 and self.difficulty > 1:
                self.difficulty -= 1
                return False, f"Not quite. The answer is {correct_answer}. Adjusting to easier questions."
            return False, f"Not quite. The answer is {correct_answer}. Keep trying!"
    
    def stats(self):
        accuracy = (self.correct / self.total * 100) if self.total > 0 else 0
        return f"Score: {self.correct}/{self.total} ({accuracy:.0f}%) | Current Level: {self.difficulty}"

# Simulate a learning session
student = AdaptiveLearningSystem("Alex")

# Simulate answering questions (some correct, some wrong)
session = [
    ("What is 2 + 2?", "4", "4"),          # correct
    ("What is 5 - 3?", "2", "2"),          # correct
    ("What is 3 * 2?", "6", "6"),          # correct - should level up
    ("What is 15 * 8?", "120", "100"),     # wrong
    ("What is 15 * 8?", "120", "120"),     # correct
]

print(f"Adaptive Learning Session for: {student.student}")
print()

for question, correct_answer, student_answer in session:
    is_correct, feedback = student.answer_question(question, correct_answer, student_answer)
    status = "Correct" if is_correct else "Wrong"
    print(f"  Q: {question}")
    print(f"  A: {student_answer} -> {status}")
    print(f"  Feedback: {feedback}")
    print(f"  {student.stats()}")
    print()