
    Design a function for an adaptive learning platform that analyzes a student's performance pattern (represented as a binary sequence of correct/incorrect answers) to determine how many unique difficulty adjustments would be needed when considering different starting points in their learning sequence. Given a binary string of student responses and the number of rotational analyses to perform, calculate how many of these rotated sequences would result in an odd numerical value, indicating a need for difficulty adjustment.
    

    
def odd_Equivalent(s, n):
    """
    Design a function for an adaptive learning platform that analyzes a student's performance pattern (represented as a binary sequence of correct/incorrect answers) to determine how many unique difficulty adjustments would be needed when considering different starting points in their learning sequence. Given a binary string of student responses and the number of rotational analyses to perform, calculate how many of these rotated sequences would result in an odd numerical value, indicating a need for difficulty adjustment.
    

    """
def odd_Equivalent(s, n):
    """
    Design a function for an adaptive learning platform that analyzes a student's performance pattern (represented as a binary sequence of correct/incorrect answers) to determine how many unique difficulty adjustments would be needed when considering different starting points in their learning sequence. Given a binary string of student responses and the number of rotational analyses to perform, calculate how many of these rotated sequences would result in an odd numerical value, indicating a need for difficulty adjustment.
    

    """
    count = 0
    for i in range(0, n):
        if s[i] == '1':
            count = count + 1
    return count