
    Develop a function to analyze a student's sorted learning style assessment data to determine if a specific learning approach is their dominant preference. The function should take three inputs: a chronologically sorted array of learning style codes from multiple assessments, the total number of assessments conducted, and a specific learning style code to evaluate. Your function must determine if the given learning style appears in more than half of the student's assessments, indicating it should be the primary focus for their personalized learning path.
    

    
def binary_search(arr, low, high, x):
    if high >= low:
        mid = (low + high) // 2
        if (mid == 0 or x > arr[mid - 1]) and arr[mid] == x:
            return mid
        elif x > arr[mid]:
            return binary_search(arr, mid + 1, high, x)
        else:
            return binary_search(arr, low, mid - 1, x)
    return -1

def is_majority(arr, n, x):
    """
    Develop a function to analyze a student's sorted learning style assessment data to determine if a specific learning approach is their dominant preference. The function should take three inputs: a chronologically sorted array of learning style codes from multiple assessments, the total number of assessments conducted, and a specific learning style code to evaluate. Your function must determine if the given learning style appears in more than half of the student's assessments, indicating it should be the primary focus for their personalized learning path.
    

    """
def binary_search(arr, low, high, x):
    if high >= low:
        mid = (low + high) // 2
        if (mid == 0 or x > arr[mid - 1]) and arr[mid] == x:
            return mid
        elif x > arr[mid]:
            return binary_search(arr, mid + 1, high, x)
        else:
            return binary_search(arr, low, mid - 1, x)
    return -1

def is_majority(arr, n, x):
    """
    Develop a function to analyze a student's sorted learning style assessment data to determine if a specific learning approach is their dominant preference. The function should take three inputs: a chronologically sorted array of learning style codes from multiple assessments, the total number of assessments conducted, and a specific learning style code to evaluate. Your function must determine if the given learning style appears in more than half of the student's assessments, indicating it should be the primary focus for their personalized learning path.
    

    """
    i = binary_search(arr, 0, n - 1, x)
    if i == -1:
        return False
    if i + n // 2 <= n - 1 and arr[i + n // 2] == x:
        return True
    else:
        return False