
    Design an adaptive learning system that creates a personalized learning path by breaking down complex topics into simpler sub-modules. Given an initial module difficulty level, the system needs to generate progressively easier versions by reducing the complexity by 2 points at each step until reaching the basic level (zero or below). Calculate the total complexity points across all difficulty levels in this adaptive path, which helps determine the overall learning effort required. For example, if a module starts at difficulty level 7, the path would include levels 7, 5, 3, and 1, and the system should sum these values to quantify the total complexity of the personalized learning journey.
    

    
def sum_series(n):
    """
    Design an adaptive learning system that creates a personalized learning path by breaking down complex topics into simpler sub-modules. Given an initial module difficulty level, the system needs to generate progressively easier versions by reducing the complexity by 2 points at each step until reaching the basic level (zero or below). Calculate the total complexity points across all difficulty levels in this adaptive path, which helps determine the overall learning effort required. For example, if a module starts at difficulty level 7, the path would include levels 7, 5, 3, and 1, and the system should sum these values to quantify the total complexity of the personalized learning journey.
    

    """
def sum_series(n):
    """
    Design an adaptive learning system that creates a personalized learning path by breaking down complex topics into simpler sub-modules. Given an initial module difficulty level, the system needs to generate progressively easier versions by reducing the complexity by 2 points at each step until reaching the basic level (zero or below). Calculate the total complexity points across all difficulty levels in this adaptive path, which helps determine the overall learning effort required. For example, if a module starts at difficulty level 7, the path would include levels 7, 5, 3, and 1, and the system should sum these values to quantify the total complexity of the personalized learning journey.
    

    """
    if n < 1:
        return 0
    else:
        return n + sum_series(n - 2)