data:image/png;base64,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 list of numbers is confusing because it is not obvious which numbers are x and which are y coordinates. It will also be difficult to maintain (add or delete coordinates to the lists). It would be better to create a matrix (a list of list). Each item in the list will be a list of x and y coordinates.Abstract Data Types (ADT) is a custom data type created by the programmer to provide meaning to the data in your program. It is not built into the programming language. ADT are created with custom constructor and selector functions (blocks). ADT are a form of abstraction because they make are program easier to understand, read, and debug.Lists and Numbers are examples of Primitive Data TypesStep 2: Create two report blocks (the selectors) that will take the list created by the contructor block as the domain and output a single number as the range (one the x coordinate the second block the y coordinate).Step 3: Create a list that stores the necessary Coordinte Points to draw your specified shape Step 4: Create a Draw Shape Command Block whose domain will be the list of Coordinate Points create in step 3. The command block will draw the shape on the screen by using a the for each item block and the selector blocks created in Step 2.240,00,100-240,00,-100240,0