Measurement range increment in a method for evaluating Panoramic Understanding of Programming

In a prior study we introduced the Programmed Visual Contents Comparison Method (PVCC) for assessment of programming abilities related with Panoramic Understanding of Programming (PUP). With this method, by comparing two or more output pictures produced by programming samples (a question), a student must decide which one of the programs producing them is more difficult to build with programming, or, if the difficulty is similar for all of them. This study reported also the results of a test to evaluate this method's validity performed with groups of students of diverse fields. Validity was verified by comparing the initial programming ability reported by programming professors of these groups with the test results; this confirmed that the PVCC method worked well to find programming abilities related with PUP. In this paper we propose an enhancement to the PVCC Method based on the preparation of New Questions where two or more samples displaying both input data and output pictures are shown. By adding input data to output pictures and focus strictly on the programming processes needed to obtain these pictures from the provided input data, we aim to broaden the range of discernible programming abilities related with PUP. The results of a test performed to verify the suitability of New Questions performed with professors of programming is also reported.