Outcome-based education (OBE) is uniquely adapted by most of the educators across the world for objective processing, evaluation and assessment of computing programs and its students. However, the extraction of knowledge from OBE in common is a challenging task because of the scattered nature of the data obtained through Program Educational Objectives (PEOs), Program Learning Outcomes (PLOs) and Course Learning Outcomes (CLOs). Computer programming correctly is the most demanded skill in the computing industry for which it is included in the CLOs of many computing courses at diverse levels of Bloom's taxonomy. This study is typically aimed to develop a decision tree classifier for the comprehensive assessment of PLOs in direct correlation with the CLOs related to computer programming. The PLOs of a computing program defined by Seoul Accord are correlated by using Spearman ranked correlation with the programming-related CLOs and mapped on a C4.5 decision tree to rank the importance of different metrics for objective learning. For the testing of the method the data were collected for two semesters of the academic BSCS program of Fall-2016 and Fall-2017 intake. The results obtained through decision tree classifier are more accurate than the conventionally practiced method.