From the computer science domain itself, the taxonomy improves curricular design and assessments (Scoot, 2003). Normally, academicians would categorise a question according to the Bloom’s cognitive level manually. However, according to Yusof and Chai (2010), not all can identify the cognitive level of a question correctly. This may lead to miscategorizing of the exam questions and subsequently may fail to meet the examination standard required for the subject. In addition, some academicians also show no significant agreement on how to use Bloom's taxonomy in educating students (Johnson & Fuller, 2006). The aim of this paper is to propose a rule-based approach in determining the Bloom’s taxonomy cognitive level of examination questions through natural language processing. Exam questions will be analyzed and each question will be categorized based on the Bloom’s taxonomy cognitive level. The scope of the work is limited to computer programming domain. This will assist the academicians in setting up suitable exam questions according to the requirements.