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The course description provided by instructors is an essential piece ofinformation as it defines what is expected from the instructor and what he/sheis going to deliver during a particular course. One of the key components of acourse description is the Learning Objectives section. The contents of thissection are used by program managers who are tasked to compare and match twodifferent courses during the development of Transfer Agreements between variousinstitutions. This research introduces the development of semantic similarityalgorithms to calculate the similarity between two learning objectives of thesame domain. We present a novel methodology which deals with the semanticsimilarity by using a previously established algorithm and integrating it withthe domain corpus utilizing domain statistics. The disambiguated domain servesas a supervised learning data for the algorithm. We also introduce Bloom Indexto calculate the similarity between action verbs in the Learning Objectivesreferring to the Blooms taxonomy.

Similarity between Learning Outcomes from Course Objectives using Semantic Analysis, Blooms taxonomy and Corpus statistics