Linear Algebra, the common Engineering Mathematics subjects contains abstract concepts that students find it difficult to understand. This study aimed to identify the specific difficult course outcomes or difficult topics for the Linear Algebra subject. The difficult course outcomes are identified from a pre-test which was given to hundred Electrical Engineering students at the end of a fourteen-week course in a public university in Malaysia. The pre-test questions cover the entire course outcomes of the Linear Algebra subject. The pre-test questions consist of the level of Bloom Taxonomy (Knowledge, Comprehension, Application, Analysis, Synthesis, and Evaluation). Rasch model is used to analyze the results of the pre-test. The output achieved from the Rasch model is summary statistics for the item, fit statistics, and item dimensionality test. Summary statistics for items indicated a good item difficulty of spread. Fit statistics identified two questions as a misfit. These questions need to be rephrased. The item dimensionality test indicates the pre-test questions are within the scope of measuring students' problem-solving ability. Rasch model analysis illustrated that two-course outcome identified as the difficult course outcomes in Linear Algebra subject. They are the concepts of vector space, diagonalization, quadratic forms, and power series. On the other hand, questions related to comprehension and application level of Bloom Taxonomy are difficult for engineering students. This study provides an insight view of the Linear Algebra subject by under-pinning the difficult area of the subject. Efforts should be taken by lecturers to illustrate these topics in a much simpler way.