  Brain computer interface applications can be used to overcome learning
problems, especially student anxiety, lack of focus, and lack of attention.
This paper introduces a system based on brain computer interface (BCI) to be
used in education to measure intended learning outcomes and measure the impact
of noise on the degree of system accuracy. This system works online and is
based on recorded brain signal dataset. The system can be considered as a
special case of P300 speller accepting only letters from A to D. These are the
possible answers to multiple-choice questions MCQ. The teacher makes exams,
stores them in an exam database and delivers them to students. Students enroll
into the system and record their brain signals. Brain signals go through
preprocessing phase in which signals undergo low and high pass filter. Then the
signals undergo a subsampling and segmentation. The features obtained are used
as inputs to Linear Discriminant Analysis (LDA). Gained accuracy is 91%.
