Due to the computerization of assessment tests, the use of Item Response Theory (IRT) has become commonplace for educational assessment development, evaluation, and refinement. When used appropriately by a Learning Management System (LMS), IRT can improve the assessment quality, increase the efficiency of the testing process, and provide in-depth descriptions of item and test properties. This paper introduces a methodological and architectural framework which embeds an IRT analysis tool in an LMS so as to extend its functionality with assessment optimization support. By applying a set of validity rules to the statistical indices produced by the IRT analysis, the enhanced LMS is able to detect several defective items from an item pool which are then reported for reviewing of their content. Assessment refinement is achieved by repeatedly employing this process until all flawed items are eliminated
