LUCID is a web-based assessment system that provides many novel features, including POGIL activities with interactive models, support for teams in a computer classroom, peer review, computer analysis of symbolic responses such as molecular structures, and import of form-based responses from examinations. This presentation will focus on LUCID's multidimensional assessment model. Multidimensional assessment goes beyond common score-based assessment by scoring responses with respect to learning objectives. A single response can be associated with one or more objectives and analyzed to determine which have and have not been demonstrated. Taxonomies for classifying objectives by topic and educational objective (e.g., Bloom's taxonomy) enable students and instructors to review learning outcomes in multiple dimensions and at varying levels of resolution. Measures of learning outcomes in General Chemistry at Stony Brook will be presented and issues in using such measures to improve student learning will be discussed.