E-assessment is an important component of e-learning and e-qualification. Formative and summative assessment serve different purposes and both types of evaluation are critical to the pedagogicalprocess. While students are studying, practicing, working, or revising, formative assessment provides direction, focus, and guidance. Summative assessment provides the means to evaluate a learner's achievement and communicate that achievement to interested parties. Latent Semantic Analysis (LSA) is a statistical method for inferring meaning from a text. Applications based on LSA exist that provide both summative and formative assessment of a learner's work. However, the huge computational needs are a major problem with this promising technique. This paper explains how LSA works, describes the breadth of existing applications using LSA, explains how LSA is particularly suited to e-assessment, and proposes research to exploit the potential computational power of the Grid to overcome one of LSA's drawbacks
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