Abstract

In a previous paper (Wolfe, Schreiner, Rehder, Laham, Foltz, Kintsch & Landauer, this issue) we have shown how Latent Semantic Analysis (LSA) can be used to assess student knowledge - how essays can be graded by LSA and how LSA can match students with appropriate instructional texts. We did this by comparing an essay written by a student with one or more target instructional texts in terms of the cosine between the vector representation of the student's essay and the instructional text in question. This simple method was effective for the purpose, but questions remain about how LSA achieves it's results and how they might be improved. Here we address four such questions: (a) what role use of technical vocabulary per se plays, (b) how long should the student essays be, (c) whether the cosine is optimal measure of semantic relatedness, and (d) how to deal with the directionality of knowledge in the high-dimensional space. Latent Semantic Analysis 3 Using Latent Semantic Analysis to ass...

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