Using latent semantic analysis to assess knowledge
Some technical considerations
Bibliographic Data
| ID | 11273178 |
|---|---|
| Authors | Bob Rehder (0000-0001-7795-7108, corresponding author), M E Schreiner, Michael Schreiner (0000-0001-6297-8707, University of Colorado Boulder), Michael B W Wolfe, Michael B Wolfe (0000-0001-7431-9274, University of Colorado Boulder), Darrell Laham (University of Colorado Boulder), Thomas K Landauer (University of Colorado Boulder), Walter Kintsch (University of Colorado Boulder) |
| Year | 1998 |
| Volume | 25 |
| Issue | 2-3 |
| Pages | 337-354 |
| Publication date | 1998-01-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Discourse Processes (JOURNAL) |
| Journal identifiers | ISSN: 0163-853X • E-ISSN: 1532-6950 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/01638539809545031 |
| OpenAlex | W2047954909 |
| Language | EN |
| Citations received | 11 |
| References cited | 4 |
In another article (Wolfe et al., 1998/this issue) we showed 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 its results and how the results might be improved. Here, we address four such questions: (a) What role does the use of technical vocabulary play? (b) how long should the student essays be? (c) is the cosine the optimal measure of semantic relatedness? and (d) how does one deal with the directionality of knowledge in the high‐dimensional space
Cosine similarity · Latent semantic analysis · Linguistics · Mathematics education · Natural language processing · Pattern recognition (psychology · Representation (politics · Vocabulary · Computer Science · Natural Language Processing Techniques · Psychology · Text Readability and Simplification · Topic Modeling · Artificial Intelligence
Topics in semantic representation.
Is the Reliability of Objective Originality Scores Confounded by Elaboration
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Similarity of Semantic Relations
Humans Learn Language from Situated Communicative Interactions. What about Machines
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Committed to Caring
An introduction to latent semantic analysis
Transforming Selected Concepts Into Dimensions in Latent Semantic Analysis
Learning from text
Moral Identity in Adolescence
| Unique citing works | 11 |
|---|---|
| Citations per year | 0,39 |
| Citation span | 1998 - 2024 (27) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 11 |