Identifying reading strategies using latent semantic analysis: Comparing semantic benchmarks |
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Authors: | Email author" target="_blank">Keith?MillisEmail author Hyun-Jeong?Joyce?Kim Stacey?Todaro Joseph?P?Magliano Katja?Wiemer-Hastings Danielle?S?McNamara |
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Institution: | (1) Department of Psychology, Northern Illinois University, 60115 DeKalb, IL;(2) Rhodes College, Memphis, Tennessee;(3) University of Memphis, Memphis, Tennessee |
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Abstract: | We explored methods of using latent semantic analysis (LSA) to identify reading strategies in students’ self-explanations
that are collected as part of a Web-based reading trainer. In this study, college students self-explained scientific texts,
one sentence at a time. LSA was used to measure the similarity between the self-explanations andsemantic benchmarks (groups of words and sentences that together represent reading strategies). Three types of semantic benchmarks were compared:
content words, exemplars, and strategies. Discriminant analyses were used to classify global and specific reading strategies
using the LSA cosines. All benchmarks contributed to the classification of general reading strategies, but the exemplars did
the best in distinguishing subtle semantic differences between reading strategies. Pragmatic and theoretical concerns of using
LSA are discussed. |
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Keywords: | |
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