Computerizing reading training: evaluation of a latent semantic analysis space for science text.

Full Abstract

The effectiveness of a domain-specific latent semantic analysis (LSA) in assessing reading strategies was examined. Students were given self-explanation reading training (SERT) and asked to think aloud after each sentence in a science text. Novice and expert human raters and two LSA spaces (general reading, science) rated the similarity of each think-aloud protocol to benchmarks representing three different reading strategies (minimal, local, and global). The science LSA space correlated highly with human judgments, and more highly than did the general reading space. Also, cosines from the science LSA spaces can distinguish between different levels of semantic similarity, but may have trouble in distinguishing local processing protocols. Thus, a domain-specific LSA space is advantageous regardless of the size of the space. The results are discussed in the context of applying the science LSA to a computer-based version of SERT that gives online feedback based on LSA cosines.

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Author information

Author/s: Kurby, Christopher A (CA); Wiemer-Hastings, Katja (K); Ganduri, Nagasai (N); Magliano, Joseph P (JP); Millis, Keith K (KK); McNamara, Danielle S (DS);

Affiliation: Department of Psychology, Northern Illinois University, DeKalb, Illinois 60115, USA. ckurby(-atsign-)niu.edu

Journal and publication information

Publication Type: Comparative Study; Evaluation Studies; Journal Article; Research Support, U.S. Gov't, Non-P.H.S.

Journal: Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc (Behav Res Methods Instrum Comput), published in United States. (Language: eng)

Reference: 2003-May; vol 35 (issue 2) : pp 244-50

Dates: Created 2003/07/01; Completed 2003/08/29; Revised 2007/11/15;

PMID: 12834079, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Artificial Intelligence
Computer-Assisted Instruction - methods
Evaluation Studies as Topic
Humans
Learning
Mental Processes

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