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Grounding Collaborative Knowledge Building in Semantics-Based Critiquing
Author(s) -
Anders I. Mørch,
William K. Cheung,
Kelvin C. Wong,
Jiming Liu,
Cynthia Lee,
Mason H. Lam,
Janti P. Tang
Publication year - 2005
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-27895-8
DOI - 10.1007/11528043_24
Subject(s) - session (web analytics) , computer science , reflection (computer programming) , component (thermodynamics) , interface (matter) , composition (language) , latent semantic analysis , semantics (computer science) , human–computer interaction , work (physics) , software , user interface , multimedia , software engineering , programming language , world wide web , artificial intelligence , linguistics , engineering , mechanical engineering , philosophy , physics , bubble , maximum bubble pressure method , parallel computing , thermodynamics
In this paper we investigate the use of Latent Semantic Analysis (LSA), Critiquing Systems, and Knowledge Building to support computer-based teaching of English composition. We have built and tested an English Composition Critiquing System that make use of LSA to analyze student essays and compute feedback by comparing their essays with teacher's model essays. LSA values are input to a critiquing component to provide a user interface for the students. A software agent can also use the critic feedback to coordinate a collaborative knowledge building session with multiple users (students and teachers). Shared feedback provides seed questions that can trigger discussion and extended reflection about the next phase of writing. We present the first version of a prototype we have built, and report the results from an informal experiment. We end the paper by describing our plans for future work.

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