Developing Summarization Skills through the Use of LSA-Based Feedback

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Abstract
This paper describes a series of classroom trials during which we developed Summary Street, an educational software system that uses Latent Semantic Analysis to support writing and revision activities. Summary Street provides various kinds of feedback, primarily about whether a student summary adequately covers important source content and fulfills other requirements, such as length. The feedback allows students to engage in extensive, independent practice in writing and revising without placing excessive demands on teachers for feedback. We first discuss the underlying educational rationale, then present some results of the trials conducted with the system. We describe the collaborative process among researchers and teachers which enabled the development of a viable and supportive educational tool and its integration into classroom instruction.

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