Une archive numérique francophone des articles de recherche en Traitement Automatique de la Langue.

Toward Using Text Summarization for Essay-Based Feedback

Jill Burstein, Daniel Marcu

Abstract : We empirically study the impact of using automatically generated summaries in the context of electronic essay rating. Our results indicate that 40% and 60% discourse-based essay summaries improve the performance of the topical analysis module of e-rater. E-rater is a system that electronically scores GMAT essays. We envision using automatically generated essay summaries for instructional feedback, as a supplement to the e-rater score.