ESCRITO - An NLP-Enhanced Educational Scoring Toolkit

Abstract

We propose Escrito, a toolkit for scoring student writings using NLP techniques that addresses two main user groups: teachers and NLP researchers. Teachers can use a high-level API in the teacher mode to assemble scoring pipelines easily. NLP researchers can use the developer mode to access a low-level API, which not only makes available a number of pre-implemented components, but also allows the user to integrate their own readers, preprocessing components, or feature extractors. In this way, the toolkit provides a ready-made testbed for applying the latest developments from NLP areas like text similarity, paraphrase detection, textual entailment, and argument mining within the highly challenging task of educational scoring and feedback. At the same time, it allows teachers to apply cutting-edge technology in the classroom.

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