Types of automated feedback on academic writing: first results from a comparative case description1

Abstract

The purpose of this article is to present the preliminary results of an ongoing project that aims to describe, compare, and determine the scope of types of writing feedback, particularly academic, that can be provided automatically by freely available computational tools.
Specifically, the preliminary results of the analysis of four computational tools are presented: an artificial intelligence (ChatGPT 3.5) and specific academic writing support tools (ArText, Estilector, and PEUMO). The methodological approach employed identifies the type of feedback they provide based on the categories proposed by Alvarez et al. (2011) and Guasch et al. (2013), which include corrective, epistemic, suggestive, and epistemic-suggestive.