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

Authors

  • Javier Obreque Fundación Instituto Profesional Duoc UC. Valparaíso, Chile.
  • Ignacio Lobos Fundación Instituto Profesional Duoc UC. Valparaíso, Chile.
  • Marjory Astudillo Fundación Instituto Profesional Duoc UC. Valparaíso, Chile.
  • Karin Arismendi Fundación Instituto Profesional Duoc UC. Valparaíso, Chile.

DOI:

https://doi.org/10.15443/codes2019

Keywords:

Feedback, computational tools and academic writing

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.

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Published

2023-11-08

How to Cite

Obreque, J., Lobos, I., Astudillo, M., & Arismendi, K. (2023). Types of automated feedback on academic writing: first results from a comparative case description1. Higher Education Teaching Congress CODES, 5. https://doi.org/10.15443/codes2019