Developing automated ways to give essay writing feedback to students

Edwards, Chris; Whitelock, Denise; Cross, Simon and Wild, Fridolin (2022). Developing automated ways to give essay writing feedback to students. In: INTED2022 Proceedings: 16th International Technology, Education and Development Conference (Chova, Luis Gómez; Martínez, Agustín López and Torres, Ignacio Candel eds.), INTED Proceedings, IATED Academy, Valencia, Spain, pp. 5446–5450.

DOI: https://doi.org/10.21125/inted.2022.1407

Abstract

Students are likely to receive feedback on their writing from several different academics during their undergraduate studies. Sometimes this feedback is partial, only mentioning one or two highlights and issues: ignoring the bulk of what was written. Sometimes feedback can be inconsistent between academics and confuse students. Even where there is a very clear rubric for marking a piece of academic writing, different colleagues may give significantly different marks; and the mark a single academic gives might depend on the time it was given. This variation reveals an opportunity to better support students in learning to produce good quality academic text.

In this paper we describe a new online tool designed to give students automated feedback on their academic writing. Students’ work is held confidentially and feedback is provided without any interaction from their tutor. It forms a zero stakes transaction. The resulting Open Essay Optimiser (OEO) is a tuned and enhanced successor of an earlier tool called Open Essayist. It was tuned using many anonymised scripts from students and enhanced with the input of expert programmers and designers. OEO examines the argument coherence within a text: how ideas are set out, discussed and then brought together in a conclusion. It provides different ways to present this coherence to students, whilst allowing them to edit their text within the tool and see the impact of these changes. There are other features including the listing and highlighting key words and phrases, and key sentences. Also, a review of the references used and the possibility to suggest others. This paper will include the outcomes of the initial trial, including the student response to it, and consider its potential to support students.

Viewing alternatives

Look up in Google Scholar

Download history

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions

Export

About

  • Item ORO ID
  • 82372
  • Item Type
  • Conference or Workshop Item
  • ISBN
  • 84-09-37758-6, 978-84-09-37758-9
  • ISSN
  • 2340-1079
  • Keywords
  • assessment; feedback; automated feedback; educational technology; online learning; enhancing student experience
  • Academic Unit or School
  • Institute of Educational Technology (IET)
  • Copyright Holders
  • © 2022 IATED
  • Related URLs
  • Depositing User
  • Chris Edwards
CORE (COnnecting REpositories)

Recommendations