Cited by 151Student Assessment and FeedbackDiscourse Analysis in Language StudiesOnline Learning and Analytics

AcaWriter: A learning analytics tool for formative feedback on academic writing

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Knight, S., Shibani, A., Abel, S., Gibson, A., Ryan, P.·2020·Journal of Writing Research

Abstract

Written communication is an important skill across academia, the workplace, and civic participation. Effective writing incorporates instantiations of particular text structures - rhetorical moves - that communicate intent to the reader. These rhetorical moves are important across a range of academic styles of writing, including essays and research abstracts, as well as in forms of writing in which one reflects on learning gained through experience. However, learning how to effectively instantiate and use these rhetorical moves is a challenge. Moreover, educators often struggle to provide feedback supporting this learning, particularly at scale. Where effective support is provided, the techniques can be hard to share beyond single implementation sites. We address these challenges through the open-source AcaWriter tool, which provides feedback on rhetorical moves, with a design that allows feedback customization for specific contexts. We introduce three example implementations in which we have customized the tool and evaluated it with regard to user perceptions, and its impact on student writing. We discuss the tool's general theoretical background and provide a detailed technical account. We conclude with four recommendations that emphasize the potential of collaborative approaches in building, sharing and evaluating writing tools in research and practice.

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  1. Boud, D., Keogh, R., & Walker, D. (1985). What is reflection in learning. In D. Boud (Ed.), Reflection: Turning experience into learning (pp. 7-17). Kogan Page.
  2. Cope, B., & Kalantzis, M. (1993). The Powers of Literacy: A Genre Approach to Teaching Writing. Routledge.
  3. Elsevier. (2015). New open access resource will support text mining and natural language processing. Elsevier Connect. https://www.elsevier.com/connect/new-open-accessresource-will-support-text-mining-and-natural-language-processing
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  6. Shibani, A., Knight, S., & Shum, S. B. (2019). Contextualizable Learning Analytics Design: A Generic Model and Writing Analytics Evaluations. Proceedings of the 9th International

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Authors
Knight, S., Shibani, A., Abel, S., Gibson, A., & Ryan, P.
Affiliations
  • University of Technology Sydney (AU)
  • Queensland University of Technology (AU)
Corresponding author
Knight, S.
Venue
Journal of Writing Research
Published
2020-06
Volume
12
Issue
vol. 12 issue 1
Pages
141-186
ISSN
  • 2030-1006 (ISSN-L)
  • 2294-3307
OpenAlex
W3024117512
Cited by
151
References
49
Citations by year
2026: 18 · 2025: 30 · 2024: 21 · 2023: 30 · 2022: 23 · 2021: 18 · 2020: 10 · 2019: 1
FWCI
30.66
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Journal of Writing Research (publishedVersion, cc-by-nc-nd)
  • ANU Open Research (Australian National University) (submittedVersion, cc-by-nc-nd)
  • QUT ePrints (Queensland University of Technology) (submittedVersion, cc-by-nc-nd)
  • UTS ePRESS (University of Technology Sydney) (submittedVersion, other-oa)
Topics
  • Social Sciences › Education › Student Assessment and Feedback
  • Social Sciences › Arts and Humanities › Literature and Literary Theory › Discourse Analysis in Language Studies
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
Keywords
learning analytics, formative feedback, academic writing, rhetorical moves, writing instruction, student writing, user perception

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