AcaWriter: A learning analytics tool for formative feedback on academic writing
Open accessAbstract
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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A further interesting area of work involves the use of feedback analytics to support student academic writing.
“A further interesting area of work involves the use of feedback analytics to support student academic writing (Gibson et al., 2017; Knight et al., 2020).”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Knight et al., 2020
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Self-citationPapagAI: Automated Feedback for Reflective Essays
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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
- diamond
- doi.org
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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