Exploring the Use of Artificial Intelligence to Improve Law Students' Self-Assessments

Philippa Ryan

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    Abstract

    Analytical writing is a core professional skill for lawyers. For this reason, many law degrees include writing tasks. This paper discusses a study being conducted by the author at the University of Technology Sydney (UTS), which has revealed this misalignment between law students self-assessments and the markers assessments of their work. Indeed, the scholarship on this point paints a negative impression of students ability to self-assess. This paper examines the trial of writing analytics technology to give students pre-submission feedback. This software is being developed by the Connected Intelligence Centre at UTS in conjunction with Xerox in France. It is argued that natural language processing powered by Artificial Intelligence (AI) can offer rapid formative feedback on draft essays. By coding their text, the application makes visible to learners their use (or lack) of key features of analytical writing. This innovative technology is intended to improve law students self-assessments and it also provides an opportunity for students to trial and critique a future tool of their trade. Part one of this paper explains why students struggle to read their draft essays critically. Part two considers this problem and early unsuccessful attempts to teach self-assessment. Part three examines the trial of writing analytics technology to improve students self-assessments. This paper tentatively concludes that by exposing students to natural language processing technology, they are better equipped to discern and improve their essays; while at the same time experiencing in a practice-authentic way how AI works, including its limitations (at this time).
    Original languageEnglish
    Title of host publicationThe Future of Australian Legal Education: A Collection
    EditorsKevin Edmund Lindgren, François Kunc, Michael Coper
    Place of PublicationSydney
    PublisherThomson Reuters
    Pages401-428
    Volume1
    ISBN (Print)9780455241357
    Publication statusPublished - 2018

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