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OpenEssayist: a supply and demand learning analytics tool for drafting academic essays

Published:16 March 2015Publication History

ABSTRACT

This paper focuses on the use of a natural language analytics engine to provide feedback to students when preparing an essay for summative assessment. OpenEssayist is a real-time learning analytics tool, which operates through the combination of a linguistic analysis engine that processes the text in the essay, and a web application that uses the output of the linguistic analysis engine to generate the feedback. We outline the system itself and present analysis of observed patterns of activity as a cohort of students engaged with the system for their module assignments. We report a significant positive correlation between the number of drafts submitted to the system and the grades awarded for the first assignment. We can also report that this cohort of students gained significantly higher overall grades than the students in the previous cohort, who had no access to OpenEssayist. As a system that is content free, OpenEssayist can be used to support students working in any domain that requires the writing of essays.

References

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      • Published in

        cover image ACM Other conferences
        LAK '15: Proceedings of the Fifth International Conference on Learning Analytics And Knowledge
        March 2015
        448 pages
        ISBN:9781450334174
        DOI:10.1145/2723576

        Copyright © 2015 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 16 March 2015

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        LAK '15 Paper Acceptance Rate20of74submissions,27%Overall Acceptance Rate236of782submissions,30%

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