Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/116
Title: Writing Analytics for Epistemic Features of Student Writing
Authors: Knight, Simon
Allen, Laura
Littleton, Karen
Rienties, Bart
Tempelaar, Dirk
Issue Date: Jul-2016
Publisher: Singapore: International Society of the Learning Sciences
Citation: Knight, S., Allen, L., Littleton, K., Rienties, B., & Tempelaar, D. (2016). Writing Analytics for Epistemic Features of Student Writing In Looi, C. K., Polman, J. L., Cress, U., and Reimann, P. (Eds.). Transforming Learning, Empowering Learners: The International Conference of the Learning Sciences (ICLS) 2016, Volume 1. Singapore: International Society of the Learning Sciences.
Abstract: Literacy, encompassing the ability to produce written outputs from the reading of multiple sources, is a key learning goal. Selecting information, and evaluating and integrating claims from potentially competing documents is a complex literacy task. Prior research exploring differing behaviours and their association to constructs such as epistemic cognition has used ‘multiple document processing’ (MDP) tasks. Using this model, 270 paired participants, wrote a review of a document. Reports were assessed using a rubric associated with features of complex literacy behaviours. This paper focuses on the conceptual and empirical associations between those rubric-marks and textual features of the reports on a set of natural language processing (NLP) indicators. Findings indicate the potential of NLP indicators for providing feedback regarding the writing of such outputs, demonstrating clear relationships both across rubric facets and between rubric facets and specific NLP indicators.
URI: https://repository.isls.org/handle/1/116
https://dx.doi.org/10.22318/icls2016.27
Appears in Collections:ICLS 2016

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