Chapter 17

Handbook of Learning Analytics
First Edition

Data Mining Large-Scale Formative Writing

Peter W. Foltz & Mark Rosenstein


Abstract

Student writing in digital educational environments can provide a wealth of information about the processes involved in learning to write as well as evidence for the impact of the digital environment on those processes. Developing writing skills is highly dependent on students having opportunities to practice, most particularly when they are supported with frequent feedback and are taught strategies for planning, revising, and editing their compositions. Formative systems incorporating automated writing scoring provide the opportunities for students to write, receive feedback, and then revise essays in a timely iterative cycle. This chapter provides an analysis of a large-scale formative writing system using over a million student essays written in response to several hundred pre-defined prompts used to improve educational outcomes, better understand the role of feedback in writing, drive improvements in formative technology, and design better kinds of feedback and scaffolding to support students in the writing process.

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About this Chapter

Title
Data Mining Large-Scale Formative Writing

Book Title
Handbook of Learning Analytics

Pages
pp. 199-210

Copyright
2017

DOI
10.18608/hla17.017

ISBN
978-0-9952408-0-3

Publisher
Society for Learning Analytics Research

Authors
Peter W. Foltz1,2
Mark Rosenstein2

Author Affiliations
1. Institute of Cognitive Science, University of Colorado, USA
2. Advanced Computing and Data Science Laboratory, Pearson, USA

Editors
Charles Lang3
George Siemens4
Alyssa Wise5
Dragan Gašević6

Editor Affiliations
3. Teachers College, Columbia University, USA
4. LINK Research Lab, University of Texas at Arlington, USA
5. Learning Analytics Research Network, New York University, USA
6. Schools of Education and Informatics, University of Edinburgh, UK

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