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Scaling Academic Writing Instruction: Evaluation of a Scaffolding Tool (Thesis Writer)

Article

Abstract

No thesis - no graduation. Academic writing poses manifold challenges to students, instructors and institutions alike. High labor costs, increasing student numbers, and the Bologna Process (which has reduced the period after which undergraduates in Europe submit their first thesis and thus the time available to focus on writing skills) all pose a threat to students’ academic writing abilities. This situation gave rise to the practical goal of this study: to determine if, and to what extent, academic writing and its instruction can be scaled (i.e., designed more efficiently) using a technological solution, in this case Thesis Writer (TW), a domain-specific, online learning environment for the scaffolding of student academic writing, combined with an online editor optimized for producing academic text. Compared to existing automated essay scoring and writing evaluation tools, TW is not focusing on feedback but on instruction, planning, and genre mastery. While most US-based tools, particularly those also used in secondary education, are targeting on the essay genre, TW is tailored to the needs of theses and research article writing (IMRD scheme). This mixed-methods paper reports data of a test run with a first-year course of 102 business administration students. A technology adoption model served as a frame of reference for the research design. From a student’s perspective, problems posed by the task of writing a research proposal as well as the use, usability, and usefulness of TW were studied through an online survey and focus groups (explanatory sequential design). Results seen were positive to highly positive – TW is being used, and has been deemed supportive by students. In particular, it supports the scaling of writing instruction in group assignment settings.

Keywords

Computer-supported writing instruction Writing instruction Intelligent tutoring system Academic writing Evaluation 

Notes

Acknowledgements

We gratefully acknowledge the feedback of Ann Devitt (University of Dublin, Ireland), Otto Kruse (Zurich University of Applied Sciences, Winterthur, Switzerland), and Antje Proske (Technical University Dresden, Germany) on drafts of this article.

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Copyright information

© International Artificial Intelligence in Education Society 2018

Authors and Affiliations

  1. 1.Zurich University of Applied SciencesWinterthurSwitzerland
  2. 2.PrognosiX AGZurichSwitzerland

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