How to provide automated feedback on the writing process? A participatory approach to design writing analytics tools. Issue 8 (2nd November 2022)

• Record Type: Journal Article
• Authors: Conijn, Rianne; Martinez-Maldonado, Roberto; Knight, Simon; Buckingham Shum, Simon; Van Waes, Luuk; van Zaanen, Menno
• Is Part Of: Computer assisted language learning. Volume 35:Issue 8(2022)
• Page Start: 1838
• Page End: 1868
• Publication Date: 2022-11-02
• Subjects: Feedback -- learning analytics -- participatory consultation -- writing process -- writing tools; Language and languages -- Computer-assisted instruction -- Periodicals; 418.00285
• DOI: 10.1080/09588221.2020.1839503
• Languages: English
• ISSNs: 0958-8221

Abstract

Abstract: Current writing support tools tend to focus on assessing final or intermediate products, rather than the writing process. However, sensing technologies, such as keystroke logging, can enable provision of automated feedback during, and on aspects of, the writing process. Despite this potential, little is known about the critical indicators that can be used to effectively provide this feedback. This article proposes a participatory approach to identify the indicators of students' writing processes that are meaningful for educational stakeholders and that can be considered in the design of future systems to provide automated, personalized feedback. This approach is illustrated through a qualitative research design that included five participatory sessions with five distinct groups of stakeholders: bachelor and postgraduate students, teachers, writing specialists, and professional development staff. Results illustrate the value of the proposed approach, showing that students were especially interested in lower-level behavioral indicators, while the other stakeholders focused on higher-order cognitive and pedagogical constructs. These findings lay the groundwork for future work in extracting these higher-level indicators from in-depth analysis of writing processes. In addition, differences in terminology and the levels at which the indicators were discussed, highlight the need for human-centered, participatory approaches to design and develop writing analytics tools.