Visualizing Formative Feedback in Statistics Writing:A Case Study of Student Motivation Using Docuscope Write & Audit

Abstract

Recently, formative writing feedback has been supported by technologies generally referred to as Automated Writing Evaluation tools. However, such tools are limited in their capacity to explore disciplinary genres, and they have shown mixed results in student writing improvement. We explore how our new software can promote self-efficacy in the user’s writing choices, both reinforcing content knowledge and increasing student motivation.Using a text-visualization tool called Write & Audit, we hosted revision workshops for an introductory-level statistics course. The tool is designed to be flexible: instructors of various courses can create expectations and predefine topics that are genre-specific. In this way, students are offered non-evaluative formative feedback which redirects them to field-specific strategies. To gauge the usefulness of Write & Audit, we used a previously validated survey instrument designed to measure the construct model of student motivation (Ling et al. 2021). Our results show significant increases in student self-efficacy and beliefs about the importance of content in successful writing. We contextualize these findings with data from student think-aloud interviews which demonstrate metacognitive awareness while using the tool. Ultimately, this case study contributes a novel approach to automated formative feedback and confirms the promising potential of Write & Audit.

Keywords: Automated writing evaluation (AWE), Formative Feedback, Statistics, Writing in the Disciplines (WID), Writing assessment, Writing motivation