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Automated Writing Evaluation and Feedback: Multiple Metrics of Efficacy
Abstract
The present study extended research on the effectiveness of automated writing evaluation (AWE) systems. Sixth graders were randomly assigned by classroom to an AWE condition that used Project Essay Grade Writing ( n = 56) or a word-processing condition that used Google Docs ( n = 58). Effectiveness was evaluated using multiple metrics: writing self-efficacy, holistic writing quality, performance on a state English language arts test, and teachers' perceptions of AWE's social validity. Path analyses showed that after controlling for pretest measures, composing condition had no effect on holistic writing quality, but students in the AWE condition had more positive writing self-efficacy and better performance on the state English language arts test. Posttest writing self-efficacy partially mediated the effect of composing condition on state test performance. Teachers reported positive perceptions of AWE's social validity. Results emphasize the importance of using multiple metrics and considering both contextual factors and AWE implementation methods when evaluating AWE effectiveness.
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“Several studies have demonstrated that automated essay scoring tools like MI Write can help students to improve their writing motivation (Wilson & Czik, 2016), writing self-efficacy (Wilson & Roscoe, 2020) and writing skills (Palermo & Thomson, 2018)”
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Metadata
- Authors
- Wilson, J., & Roscoe, R. D.
- Affiliations
- University of Delaware (US)
- Arizona State University (US)
- Corresponding author
- Wilson, Joshua
- Venue
- Journal of Educational Computing Research
- Publisher
- SAGE Publications
- Published
- 2019-03-26
- Volume
- 58
- Issue
- 1
- Pages
- 87-125
- ISSN
- 0735-6331 (ISSN-L)
- 1541-4140
- OpenAlex
- W2923646821
- Cited by
- 176
- References
- 75
- Citations by year
- 2026: 34 · 2025: 30 · 2024: 30 · 2023: 27 · 2022: 26 · 2021: 17 · 2020: 10 · 2019: 2
- FWCI
- 37.10
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Educational Computing Research (publishedVersion)
- Topics
- Social Sciences › Education › Writing and Handwriting Education
- Social Sciences › Education › Student Assessment and Feedback
- Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
- Keywords
- automated writing evaluation, writing self-efficacy, writing quality, Google Docs, writing instruction, teacher perceptions, social validity, junior high school students, writing feedback
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