Predictors of middle school students’ perceptions of automated writing evaluation

This study examined middle school students' perceptions of an automated writing evaluation (AWE) system, MI Write. We summarize students' perceptions of MI Write's usability, usefulness, and desirability both quantitatively and qualitatively. We then estimate hierarchical entry regression models that account for district context, classroom climate, demographic factors (i.e., gender, special education status, limited English proficiency status, socioeconomic status, grade), students' writing-related beliefs and affect, and students' writing proficiency as predictors of students' perceptions. Controlling for districts, students reporting more optimal classroom climate also reported higher usability, usefulness, and desirability for MI Write. Also, model results revealed that eighth graders, students with limited English proficiency, and students of lower socioeconomic status perceived MI Write relatively more useable; students with lower socioeconomic status also perceived MI Write relatively more useful and desirable. Students who liked writing more and more strongly believed that writing is a recursive process viewed MI Write as more useable, useful, and desirable. Students with greater writing proficiency viewed MI Write as less useable and useful; writing proficiency was not related to desirability perceptions. We conclude with a discussion of implications and future directions. Highlights • We study middle school students' perceptions of an AWE system called MI Write. • Students with LEP and lower SES perceived MI Write more useable/useful. • So too did students who liked writing and believed that revising was important. • Less proficient writers more strongly agreed that MI Write was useable and useful.
This article was originally published in Computers & Education. The version of record is available at: © 2023 The Authors. Published by Elsevier Ltd.
automated writing evaluation, automated feedback, writing, social validity, perceptions
Wilson, Joshua, Fan Zhang, Corey Palermo, Tania Cruz Cordero, Matthew C. Myers, Halley Eacker, Andrew Potter, and Jessica Coles. “Predictors of Middle School Students’ Perceptions of Automated Writing Evaluation.” Computers & Education 211 (April 2024): 104985.