The Effect of Microsoft Word AutoCorrection and Grammarly on Iranian Elementary EFL Learners' Grammar and Spelling Development: A Sociocultural Perspective

Nabilou, Mahmoud; Zarei, Abbas Ali

doi:10.22080/iselt.2026.31628.1185

The Effect of Microsoft Word AutoCorrection and Grammarly on Iranian Elementary EFL Learners' Grammar and Spelling Development: A Sociocultural Perspective

Document Type : Original Article

Authors

Department of English Language Teaching, Faculty of Humanities, Imam Khomeini International University, Qazvin, Iran

10.22080/iselt.2026.31628.1185

Abstract

Grounded in Vygotskian sociocultural theory, this quasi-experimental study compared the effects of two distinct types of automated corrective feedback—the rule‑based Microsoft Word AutoCorrection and the AI‑powered Grammarly—against traditional paper‑based teacher correction on learning grammar and the development of spelling among Iranian elementary English as a foreign language (EFL) learners. Ninety‑six male secondary students (aged 15) in Alvand, Qazvin, were recruited in the 2025–2026 academic year and randomly assigned to Microsoft Word (n = 32), Grammarly (n = 32), or control (n = 32) groups. The participants completed grammar and spelling exercises over six 75‑minute sessions. Separate ANCOVAs on posttest scores, covarying pretest scores, yielded statistically significant main effects of instructional method: grammar, F(2, 89) = 11.83, p < .001, partial η² = .20; spelling, F(2, 89) = 7.41, p = .001, partial η² = .14, representing large effects. Bonferroni‑corrected pairwise comparisons showed both experimental groups significantly outperformed the control group on both measures. For spelling, Grammarly significantly outperformed Microsoft Word (p = .041, d = 0.42); for grammar, the difference between the two groups was not statistically significant. Drawing on the constructs of mediation, Zone of Proximal Development (ZPD), and scaffolding, the tools are interpreted as mediational artifacts that provided immediate, scaffolded feedback within learners’ ZPDs, thereby facilitating a gradual shift from other‑regulation to self‑regulation. These findings contribute to the literature on automated written corrective feedback by demonstrating the differential effectiveness of general‑purpose and AI‑powered grammar checkers across linguistic domains and offer practical implications for integrating widely available digital tools into EFL grammar and spelling instruction.

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Main Subjects

Copyright © 2027 The Author(s). Published by the Faculty of Persian Literature and Foreign Languages at the University of Mazandaran. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.

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