Original Research Article

Auto-Correct and Auto-Suggestion in Students’ Academic Writing

ISSN 2979-8582  ·  Article No. 033

Eseoghene Aleh✉ Richard Okiemute Ikolo Tamara Faith Okiyefa

Publication Details

Publication Date
10/11/2026
Volume / Issue
Vol 1, Issue 6 (2026)
Article No.
033
Journal
British Journal of Contemporary Research
Received
16 Oct 2026
Views
20
Downloads
12
Affiliations

Eseoghene Aleh: Languages and Linguistics, Faculty of Arts, Delta State University, Abraka , Nigeria

Richard Okiemute Ikolo: Languages and Linguistics, Faculty of Arts, Delta State University, Abraka

Tamara Faith Okiyefa: Languages and Linguistics, Faculty of Arts, Delta State University, Abraka

Abstract

The increasing integration of auto-correct and auto-suggestion technologies into digital writing environments has changed the ways students compose, revise, and monitor written texts. While these technologies are designed to facilitate accurate and efficient writing, their influence on students’ independent spelling and grammatical proficiency remains an important area of investigation. This study examines spelling and grammatical errors occurring in students’ digitally produced academic texts, with particular attention to patterns that may be associated with the use of auto-correct and auto-suggestion. The study adopts a qualitative content-analysis design supplemented by descriptive quantitative analysis. Data were drawn from thirty assignment scripts produced by tertiary-level students across different disciplines. The scripts were coded for recurring spelling and grammatical features. The analysis identified 37 spelling-error instances distributed across four categories: omission of letters (14; 37.8%), homophone confusion (11; 29.7%), auto-correct substitution (7; 18.9%), and addition of letters (5; 13.5%). Thirty-six grammatical-error instances were identified across seven categories: subject-verb agreement (8; 22.2%), tense inconsistency (6; 16.7%), preposition errors (6; 16.7%), article misuse (4; 11.1%), run-on sentences (4; 11.1%), sentence fragments (4; 11.1%), and structurally simplistic constructions (4; 11.1%). The study further considers the pedagogical implications of these findings within a digitally mediated academic-writing environment. The results suggest that the educational value of automated writing assistance depends not simply on the availability of the technology but also on students’ ability to evaluate, interpret, and learn from the feedback it provides. The findings indicate that although digital writing technologies may assist students by identifying or correcting some surface-level errors, they do not eliminate persistent difficulties involving orthographic conventions, lexical choice, grammatical agreement, tense consistency, and sentence construction. The study argues that auto-correct and auto-suggestion should be regarded as supplementary writing aids rather than substitutes for students’ independent proofreading and linguistic knowledge. The findings are interpreted within Vygotsky’s Sociocultural Theory, particularly the concepts of mediation and scaffolding.

Keywords

Auto-Correct Auto-Suggestion Academic Writing Spelling Errors Grammatical Errors

License

CC BY 4.0

This article is published under the Creative Commons Attribution 4.0 International License . Free to read, share, and adapt with attribution.

Cite This Article

Eseoghene Aleh, Richard Okiemute Ikolo, Tamara Faith Okiyefa (2026). Auto-Correct and Auto-Suggestion in Students’ Academic Writing. British Journal of Contemporary Research, 1(6), Article 033. https://doi.org/10.67693/BJCR-99REB32G
Eseoghene Aleh. “Auto-Correct and Auto-Suggestion in Students’ Academic Writing.” British Journal of Contemporary Research, vol. 1, no. 6, 2026.
Eseoghene Aleh. “Auto-Correct and Auto-Suggestion in Students’ Academic Writing.” British Journal of Contemporary Research 1, no. 6.

Metadata

ISSN 2979-8582
DOI Prefix 10.67693
Tracking ID BEX_OCT_26_137

British Journal of Contemporary Research

Open Access · Peer Reviewed · Published by Bexford Publishing Ltd

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