IJIET 2025 Vol.15(10): 2297-2307
doi: 10.18178/ijiet.2025.15.10.2425
doi: 10.18178/ijiet.2025.15.10.2425
MindTer: Web Application for Grammar Correction of English Writing Using Natural Language Processing Techniques
Nancy Rodríguez*, Paola Benitez, Lucrecia Llerena, and Cristhian Hidalgo
Department of Software Engineering, Faculty of Computer Science and Digital Design,
State Technical University of Quevedo, Quevedo, Ecuador
Email: nrodriguez@uteq.edu.ec (N.R.); pbenitez@uteq.edu.ec (P.B.); lllerena@uteq.edu.ec (L.L.); cristhian.hidalgo2017@uteq.edu.ec (C.H.)
*Corresponding author
Email: nrodriguez@uteq.edu.ec (N.R.); pbenitez@uteq.edu.ec (P.B.); lllerena@uteq.edu.ec (L.L.); cristhian.hidalgo2017@uteq.edu.ec (C.H.)
*Corresponding author
Manuscript received March 13, 2025; revised March 31, 2025; accepted June 18, 2025; published October 24, 2025
Abstract—In a globalized world where English language proficiency is crucial, the discrepancy in writing skills, particularly among non-native speakers, motivated the development of “MindTer”. The name “MindTer” combines “Mind” and “Writer”, reflecting its focus on cognitive assistance and language accuracy in academic writing. MindTer was designed as a solution to correct grammatical errors in English and improve written communication skills, facilitating selfdirected learning and supporting educators in language instruction. Additionally, it promotes linguistic fluency in a digital and global environment. MindTer is an innovative web application supported by artificial intelligence and focused on natural language processing techniques. In the development of MindTer, a systematic mapping approach was employed to identify applicable Natural Language Processing (NLP) models, and the evolutionary prototyping methodology was adopted throughout the implementation process. MindTer was evaluated remotely by users from various regions, utilizing established usability assessment techniques, including Remote Observation, Think-Aloud Protocol, and the System Usability Scale (SUS) questionnaire. The usability evaluation yielded an average SUS score of 77.0, reflecting a generally favorable perception of the system. These results, along with the identified areas for improvement, provide a robust foundation for future enhancements, thereby supporting the pursuit of excellence in English language instruction and grammatical precision. This study underscores the significance of integrating advanced technologies into language learning and outlines a pathway toward more personalized and effective educational experiences.
Keywords—formal learning, language learning, education, syntax error detection, natural language processing
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—formal learning, language learning, education, syntax error detection, natural language processing
Cite: Nancy Rodríguez, Paola Benitez, Lucrecia Llerena, and Cristhian Hidalgo, "MindTer: Web Application for Grammar Correction of English Writing Using Natural Language Processing Techniques," International Journal of Information and Education Technology, vol. 15, no. 10, pp. 2297-2307, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).