The effectiveness of automated writing evaluation: a structural analysis approach

Abdulaziz B. Sanosi, Mohammed Omar Musa Mohammed


Modern advancement in learning technologies and tools has presented innovative written corrective feedback (WCF) methods based on artificial intelligence (AI) and existing corpora. Research has shown that these tools are perceived as exciting and useful by students, yet studies on their effectiveness and impact on students’ writing are relatively insufficient. To this end, the present study investigated the effectiveness of Grammarly writing assistant as perceived by 98 undergraduates who used the tool for a 14-week semester. The study adopted a questionnaire based on a modified technology acceptance model (TAM). The gathered data was analyzed using SmartPLS 3 software. The results revealed that different factors predict students’ perceptions about Grammarly and their intention to use it. Some of these factors were not presupposed. The findings imply using Grammarly as an extra learning tool rather than a basic one. It is suggested that future research on the efficacy of Grammarly should adopt longitudinal and experimental approaches.


Automated corrective feedback; Feedback; Grammarly; Technology acceptance; Writing correction

Full Text:




  • There are currently no refbacks.

Copyright (c) 2024 Institute of Advanced Engineering and Science

International Journal of Evaluation and Research in Education (IJERE)
p-ISSN: 2252-8822, e-ISSN: 2620-5440
The journal is published by Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU) 

View IJERE Stats

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.