Grammarly software-based editorial intervention to enhance scholarly writing performance in mathematics and science education

Authors

  • Nduka Wonu Ignatius Ajuru University of Education, Port Harcourt, River State, Nigeria
  • Patrick Kyeremeh St. Joseph’s College of Education, Bechem, Ghana
  • Christopher Yarkwah University of Cape Coast, Cape Coast, Ghana

Keywords:

Grammarly, Quality, Writing performance, Artificial intelligence, Readability, Vocabulary

Abstract

Grammarly is useful in the detection and correction of typographical and grammatical errors in written texts instantaneously. It makes suggestions to improve grammar, clarity, spelling, fluency, tone, and style in written documents. This study aimed to investigate the effect of Grammarly software on the writing quality of researchers in mathematics and science education in terms of performance, readability, and vocabulary. The study adopted a pretest-posttest design, to compare the research writing scores before and after the application of Grammarly for corrections. A total of 34 researchers who contributed 20 chapters to a book on Mathematics and Science Education formed the sample size of the study. Fourteen chapters had a pair of contributors each whereas six chapters had lone authors. Participation in the book writing project is the sole criterion for inclusion in the study. The descriptive (mean, and standard deviation) and inferential statistics (paired-sample t-test) were used for data analyses. The statistics showed that Grammarly significantly improved the researchers' overall writing abilities. However, there were no significant improvements in vocabulary or reading. We conclude that Grammarly helps improve the overall writing quality of authors and researchers in the field of academic publication. It was recommended among others that Grammarly developers should include more targeted feedback and suggestions on readability and vocabulary to help users improve their writing skills even further.

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Published

2024-03-30

How to Cite

Wonu, N., Kyeremeh, P., & Yarkwah, C. (2024). Grammarly software-based editorial intervention to enhance scholarly writing performance in mathematics and science education. Faculty of Natural and Applied Sciences Journal of Mathematical and Statistical Computing, 1(2), 11–19. Retrieved from https://fnasjournals.com/index.php/FNAS-JMSC/article/view/292