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Exploring the Extent Quillbot and Grammarly Are Tools for Enhancing the Quality of Academic Writing in Public Universities in Anambra State, Nigeria

Year: 2025

Type: article

Abstract: The main purpose of the study was to explore the extent Quillbot and Grammarly are tools for enhancing the quality of academic writing in public universities in Anambra State, Nigeria. Two research questions guided the study. Two hypotheses were tested at 0.05 level of significance. The correlational survey research design was adopted for the study. The population of the study was made of 155 lecturers of the Department of Educational Management in two public universities in Anambra State. Two structured researcher developed validated questionnaires were used to collect data for the study. The reliability of the instruments was attained through a pilot test. The data collected were analyzed using Cronbach Alpha. The reliability coefficient values of 0.84 and 0.88 were obtained for clusters A and B respectively with an overall reliability co-efficient value of 0.86 for QUQGTEQAWPU and 0.92 for QQAW. Mean, standard deviation and simple regression analysis were used to analyse data for the study. The finding of the study revealed that Quillbot is a tool for enhancing the quality of academic writing in public universities in Anambra State, Nigeria to a high extent. Finding also showed that Grammarly is a tool for enhancing the quality of academic writing in public universities in Anambra State, Nigeria to a high extent. Furthermore, the finding also showed that Quillbot and Grammarly significantly enhances the quality of academic writing in public universities in Anambra State, Nigeria. Based on these findings the researcher recommended among others that administrators of universities in Anambra State should incorporate AI-powered writing tools like QuillBot and Grammarly into academic writing courses and research methodology training to help students develop strong writing skills.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15051130

Authors: Onyekwelu, Raphael Azubuike PhD, Helen, Chinelo Onuorah PhD.

Institutions: Chukwuemeka Odumegwu Ojukwu University, Chukwuemeka Odumegwu Ojukwu University, Igbariam Campus, Nnamdi Azikiwe University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: green

OpenAlex ID: W6949944065

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