Influence of Grammarly AI Writing Tools on Undergraduate Students’ Perceived Academic Writing Performance in Selected Northern Nigerian Universities

Cite this article as: Iorhemen, B. T., Fatai, S., Alhamdu, Y., &Wasagu, S. M. (2026). Influence of Grammarly AI writing tools on undergraduate students’ perceived academic writing performance in selected Northern Nigerian universities. Sokoto Journal of Linguistics and Communication Studies (SOJOLICS), 2(1), 51-58. https://doi.org/10.36349/sojolics.2026.v02i01.005

By

IORHEMEN, Benjamin Terzungwe,

Department of Arts and Social Science Education, Faculty of Education,

Federal University of Kashere, Gombe State, Nigeria

benudus2016@gmail.com|

ORCID:https://orcid.org/0000-0002-13577859

 +2348034581621, +2348157825839

&

FATAI, Shittu Ph.D

Department of European Languages and Literary Studies, Faculty of Arts,

Federal University, Birnin Kebbi, Kebbi State,Nigeria

shitu.fatai@fubk.edu.ng;

&

ALHAMDU, Yakubu

Department of Arts Education, Faculty of Education,

University of Jos, Plateau State, Nigeria

alhamduyakubu83@gmail.com;

&

Wasagu, Samira Muhammad

Department of English and Literary Studies, Faculty of Arts,

UsmanuDanfodiyo University, Sokoto, Nigeria

samirawasagu1@gmail.com

Abstract

The increasing adoption of artificial intelligence (AI) writing tools has transformed academic writing practices among university students. This study investigated the influence of Grammarly AI writing tools on undergraduate students perceived academic writing performance in selected Northern Nigerian universities. Anchored on the Technology Acceptance Model (TAM) and Self-Regulated Learning (SRL) Theory, the study examined the level of Grammarly usage, students perceived academic writing performance, the relationship between Grammarly usage and academic writing performance, and the predictive influence of Grammarly usage on writing performance. A quantitative cross-sectional survey design was adopted. The population comprised 8,450 undergraduate students drawn from three Northern Nigerian universities, from which 392 respondents were selected using a multistage sampling technique. Data were collected using a structured questionnaire validated by experts in Educational Technology, Measurement and Evaluation, and English Language Education. The instrument yielded a Cronbach’s alpha coefficient of .88, indicating high reliability. Data were analysed using descriptive statistics, Pearson Product-Moment Correlation, and linear regression. Findings revealed high Grammarly usage (M = 4.09, SD = 0.83) and high perceived academic writing performance (Grand Mean = 4.15). Grammarly usage was positively related to academic writing performance (r = .56, p < .01) and significantly predicted writing performance (β = .56, p < .001), accounting for 31% of the variance (R² = .31). The study concludes that Grammarly is an effective supplementary writing-support tool and recommends its integration into university writing instruction with appropriate ethical guidance.

Keywords: Artificial Intelligence, Academic Writing Performance, Automated Writing Evaluation, Grammarly, Undergraduate Students, Nigeria.

1.       Introduction

The integration of artificial intelligence (AI) into education has generated considerable interest across teaching and learning research. AI technologies promise adaptive and interactive learning environments that respond to individual learner needs, shifting the role of the teacher from information provider to facilitator of learning across higher education institutions worldwide (Zawacki-Richter et al., 2019; Iorhemen, Wasagu& Dahiru, 2026). Among the most widely adopted AI applications in education are automated writing evaluation tools that provide learners with immediate feedback on grammar, vocabulary, style, and textual clarity.

Academic writing remains a fundamental requirement for success in higher education because it facilitates knowledge construction, critical thinking, scholarly communication, and research dissemination. However, many undergraduate students, particularly those learning English as a second language, experience difficulties in grammar, coherence, vocabulary use, sentence structure, and organization of ideas. These challenges are especially evident in Nigerian universities where students often receive limited individualized feedback due to large class sizes and heavy instructional workloads.

Grammarly has become one of the most popular AI-powered writing assistants used by university students. Grammarly is an AI-powered automated writing evaluation tool that provides real-time feedback on grammar, spelling, punctuation, vocabulary, and writing style to help improve the quality and accuracy of written texts. However, in this study, Grammarly is conceptualise as an AI-powered writing assistance tool used by undergraduate students to review, edit, and improve their academic writing through automated feedback on grammar, sentence structure, clarity, and writing quality. Through natural language processing and machine learning algorithms, Grammarly identifies grammatical errors, punctuation problems, vocabulary misuse, and stylistic weaknesses while providing instant corrective feedback. Research has shown that automated writing feedback can improve linguistic accuracy and support writing revision processes (Abdelhalim, 2024; Sanosi, 2022). Nevertheless, concerns remain regarding students’ overreliance on AI-generated feedback and the extent to which such tools promote genuine learning beyond surface-level corrections (Zhang & Hyland, 2023).

Despite the increasing popularity of Grammarly among Nigerian university students, empirical evidence regarding its influence on academic writing performance remains limited, particularly within Northern Nigerian universities. Most existing studies have been conducted in Western or Asian educational contexts, creating a contextual research gap. This study therefore fills that gap by examining the influence of Grammarly AI writing tools on undergraduate students perceived academic writing performance in selected Northern Nigerian universities. The study is guided by these research questions: What is the level of Grammarly AI writing tool usage among undergraduate students in selected Northern Nigerian universities? What is the level of undergraduate students perceived academic writing performance when using Grammarly AI writing tools? What relationship exists between Grammarly AI writing tool usage and undergraduate students perceived academic writing performance in selected Northern Nigerian universities? To what extent does Grammarly AI writing tool usage predict undergraduate students perceived academic writing performance in selected Northern Nigerian universities? Addressing this gap is essential, as students’ perceptions of the effectiveness of AI writing tools can provide invaluable insights for educators, universities, and policymakers seeking to devise improved academic writing instruction in higher education.

2.        Literature Review

Automated Writing Evaluation (AWE) systems have attracted considerable attention in higher education because of their ability to provide immediate feedback and support writing revision. Grammarly, in particular, has become widely used due to its accessibility and ability to identify grammatical and stylistic errors in real time. Studies have consistently reported positive effects of Grammarly on students’ writing quality, grammatical accuracy, and revision behaviour (Ng et al., 2025; Sanosi, 2022; Ghufron, 2019). Abdelhalim (2024) reported that AI-supported feedback significantly improved revision quality among English language learners. Similarly, Huang et al. (2020) found that students who used Grammarly over a sixteen-week period demonstrated significant improvement in writing performance and expressed positive attitudes toward the tool.

Recent studies suggest that Grammarly supports self-regulated learning by providing immediate feedback that enables students to monitor, evaluate, and revise their writing independently. Through repeated engagement with automated feedback, learners develop greater writing self-efficacy and become more active participants in the revision process. Su (2024) reported a positive relationship between Grammarly-based automated writing evaluation and learners’ writing self-efficacy within self-regulated learning environments. From a technology acceptance perspective, students are more likely to adopt educational technologies that are perceived as useful and easy to use (Davis, 1989). Furthermore, Abu Qub’a et al. (2024) observed that Grammarly assists writers in identifying language problems and improving academic writing quality, although it should complement rather than replace human feedback. These findings indicate that Grammarly promotes both technology acceptance and self-regulated learning, making it a valuable tool for supporting academic writing in higher education.

However, scholars have also identified limitations associated with AI writing tools. Zhang and Hyland (2023) argued that automated feedback systems primarily focus on lower-order concerns such as grammar and mechanics while offering limited support for higher-order skills including argumentation, critical analysis, and rhetorical development.

Consequently, Grammarly should be viewed as a complementary instructional tool rather than a substitute for human feedback.

3.       Methodology

This study adopted a quantitative cross-sectional survey design to examine the influence of Grammarly AI writing tools on undergraduate students perceived academic writing performance in selected Northern Nigerian universities. The population comprised 8,450 undergraduate students ‘drawn from three Northern Nigerian universities. A sample of 392 respondents was selected using a multistage sampling technique based on Krejcie and Morgan's sampling guideline.

Data were collected using a structured questionnaire consisting of items on Grammarly usage and perceived academic writing performance. The instrument was validated by experts in Educational Technology, Measurement and Evaluation, and English Language Education to ensure content relevance and clarity. Reliability was established using Cronbach's alpha, which yielded a coefficient of .88, indicating high internal consistency.

Following institutional approval, the researchers administered the questionnaire directly to the selected respondents with the assistance of trained research assistants. Online administration was also employed to reach respondents who could not be accessed physically. Completed questionnaires were retrieved and screened for completeness before analysis. Data analysis involved descriptive statistics, Pearson Product-Moment Correlation, and linear regression at a .05 significance level.

4.     Theoretical Framework

The study was anchored on the Technology Acceptance Model (TAM) and Self-Regulated Learning (SRL) Theory.

4.1.      The Technology Acceptance Model developed by Davis (1989) explains technology adoption through two principal constructs: perceived usefulness and perceived ease of use. Students are more likely to adopt Grammarly when they perceive that it improves writing performance and can be used with minimal effort.

4.2.      Self-Regulated Learning Theory emphasizes learners’ ability to plan, monitor, evaluate, and regulate their learning activities (Zimmerman, 2002). Grammarly supports self-regulation by enabling students to review feedback, revise drafts, and monitor writing quality during the writing process. Together, TAM and SRL provide a comprehensive explanation of why students adopt Grammarly and how its use contributes to perceived improvements in academic writing.

5.      Data Presentation and Analysis

Table 1: Demographic Characteristics of Respondents (N = 392)

Variable                          Category                 Frequency                   Percentage (%)

Gender                               Male                          214            54.6                                             Female                      178                                45.4 Level of study                     100 Level                  82                                 20.9                                              200 Level                 96                                  24.5                                              300 Level                 110                                28.1                                              400 Level                 104                                26.5

(Source: Field work, 2026)

Table 1 presents the demographic characteristics of the respondents.

Table 2: Level of Grammarly Usage among Students

Variable                                                                       Mean                                       SD

Grammarly usage for academic writing                      4.09                                         0.83

(Source: Field work, 2026)

The result in Table 2 indicates a high level of Grammarly usage among respondents (M = 4.09, SD = 0.83).

Table 3: Descriptive Statistics for Perceived Academic Writing Performance

Item                                                          Mean                       SD

Grammarly helps grammatical accuracy 4.18                          0.78                   Grammarly supports sentence clarity 4.11                         0.82 Grammarly enhances errors detection        4.27                         0.74 Grammarly improves writing quality generally                       4.14    0.86 Grammarly facilitates organization of ideas                            4.03        0.88  Grand Mean = 4.15

(Source: Field work, 2026)

Table 3 result Grand Mean = 4.15 reveals that students perceive improvements in their writing such as grammar accuracy, clarity and organization.

 

Table 4: Reliability Analysis of the Academic Writing Performance Scale

Construct                                                      Number of Items                  Cronbach’s Alpha

Perceived Academic Writing Performance              5                                        0.88

(Source: Field work, 2026)

Table 4 presents the reliability statistics for the perceived academic writing performance scale used in the study. The Cronbach’s alpha coefficient for the scale is 0.88, which exceeds the commonly accepted threshold of 0.70 for internal consistency.

Table 5

Correlation Matrix of Grammarly Usage and Academic Writing Performance

Variable                                                                                1                              2

Grammarly Usage— Academic Writing Performance.56**— Note: p < .01

(Source: Field work, 2026)

Table 5 presents the Pearson correlation analysis. The results reveal a moderate positive correlation (r = .56) between Grammarly usage and academic writing performance, which is statistically significant at the 0.01 level.

Table 6

Regression Analysis Predicting Academic Writing Performance

Predictor                               B                  SE                   β                         t                  p

Grammarly Usage0.520.05.5610.41< .001 Model Summary   R        R²      Adjusted R²    F .56.31.30108.40***

(Source: Field work, 2026)

The regression analysis results in Table 6 depicts that Grammarly usage has a significant positive effect on academic writing performance (β = .56, p < .001). The model summary indicates that Grammarly usage explains 31% of the variance in academic writing performance (R² = .31).

6.       Discussion of Findings

The findings demonstrate that Grammarly has become an integral component of students’ academic writing practices. The high level of usage observed among respondents suggests increasing acceptance of AI-powered educational technologies within Nigerian universities. This finding supports the Technology Acceptance Model, which posits that users are more likely to adopt technologies they perceive as useful and easy to use (Davis, 1989).

Students also reported positive perceptions regarding their academic writing performance. Specifically, respondents believed that Grammarly improved grammatical accuracy, sentence clarity, error detection, and overall writing quality. These findings corroborate earlier studies that identified Grammarly as an effective writing-support tool for enhancing linguistic accuracy and revision practices (Sanosi, 2022; Abu Qub’a et al. 2024; Ng et al., 2025).

The significant positive relationship between Grammarly usage and perceived academic writing performance further suggests that students who engage more frequently with Grammarly experience greater perceived improvements in writing. This finding aligns with Self-Regulated Learning Theory, which emphasizes the importance of monitoring, revising, and evaluating learning outputs (Zimmerman, 2002). Grammarly appears to facilitate these processes by providing immediate feedback that encourages iterative revision.

The regression results indicate that Grammarly usage is a significant predictor of academic writing performance. Although Grammarly explained a substantial proportion of the variance in writing performance, other factors such as language proficiency, motivation, instructor feedback, and academic experience may also influence writing outcomes. Therefore, Grammarly should be considered one component of a broader academic writing support system.

7.         Conclusion

This study investigated the influence of Grammarly AI writing tools on undergraduate students perceived academic writing performance in selected Northern Nigerian universities. The findings revealed high levels of Grammarly usage and positive perceptions of academic writing performance among students. Grammarly usage was significantly associated with and predictive of perceived academic writing performance.

The study concludes that Grammarly is a valuable supplementary educational technology capable of supporting academic writing development through automated feedback, self-monitoring, and revision. However, its effectiveness is maximized when used alongside traditional writing instruction and instructor feedback. Consequently, universities should embrace AI-assisted writing technologies while promoting responsible, ethical, and pedagogically sound practices. Hence, the integration of Grammarly into university writing instruction may contribute to improved writing outcomes and enhanced learner autonomy.

 

References

Abu Qub’a, A., Abu Guba, M. N., & Fareh, S. (2024). Exploring the use of Grammarly in assessing English academic writing. Heliyon, 10(15), e34893. https://doi.org/10.1016/j.heliyon.2024.e34893

Abdelhalim, S. M. (2024). Artificial intelligence and automated writing feedback in EFL academic contexts: Effects on revision quality. Computers & Education: Artificial Intelligence, 6, 100206. https://doi.org/10.1016/j.caeai.2024.100206

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Ghufron, M. A. (2019, April). Exploring an automated feedback program ‘Grammarly ‘and teacher corrective feedback in EFL writing assessment: Modern vs. traditional assessment. In Proceedings of the 3rd English language and literature international conference, ELLiC (pp. 307-315).

Huang, H.-W., Li, Z., & Taylor, L. (2020). The effectiveness of using Grammarly to improve students’ writing skills. In Proceedings of the 5th International Conference on Distance Education and Learning (pp. 122–127).

Iorhemen, B. T., Wasagu, S. M., & Dahiru, A. (2026). Transforming English language teaching in the era of artificial intelligence: Examining the opportunities and challenges of ChatGPT. In Synergy of Ideas: AKASA Multidisciplinary Book Chapter Contributions (2nd ed., pp. 37–55). https://doi.org/10.64726/m83kg860

Ng, W., Yunus, M. M., & Ismail, H. H. (2025). Investigating the effect of Grammarly on enhancing writing skills in ELT classrooms: A systematic literature review (2020–2024). International Journal of Academic Research in Progressive Education and Development, 14(1), 1454–1474. https://doi.org/10.46886/IJARPED/v14-i1/17500

Sanosi, A. B. (2022). The impact of automated written corrective feedback on EFL learners’ academic accuracy. Journal of Teaching English for Specific and Academic Purposes, 7(2), 301–317.https://doi.org/10.22190/JTESAP2202301S

Su, Y. (2024). A correlation study of automated writing evaluation system (Grammarly) and Chinese EFL learners’ writing self-efficacy in their self-regulated learning. Journal of Electrical Systems, 20(3), 1874–1895. https://doi.org/10.52783/jes.3904

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39).https://doi.org/10.1186/s41239-019-0171-0

Zhang, Z., & Hyland, K. (2023). The role of digital literacy in student engagement with automated writing evaluation feedback. Computer Assisted Language Learning. https://doi.org/10.1080/09588221.2023.2256815

Zimmerman, B. J. (2002). Becoming a self-regulated learner. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/S15430421TIP4102_2