Lexico-Syntactic Complexity in Grok 4-Generated and Human-Written Essays: Implications for Writing

Ahmad, S., Khan, W. M., Nadeem, A., & Kashif, M. (2025). The role of AI in supporting writing development while sustaining deep learning processes. Journal of Arts and Linguistics Studies, 3(2), 2993–3003. https://doi.org/10.71281/jals.v3i2.357

Akinwande, M., Adeliyi, O., & Yussuph, T. (2024). Decoding AI and human authorship: Nuances revealed through NLP and statistical analysis. International Journal on Cybernetics & Informatics (IJCI), 13(4), 85–103. https://doi.org/10.5121/ijci.2024.130408

Al-Zubaidi, K. (2025). The role of generative AI in higher education: Institutional guidelines, generational gaps, and the Grok 4 challenge. Arab World English Journal (AWEJ), 11, 1–4. https://doi.org/10.24093/awej/call11.1A

AlAfnan, M. A., & MohdZuki, S. F. (2023). Do artificial intelligence chatbots have a writing style? An investigation into the stylistic features of ChatGPT-4. Journal of Artificial Intelligence and Technology, 3(3), 85–94. https://doi.org/10.37965/jait.2023.0267

Alqurashi, N., & Hamed, D. M. (2026). Phraseological patterns within human–artificial intelligence togetherness (HAIT): A corpus-based comparison of ESL development and AI simulation. Sage Open, 16(1), 21582440261419890. https://doi.org/10.1177/21582440261419890

Amirjalili, F., Neysani, M., & Nikbakht, A. (2024). Exploring the boundaries of authorship: A comparative analysis of AI-generated text and human academic writing in English literature. Front. Educ, 9. https://doi.org/10.3389/feduc.2024.1347421

Bahari, A. (2025). Balancing syntactic complexity and clarity: The role of AI in enhancing academic writing proficiency. Saudi Journal of Language Studies, 5(4), 271–290. https://doi.org/10.1108/sjls-10-2024-0062

Biber, D. (1993). Representativeness in corpus design. Literary and Linguistic Computing, 8(4), 243–257. https://doi.org/10.1093/llc/8.4.243

Biber, D., & Conrad, S. (2019). Register, genre, and style (2nd ed.). Cambridge University Press. https://doi.org/10.1017/9781108686136

Biber, D., Gray, B., & Poonpon, K. (2011). Should we use characteristics of conversation to measure grammatical complexity in L2 writing development? TESOL Quarterly, 45(1), 5–35. https://doi.org/10.5054/tq.2011.244483

Bozorgian, H., & Rahimi, H. (2025). Peer e-feedback and chatgpt-4o in EFL writing: A cognitive-interpersonal comparison based on EFL students. Journal of Language and Education, 11(4). https://doi.org/10.17323/jle.2025.27195

Bulté, B., & Housen, A. (2012). Defining and operationalising L2 complexity. In A. Housen, I. Vedder, & F. Kuiken (Eds.), Dimensions of L2 performance and proficiency – Investigating complexity, accuracy and fluency in SLA (pp. 21–46). John Benjamins.

Bulté, B., & Housen, A. (2014). Conceptualizing and measuring short-term changes in L2 writing complexity. Journal of Second Language Writing, 26, 42–65. https://doi.org/10.1016/j.jslw.2014.09.005

Bulté, B., & Housen, A. (2018). Syntactic complexity in L2 writing: Individual pathways and emerging group trends. International Journal of Applied Linguistics, 28(1), 147–164. https://doi.org/10.1111/ijal.12196

Csomay, E., & Prades, A. (2018). Academic vocabulary in ESL student papers: A corpus-based study. Journal of English for Academic Purposes, 33, 100–118. https://doi.org/10.1016/j.jeap.2018.02.003

Daller, H., van Hout, R., & Treffers‐Daller, J. (2003). Lexical richness in the spontaneous speech of bilinguals. Applied Linguistics, 24(2), 197–222. https://doi.org/10.1093/applin/24.2.197

Dergaa, I., Chamari, K., Zmijewski, P., & Ben Saad, H. (2023). From human writing to artificial intelligence generated text: Examining the prospects and potential threats of ChatGPT in academic writing. Biol Sport, 40(2), 615–622. https://doi.org/10.5114/biolsport.2023.125623

Etaat, F. (2026). Exploring linguistic fingerprints in human and AI-generated texts: An NLP-based approach in second language writing. Ampersand, 16, 100258. https://doi.org/10.1016/j.amper.2026.100258

Fedoriv, Y., Pirozhenko, I., & Shuhai, A. (2023). Linguistic analysis of human- and AI-created content in academic discourse. Journal of Vasyl Stefanyk Precarpathian National University. Philology(10), 47–67. https://doi.org/10.15330/jpnuphil.10.47-67

Fredrick, D. R., & Craven, L. (2025). Lexical diversity, syntactic complexity, and readability: A corpus-based analysis of ChatGPT and L2 student essays [Original Research]. Frontiers in Education, Volume 10 - 2025. https://doi.org/10.3389/feduc.2025.1616935

Georgiou, G. P. (2025). Differentiating between human-written and AI-generated texts using automatically extracted linguistic features. Information, 16(11), 979. https://doi.org/10.3390/info16110979

Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning & Technology, 26(2). https://doi.org/10125/44747

Gregori-Signes, C., & Clavel-Arroitia, B. (2015). Analysing lexical density and lexical diversity in university students’ written discourse. Procedia - Social and Behavioral Sciences, 198, 546–556. https://doi.org/10.1016/j.sbspro.2015.07.477

Hadji Jamel, A. J. (2025). AI-human writing divide: Pedagogical considerations. International Journal of Linguistics, Literature and Translation, 8(12), 103–113. https://doi.org/10.32996/ijllt.2025.8.12.12

Halliday, M., & Matthiessen, C. (2014). An introduction to functional grammar (3rd ed.). Routledge.

Herbold, S., Hautli-Janisz, A., Heuer, U., Kikteva, Z., & Trautsch, A. (2023). A large-scale comparison of human-written versus ChatGPT-generated essays. Scientific Reports, 13(1), 18617. https://doi.org/10.1038/s41598-023-45644-9

Housen, A., De Clercq, B., Kuiken, F., & Vedder, I. (2019). Multiple approaches to complexity in second language research. Second Language Research, 35(1), 3–21. https://doi.org/10.1177/0267658318809765

Hunt, K. W. (1966). Recent measures in syntactic development. Elementary English, 43(7), 732–739. https://doi.org/https://www.jstor.org/stable/41386067

Ismail, H. Y. S. (2023). Cohesion and coherence in essays generated by ChatGPT: A comparative analysis to university students’ writing. CDELT Occasional Papers in the Development of English Education, 83(1), 143–165. https://doi.org/10.21608/opde.2023.325331

Jaashan, H. M. S., & Bin-Hady, W. R. A. (2025). Stylometric analysis of AI-generated texts: A comparative study of ChatGPT and DeepSeek. Cogent Arts & Humanities, 12(1), 2553162. https://doi.org/10.1080/23311983.2025.2553162

Johansson, V. (2008). Lexical diversity and lexical density in speech and writing: A developmental perspective. Working papers/Lund University, Department of Linguistics and Phonetics, 53, 61–79–61–79.

Kuhn, D., & Moore, W. (2015). Argumentation as core curriculum. Learning: Research and Practice, 1(1), 66–78. https://doi.org/10.1080/23735082.2015.994254

Kujur, A. (2025). A comparative analysis of AI-generated and human-written text: Linguistic patterns, detection accuracy, and implications for modern communication. SSRN. https://doi.org/10.2139/ssrn.5833302

Kyle, K. (2016). Measuring syntactic development in L2 writing: Fine grained indices of syntactic complexity and usage-based indices of syntactic sophistication [Unpublished doctoral dissertation]. Georgia State University.

Kyle, K. (2020). Measuring lexical richness. In S. Webb (Ed.), The Routledge handbook of vocabulary studies (1st ed., pp. 454–458). Routledge.

Kyle, K., & Crossley, S. A. (2015). Automatically assessing lexical sophistication: Indices, tools, findings, and application. TESOL Quarterly, 49(4), 757–786. https://doi.org/10.1002/tesq.194

Lahuerta Martínez, A. C. (2018). Analysis of syntactic complexity in secondary education EFL writers at different proficiency levels. Assessing Writing, 35, 1–11. https://doi.org/10.1016/j.asw.2017.11.002

Laufer, B. (1994). The lexical profile of second language writing: Does it change over time? RELC Journal, 25(2), 21–33. https://doi.org/10.1177/003368829402500202

Laufer, B., & Nation, P. (1995). Vocabulary size and use: Lexical richness in l2 written production. Applied Linguistics, 16(3), 307–322. https://doi.org/10.1093/applin/16.3.307

Liu, W., & Liu, X. (2025). A comparative analysis of syntactic complexity in argumentative essays from rhetorical perspective: ChatGPT vs. English native speakers. PLoS One, 20(8), e0329410. https://doi.org/10.1371/journal.pone.0329410

Lu, C., Bu, Y., Wang, J., Ding, Y., Torvik, V., Schnaars, M., & Zhang, C. (2019). Examining scientific writing styles from the perspective of linguistic complexity. Journal of the Association for Information Science and Technology, 70(5), 462–475. https://doi.org/10.1002/asi.24126

Lu, X. (2010). Automatic analysis of syntactic complexity in second language writing. International Journal of Corpus Linguistics, 15(4), 474–496. https://doi.org/10.1075/ijcl.15.4.02lu

Lu, X. (2011). A corpus‐based evaluation of syntactic complexity measures as indices of college‐level ESL writers' language development. TESOL Quarterly, 45(1), 36–62. https://doi.org/10.5054/tq.2011.240859

Lu, X. (2012). The relationship of lexical richness to the quality of ESL learners’ oral narratives. The Modern Language Journal, 96(2), 190–208. https://doi.org/10.1111/j.1540-4781.2011.01232_1.x

McEnery, T., & Hardie, A. (2011). Corpus linguistics: Method, theory and practice. Cambridge University Press.

Mohammed, A. A. Q., Mudhsh, B. A., Bin-Hady, W. R. A., & Al-Tamimi, A. S. (2025). Deepseek and grok in the spotlight after chatgpt in english education: A review study. Journal of English Studies in Arabia Felix, 4(1), 13–22. https://doi.org/10.56540/jesaf.v4i1.114

Nkhobo, T., & Chaka, C. (2023). Student-written versus ChatGPT-generated discursive essays: A comparative coh-metrix analysis of lexical diversity, syntactic complexity, and referential cohesion. International Journal of Education and Development Using Information and Communication Technology, 19(3), 69–84.

Ortega, L. (2003). Syntactic complexity measures and their relationship to L2 proficiency: A research synthesis of college‐level L2 writing. Applied Linguistics, 24(4), 492–518. https://doi.org/10.1093/applin/24.4.492

Ortega, L. (2012). Interlanguage complexity: A construct in search of theoretical renewal. In B. Kortmann & B. Szmrecsanyi (Eds.), Linguistic complexity: Second language acquisition, indigenization, contact (pp. 127–155). DeGruyter.

Read, J. A. (2000). Assessing vocabulary. Cambridge University Press.

Rehman, F., & Farooq, M. (2024). Instructor-led  versus  AI-generated  feedback: Implications for academic writing development. Journal of Language and Education, 10(3), 101–118.

Reviriego, P., Conde, J., Merino-Gómez, E., Martínez, G., & Hernández, J. A. (2024). Playing with words: Comparing the vocabulary and lexical diversity of ChatGPT and humans. Machine Learning with Applications, 18, 100602. https://doi.org/10.1016/j.mlwa.2024.100602

Smythos. (2025). What’s new in Grok 4: Release facts, benchmarks, and value. Retrieved December 10, 2025, from https://smythos.com/developers/ai-models/whats-new-in-grok-4-release-factsbenchmarks-and-value

Spring, R., & Johnson, M. (2022). The possibility of improving automated calculation of measures of lexical richness for EFL writing: A comparison of the LCA, NLTK and SpaCy tools. System, 106, 102770. https://doi.org/10.1016/j.system.2022.102770

Staples, S., & Reppen, R. (2016). Understanding first-year L2 writing: A lexico-grammatical analysis across L1s, genres, and language ratings. Journal of Second Language Writing, 32, 17–35. https://doi.org/10.1016/j.jslw.2016.02.002

Sulistyo, T., & Heriyawati, D. F. (2017). Reformulation, text modeling, and the development of EFL academic writing. Journal on English as a Foreign Language, 7(1), 1–16. https://doi.org/10.23971/jefl.v7i1.457

Sun, S., & Li, Y. (2025). AI-generated, L2 learner, and native German writing: A comparative analysis of linguistic complexity. Glottotheory, 16(2), 127–148. https://doi.org/10.1515/glot-2025-2011

Varga, E., & Baksa, A. (2025). Syntactic comparison of human and AI-written scientific texts. Annales Mathematicae et Informaticae, 61, 248–260. https://doi.org/10.33039/ami.2025.10.013  

Verma, A., & Arora, S. (2025). Authorship, originality, and linguistic merits in the era of artificial intelligence. Journal of English Language Teaching, 67(3), 20 – 28. https://doi.org/10.66121/08m1rd81

Wang, C. (2023, September). A syntactic complexity analysis of revised composition through artificial intelligence-based question-answering systems 2nd international conference on artificial intelligence and computer information technology (AICIT), Yichang, China.

Wangsa, K., Karim, S., Gide, E., & Elkhodr, M. (2024). A systematic review and comprehensive analysis of pioneering AI chatbot models from education to healthcare: Chatgpt, Bard, Llama, Ernie And Grok. Future Internet, 16(7), 219. https://doi.org/10.3390/fi16070219

Wind, A. M. (2025). Linguistic complexity and cohesive features of AI-generated and human-produced argumentative essays: A corpus-based analysis. DEAL, 155–175. https://doi.org/10.21862/ELTE.DEAL.2025.7

Wolfe-Quintero, K. E., Inagaki, S., & Kim, H.-Y. (1998). Second language development in writing: Measures of fluency, accuracy and complexity. University of Hawaii, Second Language Teaching and Curriculum Center.

Wu, J. (2025). Comparing linguistic features between human-written high-scoring IELTS essays and AI-generated ones. Journal of Humanities and Social Sciences Studies, 7(8), 68–77. https://doi.org/10.32996/jhsss.2025.7.8.8

xAI. (2025). Grok-4 and Grok-4 heavy release notes. Retrieved December, 28 from https://x.ai/news/grok-4

Zanotto, S. E., & Aroyehun, S. (2024). Human variability vs. machine consistency: A linguistic analysis of texts generated by humans and large language models. arXiv:2412.03025. Retrieved December 01, 2024, from https://ui.adsabs.harvard.edu/abs/2024arXiv241203025Z

Zindela, N. (2023). Comparing measures of syntactic and lexical complexity in artificial intelligence and L2 human-generated argumentative essays. International Journal of Education and Development Using Information and Communication Technology, 19(3), 50–68.