AI-Generated Assignments: Lecturers’ Perspectives on Linguistic Integrity and Pedagogical Strategies in Higher Education
DOI:
https://doi.org/10.31849/h1yr9h06Keywords:
Academic integrity, Artificial intelligence, Higher education, Lecturer perspectives, Pedagogy, Linguistic integrityAbstract
The rapid proliferation of generative Artificial Intelligence (AI) tools in higher education has fundamentally reshaped academic writing practices while simultaneously raising serious concerns about academic and linguistic integrity. Within language education, this transformation creates a critical tension between technological efficiency and the preservation of authentic student learning. Addressing this emerging challenge, the present study investigates lecturers’ perspectives on AI generated assignments with particular attention to linguistic integrity and pedagogical responses in the TBI Study Program at Universitas Islam Negeri Sumatera Utara. Using a mixed methods design, the study combined a survey of 20 lecturers with semi structured interviews involving 10 purposively selected participants who regularly assess student assignments. Quantitative data were analyzed using descriptive statistics, while interview transcripts were examined through thematic analysis to identify patterns related to authenticity, assessment practices, and institutional support. The findings reveal that the majority of lecturers have encountered AI generated assignments that demonstrate high grammatical accuracy but frequently lack originality, critical engagement, and a recognizable student voice. Lecturers also reported growing concerns that excessive reliance on AI weakens students’ critical thinking and reflective learning processes. In response, educators employ strategies such as drafts, reflective commentaries, oral defenses, and multimodal assessments to emphasize learning processes rather than final products. The study also highlights the lack of clear institutional policies on AI use in assignments and shows how language educators navigate the tension between technological innovation and academic authenticity, informing the development of AI aware pedagogical frameworks and policies that safeguard linguistic integrity in higher education.
References
Abdelrahim, A., & Abdelrahim, M. (2019). Teaching and assessing metadiscoursal features in argumentative writing: A professional development training for EFL teachers. International Journal of Applied Linguistics, 30(1), 70–91. https://doi.org/10.1111/ijal.12264
Abramova, V., Veksler, A., Glubokova, E., Nazmutdinova, T., Popova, R., Chernyshova, E., & Kalabina, I. (2024). Objective assessment of learning outcomes: Peculiarities of design and application of assessment tools in modern conditions of digital development. Science for Education Today, 14(1), 125–148. https://doi.org/10.15293/2658-6762.2401.06
Barrasso, A., & Spilios, K. (2021). A scoping review of literature assessing the impact of the learning assistant model. International Journal of STEM Education, 8(1), Article 12. https://doi.org/10.1186/s40594-020-00267-8
Bell, R., & Bell, H. (2020). Applying educational theory to develop a framework to support the delivery of experiential entrepreneurship education. Journal of Small Business and Enterprise Development, 27(6), 987–1004. https://doi.org/10.1108/jsbed-01-2020-0012
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Butakor, P. (2023). Exploring pre service teachers’ beliefs about the role of artificial intelligence in higher education in Ghana. International Journal of Innovative Technologies in Social Science, 3(39). https://doi.org/10.31435/rsglobal_ijitss/30092023/8057
DerSimonian, H., & Montagnino, F. (2025). Institutional responses to AI in higher education. Higher Education Policy Review, 42(1), 23–41.
Dison, L., & Padayachee, K. (2022). Possibilities for long term shifts in higher education assessment praxis: Reflecting on COVID 19 as a stimulus for change. South African Journal of Higher Education, 36(4), 154–172. https://doi.org/10.20853/36-4-5193
Hatami, A. (2025). Generative AI and academic integrity: Institutional challenges. Journal of Academic Ethics, 19(2), 87–104.
Jared, B., & Hanna, K. (2024). Academic integrity: Unique challenges for professional healthcare education with new emerging threats. New Directions for Teaching and Learning, 2024(179), 49–57. https://doi.org/10.1002/tl.20596
Jarrah, A., Wardat, Y., & Fidalgo, P. (2023). Using ChatGPT in academic writing is (not) a form of plagiarism: What does the literature say? Online Journal of Communication and Media Technologies, 13(4), e202346. https://doi.org/10.30935/ojcmt/13572
Kang, J., & Ahn, J. (2025). Technologies, opportunities, challenges, and future directions for integrating generative artificial intelligence into medical education: A narrative review. Ewha Medical Journal, 48(4), e53. https://doi.org/10.12771/emj.2025.00787
Kangaslampi, R., Asikainen, H., & Virtanen, V. (2022). Students’ perceptions of self assessment and their approaches to learning in university mathematics. Lumat: International Journal on Math, Science and Technology Education, 10(1). https://doi.org/10.31129/lumat.10.1.1604
Kaur, A., Bhatia, M., & Stea, G. (2022). A survey of smart classroom literature. Education Sciences, 12(2), 86. https://doi.org/10.3390/educsci12020086
Kronivets, T., Yakovenko, O., Tymoshenko, Y., Ilnytskyi, M., Iasechko, S., & Iasechko, M. (2023). Legal and ethical dimensions of AI in education: Navigating new frontiers. Review of Artificial Intelligence in Education, 4, e0021. https://doi.org/10.37497/rev.artif.intell.educ.v4i00.21
Kusrini, N. (2023). The effect of students’ self assessment on their English performance in ELT classroom. Educatif Journal of Education Research, 5(3), 311–323. https://doi.org/10.36654/educatif.v5i3.297
Lau, S. (2025). Barriers that programming instructors face while performing emergency pedagogical design to shape student AI interactions with generative AI tools. arXiv Preprint. https://doi.org/10.48550/arxiv.2510.09492
Lehman, I., Bednarek, A., & Sułkowski, Ł. (2024). The role of reader-inclusive authorial voice in the process of academic socialization of management and English philology students. Ibérica, 47, 275–300. https://doi.org/10.17398/2340-2784.47.275
Lehman, I., Celis, K., & Sułkowski, Ł. (2022). Writing to make a difference: Discursive analysis of writer identity in research articles on management. Ibérica, 44, 155–178. https://doi.org/10.17398/2340-2784.44.155
Lendvai, G. (2025). ChatGPT in academic writing: A scientometric analysis of literature published between 2022 and 2023. Journal of Empirical Research on Human Research Ethics, 20(3), 131–148. https://doi.org/10.1177/15562646251350203
Luckin, R. (2025). AI and the future of learning: Balancing innovation and responsibility. Routledge.
Mah, C., Walker, H., Phalen, L., Levine, S., Beck, S., & Pittman, J. (2024). Beyond cheatbots: Examining tensions in teachers’ and students’ perceptions of cheating and learning with ChatGPT. Education Sciences, 14(5), 500. https://doi.org/10.3390/educsci14050500
Mahlangu, T. (2024). A bibliometric analysis of assessment as learning in higher education. Proceedings of the World Conference on Teaching and Education, 3(1), 28–38. https://doi.org/10.33422/worldcte.v3i1.603
McClain, A. (2025). Leveraging artificial intelligence in research and scholarly work: Innovative approaches and practical applications. New Directions for Adult and Continuing Education, 2025(188), 48–56. https://doi.org/10.1002/ace.70015
Meyer, J., Urbanowicz, R., Martin, P., O’Connor, K., Li, R., Peng, P., & Moore, J. (2023). ChatGPT and large language models in academia: Opportunities and challenges. Biodata Mining, 16(1), Article 20. https://doi.org/10.1186/s13040-023-00339-9
Mugambi, M. (2018). Linking constructivism theory to classroom practice. International Journal of Humanities Social Sciences and Education, 5(9). https://doi.org/10.20431/2349-0381.0509014
Nadhifah, A., Syukur, H., Haryanto, M., Luthfiyyah, R., & Rozak, D. (2024). Pre service English teacher perceptions of AI in writing skills. Journal of World Englishes and Educational Practices, 6(2), 26–32. https://doi.org/10.32996/jweep.2024.6.2.3
Namutebi, E. (2024). Exploring artificial intelligence as a remedy to the heavy teaching workloads caused by massification of Ugandan public universities. East African Journal of Education Studies, 7(3), 98–118. https://doi.org/10.37284/eajes.7.3.2057
Peng, J., & Zheng, Y. (2021). Metadiscourse and voice construction in discussion sections in BA theses by Chinese university students majoring in English. SAGE Open, 11(2), Article 21582440211008870. https://doi.org/10.1177/21582440211008870
Petricini, T., Wu, C., & Zipf, S. (2023). Perceptions about generative AI and ChatGPT use by faculty and college students. Open Science Framework Preprints. https://doi.org/10.35542/osf.io/jyma4
PireciSejdiu, N., & Sejdiu, S. (2025). The quiet transformation of higher education in the AI era. Open Research Europe, 5, 249. https://doi.org/10.12688/openreseurope.20715.1
Pokhrel, P. (2021). English teachers’ perceptions on inquiry based teaching. Journal of NELTA Gandaki, 4(1–2), 98–108. https://doi.org/10.3126/jong.v4i1-2.42647
Pratiwi, H., Suherman, S., Hasruddin, & Ridha, M. (2025). Between shortcut and ethics: Navigating the use of artificial intelligence in academic writing among Indonesian doctoral students. European Journal of Education, 60(2), e70083. https://doi.org/10.1111/ejed.70083 (ERIC)
Qadhi, S., Alduais, A., Chaaban, Y., & Khraisheh, M. (2024). Generative AI, research ethics, and higher education research: Insights from a scientometric analysis. Information, 15(6), 325. https://doi.org/10.3390/info15060325
Raptopoulou, A. (2025). ChatGPT in higher education: Supporting academic literacy through ChatGPT based activities. European Journal of Education, 60(2). https://doi.org/10.1111/ejed.70131
ROA, A., & Halim, S. (2024). The impact of AI powered software on second language writing: A systematic literature review. Research and Innovation in Applied Linguistics Electronic Journal, 2(2), 138. https://doi.org/10.31963/rial.v2i2.4801
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1). https://doi.org/10.37074/jalt.2023.6.1.9
Selwyn, N. (2024). Education and AI: Critical perspectives. Polity Press.
Singh, M. (2023). Maintaining the integrity of the South African university: The impact of ChatGPT on plagiarism and scholarly writing. South African Journal of Higher Education, 37(5). https://doi.org/10.20853/37-5-5941
Sun, F. (2023). Effects of inquiry based teaching on learning efficiency in an augmented reality environment. International Journal of Emerging Technologies in Learning, 18(15), 23–35. https://doi.org/10.3991/ijet.v18i15.41357
Takrouni, A., & Assalahi, H. (2022). An inquiry into EFL teachers’ perceptions of integrating student self assessment into teaching academic writing at a Saudi university. Theory and Practice in Language Studies, 12(3), 471–481. https://doi.org/10.17507/tpls.1203.06
UNESCO. (2024). AI and education: Guidance for policy-makers. Paris: UNESCO Publishing. Retrieved from https://www.unesco.org/en/articles/ai-and-education-guidance-policy-makers
Wach Kąkolewicz, A. (2023). University lecturers’ skills for designing collaborative online classes. In University Teaching and Learning in Digital Era (pp. 11–28). https://doi.org/10.12657/9788379863761-2
Walsh, J., Krienert, J., Cannon, K., & Honan, S. (2024). Professors call it cheating, students call it teamwork: Evolving norms of academic integrity in the transformative era of online education. Journal of the Scholarship of Teaching and Learning, 24(2), 47–63. https://doi.org/10.14434/josotl.v24i2.35191
Whalley, B., France, D., Park, J., Mauchline, A., & Welsh, K. (2019). Developing active personal learning environments on smart mobile devices. In Smart Learning Environments (pp. 871–889). https://doi.org/10.1007/978-3-030-32523-7_64
Wu, C., Wang, X., Carroll, J., & Rajtmajer, S. (2024). Reacting to generative AI: Insights from student and faculty discussions on Reddit. In Proceedings of the ACM Conference on Learning at Scale (pp. 103–113). https://doi.org/10.1145/3614419.3644014
Yan, D. (2023). How ChatGPT automatic text generation impacts learners in an L2 writing practicum: An exploratory investigation. Open Science Framework Preprints. https://doi.org/10.35542/osf.io/s4nfz
Zhao, J., & Liu, Y. (2021). A developmental view of authorial voice construction in master’s thesis: A case study of two novice L2 writers. SAGE Open, 11(4), Article 21582440211054483. https://doi.org/10.1177/21582440211054483
Zhu, L., & Atompag, S. (2023). The application of the constructivism theory in enhancing classroom teaching. Journal of Contemporary Educational Research, 7(12), 209–213. https://doi.org/10.26689/jcer.v7i12.5792
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