Innovating AI-Assisted Academic Literacy in Higher Education: Human Epistemic Control and Sustainable Human–AI Cognitive Partnership
Abstract
This study aims to (1) examine the redefinition of AI literacy through human-AI interaction in academic writing, (2) identify the activation of higher-order thinking skills (HOTS) when students evaluate and revise AI-generated content, and (3) explain how transparency in human-AI collaboration supports academic integrity. Twenty Tourism Study Program students in Bandung participated in in-depth interviews analyzed using NVivo. Nine themes emerged namely: efficiency and ease of AI use, transparency and reflection through the AI-interaction log, idea development and understanding, dependency and risk, paraphrasing and text personalization, critical thinking and information evaluation, ethics and academic integrity, ongoing AI learning, and the burden and effectiveness of the AI-interaction log. These themes were synthesized into six dimensions of AI-assisted academic literacy namely: instrumental, cognitive, textual-authorial, critical-evaluative, ethical-integrity, and reflective-regulatory. Students activated HOTS by comparing AI outputs with other sources, assessing accuracy and relevance, and making revision decisions based on their own judgment. The AI-interaction log enhanced transparency and accountability. The model positions AI as a cognitive partner while students retain epistemic control, authorship, and academic responsibility, ensuring that AI supports rather than replaces their thinking processes
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References
Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21(10), 1–22. https://doi.org/10.1186/s41239-024-00444-7
Almatrafi, O., Johri, A., & Lee, H. (2024). A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023). Computers and Education Open, 6, 100173. https://doi.org/10.1016/j.caeo.2024.100173
Almumen, H. A., & Jouhar, M. R. (2025). The impact of ChatGPT as a brainstorming tool on gifted students’ persuasive writing. Journal of Writing Research, 17(2), 181–207. https://doi.org/10.17239/jowr-2025.17.02.01
Alubthane, F. O. (2026). Amplifier or substitute? A systematic review of generative AI’s impact on higher-order cognitive skills among university students. Frontiers in Psychology, 17, Article 1863931. https://doi.org/10.3389/fpsyg.2026.1863931
Anderson, L. W., & Krathwohl, D. R. (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. Longman.
Angela, L., Handican, R., & Casanova, A. (2025). Linking belief to thought: A structural equation modeling analysis of self-efficacy and critical thinking among Indonesian pre-service teacher. Indonesian Journal on Learning and Advanced Education (IJOLAE), 393–410.
Archana, S. N., Renjith, V. R., Padmakumar, P. K., C, S., & Aboobaker, N. (2025). AI assisted learning and research: An exploratory study among university students and scholars. Discover Education, 4(1), 390.
Balalle, H., & Pannilage, S. (2025). Reassessing academic integrity in the age of AI: A systematic literature review on AI and academic integrity. Social Sciences & Humanities Open, 11, 101299. https://doi.org/10.1016/j.ssaho.2025.101299
Baldrich, K., Pérez-García, C., & Santamarina-Sancho, M. (2025, November). Artificial intelligence in academic literacy: Empirical evidence on reading and writing practices in higher education. In Frontiers in Education (Vol. 10, p. 1701238). Frontiers Media SA.
Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
Begmatova, K., & Saydazimova, I. (2025). Enhancing learners’ academic writing skills: A comparative analysis of traditional and AI-assisted instruction approaches. Applied Corpus Linguistics, 100176.
Bittle, K., & El-Gayar, O. (2025). Generative AI and academic integrity in higher education: A systematic review and research agenda. Information, 16(4), 296. https://doi.org/10.3390/info16040296
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Burneo-Arteaga, P., Lira, Y., Murzi, H., Balula, A., & Costa, A. P. (2025). Capability-based training framework for generative AI in higher education. Frontiers in Education, 10, Article 1594199. https://doi.org/10.3389/feduc.2025.1594199
Chea, P., & Xiao, Y. (2024). Artificial intelligence in higher education: The power and damage of AI-assisted tools on academic English reading skills. Journal of General Education and Humanities, 3(3), 287–306.
Chee, H., Ahn, S., & Lee, J. (2025). A competency framework for AI literacy: Variations by different learner groups and an implied learning pathway. British Journal of Educational Technology, 56(5), 2146–2182. https://doi.org/10.1111/bjet.13556
Chen, C., & Gong, Y. (2025). The role of AI-assisted learning in academic writing: A mixed-methods study on Chinese as a second language students. Education Sciences, 15(2), 141.
Chiu, T. K. F., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171. https://doi.org/10.1016/j.caeo.2024.100171
Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7–19. https://doi.org/10.1093/analys/58.1.7
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
Currie, G. M. (2023). Academic integrity and artificial intelligence: Is ChatGPT hype, hero or heresy? Seminars in Nuclear Medicine, 53(5), 719–730. https://doi.org/10.1053/j.semnuclmed.2023.04.008
Daniel, K., Msambwa, M. M., & Wen, Z. (2025). Can generative AI revolutionise academic skills development in higher education? A systematic literature review. European Journal of Education, 60(1), Article e70036. https://doi.org/10.1111/ejed.70036
Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2025). Integrating critical thinking and artificial intelligence in higher education: A bibliometric and systematic review of skills and strategies. Social Sciences & Humanities Open, 12, 101924. https://doi.org/10.1016/j.ssaho.2025.101924
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
Dinç, E., Wherley, M. S., & Sankey, H. (2024). Student perception of journaling as an assessment for an engagement experience. Journal of Experiential Education, 47(3), 484–503. https://doi.org/10.1177/10538259231203671
Dogru, T., Line, N., Hanks, L., Acikgoz, F., Abbott, J., Bakir, S., & Suess, C. (2024). The implications of generative artificial intelligence in academic research and higher education in tourism and hospitality. Tourism and Hospitality Research. https://doi.org/10.1177/13548166231204065
Eaton, S. E., & Christensen Hughes, J. (2022). Academic integrity in Canada: An enduring and essential challenge. Springer. https://doi.org/10.1007/978-3-030-83255-1
Elkhatat, A. M., Elsaid, K., & Almeer, S. (2023). Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text. International Journal for Educational Integrity, 19(1), 17. https://doi.org/10.1007/s40979-023-00140-5
Escalante, J., Pack, A., & Barrett, A. (2023). AI-generated feedback on writing: Insights into efficacy and ENL student preference. International Journal of Educational Technology in Higher Education, 20, Article 57. https://doi.org/10.1186/s41239-023-00425-2
Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., & Gašević, D. (2025). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489–530. https://doi.org/10.1111/bjet.13544
Fathy, E. A., Zidan, H. A. K. Y., El Sayed, A. H., & Fouad, A. M. (2025). Integrating ChatGPT in tourism and hospitality education: A systematic and bibliometric analysis of research trends, applications, and implications. Journal of Hospitality & Tourism Education. https://doi.org/10.1177/14673584251357510
Fauzi, F., Tuhuteru, L., Sampe, F., Ausat, A. M. A., & Hatta, H. R. (2023). Analysing the role of ChatGPT in improving student productivity in higher education. Journal on Education, 5(4), 14886–14891. https://doi.org/10.31004/joe.v5i4.2563
Firaina, R., & Sulisworo, D. (2023). Exploring the usage of ChatGPT in higher education: Frequency and impact on productivity. Buletin Edukasi Indonesia, 2(1), 39–46. https://doi.org/10.56741/bei.v2i01.310
Flower, L., & Hayes, J. R. (1981). A cognitive process theory of writing. College Composition and Communication, 32(4), 365–387. https://doi.org/10.2307/356600
Gasaymeh, A. M. M., Beirat, M. A., & Abu Qbeita, A. A. (2024). University students’ insights of generative artificial intelligence (AI) writing tools. Education Sciences, 14(10), 1062. https://doi.org/10.3390/educsci14101062
Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006
Gonsalves, C. (2024). Generative AI’s impact on critical thinking: Revisiting Bloom’s taxonomy. Journal of Marketing Education. https://doi.org/10.1177/02734753241305980
Harmadi, F., Maryani, I., Sukirman, S., & Montano, E. C. N. (2025). Digital transformation: Exploring the relationship between literacy, motivation, and TPACK in elementary education. Indonesian Journal on Learning and Advanced Education (IJOLAE), 295–311.
Harris, S. L., Shaw, M., & Green, J. F. (2024). Utilizing asynchronous email interviewing for qualitative research among multiple participant groups: Perspectives on met and unmet needs from chaplain staffing. International Journal of Qualitative Methods, 23. https://doi.org/10.1177/16094069241257943
International Center for Academic Integrity. (2021). The fundamental values of academic integrity (3rd ed.). Clemson University.
Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., & Fung, P. (2023). Survey of hallucination in natural language generation. ACM Computing Surveys, 55(12), Article 248. https://doi.org/10.1145/3571730
Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20(1), 2. https://doi.org/10.1007/s40979-024-00149-4
Jose, B., Cleetus, A., Joseph, B., Joseph, L., Jose, B., & John, A. K. (2025). Epistemic authority and generative AI in learning spaces: Rethinking knowledge in the algorithmic age. Frontiers in Education, 10, Article 1647687. https://doi.org/10.3389/feduc.2025.1647687
Kangwa, D., Msafiri, M. M., & Fute, A. (2025). Exploring the factors that promote a balance between academic integrity and the effective use of GenAI tools in higher education: A systematic review. Journal of Computer Assisted Learning, 41(5), e70109. https://doi.org/10.1111/jcal.70109
Kim, J., Lee, S.-S., Detrick, R., Wang, J., & Li, N. (2026). Students-generative AI interaction patterns and its impact on academic writing. Journal of Computing in Higher Education, 38, 504–525. https://doi.org/10.1007/s12528-025-09444-6
Kim, J., Yu, S., Lee, S.-S., & Detrick, R. (2025). Students’ prompt patterns and its effects in AI-assisted academic writing: Focusing on students’ level of AI literacy. Journal of Research on Technology in Education, 58(3), 638–655. https://doi.org/10.1080/15391523.2025.2456043
Kim, J., Yu, S., Lee, S. S., & Detrick, R. (2026). Students’ prompt patterns and its effects in AI-assisted academic writing: Focusing on students’ level of AI literacy. Journal of Research on Technology in Education, 58(3), 638–655.
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. https://doi.org/10.1207/s15326985ep4102_1
Kovári, A. (2025). Ethical use of ChatGPT in education—Best practices to combat AI-induced plagiarism. Frontiers in Education, 9, Article 1465703. https://doi.org/10.3389/feduc.2024.1465703
Kudritskaya, M., Plastinina, N., Kushnina, L., Plekhanova, Y., Matytcina, M., & Stepanova, M. (2024, June). Balancing innovation with ethics: AI applications for enhancing language competence in academic writing and reading. In 2024 4th International Conference on Technology Enhanced Learning in Higher Education (TELE) (pp. 380–385). IEEE.
Li, C., Cui, H., & Hagedorn, L. S. (2026). The cognitive impact of ChatGPT in higher education: A systematic review of critical and creative thinking outcomes. Computers and Education: Artificial Intelligence, 10, Article 100571. https://doi.org/10.1016/j.caeai.2026.100571
Li, S., & Liu, J. (2026). Mapping the distribution and depth of metacognitive processes in generative AI-assisted learning: Evidence from interaction logs and concurrent think-aloud protocols. Behavioral Sciences, 16(8), 1365. https://doi.org/10.3390/bs16081365
Lintner, T. (2024). A systematic review of AI literacy scales. npj Science of Learning, 9, 64. https://doi.org/10.1038/s41539-024-00264-4
Liu, J. E., Qiu, Z., & Lin, A. M. Y. (2026). Integrating GenAI with genre-based pedagogy and the PAA model in a college writing course: Enhancing critical engagement in an AI-mediated learning ecology. Linguistics and Education.
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1–16). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376727
Memarian, B., & Doleck, T. (2026). A systematic review of academic integrity and misconduct with artificial intelligence in higher education. SN Computer Science, 7, Article 49. https://doi.org/10.1007/s42979-025-04569-y
Miao, F., & Cukurova, M. (2024). AI competency framework for teachers. UNESCO. https://doi.org/10.54675/ZJTE2084
Miraz, M. H., Annamalah, S., & Sham, R. (2025). Integrating PLS-SEM and NVivo in mixed-methods educational research: A comprehensive evaluation of quantitative and qualitative analytical tools. Educational Process: International Journal, 19, Article e2025531. https://doi.org/10.22521/edupij.2025.19.531
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, Article 100041. https://doi.org/10.1016/j.caeai.2021.100041
Ng, D. T. K., Luo, W., Chan, H. M. Y., & Chu, S. K. W. (2024). Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach. British Journal of Educational Technology, 55(3), 1082–1104. https://doi.org/10.1111/bjet.13411
Onal, S., Kulavuz-Onal, D., & Childers, M. (2025). Patterns of ChatGPT usage and perceived benefits on academic performance across disciplines: Insights from a survey of higher education students in the United States. Journal of Educational Computing Research. https://doi.org/10.1177/00472395251341214
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, Article 422. https://doi.org/10.3389/fpsyg.2017.00422
Qian, Y. (2025). Pedagogical applications of generative AI in higher education: A systematic review of the field. TechTrends, 69, 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
Rafi, M. S., Ng, D. T. K., Amjad, I., & Ho Siu Yee, W. (2026, December). Guest editorial: AI-assisted academic writing, translation, and literacy for the promotion of human agency in higher education. Artificial Intelligence in Education, 2(2), 247–251. Emerald Publishing Limited.
Rahiem, M. D. H. (2026). Generative AI in higher education in Indonesia: Patterns of use and learning impact. Social Sciences & Humanities Open. https://doi.org/10.1016/j.ssaho.2026.102672
Rahman, S. S., Islam, M. A., Alam, M. M., Zeba, M., Rahman, M. A., Chowa, S. S., … Azam, S. (2026). Hallucination to truth: A review of fact-checking and factuality evaluation in large language models. Artificial Intelligence Review, 59(2), 1–54. https://doi.org/10.1007/s10462-025-11454-w
Riazi, A. M., Rezvani, R., & Ghanbar, H. (2023). Trustworthiness in L2 writing research: A review and analysis of qualitative articles in the Journal of Second Language Writing. Research Methods in Applied Linguistics, 2(3), Article 100065. https://doi.org/10.1016/j.rmal.2023.100065
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), 342–363. https://doi.org/10.37074/jalt.2023.6.1.9
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Strzelecki, A., Cicha, K., Rizun, M., & Rutecka, P. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5, 100190. https://doi.org/10.1016/j.caeai.2023.100190
Sunengko, S., Firmansyah, F., Fitriani, D., Nurfaisal, N., Idayanti, I., Najamudin, N. M., & Saputri, R. (2025). Critical digital literacy in AI-assisted academic writing among English literature students: A mixed-methods study. JUPEIS: Jurnal Pendidikan dan Ilmu Sosial, 4(4), 127–136.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
UNESCO, Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://doi.org/10.54675/EWZM9535
Uppal, K., & Hajian, S. (2025). Students’ perceptions of ChatGPT in higher education: A study of academic enhancement, procrastination, and ethical concerns. European Journal of Educational Research, 14(1), 199–211. https://doi.org/10.12973/eu-jer.14.1.199
Uslan, U., Abdullah, N. B., Aiman, U., & Yenni, Y. (2025). Pedagogical efficacy of guided inquiry modules: Enhancing critical thinking in elementary education through quasi-experimental validation. Indonesian Journal on Learning and Advanced Education (IJOLAE), 601–617.
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
Wang, G., Wang, W., Yang, D., & Ren, J. (2026). Generative AI, cognitive offloading, and learner agency in higher education: A scoping review. Behavioral Sciences, 16(7), 1150. https://doi.org/10.3390/bs16071150
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
Wu, J.-Y., Lee, Y.-H., Chai, C. S., & Tsai, C.-C. (2025). Strengthening human epistemic agency in the symbiotic learning partnership with generative artificial intelligence. Educational Researcher, 54(6), 358–368. https://doi.org/10.3102/0013189X251333628
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8(10), 1839–1850. https://doi.org/10.1038/s41562-024-02004-5
Yan, Lixiang, Greiff, S., Lodge, J. M., & Gašević, D. (2025). Distinguishing performance gains from learning when using generative AI. Nature Reviews Psychology, 4, 435–436. https://doi.org/10.1038/s44159-025-00467-5
Yan, W. (2023). An introduction to process tracing as an innovative qualitative research method to explore affective variables in SLA. Frontiers in Psychology, 13, Article 984444. https://doi.org/10.3389/fpsyg.2022.984444
Yanti, F. A., Wardana, R. W., Buyung, B., Heryensi, E., & Khamis, N. (2025). Automatic assessment-based artificial intelligent to measure students environmental literacy. Indonesian Journal on Learning and Advanced Education (IJOLAE), 461–480.
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.
Zhan, Y., & Yan, Z. (2025). Students’ engagement with ChatGPT feedback: Implications for student feedback literacy in the context of generative artificial intelligence. Assessment & Evaluation in Higher Education. https://doi.org/10.1080/02602938.2025.2471821
Zhang, L., & Xu, J. (2025). The paradox of self-efficacy and technological dependence: Unraveling generative AI’s impact on university students’ task completion. The Internet and Higher Education, 65, 100978. https://doi.org/10.1016/j.iheduc.2024.100978
Zhang, S., Zhao, X., Zhou, T., & Kim, J. H. (2024). Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior. International Journal of Educational Technology in Higher Education, 21(1), 34. https://doi.org/10.1186/s41239-024-00467-0
Zhao, G., Sheng, H., Wang, Y., Cai, X., & Long, T. (2025). Generative artificial intelligence amplifies the role of critical thinking skills and reduces reliance on prior knowledge while promoting in-depth learning. Education Sciences, 15(5), 554. https://doi.org/10.3390/educsci15050554
Zhou, X., Li, Y., Chai, C. S., & Chiu, T. K. F. (2025). Defining, enhancing, and assessing artificial intelligence literacy and competency in K-12 education from a systematic review. Interactive Learning Environments. https://doi.org/10.1080/10494820.2025.2487538
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