Open Access Peer-reviewed Research Article

Exploring Students’ Perceptions of Generative AI: Benefits, Challenges, and Academic Ethics

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Submitted   Dec 2, 2025
Published   Mar 10, 2026
Issue    Vol 6 No 1 (2026)
DOI   10.25082/AMLER.2026.01.011

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Gema Rullyana corresponding author
Department of Library and Information Science, Universitas Pendidikan Indonesia, Bandung, Indonesia
Fikri Dwi Oktaviani
Department of Library and Information Science, Universitas Pendidikan Indonesia, Bandung, Indonesia
Ardiansah Ardiansah
Department of Library and Information Science, Universitas Pendidikan Indonesia, Bandung, Indonesia
Triandari Rizki
Postgraduate Department of Educational Technology, Universitas Pelita Harapan, Banten, Indonesia

Abstract

The emergence of Generative Artificial Intelligence (GAI) has transformed how students interact with technology in academic contexts. This study aims to explore students' perceptions of the benefits, challenges, and academic integrity related to GAI usage. The research was conducted through a survey involving 71 students from the Library and Information Science Program who have used GAI in their academic activities. Data was collected using a 5-point Likert scale and analyzed descriptively using SPSS software. The findings reveal that students perceive GAI as a tool that facilitates academic tasks, improves time efficiency, and enhances language and critical thinking skills. However, they also identify various challenges, including privacy risks, information reliability, and potential plagiarism. Despite these concerns, awareness of academic integrity remains high, with students emphasizing the importance of honesty and originality in utilizing this technology. These findings provide valuable insights for educational institutions in designing policies and learning strategies that maximize the benefits of GAI while mitigating its risks. This study is expected to serve as a foundation for developing digital literacy and academic policies that are more adaptive to technological advancements. Furthermore, the accessibility of GAI through mobile devices opens opportunities for the development of learning strategies by shifting the learning paradigm from conventional classrooms toward ubiquitous learning, enabling students to learn flexibly without the constraints of time and place.

Keywords
GAI, student perception, perceived benefits, challenges of using GAI, academic integrity

Article Details

How to Cite
Rullyana, G., Oktaviani, F. D., Ardiansah, A., & Rizki, T. (2026). Exploring Students’ Perceptions of Generative AI: Benefits, Challenges, and Academic Ethics. Advances in Mobile Learning Educational Research, 6(1), 1767-1777. https://doi.org/10.25082/AMLER.2026.01.011
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References

  1. Abrahamson, E. D., & Mann, J. (2018). For Whom Is the Feedback Intended? A Student-Focused Critical Analysis of Turnitin Software as a Tool for Learning. Journal of Pedagogical Research, 2(3), 145-166.
  2. Al-Hajaya, K. (2025). Academic integrity is under fire in the Generative AI age: insights from accounting educators to overcome challenges, threats and ethical concerns. Higher Education, Skills and Work-Based Learning, 16(1), 237–255. https://doi.org/10.1108/heswbl-02-2025-0060
  3. Al-kfairy, M. (2024a). Factors Impacting the Adoption and Acceptance of ChatGPT in Educational Settings: A Narrative Review of Empirical Studies. Applied System Innovation, 7(6), 110. https://doi.org/10.3390/asi7060110
  4. Al-kfairy, M., Mustafa, D., Kshetri, N., Insiew, M., & Alfandi, O. (2024b). Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective. Informatics, 11(3), 58. https://doi.org/10.3390/informatics11030058
  5. Almassaad, A., Alajlan, H., & Alebaikan, R. (2024). Student Perceptions of Generative Artificial Intelligence: Investigating Utilization, Benefits, and Challenges in Higher Education. Systems, 12(10), 385. https://doi.org/10.3390/systems12100385
  6. Amjad, A. I., Aslam, S., Tabassum, U., Sial, Z. A., & Shafqat, F. (2024). Digital Equity and Accessibility in Higher Education: Reaching the Unreached. European Journal of Education, 59(4). Portico. https://doi.org/10.1111/ejed.12795
  7. Arowosegbe, A., Alqahtani, J. S., & Oyelade, T. (2024). Perception of generative AI use in UK higher education. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1463208
  8. Assefa, Y., Gebremeskel, M. M., Moges, B. T., Tilwani, S. A., & Azmera, Y. A. (2024). Rethinking the digital divide and associated educational in(equity) in higher education in the context of developing countries: the social justice perspective. The International Journal of Information and Learning Technology, 42(1), 15–32. https://doi.org/10.1108/ijilt-03-2024-0058
  9. Baidoo-Anu, D., Asamoah, D., Amoako, I., & Mahama, I. (2024). Exploring student perspectives on generative artificial intelligence in higher education learning. Discover Education, 3(1). https://doi.org/10.1007/s44217-024-00173-z
  10. Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and Higher Education: Trends, Challenges, and Future Directions from a Systematic Literature Review. Information, 15(11), 676. https://doi.org/10.3390/info15110676
  11. Bukar, U. A., Sayeed, Md. S., Fatimah Abdul Razak, S., Yogarayan, S., & Sneesl, R. (2024). Decision-Making Framework for the Utilization of Generative Artificial Intelligence in Education: A Case Study of ChatGPT. IEEE Access, 12, 95368–95389. https://doi.org/10.1109/access.2024.3425172
  12. Castillo, K. C., Zárate Hernández, X. M., Gazca Herrera, L. A., & Garizurieta Bernabe, J. (2024). Study of perception on the use of generative artificial intelligence in higher-level students. 2024 IEEE International Conference on Engineering Veracruz (ICEV), 1–5. https://doi.org/10.1109/icev63254.2024.10765939
  13. Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers? Smart Learning Environments, 10(1). https://doi.org/10.1186/s40561-023-00269-3
  14. Chen, M.-S., Hsu, T.-P., & Hsu, T.-C. (2024). GAI-Assisted Personal Discussion Process Analysis. Innovative Technologies and Learning, 194–204. https://doi.org/10.1007/978-3-031-65884-6_20
  15. Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187–6203. https://doi.org/10.1080/10494820.2023.2253861
  16. Ciolacu, M. I., Marghescu, C., Mihailescu, B., & Svasta, P. (2024). Does Industry 5.0 Need an Engineering Education 5.0? Exploring Potentials and Challenges in the Age of Generative AI. 2024 IEEE Global Engineering Education Conference (EDUCON), 1–10. https://doi.org/10.1109/educon60312.2024.10578712
  17. Cox, A. M., & Corrall, S. (2013). Evolving academic library specialties. Journal of the American Society for Information Science and Technology, 64(8), 1526–1542. Portico. https://doi.org/10.1002/asi.22847
  18. Davis, F. D. (1989). Technology acceptance model: TAM. Al-Suqri, MN, Al-Aufi, AS: Information seeking behavior and technology adoption, 205(219), 5.
  19. Duane, A. (2024). Can Artificial Intelligence Complete My Assessment? A Student Led Initiative to Stress Test the Academic Integrity of University Assessment Using Generative AI. 10th International Conference on Higher Education Advances (HEAd’24). https://doi.org/10.4995/head24.2024.17143
  20. El-Khalili, N., Al-Nashashibi, M., & Al-E’mari, S. (2024). The Impact of Generative Artificial Intelligence on Learning: A Case Study at the University of Petra. 2024 2nd International Conference on Cyber Resilience (ICCR), 1–6. https://doi.org/10.1109/iccr61006.2024.10532824
  21. El mourabit, I., Jai Andaloussi, S., Ouchetto, O., & Miyara, M. (2025). AI Chatbots in Higher Education: Opportunities and Challenges for Personalized and Mobile Learning. International Journal of Interactive Mobile Technologies (IJIM), 19(12), 19–37. https://doi.org/10.3991/ijim.v19i12.54163
  22. Espinoza Vidaurre, S. M., Velásquez Rodríguez, N. C., Gambetta Quelopana, R. L., Martinez Valdivia, A. N., Leo Rossi, E. A., & Nolasco-Mamani, M. A. (2024). Perceptions of Artificial Intelligence and Its Impact on Academic Integrity Among University Students in Peru and Chile: An Approach to Sustainable Education. Sustainability, 16(20), 9005. https://doi.org/10.3390/su16209005
  23. Feerrar, J. (2019). Development of a framework for digital literacy. Reference Services Review, 47(2), 91–105. https://doi.org/10.1108/rsr-01-2019-0002
  24. Gladue, K., & Poitras Pratt, Y. (2024). The Integrity of Good Relations: Indigenous Approaches to Respect, Relationality, and Reciprocity in Higher Learning. Second Handbook of Academic Integrity, 1223–1244. https://doi.org/10.1007/978-3-031-54144-5_132
  25. Guettala, M., Bourekkache, S., Kazar, O., & Harous, S. (2024). Generative Artificial Intelligence in Education: Advancing Adaptive and Personalized Learning. Acta Informatica Pragensia, 13(3), 460–489. https://doi.org/10.18267/j.aip.235
  26. Henderson, M., Selwyn, N., & Aston, R. (2015). What works and why? Student perceptions of ‘useful’ digital technology in university teaching and learning. Studies in Higher Education, 42(8), 1567–1579. https://doi.org/10.1080/03075079.2015.1007946
  27. Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2021). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1
  28. Johan, R. C., Rullyana, G., & Ardiansah, A. (2022). Hyper content e-module in information behavior course with the assistant of screencast. Journal of Education and Learning (EduLearn), 16(2), 210–218. https://doi.org/10.11591/edulearn.v16i2.20339
  29. Johan, R. C., Sutisna, M. R., Rullyana, G., & Ardiansah, A. (2020). Developing online learning communities. Borderless Education as a Challenge in the 5.0 Society, 145–153. https://doi.org/10.1201/9781003107279-29
  30. Kaldaras, L., Akaeze, H. O., & Reckase, M. D. (2024). Developing valid assessments in the era of generative artificial intelligence. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1399377
  31. Kanont, K., Pingmuang, P., Simasathien, T., Wisnuwong, S., Wiwatsiripong, B., Poonpirome, K., Songkram, N., & Khlaisang, J. (2024). Generative-AI, a Learning Assistant? Factors Influencing Higher-Ed Students’ Technology Acceptance. Electronic Journal of E-Learning, 22(6), 18–33. https://doi.org/10.34190/ejel.22.6.3196
  32. Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
  33. Knibbe, J., Peschl, R., & Osiyevskyy, O. (2024). Unleashing Creative Potential. Impacts of Generative AI on Creativity in Higher Education, 405–428. https://doi.org/10.4018/979-8-3693-2418-9.ch015
  34. Koltay, T. (2016). Data literacy for researchers and data librarians. Journal of Librarianship and Information Science, 49(1), 3–14. https://doi.org/10.1177/0961000615616450
  35. Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2022). Impacts of an AI-based chabot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development, 70(5), 1843–1865. https://doi.org/10.1007/s11423-022-10142-8
  36. Liang, J., Wang, L., Luo, J., Yan, Y., & Fan, C. (2023). The relationship between student interaction with generative artificial intelligence and learning achievement: serial mediating roles of self-efficacy and cognitive engagement. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1285392
  37. Zhi Lin Liu. (2025). Generative AI and Mobile Learning in Higher Education: Comparing Student and Faculty Perspectives on Employability Impact. International Journal of Interactive Mobile Technologies (IJIM), 19(01), 34–45. https://doi.org/10.3991/ijim.v19i01.51325
  38. Liu, Y., Park, J., & McMinn, S. (2024). Using generative artificial intelligence/ChatGPT for academic communication: Students’ perspectives. International Journal of Applied Linguistics, 34(4), 1437–1461. Portico. https://doi.org/10.1111/ijal.12574
  39. Exploring the future of learning and the relationship between human intelligence and AI. An interview with Professor Rose Luckin. (2024). Journal of Applied Learning & Teaching, 7(1). https://doi.org/10.37074/jalt.2024.7.1.27
  40. Majidah, Rullyana, G., & Triandari, R. (2025). Google Gemini as a Learning Assistant: Exploring Student Perceptions. Jurnal PAJAR (Pendidikan Dan Pengajaran), 9(2), 163–172. https://doi.org/10.33578/pjr.v9i2.10008
  41. Narang, N. K. (2024). Mentor’s Musings on Concerns, Challenges & Opportunities for Generative AI at the Edge in IoT. IEEE Internet of Things Magazine, 7(3), 6–11. https://doi.org/10.1109/miot.2024.10517510
  42. Nikolopoulou, K. (2024). Generative Artificial Intelligence in Higher Education: Exploring Ways of Harnessing Pedagogical Practices with the Assistance of ChatGPT. International Journal of Changes in Education, 1(2), 103–111. https://doi.org/10.47852/bonviewijce42022489
  43. Noviandy, T. R., Maulana, A., Idroes, G. M., Zahriah, Z., Paristiowati, M., Emran, T. B., Ilyas, M., & Idroes, R. (2024). Embrace, Don’t Avoid: Reimagining Higher Education with Generative Artificial Intelligence. Journal of Educational Management and Learning, 2(2), 81–90. https://doi.org/10.60084/jeml.v2i2.233
  44. Paliktzoglou, V., & Vlachopoulou, O. (2024). Exploring the Educational Transformations: A Systematic Literature Review on the Influence of the Internet of Things in Higher Education. EAI Endorsed Transactions on Internet of Things, 11. https://doi.org/10.4108/eetiot.4999
  45. Peng, Y., Wang, X., Chen, J., Wang, Y., Dong, Z., Wang, Y., Lyu, S., & Wang, W. (2025). The impact of AI-supported instructional interventions on students’ creative thinking: a meta-analysis of 56 experimental studies. Journal of Research on Technology in Education, 1–25. https://doi.org/10.1080/15391523.2025.2557392
  46. Plata, S., De Guzman, M. A., & Quesada, A. (2023). Emerging Research and Policy Themes on Academic Integrity in the Age of Chat GPT and Generative AI. Asian Journal of University Education, 19(4), 743–758. https://doi.org/10.24191/ajue.v19i4.24697
  47. Ramdani, Z. (2018). Construction of academic integrity scale. International Journal of Research Studies in Psychology, 7(1). https://doi.org/10.5861/ijrsp.2018.3003
  48. Rasul, T., Nair, S., Kalendra, D., Balaji, M. S., Santini, F. de O., Ladeira, W. J., Rather, R. A., Yasin, N., Rodriguez, R. V., Kokkalis, P., Murad, M. W., & Hossain, M. U. (2024). Enhancing academic integrity among students in GenAI Era:A holistic framework. The International Journal of Management Education, 22(3), 101041. https://doi.org/10.1016/j.ijme.2024.101041
  49. Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023). Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix. Sustainability, 15(15), 11524. https://doi.org/10.3390/su151511524
  50. Setyowati, Y., Priambudi, S., & Wijayanti, G. C. W. (2024). Students’ Reflections on Grammarly as a Tool for Academic Writing Support: Perceived Knowledge and Challenges in Higher Education. Scope: Journal of English Language Teaching, 9(1), 577. https://doi.org/10.30998/scope.v9i1.24854
  51. Silvana, H., Rullyana, G., & Hadiapurwa, A. (2018). Persepsi mahasiswa terhadap tindakan plagiarisme dalam penyusunan tugas akhir. EDUTECH, 16(3), 338. https://doi.org/10.17509/e.v16i3.8508
  52. Susilana, R., Rullyana, G., Ardiansah, A., & Wulandari, Y. (2022). Pedagogia Dictionary: Web Application Development. International Journal of Instruction, 15(1), 197–218. https://doi.org/10.29333/iji.2022.15112a
  53. Tatum, H. E. (2022). Honor Codes and Academic Integrity: Three Decades of Research. Journal of College and Character, 23(1), 32–47. https://doi.org/10.1080/2194587x.2021.2017977
  54. ul Haq, F., Asim, M., Suki, N. M., Zakaria, N., & Hussain, S. (2025). AI Adoption and Educational Effectiveness in Emerging Higher Education Institutions: The Moderating Role of Digital Literacy and Institutional Support. Journal of Information & Knowledge Management. https://doi.org/10.1142/s021964922550090x
  55. Yang, Y., Xia, Q., Liu, C., & Chiu, T. K. F. (2025). The impact of TPACK on teachers’ willingness to integrate generative artificial intelligence (GenAI): The moderating role of negative emotions and the buffering effects of need satisfaction. Teaching and Teacher Education, 154, 104877. https://doi.org/10.1016/j.tate.2024.104877
  56. Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-024-00453-6
  57. Zlotnikova, I., Hlomani, H., Mokgetse, T., & Bagai, K. (2025). Establishing ethical standards for GenAI in university education: a roadmap for academic integrity and fairness. Journal of Information, Communication and Ethics in Society, 23(2), 188–216. https://doi.org/10.1108/jices-07-2024-0104