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The Generative AI Landscape in Education: Mapping the Terrain of Opportunities, Challenges, and Student Perception
Open accessAbstract
Generative AI (GAI) technologies like ChatGPT are permanently changing academic education. Their integration opens up vast opportunities for bespoke learning and better student interaction but also brings about academic honesty issues and the application of real-life educators. This study aims to fill the literature gap regarding the use of multiple GAI tools and their effect on academic outcomes via a comprehensive review. A systematic literature review was performed following PRISMA guidelines to synthesize results on the potential and drawbacks of GAI in educational domains. We included theoretical and empirical papers that used qualitative, quantitative, or mixed-methods study designs. We have also explored conceptual frameworks and the most creative AI applications with a special emphasis on uniqueness and practicability. Experiences, and Perceptions Concerning To compile the information needed we gathered insights into what students were going through by conducting the survey which contains 200 respondents of undergraduate university students gathering insights into the college students’ experiences and perceptions related to GAI used for educational purposes. At the basic level, GAI comprises areas like personalization, task automation, teacher assistance, and efficiency among others, and respective solutions for the immersion of a learner in learning processes to reform directions. However, it generates plenty of challenges such as the question of assessment integrity, the risk that too much automated grading could overwhelm educational value, and relevantly the veracity of AI-generated content as well as the potential disruption to skills like critical thinking, in addition to data privacy and ethical issues. Student Perception Survey the text also indicates that most students, as per the student perception survey found AI systems useful in academic support. However, they also know the other side of the coin and are very familiar with the technology constraints and challenges.
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“Studies have revealed that traditional plagiarism detection tools, such as Turnitin, are ineffective in identifying AI-gen -erated content, often yielding false positives or negatives [ 31, 60, 85, 89, 90 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [60]
In the citing paper
“The reliance on AI for tasks requiring cognitive engagement results in declining independent reasoning, writing abilities, critical thinking, and analytical skills, making students less prepared for realworld problem-solving scenarios [ 60, 72, 93, 97, 98].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [60]
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“Extensive research has demonstrated AIGC as a promising approach to develop course design materials, provide adaptive instructions and feedback, and support academic writing in higher education [5].”
Research on Generative AI-Empowered Smart Education in Automotive Structure Course
Han, X., Xing, X., Yang, H., Jiang, Y., Lyu, J., & Shi, L. (2025) · International Conference on Educational Technology Management (ICETM) · doi:10.1109/icetm67477.2025.11413516
Wu, Y., Li, X. Y., Zhao, Y., & Lin, X. (2025) · International Conference on Educational Technology Management (ICETM) · doi:10.1109/icetm67477.2025.11413442
“Concurrently, the profound application of digitally-intelligent technologies in higher education is driving the transformation of course content, teaching methodologies, and assessment frameworks [4].”
Low-Resource Strategies for IELTS Writing Preparation using Free Generative AI
Sangia, R. A. (2026) · International Journal of Advanced Corporate Learning (iJAC) · doi:10.3991/ijac.v19i1.58935
Principles, Capabilities, and Applications of Generative AI
Routray, S. K. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/404023
Survey on the Use of Generative AI Tools by Undergraduate Computer Science Students
Pezer, M., Zafar, M. N., Naderi, M., Salem, H., Mazzara, M., & Stanko, T. (2026) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-95-4423-3_47
Artificial Intelligence as a Catalyst in Educational Policy Transformation
Jain, S., Jain, R., & Gandhi, P. (2025) · IEEE Global Conference on Wireless Computing and Networking (GCWCN) · doi:10.1109/gcwcn66157.2025.11448540
“…underrated since, when creating a society able to ensure the delivery of a digital economy to future generations, the education system is to evolve towards adoption of AI; yet not merely as a tool but as an engine of the very one that is to guide equity, accessibility, and life-long education [1].”
From Usefulness to Trust: How AI Shapes Learning Attitudes in Higher Education
Jeranah, J., Kurniawan, N. C., & Ahmad, A. (2026) · International Journal of Contemporary Educational Research · doi:10.52380/ijcer.2026.13.1.876
“In addition, Leong et al. (2024) dan Ahmed et al. (2024) gave the opinion that the proactive attitude of students cannot be separated from the role of AI to provide personalization in learning.”
Qomariyah, N. N., & Heriyanni, E. (2026) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-05-2025-0100
Optimization of a Teacher’s Time Management Using Artificial Intelligence
Pšenák, P., & Pšenáková, I. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-18888-5_4
VLAgeBench: Benchmarking Large Vision-Language Models for Zero-Shot Human Age Estimation
Sajib, R. H., Morol, M. K., Gupta, R. D., Mahmood, M. S., & Das, S. S. (2025) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit68739.2025.11490216
“GPT-4o, in particular, enables direct image-text interaction and produces free-form outputs, including accurate numerical estimates [14].”
Self-citationCommunity and Stakeholder Engagement in Human-AI Learning Ecosystems
Magesh, S., Vijayalakshmi, S., Nivedha, V., Rajakumar, P. S., & Manikandan, R. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-6063-8.ch010
Triangga, B., Noermijati, N., Rohman, F., & Sumiati, S. (2026) · Artificial Intelligence in Education · doi:10.1108/aiie-07-2025-0177
Thi, T. N., Hai, G. H., Hoang, L. N., & Minh, D. H. (2026) · BMC Medical Education · doi:10.1186/s12909-026-09368-4
“In addition, students worried that GenAI might encourage academic shortcuts, reducing engagement in critical thinking—concerns consistent with a prior study [26], which warned that while GenAI enhances personalized learning, it also risks undermining academic integrity.”
Wang, J., Wang, L., Zhang, M., Dong, J., & Xiong, J. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14044-7
“Moreover, GenAI’s dialog-based interactions may not only affect users’ mental health but also weaken their foundational relationships and social bonds, ultimately impacting their overall emo - tional well-being (Ahmed et al., 2024; Illia et al., 2022 ).”
Türker, P. M., Pala, F. K., & Öztürk, M. (2026) · Journal of Computing in Higher Education · doi:10.1007/s12528-026-09499-z
Are digital natives ready to use GenAI for serious work?
Alexeeva-Alexeev, I., & Comesaña-Comesaña, P. (2026) · Technology in Society · doi:10.1016/j.techsoc.2026.103425
Pangngay, J. J., Mondina, K. L., Latoja, M. A., Lazaga, M. J., & Caranay, L. (2026) · Raniag International Journal of Education Management and Social Action · doi:10.66332/ed.fadf2971
The University Library, Generative Artificial Intelligence, and the Sustainability of Knowledge
Sandoval, J. L. G., Arteaga, J. M., Rodríguez, F. J. Á., & Esparza, A. C. M. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-9048-2.ch012
Intelligent Tutoring System using Generative AI for Personalized Learning
Janani, J., Kalyani, J. U., & Ahmad, M. O. (2026) · International Conference on Inventive Computing and Informatics (ICICI) · doi:10.1109/icici68773.2026.11580657
“However, conventional learning platforms are based on conventional learning strategies and content, which are not sufficient to meet the dynamic requirements of students [2], [3].”
Multimodal AI Support for Academic Writing: A Semester-Long Higher Education Intervention Study
Hamam, D., Hysaj, A., Ouda, Y., & Farhat, A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-31418-5_16
Formative Assessments in the Age of AI: Evaluating Learning Outcomes in Engineering Mathematics
Peter, A. K., Hussain, T., & Saadi, F. A. (2026) · Lecture notes in mechanical engineering · doi:10.1007/978-981-95-5907-7_31
Thode, M., & Paliokas, I. (2026) · Computers · doi:10.3390/computers15070443
Kadırhan, Z. (2026) · Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi · doi:10.35379/cusosbil.1696829
Rosio, S. G. J., Palomino, M. O., Velásquez, V. R., Edith, D. C. E., & Reyes, V. M. (2026) · Prohominum · doi:10.47606/acven/ph0523
Metadata
- Authors
- Ahmed, Z., Shanto, S. S., Rime, M. H. K., Morol, M. K., Fahad, N., Hossen, M. J., & Abdullah-Al-Jubair, M.
- Affiliations
- American International University-Bangladesh (BD)
- University of Rajshahi (BD)
- Multimedia University (MY)
- ORCID
- Venue
- IEEE Access
- Published
- 2024
- Volume
- 12
- Pages
- 147023-147050
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W4402772412
- Cited by
- 123
- References
- 96
- Citations by year
- 2026: 57 · 2025: 61 · 2024: 5
- FWCI
- 46.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- IEEE Access (publishedVersion, cc-by-nc-nd)
- Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- generative AI in education, ChatGPT, student perceptions, academic integrity, automated grading, AI-generated content, personalized learning, critical thinking, data privacy, AI ethics, undergraduate students, academic support
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