The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.
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]
Citations
Cites
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“This transformation improves operational efficiency and contributes to creating a more adaptable and digital educational environment [50].”
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Cited by
Sorted by citations
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Álvarez-Jiménez, M., Pomagualli, A. G. C., Gamboa, D., & Oscullo, D. S. P. (2026) · Computers · doi:10.3390/computers15070466 · Cited by 1
“A similar pattern emerges in item-level ethical concerns: students associate GenAI with issues of authorship, authenticity, and privacy rather than with direct effects on perceived academic efficiency/performance, aligning with observations reported in [49,62].”
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Oddone, K., Merrell, T., Tait, E., & Phillips-Peddlesden, B. (2026) · Journal of the Australian Library and Information Association · doi:10.1080/24750158.2026.2712033
Self-directed learning in silence: graduate students’ navigation of AI use in academic contexts
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“Studies show that AI can make learning more inclusive and fairer by personalizing content, reducing bias in evaluation, and providing support to diverse learners (Ahmed et al., 2024; Pellegrino, 2025; Taskin, 2025).”
Kilat, R. V., Valle, L. C., Cruz, J. D., & Lim, J. B. (2026) · Discover Education · doi:10.1007/s44217-026-01963-3
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Sneha.V.K, S. V. K. (2026) · International Journal of Technology & Emerging Research · doi:10.64823/ijter.2621019
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From diffusion to negotiation: generative AI and academic integrity in higher education assessment
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Adaptive and Personalized Assessment Systems Using Generative Artificial Intelligence
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“The measurement model was evaluated through convergent validity, discriminant validity, and reliability assessments using SmartPLS 4 [1].”
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Educación científica: Preguntar, investigar y decidir con evidencia
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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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