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.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Traditional plagiarism detection tools, such as Turnitin, are ineffective in identifying AI-generated content, often yielding false positives or negatives.
“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]
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 real-world problem-solving.
“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]
Cites
1 retracted
Yu, H. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e24289 · Cited by 225 · cited 3× · see citing works
“This transformation improves operational efficiency and contributes to creating a more adaptable and digital educational environment [50].”
BackgroundRetractedThe PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · International Journal of Surgery · doi:10.1016/j.ijsu.2021.105906 · Cited by 11,748 · see citing works
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 4× · see citing works
“It also promotes innovative teaching methods by introducing novel pedagogical strategies that leverage GAI capabilities [2].”
BackgroundMethodInfluentialSallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · cited 2× · see citing works
“The guidelines should cover topics such as data privacy and security, algorithmic bias mitigation, transparency and accountability in GAI systems, and ethical considerations in developing and deploying AI technologies [7], [26], [61].”
BackgroundChatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087 · see citing works
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079 · see citing works
Baidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004 · cited 4× · see citing works
“A key area of impact highlighted in recent research is the generation of prompts for formative assessment activities, which is instrumental in fostering personalized and interactive learning environments [6], [24], [25].”
BackgroundMethodInfluentialStudents' voices on generative ai: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · arXiv · doi:10.48550/arxiv.2305.00290 · Cited by 2,504 · see citing works
Zero-shot text-to-image generation
Ramesh, A., Pavlov, M., Goh, G., Gray, S., Voss, C., Radford, A., Chen, M., & Sutskever, I. (2021) · arXiv · doi:10.48550/arxiv.2102.12092 · Cited by 2,417 · cited 1× · see citing works
“Meanwhile, image generators like DALL-E 2 can create original digital art, diagrams, and visual aids based only on a text description [3].”
BackgroundStudents’ voices on generative AI: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00411-8 · Cited by 2,301 · see citing works
What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
Lo, C. K. (2023) · Education Sciences · doi:10.3390/educsci13040410 · Cited by 2,024 · cited 5× · see citing works
“…could include the impact of GAI-driven personalized learning systems on student engagement and achievement, the effectiveness of AI-powered teaching assistants in supporting educators, and the role of GAI in streamlining administrative tasks and optimizing resource allocation [10], [35], [91].”
BackgroundInfluentialWhat if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00237-x · Cited by 2,003 · cited 1× · see citing works
“This concern is based on the notion that relying on AI for tasks requiring critical thinking may decrease the students’ capacity for original thought, creativity, and independent problem-solving [10], [38], [67], [69], [70].”
BackgroundChatGPT: five priorities for research
van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023) · Nature · doi:10.1038/d41586-023-00288-7 · Cited by 1,842 · cited 1× · see citing works
“At [9], the authors argue that embracing AI should not come at the cost of uniquely human traits that have long driven scientific progress.”
BackgroundBAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 1,826 · see citing works
ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.9 · Cited by 1,806 · cited 2× · see citing works
“Beyond individualized feedback, ChatGPT and similar Generative AI (GAI) systems open new horizons for personalized learning pathways, encouraging learners to pursue self-directed education [18], [27], [28], [29], [30], [31], [32].”
BackgroundExamining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence
Cooper, G. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10039-y · Cited by 1,263 · cited 2× · see citing works
“This concern is based on the notion that relying on AI for tasks requiring critical thinking may decrease the students’ capacity for original thought, creativity, and independent problem-solving [10], [38], [67], [69], [70].”
BackgroundLim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023) · The International Journal of Management Education · doi:10.1016/j.ijme.2023.100790 · Cited by 1,261 · cited 3× · see citing works
“This technological advancement facilitates the automation of specific educational tasks, thus reallocating valuable time for educators to engage more directly with students, enhancing the learning experience [8].”
BackgroundChatGPT for Education and Research: Opportunities, Threats, and Strategies
Rahman, M. M., & Watanobe, Y. (2023) · Applied Sciences · doi:10.3390/app13095783 · Cited by 1,080 · cited 4× · see citing works
“Several works have been depicted, providing an overall synopsis of the impact of ChatGPT in education [10], [11], [12].”
BackgroundInfluentialGrassini, S. (2023) · Education Sciences · doi:10.3390/educsci13070692 · Cited by 1,048 · cited 1× · see citing works
“Several works have been depicted, providing an overall synopsis of the impact of ChatGPT in education [10], [11], [12].”
BackgroundChallenges and Opportunities of Generative AI for Higher Education as Explained by ChatGPT
Michel-Villarreal, R., Vilalta-Perdomo, E., Salinas-Navarro, D. E., Thierry-Aguilera, R., & Gerardou, F. S. (2023) · Education Sciences · doi:10.3390/educsci13090856 · Cited by 877 · cited 10× · see citing works
“Educators can create interactive learning environments using simulations and role-playing scenarios that foster deeper and more meaningful student engagement [7], [18].”
BackgroundMethodInfluentialChatGPT in higher education: considerations for academic integrity and student learning
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.17 · Cited by 853 · cited 1× · see citing works
“Academic policymakers have raised significant concerns about the widespread adoption of generative AI tools in educational settings [92].”
BackgroundEngineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education
Qadir, J. (2023) · 2023 IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon54358.2023.10125121 · Cited by 707 · cited 8× · see citing works
“A key area of impact highlighted in recent research is the generation of prompts for formative assessment activities, which is instrumental in fostering personalized and interactive learning environments [6], [24], [25].”
BackgroundInfluentialChatbots in Education and Research: A Critical Examination of Ethical Implications and Solutions
Kooli, C. (2023) · Sustainability · doi:10.3390/su15075614 · Cited by 666 · cited 4× · see citing works
“It ensures students receive a well-structured and engaging learning experience [36], [50], [51].”
BackgroundInfluentialExploring the potential of using an AI language model for automated essay scoring
Mizumoto, A., & Eguchi, M. (2023) · Research Methods in Applied Linguistics · doi:10.1016/j.rmal.2023.100050 · Cited by 647 · see citing works
Bandi, A., Adapa, P. V. S. R., & Kuchi, Y. E. V. P. K. (2023) · Future Internet · doi:10.3390/fi15080260 · Cited by 638 · cited 1× · see citing works
“Generative artificial intelligence (GAI) refers to machine learning models that can produce novel, original content without being explicitly programmed to do so [1].”
BackgroundUnlocking the Power of ChatGPT: A Framework for Applying Generative AI in Education
Su (苏嘉红), J., & Yang (杨伟鹏), W. (2023) · ECNU Review of Education · doi:10.1177/20965311231168423 · Cited by 625 · cited 4× · see citing works
“It has been noted that the generation of incorrect information and the presence of biases in training data can not only mirror but also exacerbate existing prejudices [6], [7], [68].”
BackgroundInfluentialChatGPT in education: Strategies for responsible implementation
Halaweh, M. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13036 · Cited by 607 · cited 4× · see citing works
“Its ability to process and provide information instantly allows for a more integrated approach to medical training, where students can explore complex scenarios and receive immediate feedback [44].”
BackgroundMethodInfluentialChatGPT: A revolutionary tool for teaching and learning mathematics
Wardat, Y., Tashtoush, M. A., AlAli, R. M., & Jarrah, A. M. (2023) · Eurasia Journal of Mathematics Science and Technology Education · doi:10.29333/ejmste/13272 · Cited by 593 · cited 4× · see citing works
“One of the distinguishing features of GAI is its ability to provide instant feedback, particularly in quantitative subjects such as mathematics [56].”
BackgroundInfluentialUnlocking the opportunities through ChatGPT Tool towards ameliorating the education system
Javaid, M., Haleem, A., Singh, R. P., Khan, S., & Khan, I. H. (2023) · BenchCouncil Transactions on Benchmarks, Standards and Evaluations · doi:10.1016/j.tbench.2023.100115 · Cited by 535 · see citing works
Peres, R., Schreier, M., Schweidel, D., & Sorescu, A. (2023) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2023.03.001 · Cited by 535 · cited 1× · see citing works
“The emergence of GAI also prompts wider ethical discussions on authorship, plagiarism, and responsible use of AI-generated content within academic and professional fields [50], [62], [63].”
BackgroundThe impact of ChatGPT on higher education
Dempere, J., Modugu, K., Hesham, A., & Ramasamy, L. K. (2023) · Frontiers in Education · doi:10.3389/feduc.2023.1206936 · Cited by 519 · cited 4× · see citing works
“This convenience is especially beneficial in academic research and study, where time is crucial [32], [48], [49].”
BackgroundInfluentialFuture research recommendations for transforming higher education with generative AI
Chiu, T. K. F. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100197 · Cited by 511 · cited 1× · see citing works
“This study [20] investigated student perspectives on generative AI’s impact on higher education through a qualitative approach with 51 students from three research-intensive universities.”
BackgroundImpact of the Implementation of ChatGPT in Education: A Systematic Review
Montenegro-Rueda, M., Fernández-Cerero, J., Fernández-Batanero, J. M., & López-Meneses, E. (2023) · Computers · doi:10.3390/computers12080153 · Cited by 509 · cited 1× · see citing works
“Professional development programs and resources should be developed to equip educators with the knowledge and skills necessary to integrate GAI technologies into their teaching practices effectively [57], [74], [94].”
BackgroundTransformative Effects of ChatGPT on Modern Education: Emerging Era of AI Chatbots
Gill, S. S., Xu, M.-X., Patros, P., Wu, H.-M., Kaur, R., Kaur, K., Fuller, S., Singh, M., Arora, P., Parlikad, A., et al. (2023) · Internet Things Cyber Phys. Syst. · doi:10.1016/j.iotcps.2023.06.002 · Cited by 466 · cited 2× · see citing works
“This versatility improves the learning experience by facilitating collaborative group work and allowing education to be more adaptive and personalized [39].”
BackgroundWhat ChatGPT means for universities: Perceptions of scholars and students
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.22 · Cited by 431 · see citing works
Exploring Artificial Intelligence in Academic Essay: Higher Education Student's Perspective
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki (2023) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2023.100296 · Cited by 418 · see citing works
Generative Artificial Intelligence: Implications and Considerations for Higher Education Practice
Farrelly, T., & Baker, N. (2023) · Education Sciences · doi:10.3390/educsci13111109 · Cited by 414 · cited 10× · see citing works
“…could include the impact of GAI-driven personalized learning systems on student engagement and achievement, the effectiveness of AI-powered teaching assistants in supporting educators, and the role of GAI in streamlining administrative tasks and optimizing resource allocation [10], [35], [91].”
BackgroundInfluentialAlAfnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023) · Journal of Artificial Intelligence and Technology · doi:10.37965/jait.2023.0184 · Cited by 402 · cited 1× · see citing works
“This facilitates a deeper understanding of how AI can be used to improve teaching and learning outcomes [43].”
BackgroundImpact of ChatGPT on ESL students’ academic writing skills: a mixed methods intervention study
Mahapatra, S. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00295-9 · Cited by 398 · cited 1× · see citing works
“Collaboration with educational institutions will be crucial to incorporate GAI-related topics into teacher education programs and student curricula, ensuring that both educators and learners are well-prepared for the GAI-driven future of education [35], [77], [81].”
BackgroundUse of ChatGPT in academia: Academic integrity hangs in the balance
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2023) · Technology in Society · doi:10.1016/j.techsoc.2023.102370 · Cited by 394 · cited 2× · see citing works
“The ethical implications of GAI use in education encompass many issues, including but not limited to data privacy, academic integrity, and the reliability of AI-generated content [36], [38], [56], [68], [71].”
BackgroundWill generative AI replace teachers in higher education? A study of teacher and student perceptions
Chan, C. K. Y., & Tsi, L. H. Y. (2024) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2024.101395 · Cited by 387 · cited 3× · see citing works
“By automating tasks that traditionally require extensive manual input, such as scheduling, record-keeping, and communication management, AI technologies pave the way for a more streamlined and efficient administrative workflow [18], [59].”
BackgroundMethodHadi Mogavi, R., Deng, C., Juho Kim, J., Zhou, P., D. Kwon, Y., Hosny Saleh Metwally, A., Tlili, A., Bassanelli, S., Bucchiarone, A., Gujar, S., et al. (2024) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2023.100027 · Cited by 369 · cited 2× · see citing works
“It ensures students receive a well-structured and engaging learning experience [36], [50], [51].”
BackgroundRuiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023) · Sustainability · doi:10.3390/su151511524 · Cited by 340 · cited 1× · see citing works
“…AI tools and the 4PADAFE instructional design matrix in enhancing education through a MOOC course for University of ESPE Armed Forces teachers [16], revealing that integrating these tools with the instructional design matrix is crucial for developing massive virtual classrooms and…”
MethodChatGPT: Empowering lifelong learning in the digital age of higher education
Rawas, S. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12114-8 · Cited by 310 · cited 2× · see citing works
“This capability significantly has reduced educators’ time evaluating student submissions, thereby freeing up resources to focus on more interactive and student-centered teaching approaches [37].”
BackgroundReconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education
Dai, Y., Liu, A., & Lim, C. P. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.05.002 · Cited by 298 · see citing works
McDonald, N., Johri, A., Ali, A., & Collier, A. H. (2025) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2025.100121 · Cited by 295 · see citing works
Analysing the Role of ChatGPT in Improving Student Productivity in Higher Education
Fauzi, F., Tuhuteru, L., Sampe, F., Ausat, A. M. A., & Hatta, H. R. (2023) · Journal on Education · doi:10.31004/joe.v5i4.2563 · Cited by 283 · cited 2× · see citing works
“Teachers use a wide range of knowledge, including information that is not published or is understood without being directly stated [45].”
BackgroundGenerative Artificial Intelligence in Education and Its Implications for Assessment
Mao, J., Chen, B., & Liu, J. C. (2024) · TechTrends · doi:10.1007/s11528-023-00911-4 · Cited by 270 · cited 1× · see citing works
“Mao et al. [21] has taken the initiative to review the use of AI in education and examine the opportunities and challenges of employing generative AI for educational assessment through a systems thinking lens.”
BackgroundLiu, M., Ren, Y., Nyagoga, L. M., Stonier, F., Wu, Z., & Yu, L. (2023) · Future in Educational Research · doi:10.1002/fer3.10 · Cited by 267 · cited 2× · see citing works
“Providing insights from Chinese experts, the DATS framework [55] presents a balanced perspective to navigate the promises and perils of GAI tools in education.”
BackgroundChatGPT in education: Methods, potentials, and limitations
Memarian, B., & Doleck, T. (2023) · Computers in Human Behavior: Artificial Humans · doi:10.1016/j.chbah.2023.100022 · Cited by 266 · cited 5× · see citing works
“Beyond individualized feedback, ChatGPT and similar Generative AI (GAI) systems open new horizons for personalized learning pathways, encouraging learners to pursue self-directed education [18], [27], [28], [29], [30], [31], [32].”
BackgroundMethodInfluentialChaudhry, I. S., Sarwary, S. A. M., El Refae, G. A., & Chabchoub, H. (2023) · Cogent Education · doi:10.1080/2331186x.2023.2210461 · Cited by 262 · cited 2× · see citing works
“These methods should take advantage of the benefits of AI tools to enhance the learning experience without compromising the core values that underpin the integrity of education [42], [64].”
BackgroundMethodUsing Large Language Models to Enhance Programming Error Messages
Leinonen, J., Hellas, A., Sarsa, S., Reeves, B., Denny, P., Prather, J., & Becker, B. A. (2023) · Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 · doi:10.1145/3545945.3569770 · Cited by 235 · cited 2× · see citing works
“This could involve exploring natural language processing for intelligent tutoring systems, machine learning for adaptive curriculum design, and GAI-powered assessment tools that provide detailed feedback and support to students [88], [90].”
BackgroundEffects of Generative Chatbots in Higher Education
Ilieva, G., Yankova, T., Klisarova-Belcheva, S., Dimitrov, A., Bratkov, M., & Angelov, D. (2023) · Information · doi:10.3390/info14090492 · Cited by 234 · cited 1× · see citing works
“The authors also drew on their experiences and observations of AI’s application in educational contexts to formulate the framework’s components In another study, authors [87] proposed a framework that aims to systematically apply intelligent chatbots in university teaching and learning.”
BackgroundGenerative AI and ChatGPT in School Children’s Education: Evidence from a School Lesson
Jauhiainen, J. S., & Guerra, A. G. (2023) · Sustainability · doi:10.3390/su151814025 · Cited by 234 · cited 1× · see citing works
“5) with 110 primary school pupils (8–14 years) across four classes in two schools [17].”
BackgroundBower, M., Torrington, J., Lai, J. W. M., Petocz, P., & Alfano, M. (2024) · Education and Information Technologies · doi:10.1007/s10639-023-12405-0 · Cited by 220 · cited 2× · see citing works
“Nevertheless, there needs to be a more large-scale examination of how educators perceive the need for changes in teaching and assessment practices [15].”
BackgroundKadaruddin, K. (2023) · International Journal of Business, Law, and Education · doi:10.56442/ijble.v4i2.215 · Cited by 213 · cited 1× · see citing works
“Furthermore, regarding the practical applicability of this research in real-world educational settings, it is crucial to consider the resource constraints and infrastructural challenges that may hinder the widespread adoption of generative AI technologies [96].”
Background“We Need To Talk About ChatGPT”: The Future of AI and Higher Education
Neumann, M., Rauschenberger, M., & Schön, E.-M. (2023) · Hochschule Hannover · doi:10.25968/opus-2467 · Cited by 212 · cited 2× · see citing works
“A multidisciplinary task force or advisory committee should be established to develop a comprehensive set of guidelines and best practices for GAI’s ethical and responsible use in education [6], [41], [47], [71].”
BackgroundThe Advent of Generative Language Models in Medical Education
Karabacak, M., Ozkara, B. B., Margetis, K., Wintermark, M., & Bisdas, S. (2023) · JMIR Medical Education · doi:10.2196/48163 · Cited by 208 · see citing works
Students' perceptions of using ChatGPT in a physics class as a virtual tutor
Ding, L., Li, T., Jiang, S., & Gapud, A. (2023) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-023-00434-1 · Cited by 208 · see citing works
Challenges for Higher Education in the Era of Widespread Access to Generative AI
Walczak, K., & Cellary, W. (2023) · Economics and Business Review · doi:10.18559/ebr.2023.2.743 · Cited by 196 · cited 6× · see citing works
“Beyond individualized feedback, ChatGPT and similar Generative AI (GAI) systems open new horizons for personalized learning pathways, encouraging learners to pursue self-directed education [18], [27], [28], [29], [30], [31], [32].”
BackgroundMethodInfluentialCodeHelp: Using Large Language Models with Guardrails for Scalable Support in Programming Classes
Liffiton, M., Sheese, B. E., Savelka, J., & Denny, P. (2023) · Proceedings of the 23rd Koli Calling International Conference on Computing Education Research · doi:10.1145/3631802.3631830 · Cited by 192 · see citing works
Better by You, better than Me? ChatGPT-3 as writing assistance in students’ essays.
Bašić, Ž., Banovac, A., Kružić, I., & Jerković, I. (2023) · doi:10.35542/osf.io/n5m7s · Cited by 189 · see citing works
The ethical implications of using generative chatbots in higher education
Williams, R. T. (2024) · Frontiers in Education · doi:10.3389/feduc.2023.1331607 · Cited by 183 · see citing works
ChatGPT—A Challenging Tool for the University Professors in Their Teaching Practice
Kiryakova, G., & Angelova, N. (2023) · Education Sciences · doi:10.3390/educsci13101056 · Cited by 171 · see citing works
Generative AI and the Automating of Academia
Watermeyer, R., Phipps, L., Lanclos, D., & Knight, C. (2023) · Postdigital Science and Education · doi:10.1007/s42438-023-00440-6 · Cited by 151 · cited 1× · see citing works
“This means that when trying to do things quickly and efficiently, we might forget the importance of learning well and critically thinking [36], [65].”
BackgroundHow understanding large language models can inform the use of ChatGPT in physics education
Polverini, G., & Gregorcic, B. (2023) · European Journal of Physics · doi:10.1088/1361-6404/ad1420 · Cited by 131 · see citing works
Li, H.-F. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8923 · Cited by 125 · see citing works
ICT students' perceptions towards ChatGPT: An experimental reflective lab analysis
Elkhodr, M., Gide, E., Wu, M., & Darwish, O. (2023) · STEM Education · doi:10.3934/steme.2023006 · Cited by 117 · cited 2× · see citing works
“GAI tools and chatbots also play a vital role in lesson planning, test creation, and the development of sample solutions, thus improving teaching efficiency [41], [42].”
BackgroundExamining students’ intention to use ChatGPT: Does trust matter?
Rahman, M. S., Sabbir, M. M., Zhang, D. J., Moral, I. H., & Hossain, G. M. S. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8956 · Cited by 111 · cited 1× · see citing works
“This concern is based on the notion that relying on AI for tasks requiring critical thinking may decrease the students’ capacity for original thought, creativity, and independent problem-solving [10], [38], [67], [69], [70].”
BackgroundDigital transformation in engineering education: Exploring the potential of AI-assisted learning
Pham, T. T., Nguyen, T. B., Ha, S., & Ngoc, N. T. N. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8825 · Cited by 108 · cited 1× · see citing works
“Collaboration with educational institutions will be crucial to incorporate GAI-related topics into teacher education programs and student curricula, ensuring that both educators and learners are well-prepared for the GAI-driven future of education [35], [77], [81].”
BackgroundCotroneo, P., & Hutson, J. (2023) · Metaverse · doi:10.54517/m.v4i1.2164 · Cited by 104 · see citing works
Kayalı, B., Yavuz, M., Balat, Ş., & Çalışan, M. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8915 · Cited by 103 · cited 1× · see citing works
“This convenience is especially beneficial in academic research and study, where time is crucial [32], [48], [49].”
BackgroundRace with the machines: assessing the capability of generative AI in solving authentic assessments
Nguyen Thanh, B., Vo, D. T. H., Nguyen Nhat, M., Pham, T. T. T., Thai Trung, H., & Ha Xuan, S. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8902 · Cited by 87 · see citing works
Adarkwah, M. A., Amponsah, S., van Wyk, M. M., Huang, R., Tlili, A., Shehata, B., Metwally, A. H. S., & Wang, H. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.26 · Cited by 78 · see citing works
Tayan, O., Hassan, A., Khankan, K., & Askool, S. (2023) · Machine Learning with Applications · doi:10.1016/j.mlwa.2023.100513 · Cited by 75 · cited 6× · see citing works
“Moreover, the facility with which ChatGPT can produce coherent and natural-sounding responses may inadvertently encourage AI-assisted cheating, compromising the integrity of genuine learning experiences [28], [46], [57].”
BackgroundMethodInfluentialStudent Perspectives on the Role of Artificial Intelligence in Education: A Survey-Based Analysis
Idroes, G. M., Noviandy, T. R., Maulana, A., Irvanizam, I., Jalil, Z., Lensoni, L., Lala, A., Abas, A. H., Tallei, T. E., & Idroes, R. (2023) · Journal of Educational Management and Learning · doi:10.60084/jeml.v1i1.58 · Cited by 69 · cited 1× · see citing works
“Professional development programs and resources should be developed to equip educators with the knowledge and skills necessary to integrate GAI technologies into their teaching practices effectively [57], [74], [94].”
BackgroundGenerative AI: Challenges to higher education
Yeralan, S., & Lee, L. A. (2023) · Sustainable Engineering and Innovation · doi:10.37868/sei.v5i2.id196 · Cited by 67 · see citing works
Digital Content Creation Tools: American University Teachers’ Perception
Antón-Sancho, Á., Vergara, D., Lamas-Álvarez, V. E., & Fernández-Arias, P. (2021) · Applied Sciences · doi:10.3390/app112411649 · Cited by 60 · cited 1× · see citing works
“Dynamic question-and-answer functions would allow for student-driven explorations where an AI tutor provides responsive, detailed explanations [4].”
BackgroundAjlouni, A. O., Almahaireh, A. S., & Whaba, F. A.-A. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i20.42075 · Cited by 57 · see citing works
Learning Mathematics with Large Language Models
Matzakos, N., Doukakis, S., & Moundridou, M. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i20.42979 · Cited by 51 · see citing works
Koh, E., & Doroudi, S. (2023) · Learning Research and Practice · doi:10.1080/23735082.2023.2264086 · Cited by 45 · cited 5× · see citing works
“Beyond individualized feedback, ChatGPT and similar Generative AI (GAI) systems open new horizons for personalized learning pathways, encouraging learners to pursue self-directed education [18], [27], [28], [29], [30], [31], [32].”
BackgroundInfluentialAl-Obaydi, L. H., Pikhart, M., & Klímová, B. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i21.42593 · Cited by 45 · cited 1× · see citing works
“This technology dramatically helps students in other areas, such as language learning and numerous academic disciplines, by promoting interactive conversations that resemble human connection without being limited by fatigue or the need for breaks [24], [35], [54].”
BackgroundMicrosoft Copilot and Anthropic Claude AI in education and library service
Adetayo, A. J., Aborisade, M. O., & Sanni, B. A. (2024) · Library Hi Tech News · doi:10.1108/lhtn-01-2024-0002 · Cited by 45 · cited 1× · see citing works
“Adetayo et al. [13] have explored the potential applications of Microsoft Copilot and Claude.ai, two advanced artificial intelligence assistants, in education.”
BackgroundChatGPT in Ukrainian Education: Problems and Prospects
Fiialka, S., Kornieva, Z., & Honcharuk, T. (2023) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v18i17.42215 · Cited by 45 · cited 2× · see citing works
“This convenience is especially beneficial in academic research and study, where time is crucial [32], [48], [49].”
BackgroundPAIGE: A generative AI-based framework for promoting assignment integrity in higher education
Shanto, S. S., Ahmed, Z., & Jony, A. I. (2023) · STEM Education · doi:10.3934/steme.2023018 · Cited by 43 · cited 4× · see citing works
“Comprehensive studies should be conducted to assess the impact of GAI on various aspects of education, including student learning outcomes, teacher effectiveness, and administrative processes [7], [52].”
BackgroundMethodInfluentialSelf-citationGenerative AI in education: To embrace it or not？
Ariyo Okaiyeto, S., College of Mechanical and Electrical Engineering, Q. A. U., Bai, J., & Xiao, H. (2023) · International Journal of Agricultural and Biological Engineering · doi:10.25165/j.ijabe.20231603.8486 · Cited by 43 · cited 1× · see citing works
“However, critical ethical, legal, and social risks are inherent in deploying generative models in education [5].”
BackgroundMatthews, J. A., & Volpe, C. R. (2023) · Australasian Journal of Educational Technology · doi:10.14742/ajet.8896 · Cited by 42 · see citing works
EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education
Dan, Y., Lei, Z., Gu, Y., Li, Y., Yin, J., Lin, J., Ye, L., Tie, Z., Zhou, Y., Wang, Y., et al. (2023) · arXiv · doi:10.48550/arxiv.2308.02773 · Cited by 41 · see citing works
Philbin, C. A. (2023) · ACM Inroads · doi:10.1145/3610406 · Cited by 34 · cited 1× · see citing works
“Philbin [14] explored the impact of GAI tools, such as GitHub Copilot, on generating code for computer science applications.”
MethodAhmed, Z., Shanto, S. S., & Jony, A. I. (2024) · STEM Education · doi:10.3934/steme.2024011 · Cited by 32 · cited 1× · see citing works
“Moreover, the ready availability of these tools presents a significant challenge for academia in terms of effectively assessing students’ genuine understanding and competencies [95].”
BackgroundSelf-citationImpact of ChatGPT on Academic Performance among Bangladeshi Undergraduate Students
Tanvir, K., Islam, M. S., Sezan, S. B. K., Sanad, Z. A., & Ataur, A.-J. I. (2023) · International journal of research in science & engineering · doi:10.55529/ijrise.35.18.28 · Cited by 28 · cited 3× · see citing works
“Moreover, the facility with which ChatGPT can produce coherent and natural-sounding responses may inadvertently encourage AI-assisted cheating, compromising the integrity of genuine learning experiences [28], [46], [57].”
BackgroundGenerative AI and re-weaving a pedagogical horizon of social possibility
Hall, R. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00445-6 · Cited by 22 · cited 1× · see citing works
“Such protocols must prioritize the representation of diverse perspectives and experiences, ensuring that AI technologies serve as tools to improve educational opportunities for all students, regardless of their cultural background or socioeconomic status [72].”
BackgroundNaher, J., Maruf, M. H., Bakht, S. T., & Sadaf, S. S. (2023) · Technium Romanian Journal of Applied Sciences and Technology · doi:10.47577/technium.v15i.9660 · Cited by 17 · cited 5× · see citing works
“Furthermore, excessive use of GAI for the creation of academic content and research assistance can limit the ability of educators and students to engage in creative and critical analysis, further inhibiting the cultivation of these vital skills [26], [67].”
BackgroundInfluentialPerception of Generative Artificial Intelligence in Higher Education Research
Abdullah, Z. B., & Zaid, N. M. (2023) · Innovative Teaching and Learning Journal · doi:10.11113/itlj.v7.137 · Cited by 16 · see citing works
ChatGPT's Applications in Higher Education: Unmasking Opportunities and Challenges
Sarker, D. R., Eiaz-Ur-Rahman, A. F. M., Sakib, A. R., Terano, H. J. R., & Rahman, M. M. (2023) · Journal of Education Management and Development Studies · doi:10.52631/jemds.v3i4.250 · Cited by 13 · see citing works
Yakin, A. M. A., Muthmainnah, M., Apriani, E., Obaid, A. J., & Elngar, A. A. (2023) · Idarah (Jurnal Pendidikan dan Kependidikan) · doi:10.47766/idarah.v7i2.1514 · Cited by 12 · cited 1× · see citing works
“Its interactive nature and ability to simulate conversational exchanges make learning more relatable and accessible, enhancing student interest and participation in classroom activities [59], [60].”
BackgroundUnleashing the power of gen-AI for digital education development
McInnes, R., Carandang, M., & Kulkarni, A. (2023) · ASCILITE Publications · doi:10.14742/apubs.2023.520 · Cited by 11 · cited 1× · see citing works
“Policymakers emphasize the necessity of developing robust guidelines and best practices to ensure that the integration of generative AI aligns with the core values and objectives of educational institutions [93].”
BackgroundUniversity Students’ Perspective on ChatGPT and Technology Literacies
Dawa, T., Dhendup, S., Tashi, S., & Rosso, M. A. (2024) · Educational innovation and practice · doi:10.17102/eip.7.2024.10 · Cited by 4 · cited 1× · see citing works
“GAI technology, with its ability to personalize and adapt, is transforming the educational landscape by providing learning experiences that are not only captivating but are also customized to the individual needs and responses of students [30], [57], [58].”
BackgroundOgunleye, O. S. (2023) · 2023 International Conference on Computational Science and Computational Intelligence (CSCI) · doi:10.1109/csci62032.2023.00278 · Cited by 2 · cited 2× · see citing works
“The capacity of ChatGPT to complete assignments with minimal effort directly threatens the credibility and reliability of traditional assessment methods [30], [31], [34].”
Background
Flagged first, then by citations
Cited by
Sorted by citations
Shen, M., Shen, Y., Liu, F., & Jin, J. (2025) · BMC Nursing · doi:10.1186/s12912-025-03115-8 · Cited by 76 · see citing works
“Both participants expressed skepticism regarding GenAI accuracy and completeness, frequently revising and refining their prompts to improve response quality [33].”
Metaverse for Education: Developments, Challenges, and Future Direction
Chamola, V., Peelam, M. S., Mittal, U., Hassija, V., Singh, A., Pareek, R., Mangal, P., Sangwan, D., de Albuquerque, V. H. C., Mahmud, M., et al. (2025) · Computer Applications in Engineering Education · doi:10.1002/cae.70018 · Cited by 77 · see citing works
“GAI ‐ driven personalization in the Metaverse for education represents a revolutionary shift in how learning experiences are customized to individual needs and preferences [216, 217].”
A Meta‐Analysis of the Impact of Generative Artificial Intelligence on Learning Outcomes
Ma, N., & Zhong, Z. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70117 · Cited by 57 · see citing works
Dui, H., Zeng, Q., & Xie, M. (2025) · Frontiers of Engineering Management · doi:10.1007/s42524-025-4147-6 · Cited by 37 · see citing works
“Ahmed Z et al. (2024) used generative AI to assist teaching and promote learning equity.”
ChatGPT as a cognitive crutch: Evidence from a randomized controlled trial on knowledge retention
Barcaui, A. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.102287 · Cited by 51 · see citing works
AI and Creativity in Entrepreneurship Education: A Systematic Review of LLM Applications
Park, J.-H., Kim, S.-J., & Lee, S. (2025) · AI · doi:10.3390/ai6050100 · Cited by 28 · see citing works
A Meta-Survey of Generative AI in Education: Trends, Challenges, and Research Directions
Bouguettaya, S., Pupo, F., Chen, M., & Fortino, G. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9090237 · Cited by 36 · see citing works
“Ahmed and his colleagues [23] provide one of the most comprehensive contributions by reviewing four notable frameworks: PAIGE, AI-CRITIQUE, DATS, and IDEE.”
InfluentialNcube, P. D. N., Dzvapatsva, G. P., Matobobo, C., & Ranga, M. M. (2026) · AI and Ethics · doi:10.1007/s43681-025-00871-w · Cited by 31 · see citing works
“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 real-world problem-solving scenarios [ 60, 72, 93, 97, 98].”
Jukiewicz, M. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1594572 · Cited by 24 · see citing works
Chen, S.-Y., Chen, W., & Lai, C. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13758-4 · Cited by 28 · see citing works
“While these methods often provide depth, they lack immediacy and scalability (Ahmed et al., 2024 ).”
Artificial intelligence and robotics in education: Advances, challenges, and future perspectives
Cadavieco, J. F., López, J. M. S., & Castro, S. S. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101533 · Cited by 16 · see citing works
Shanto, S. S., Ahmed, Z., & Jony, A. I. (2025) · Educational Technology Quarterly · doi:10.55056/etq.788 · Cited by 14 · see citing works
“Another systematic review [3] explored the opportunities, challenges and student perception of integrating GAI tools in education settings.”
Self-citationGenerative AI: A Systematic Review of Related Interfaces and Interactions
Ordoumpozanis, K., Konstantakis, M., Zoi, S., & Caridakis, G. (2025) · Proceedings of the 3rd International Conference of the ACM Greek SIGCHI Chapter · doi:10.1145/3749012.3749052 · Cited by 12 · see citing works
“UX Dimension [63], [27], [3], [32], [31], [69], [38], [54], [16], [29], [70], [30], [9], [72] Engagement [41], [11], [78], [93], [101] Usability [23], [90], [103], [92], [102], [14], [58], [37] Emotional Impact [99], [48], [6], [47], [62], [24], [57], [68], [79], [51], [44], [39], [34], [19], [98],…”
InfluentialEthical considerations in artificial intelligence-driven environments for higher education
Mogoale, P. D., Pretorius, A. B., Mogase, R. C., & Segooa, M. A. (2025) · South African journal of information management · doi:10.4102/sajim.v27i1.2007 · Cited by 11 · see citing works
“P12: ‘The Generative AI Landscape in Education’ surveyed 200 undergraduate university students as part of a mixed-methods study design that included both qualitative and quantitative research (Ahmed et al. 2024).”
Aydın, S., Durukan, A., & Günbatar, M. S. (2025) · Science & Education · doi:10.1007/s11191-025-00677-6 · Cited by 15 · see citing works
“…a limited number of review studies that emphasize a theoretical lens have focused on only a single aspect of technology integration, or reported emerging frameworks for GenAI integration in education (Ahmed et al., 2024) rather than employing one as a theoretical lens for analyzing the literature.”
Exploring students’ perceptions of generative AI-generated feedback in learning programming
Khor, E. T., Chan, L., Koh, E., & SEOW, P. S. K. (2025) · Educational Psychology · doi:10.1080/01443410.2025.2564894 · Cited by 9 · see citing works
“Most research studying students’ perceptions of adopting GenAI in education employs an undergraduate population (Ahmed et al., 2024; Almassaad et al., 2024; dube et al., 2024), while most research on this topic set in a K-12 context investigates educators’ perspectives (Cheah & Kim, 2025; Han et…”
Jiang, H., Li, Y., Chugh, R., Xin, Y., & Cheng, H. (2026) · International Journal of STEM Education · doi:10.1186/s40594-026-00628-9 · Cited by 10 · see citing works
“First, this study limited its search to the WOS and Scopus databases, following the recommendations by Pranckutė (2021) and aligning with the practices adopted in recent systematic reviews (e.g., Ahmed et al., 2024; Batista et al., 2024).”
Licardo, M., Kranjec, E., Lipovec, A., Dolenc, K., Arcet, B., Flogie, A., Plavčak, D., Grmek, M. I., Rošer, B. B., Petek, B. S., et al. (2025) · doi:10.18690/um.pef.1.2025 · Cited by 7 · see citing works
Mwakapesa, D. S. (2025) · Information Development · doi:10.1177/02666669251366666 · Cited by 8 · see citing works
Rahim, S., Sahar, G., Jabeen, G., Khatoon, S., & Angaiz, D. (2025) · Sustainable Futures · doi:10.1016/j.sftr.2025.101206 · Cited by 9 · see citing works
Wu, C., & Carroll, J. M. (2025) · TechTrends · doi:10.1007/s11528-025-01150-5 · Cited by 6 · see citing works
Khor, E. T., Chan, L. L., & Seow, P. (2025) · Education Sciences · doi:10.3390/educsci15121569 · Cited by 7 · see citing works
Exploring the Mathematical Foundations of Generative AI Models: VAEs, GANs, Transformers, and DMs
Tera, S. P., Chinthaginjala, R., Natha, P., & Pau, G. (2025) · IEEE Access · doi:10.1109/access.2025.3647861 · Cited by 5 · see citing works
“GAI is transforming the education sector by offering tailored learning experiences, automated content creation, and virtual tutoring services [163], [164], [165], [166].”
A Systematic Literature Review of Generative AI Risks and Harms for Youth
Chang, T., & Razi, A. (2026) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3772363.3798673 · Cited by 5 · see citing works
Mapping the technological evolution of generative AI: a patent network analysis
Mohammadi, N., Dahooie, J. H., Bengari, A. A., & Rahimi, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-26810-7 · Cited by 5 · see citing works
Shanto, S. S., Ahmed, Z., & Jony, A. I. (2024) · International Conference on Computing Advancements (ICCA) · doi:10.1145/3723178.3723268 · Cited by 4 · see citing works
Self-citationDervić, M., Bećirović, S., & Polz, E. (2025) · Future education and learning spaces · doi:10.1007/978-981-96-7937-9_9 · Cited by 8 · see citing works
Development and Application of a ChatGPT-Powered AI platform for Elementary English Education
Lee, J.-H., Jung, W., & Lee, E. (2025) · The Journal of Korean Association of Computer Education · doi:10.32431/kace.2025.28.4.007 · Cited by 4 · see citing works
AIGC in Design: Critical Thinking Challenges and Opportunities Revealed Through Systematic Review
Ge, P., Meng, D., & Fan, F. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93429-2_2 · Cited by 4 · see citing works
Huang, Y., Yu, T., Chen, Y., Tian, Y., & Yim, J. (2025) · Applied Sciences · doi:10.3390/app16010063 · Cited by 3 · see citing works
Pérez-Portabella, A., de Andrés-Sánchez, J., Arias-Oliva, M., & Castillo, G. P. (2026) · Innovative Higher Education · doi:10.1007/s10755-026-09885-6 · Cited by 3 · see citing works
Luo, J., Qu, L., Wang, M., & Li, H. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2642871 · Cited by 3 · see citing works
“…advent of generative artificial intelligence (GenAI), particularly large language models (LLMs), has catalyzed a profound transformation in education, offering unprecedented potential to personalize learning and automate content creation (Ahmed et al., 2024; Rudolph et al., 2023; Zhu et al., 2023).”
Altamirano, S. F. S., Maquen-Niño, G. L. E., Roldán, C. M. G., Herrera, A. P., & Cárdenas, D. M. C. (2026) · Review of Education · doi:10.1002/rev3.70152 · Cited by 10 · see citing works
Generative Artificial Intelligence and Encounters with Knowledge in STEM Higher Education Curricula
Doorsamy, W., Padayachee, K., & Cornell, A. S. (2025) · IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon62633.2025.11016322 · Cited by 3 · see citing works
Mwaniki, S., Araka, E., Kituku, B., & Maina, E. M. (2025) · IST-Africa Conference (IST-Africa) · doi:10.23919/ist-africa67297.2025.11060553 · Cited by 2 · see citing works
“This study was done between October 2024 to November 2024 to a purposively targeted population in higher learning institutions [20] [21].”
Adhikari, M., Joshi, P., Ramos, G. V., Doulat, A. A., & Shaik, S. (2025) · International Conference on Smart Applications, Communications and Networking (SmartNets) · doi:10.1109/smartnets65254.2025.11106900 · Cited by 2 · see citing works
“The integration of Generative Artificial Intelligence (GenAI) in knowledge-intensive domains such as education has transformed the access and synthesis of information [3], [4], [5].”
Govender, R., Rzyankina, E., Bayaga, A., & Harun, I. (2025) · Discover Education · doi:10.1007/s44217-025-00726-w · Cited by 2 · see citing works
“The de-clustered network visualisation infers valuable insights into the varied applications of AI techniques in teaching and learning [26].”
Two Years “in the Wild”: A Multidisciplinary Approach to Teaching Generative AI
Orchard, A., Behrens, J. T., & Dhaliwal, R. S. (2025) · IEEE Technology and Society Magazine · doi:10.1109/mts.2025.3587581 · Cited by 2 · see citing works
Task-Centered Analysis of Higher Education Students’ Uses of Generative Artificial Intelligence
Hershkovitz, A., Tabach, M., & Lurie, L. (2025) · Education Sciences · doi:10.3390/educsci15121676 · Cited by 4 · see citing works
Lee, C.-S., Wang, M., Tseng, G.-Y., Yue, C.-C., Lin, C.-H., Lin, Y., & Kubota, N. (2025) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc58881.2025.11343717 · Cited by 2 · see citing works
“Ahmed et al. [1] highlight the impact of Generative AI (GAI) on education, enabling customized learning while addressing challenges such as assessment integrity.”
WSS-Linear: A Transformer-Enhanced Approach for Exam Score Prediction
Wu, S., Jing, H., Ye, W., & Zhi, Y. (2024) · International Conference on Information Science and Education (ICISE-IE) · doi:10.1109/icise-ie64355.2024.11025399 · Cited by 2 · see citing works
“Brown et al. (2022) pointed out that in datasets with high feature diversity and complexity, models relying solely on static weights are prone to overlook key features, leading to decreased model performance[4].”
Huynh, A.-V., & Khoa, B. T. (2025) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-031-98476-1_24 · Cited by 5 · see citing works
Zhang, M., Raytchev, B., & Sun, X. (2026) · IEEE Signal Processing Magazine · doi:10.1109/msp.2025.3599339 · Cited by 2 · see citing works
Unlocking Sentiment Analysis Potential for Low-Resource Bangla Language by Fine-Tuning LLaMA Model
Ahmed, Z., Shanto, S. S., & Jony, A. I. (2024) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit64611.2024.11021810 · Cited by 2 · see citing works
“Researchers have already begun to implement these powerful models into real-life applications in various fields such as sentiment analysis [23], healthcare and medical text analysis [24], and education [25]–[27].”
Self-citationWhat is Unethical About Software? User Perceptions in the Netherlands
Elias, Y., Humbert, T. P., Olson, L., & Guzmán, E. (2025) · IEEE/ACM International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS) · doi:10.1109/icse-seis66351.2025.00017 · Cited by 1 · see citing works
“We also find research on ethical concerns about specific technologies such as artificial intelligence (AI), in general [7]–[9], [42], in education [10], [11], large language models (LLM) [12], and facial recognition [13].”
Arroyo-Bello, E., González-Toledo, B., Abad-Valle, J., Rodríguez-Gómez, P., & Ramon, M. (2025) · Cureus · doi:10.7759/cureus.94259 · Cited by 3 · see citing works
“In the field of education, the potential of ChatGPT and related generative models lies in their ability to automatically generate customized learning materials and assessments, facilitating large-scale adaptive learning [5].”
InfluentialImproving educational quality: the role of quality 4.0 in higher education institutions
Kumar, V., Singh, A., Sharma, N. K., Verma, P., & Kaswan, M. S. (2025) · The TQM Journal · doi:10.1108/tqm-12-2024-0527 · Cited by 7 · see citing works
Pérez-Portabella, A., Arias-Oliva, M., Sánchez, J. D. A., & Castillo, G. P. (2025) · Computers · doi:10.3390/computers14110458 · Cited by 1 · see citing works
Nathaniel, J., Oyelere, S. S., Suhonen, J. T., & Tedre, M. (2026) · Frontiers in Computer Science · doi:10.3389/fcomp.2026.1789829 · Cited by 2 · see citing works
Xia, W., & Wei, W. (2026) · Innovations in Education and Teaching International · doi:10.1080/14703297.2026.2655907 · Cited by 2 · see citing works
Zhang, D., Fu, G., Cao, K., Wang, X. Q., & Li, H. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1825053 · Cited by 1 · see citing works
SHANKAR, A., ASHIKA, S. S., BHANGALE, A., Dhivyaa, C. R., & Nithya, K. (2026) · Array · doi:10.1016/j.array.2026.100998 · Cited by 1 · see citing works
Jia, Z., Dai, D. W., Aryadoust, V., & Hua, Z. (2026) · Research Synthesis in Applied Linguistics · doi:10.1080/29984475.2026.2694603 · Cited by 1 · see citing works
Hwang, J.-S., Wu, M. Y.-H., Lan, Y., Chen, N., & Yeh, H. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2689532 · Cited by 1 · see citing works
Cobblah, M.-A., Tachie‐Donkor, G., Atuase, D., Danso, T. K. O., Sarfo, J. O., & Somuah, B. A. (2026) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2026.103597 · Cited by 1 · see citing works
Liao, C.-W., Liao, Y.-C., Jhang, C.-D., Hsu, C.-M., & Lai, H.-C. (2025) · Electronics · doi:10.3390/electronics14142832 · Cited by 1 · see citing works
Cheng, J., & Jia, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5242155 · Cited by 1 · see citing works
Alomery, M. K., Hazaymeh, W. A., Alarabi, K., & El-Saleh, M. S. (2024) · International Conference on Social Networks Analysis, Management and Security (SNAMS) · doi:10.1109/snams64316.2024.10883791
“The study by [18] aims to assess the use of Generative AI (GAI) instruments in education and their impact on academic results.”
GHP-ManageFormer: A Transformer-Enhanced Approach for Logistics Transportation Time Prediction
Gao, H., Toh, J. S., Zhang, Y., & Ma, J. (2024) · International Conference on Artificial Intelligence, Robotics, and Communication (ICAIRC) · doi:10.1109/icairc64177.2024.10900180
“At the same time, a cross-modal feature fusion strategy is proposed, and a hierarchical feature processing architecture is adopted to achieve the effective integration of static, temporal, and dynamic features and improve the model's adaptability to multi-source heterogeneous data [6].”
Generative artificial intelligence 4: training companion
Furey, P. (2025) · Journal of Paramedic Practice · doi:10.12968/jpar.2025.17.4.cpd1
del Perú, U. N. D. C., Pérez, M. A. J. P., Crispín, A. E. P., Tapia, V. R. C., Santiani, P. L., & Ramírez, G. J. M. (2025) · doi:10.59899/ges-cono-73-c7
Gladston, A., Harish, T. R., & Keerthivasan, J. V. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-0370-3.ch004
Integrating Generative AI in Teacher Education
Yingsoon, G. Y., Yiming, C., Suyan, Z., Haiyan, Z., Xiaoyao, T., & Wenpang, L. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-9861-6.ch004
Kınık, F. Ş. F. (2025) · Journal of Teacher Development and Education · doi:10.29329/journalted.42 · Cited by 1 · see citing works
Ibrahim, A. I., & Iqbal, S. (2025) · International Journal of Environmental Sciences · doi:10.64252/bgewk868
“Ahmed et al. (2024) found that 68% of participants in a multi-university survey attributed better task initiation and completion rates to access to GAI.”
Dominguez, C. E., Pessoa, K. L. E. D. C., Morais, A., & Cruz, G. (2025) · International Conference of the Portuguese Society for Engineering Education (CISPEE) · doi:10.1109/cispee64787.2025.11159184
“For example, issues like plagiarism and over-reliance on GAI-generated texts challenge traditional assessment methods and raise questions about the essential skills students need to develop, such as creativity and critical thinking [2].”
Mukora, F. N., & Jere, N. R. (2025) · Conference on Information Communications Technology and Society (ICTAS) · doi:10.1109/ictas64866.2025.11155729
Visual Speech Recognition in Bangla: A Convolutional LSTM Framework
Shaheen, M., Ifti, A. Z., Hassan, A., Hossain, J., & Hossain, M. I. (2025) · International Conference on Next-Generation Computing, IoT and Machine Learning (NCIM) · doi:10.1109/ncim65934.2025.11159860
“Early methods such as Discrete Cosine Transform and Active Contour Models were used for feature extraction, often in combination with statistical models like Hidden Markov Models (HMMs) and Support Vector Machines for classification [6; 7].”
Malhotra, N., & Kumar, B. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-03740-4_28
Representation of Sensitive Issues in Media Using Generative AI
Surya, K., & Kumar, R. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-06694-7_10
Weber, N. L., & Gay, K. (2025) · Innovations in Pedagogy and Technology · doi:10.63385/ipt.v1i3.181
“GAI can generate scaffolds, re-minders, checklists, and tailored study plans [19,20] .”
Kar, M., Moghadam, A., Mortezaie, M., & Herring, P. C. (2025) · IEEE International Symposium on Technology and Society (ISTAS) · doi:10.1109/istas65609.2025.11269627
Isidori, E. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-04958-2_19
Uddin, M. F., & Togher, M. (2025) · International Conference on Information Technology Trends (ITT) · doi:10.1109/itt69610.2025.11352924
“AI influenced curriculum has significantly improved the student engagement and course design [3] Generative AI has contributed tremendously to the way students see and explore opportunities in their academic journeys [4].”
Dishari, S. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6188014
Cheng, M., Ouyang, J., Ding, C., & Luo, L. (2025) · International Conference on Information Science and Education (ICISE-IE) · doi:10.1109/icise-ie68873.2025.11378457
“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
- 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
- Physical Sciences › Computer Science › Information Systems › 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
