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Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model
Open accessAbstract
The traditional “one size fits all” education system has been largely criticized in recent years on the ground of its lacking the capacity to meet individual student needs. Global education systems are leaning towards a more personalized, student-centered approach. Innovations like Big Data, Machine Learning, and Artificial Intelligence (AI) have given the modern-day technology to accommodate the distinctive features of human beings - smart machines and computers have been built to understand individual-specific needs. This opens an avenue for “personalization” in the education sector. From, mushrooming of Education Technology (EdTech) start-ups to government funding in AI research, it is evident that the next generation educational reforms would take a quantum leap forward piloted by Big Data analysis and AI. The objective of this paper is to organize the vast literature on the use of AI for personalization of education and to shed light on the key themes by which an AI-driven approach makes structural modifications to the existing education system. To this effect, the paper employed a systematic review using a Human-In-The-Loop natural language processing model of past two years' literature (2019–2021) in English language from IEEE Xplore on countries China, India and the USA. This process yielded more than 2000 search results at first and these were eventually shortlisted to 353 relevant papers for in-depth analysis. Being the pioneers in EdTech innovations, insights from research done in these three countries provides valuable input for the development of global education systems and research. The findings bring forward AI's success in catering to specific learning requirements, learning habits, and learning abilities of students and guiding them into optimized learning paths across all three countries. Not just that, it is also evident from the literature that AI augments educational content, customizes it for any individual according to their needs, and raises the flag of caution for anticipated learning difficulties. This recalibrates the role of instructors as well as optimizes the teaching-learning environment for a better learning experience. The upward trajectory of educational development with AI opens a new horizon of personalized education for the future generation, but also comes with its challenges. Data privacy issues, availability of digital resources, and affordability constraints have been reported in the recent literature as impediments in the way of promoting such technologies for day-to-day practice.
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“The use of personalised learning approaches leads to improved student engagement, better understanding of the material, and enhanced academic performance [26, 30–33].”
From Generative AI in Higher Education: Balancing Innovation and Integrity (2025) · cites this paper as [33]
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“The use of AI can make tutoring more efficient by providing personalized content that matches the learner's ability (Bhutoria, 2022).”
From The Future of Artificial Intelligence in Special Education Technology (2023) · cites this paper as Bhutoria, 2022
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“With the improvement of mobile network technology, the struggle in the ideological field has becomemore andmore complex [4].”
BackgroundRetractedAverineni, A., Freddy Chris, M., Vamsi, V. S., Manikanta, A. M., Reddy, A. R., & Reddy, K. D. S. (2024) · International Conference on Disruptive Technologies (ICDT) · doi:10.1109/icdt61202.2024.10489346 · Cited by 13
“Traditional customer relationship management (CRM) systems struggle to provide personalised customer experiences because of their antiquated methods, inability to analyse large datasets, and inability to adjust to customer ever-evolving tastes [7] [8].”
BackgroundKomolafe, O. O., Mustofa, J., Daley, M., Walton, D. M., & Tawiah, A. K. (2025) · PLoS ONE · doi:10.1371/journal.pone.0325649 · Cited by 15
“Adaptive learning systems use several AI techniques such as machine learning (ML), natural language processing (NLP) [4], reinforcement learning, and predictive analytics [5] to deliver content that is most relevant to the learner at any given point in their educational journey.”
Li, H. (2025) · Alexandria Engineering Journal · doi:10.1016/j.aej.2025.08.029 · Cited by 14
Tech-Driven Transformation: Innovative Pricing Strategies for E-Learning
Setiawan, R., Putranto, A. M. H., Wihendro, Princes, E., Geraldina, I., Julianti, E., Safitri, J., & Pannen, P. (2024) · IEEE Access · doi:10.1109/access.2024.3392489 · Cited by 9
“Customization and Personalization [4], [22], [46]: The ability to tailor the calculator to individual needs, including selecting courses and considering financial aid options, enhances its perceived usefulness.”
BackgroundThe role of artificial intelligence in digital education
(2024) · Scientific Papers of Silesian University of Technology Organization and Management Series · doi:10.29119/1641-3466.2024.195.29 · Cited by 11
“"Artificial Intelligence" (AI) is being pushed as a means of enhancing education via more individualized, adaptable, inclusive, and captivating learning when it comes to the abundance of real-time data (Big Data) (Bhutoria, 2022; Halagatti et al.).”
InfluentialPercepciones y Aplicaciones de la IA entre Estudiantes de Secundaria
Salas, H. V. A., & Porras, J. A. D. (2024) · Revista Docentes 2 0 · doi:10.37843/rted.v17i1.458 · Cited by 16
“La IA tiene la habilidad de analizar datos y patrones específicos de cada estudiante, lo que permite adaptar el contenido y las actividades de acuerdo con sus necesidades y ritmo de aprendizaje individuales (Bhutoria, 2022).”
BackgroundMykhaylenko, V., Safonova, N. V., Ilchenko, R., Іващук, А., & Babik, I. (2024) · Data & Metadata · doi:10.56294/dm2024.241 · Cited by 14
Research on the integrated solution of physical education based on smart campus
Hu, X., & Jiang-tao, L. (2024) · AJP Advances in Physiology Education · doi:10.1152/advan.00006.2024 · Cited by 8
Application of Artificial Intelligence in Education: Opportunities, Challenges, and Suggestions
Pan, M., Wang, J., & Wang, J. (2023) · International Conference on Information Technology in Medicine and Education · doi:10.1109/itme60234.2023.00130 · Cited by 9
“The establishment of an AI education platform is an important initiative to help primary and secondary schools achieve more effective education while ensuring that students are equipped with the skills and knowledge needed in the digital age [25].”
AI Innovation in Education: Realizing Personalized Learning in the Digital Age
Qushwa, F. G., & Onia, S. I. (2024) · Educative Jurnal Ilmiah Pendidikan · doi:10.70437/educative.v2i3.822 · Cited by 8
“Apart from that, AI technology provides solutions to overcome these limitations by making it easier for humans to analyze data and personalize the learning process easily (Bhutoria, 2022).”
Venugopal, K. (2025) · Advances in human and social aspects of technology book series · doi:10.4018/979-8-3693-6366-9.ch008 · Cited by 8
Integrating artificial intelligence within South African higher learning institutions
Mogoale, P. D., Pretorius, A. B., Mogase, R. C., & Segooa, M. A. (2025) · South African journal of information management · doi:10.4102/sajim.v27i1.1939 · Cited by 21
McCarthy, S., Palmer, E., & Falkner, N. (2025) · Higher Education Research & Development · doi:10.1080/07294360.2025.2510660 · Cited by 13
“To enhance learning personalisation, educators must therefore develop competencies that allow them to creatively connect technology to learning processes and engage in self-reflection regarding their pedagogical practices (Bhutoria, 2022).”
How AI Can Be Successfully Implemented in the Classroom Settings
Kalim, U., Irfan, S., Maqbool, S., & Zafeer, H. M. I. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-1827-1.ch010 · Cited by 9
AI-Powered Tools for Personalized Learning in Educational Technology
Amoako, K., Asante, A., & Owusu, K. (2024) · International Journal of Technology and Modeling · doi:10.63876/ijtm.v3i1.115 · Cited by 11
Artificial intelligence integration and teachers’ self-efficacy in physics classrooms
Yehya, F. M., ElSayary, A., Murshidi, G. H. A., & Zaabi, A. A. (2025) · Eurasia Journal of Mathematics Science and Technology Education · doi:10.29333/ejmste/16660 · Cited by 9
Ismail, N., & Joshy, L. M. (2025) · Management and Labour Studies · doi:10.1177/0258042x251357415 · Cited by 11
“There is a paradigm shift in the way students are looking at the process of learning (Bhutoria, 2022).”
Hulus, A. (2026) · Smart Learning Environments · doi:10.1186/s40561-026-00437-1 · Cited by 8
“This understanding should guide policy development regarding autonomy and privacy protection (Sun, 2023; Wei & Niemi, 2022), socio-emotional (Baba et al., 2024; Wang et al., 2022), and cultural preservation across diverse educational environments (Bhutoria, 2022; Ming & Weng, 2023).”
Influential
Metadata
- Authors
- Bhutoria, A.
- Affiliations
- Indian Institute of Management Calcutta (IN)
- Corresponding author
- Bhutoria, Aditi
- ORCID
- Bhutoria, Aditi
- Venue
- Computers and Education: Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2022
- Volume
- 3
- Pages
- 100068
- ISSN
- 2666-920X (ISSN-L)
- OpenAlex
- W4224912036
- Cited by
- 677
- References
- 38
- Citations by year
- 2026: 128 · 2025: 251 · 2024: 210 · 2023: 74 · 2022: 14
- FWCI
- 17.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Educational Technology and Pedagogy
- Keywords
- personalized education, artificial intelligence in education, educational technology, adaptive learning paths, teacher role, data privacy, digital divide, educational reform, United States, China, India
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