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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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“In the context of the growing demand for Machine Learning (ML) education, this section reviews literature on the integration of ML into professional development, with a particular emphasis on self-paced learning for working professionals[12, 9, 3, 42, 20, 27, 41].”
Garro-Mena, L. (2024) · REDU Revista de Docencia Universitaria · doi:10.4995/redu.2024.21989 · Cited by 2
Oufkir, A. A., Mohib, Z., & Adrdour, M. (2024) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-981-97-9255-9_8 · Cited by 1
Use of Artificial Intelligence to Improve Teacher Preparation
Tillman, D. A., Cochran, C., Soto, T. J., Robertson, W. H., An, S. A., & Tinajero, J. (2024) · Artificial Intelligence x Humanities, Education, and Art (AIxHEART) · doi:10.1109/aixheart62327.2024.00014 · Cited by 3
Design of University Vocational Education Evaluation System Guided by Multiple Intelligence Theory
Zhao, S. (2025) · Journal of Cases on Information Technology · doi:10.4018/jcit.368242 · Cited by 2
Chen, Y.-S., & Chow, T.-H. (2025) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-86323-3_32 · Cited by 1
Jansen, B. J. J., Jung, S., Farooq, A., Salminen, J. O., Aldous, K. K., Msefula, P. S., Alabed, A., Khan, S. M., & O’Kennedy, R. (2025) · Gulf Studies · doi:10.1007/978-981-97-9667-0_6 · Cited by 1
IMPLEMENTATION OF ARTIFICIAL INTELLIGENCE FOR PERSONALIZATION EDUCATION TRACKS IN TERTIARY EDUCATION
Safonova, N. V., & Mykhailenko, V. (2025) · Innovate Pedagogy · doi:10.32782/2663-6085/2025/80.2.29 · Cited by 1
Leveraging Social Media Analytics For Student Project Allocation Using Deep Learning
Thoppil, I. J., Saha, J., & Gopu, A. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.04.275 · Cited by 1
AI's Impact on Social Integrity, Well-being and Academic Performance of International Students
Dhiman, P., & Kashyap, B. (2025) · Journal of Underrepresented & Minority Progress · doi:10.32674/xwf89x77 · Cited by 1
“This further applies to academic assistance, mental health resources, and general guidance (Bhutoria, 2022).”
Students' Behavioral Intentions Towards Learning and Using Chatbots in Education
Bora, B. Y., & Kölemen, C. Ş. (2025) · İnsan ve Sosyal Bilimler Dergisi · doi:10.53048/johass.1621817 · Cited by 1
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Relevance of Artificial Intelligence in Assessment
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Arias, D. P., Arias, B. I. I., Lastra, M. A. M., Camino, L. X. A., & Sani, V. E. M. (2025) · ASCE MAGAZINE · doi:10.70577/asce/2231.2251/2025 · Cited by 4
Xu, Y.-S., Khalid, Y. I. A. M., & Kassim, M. S. S. (2025) · Journal of Librarianship and Information Science · doi:10.1177/09610006251384336 · Cited by 1
“AI-driven systems optimize learning paths, meeting individual needs and learning habits effectively (Bhutoria, 2022).”
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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