Artificial Intelligence-Based Personalized Learning in Modern Education
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| Format: | Recurso digital |
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2026
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| _version_ | 1866901955433988096 |
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| author | Trupti Suryawanshi Tuljaram |
| author_facet | Trupti Suryawanshi Tuljaram |
| contents | <p class="Abstract"><em>Abstract</em></p> <p class="Abstract"><em><span><span> </span>Artificial Intelligence (AI) has recently been identified as a revolutionary technology in the field of modern education, which has made it possible to develop personalized learning systems that can be tailored to the needs, preferences, and abilities of individual learners. Conventional education systems, which are based on a one-size-fits-all approach, are unable to cater to the diverse needs of individual learners in terms of their learning styles, learning pace, and prior knowledge. This paper discusses how personalized learning systems based on AI use sophisticated technologies like Machine Learning (ML) and Learning Analytics. The study critically analyzes the essential elements of AI-based learning platforms, such as Intelligent Tutoring Systems (ITS) and predictive analytics, and their integration with blended and digital learning environments. Moreover, the paper emphasizes the quantitative and qualitative advantages of personalized learning, such as increased student engagement, motivation, and early detection of learning gaps. However, the use of AI in education also raises critical challenges with respect to data privacy, bias, and technological equity. To overcome these issues, this paper suggests a framework for the responsible and ethical use of AI. In conclusion, AI-based personalized learning is a major breakthrough in teaching methodologies, offering novel solutions to improve teaching efficiency and learner-centric education in the digital age.</span></em></p> <p class="Abstract"> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19509755 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Artificial Intelligence-Based Personalized Learning in Modern Education Trupti Suryawanshi Tuljaram Keywords: Artificial Intelligence in Education (AIEd), Personalized Learning, Machine Learning, Adaptive Learning Systems, Learning Analytics, Educational Technology, Intelligent Tutoring Systems. <p class="Abstract"><em>Abstract</em></p> <p class="Abstract"><em><span><span> </span>Artificial Intelligence (AI) has recently been identified as a revolutionary technology in the field of modern education, which has made it possible to develop personalized learning systems that can be tailored to the needs, preferences, and abilities of individual learners. Conventional education systems, which are based on a one-size-fits-all approach, are unable to cater to the diverse needs of individual learners in terms of their learning styles, learning pace, and prior knowledge. This paper discusses how personalized learning systems based on AI use sophisticated technologies like Machine Learning (ML) and Learning Analytics. The study critically analyzes the essential elements of AI-based learning platforms, such as Intelligent Tutoring Systems (ITS) and predictive analytics, and their integration with blended and digital learning environments. Moreover, the paper emphasizes the quantitative and qualitative advantages of personalized learning, such as increased student engagement, motivation, and early detection of learning gaps. However, the use of AI in education also raises critical challenges with respect to data privacy, bias, and technological equity. To overcome these issues, this paper suggests a framework for the responsible and ethical use of AI. In conclusion, AI-based personalized learning is a major breakthrough in teaching methodologies, offering novel solutions to improve teaching efficiency and learner-centric education in the digital age.</span></em></p> <p class="Abstract"> </p> |
| title | Artificial Intelligence-Based Personalized Learning in Modern Education |
| topic | Keywords: Artificial Intelligence in Education (AIEd), Personalized Learning, Machine Learning, Adaptive Learning Systems, Learning Analytics, Educational Technology, Intelligent Tutoring Systems. |
| url | https://doi.org/10.5281/zenodo.19509755 |