Personalized Learning through Artificial Intelligence: Opportunities, Risks, and Policy Perspectives

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This assessment examines personalized education through AI, revealing risks like data privacy and algorithmic bias.

Adapting educational models with AI enhances personalized learning environments and student engagement, promoting real-time adaptation.
Key opportunities include fostering motivation through personalized content, along with creating inclusive educational settings that cater to diverse needs.
Analysis focuses on risks such as algorithmic bias and data privacy, which threaten the integrity of human-centered pedagogy in education.
Recommendations for policy frameworks aim to ensure ethical AI integration, emphasizing the necessity for empirical research to support model validity.

Stоšić et al. (2025) studied this question.

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View Full Paper

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Authors

This assessment examines personalized education through AI, revealing risks like data privacy and algorithmic bias.

Adapting educational models with AI enhances personalized learning environments and student engagement, promoting real-time adaptation.
Key opportunities include fostering motivation through personalized content, along with creating inclusive educational settings that cater to diverse needs.
Analysis focuses on risks such as algorithmic bias and data privacy, which threaten the integrity of human-centered pedagogy in education.
Recommendations for policy frameworks aim to ensure ethical AI integration, emphasizing the necessity for empirical research to support model validity.

Stоšić et al. (2025) studied this question.

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