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Digital Twins and Artificial Intelligence as Pillars of Personalized Learning Models

girl with back to digital representation of self

Credit: Andrij Borys Associates; Dean Drobot

Modern educational systems have not really evolved enough to meet the needs of modern students.21 No wonder, the percentage of dropouts from university studies is quite high (40% in the U.S. and 10% in Europe7,9). The university student profile has changed over the years. While yesterday's students were mainly full-time, today's students face challenges such as work commitments, family obligations, financial constraints, physical impairments, and learning models that do not adequately engage students or help them understand core concepts.11 One might think that this issue concerns only those who fail to complete their studies, but this is view is shortsighted. Today's educational system deficiencies will affect the welfare of tomorrow's society.

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Key Insights


To improve current learning models, academic institutions around the world agree that the time has come to improve the world of education, moving from a traditional approach—where learning is standardized and available only to those with access to educational buildings—to a new paradigm that enables students to personalize their educational pathway, so they can progress at their own pace.19,21 Future learning models must address key concerns, such as reducing dropout rates, supporting students with psycho-physical impairments, integrating on-site and online students, and personalizing the learning experience.


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