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Hybrid intelligence: Human–AI coevolution and learning.

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Title: Hybrid intelligence: Human–AI coevolution and learning.
Authors: Järvelä, Sanna1 (AUTHOR) sanna.jarvela@oulu.fi, Zhao, Guoying1 (AUTHOR), Nguyen, Andy1 (AUTHOR), Chen, Haoyu1 (AUTHOR)
Source: British Journal of Educational Technology. Mar2025, Vol. 56 Issue 2, p455-468. 14p.
Subject Terms: *Artificial intelligence, *Generative artificial intelligence, *Machine learning, *Intelligent tutoring systems, Natural language processing, Language models
Abstract: The article discusses the concept of Hybrid Intelligence (HI), which aims to combine human intelligence with AI to create systems that outperform either working independently. It highlights the challenges and opportunities in developing HI systems, emphasizing the need for a multidisciplinary approach. The research explores how AI can assist in understanding human learning processes and improve collaboration between humans and AI. Future research directions include focusing on ethical integration of AI in education and ensuring that AI systems enhance human agency rather than replace it. [Extracted from the article]
Copyright of British Journal of Educational Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Hybrid intelligence: Human–AI coevolution and learning.
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  Data: <searchLink fieldCode="AR" term="%22Järvelä%2C+Sanna%22">Järvelä, Sanna</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sanna.jarvela@oulu.fi</i><br /><searchLink fieldCode="AR" term="%22Zhao%2C+Guoying%22">Zhao, Guoying</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nguyen%2C+Andy%22">Nguyen, Andy</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chen%2C+Haoyu%22">Chen, Haoyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22British+Journal+of+Educational+Technology%22">British Journal of Educational Technology</searchLink>. Mar2025, Vol. 56 Issue 2, p455-468. 14p.
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  Data: *<searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Intelligent+tutoring+systems%22">Intelligent tutoring systems</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink><br /><searchLink fieldCode="DE" term="%22Language+models%22">Language models</searchLink>
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  Label: Abstract
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  Data: The article discusses the concept of Hybrid Intelligence (HI), which aims to combine human intelligence with AI to create systems that outperform either working independently. It highlights the challenges and opportunities in developing HI systems, emphasizing the need for a multidisciplinary approach. The research explores how AI can assist in understanding human learning processes and improve collaboration between humans and AI. Future research directions include focusing on ethical integration of AI in education and ensuring that AI systems enhance human agency rather than replace it. [Extracted from the article]
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  Data: <i>Copyright of British Journal of Educational Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Machine learning
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      – SubjectFull: Intelligent tutoring systems
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              Text: Mar2025
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              Y: 2025
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