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The promise and challenges of generative AI in education.

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Title: The promise and challenges of generative AI in education.
Authors: Giannakos, Michail, Azevedo, Roger, Brusilovsky, Peter, Cukurova, Mutlu, Dimitriadis, Yannis, Hernandez-Leo, Davinia, Järvelä, Sanna, Mavrikis, Manolis, Rienties, Bart
Source: Behaviour & Information Technology. Jul2025, Vol. 44 Issue 11, p2518-2544. 27p.
Subjects: Generative artificial intelligence, Data security, Professional ethics, Computer software, Learning, Educational tests & measurements, Natural language processing, Autodidacticism, Curriculum planning, Computer assisted instruction, Teacher-student relationships, Machine learning, Professional competence
Abstract: Generative artificial intelligence (GenAI) tools, such as large language models (LLMs), generate natural language and other types of content to perform a wide range of tasks. This represents a significant technological advancement that poses opportunities and challenges to educational research and practice. This commentary brings together contributions from nine experts working in the intersection of learning and technology and presents critical reflections on the opportunities, challenges, and implications related to GenAI technologies in the context of education. In the commentary, it is acknowledged that GenAI's capabilities can enhance some teaching and learning practices, such as learning design, regulation of learning, automated content, feedback, and assessment. Nevertheless, we also highlight its limitations, potential disruptions, ethical consequences, and potential misuses. The identified avenues for further research include the development of new insights into the roles human experts can play, strong and continuous evidence, human-centric design of technology, necessary policy, and support and competence mechanisms. Overall, we concur with the general skeptical optimism about the use of GenAI tools such as LLMs in education. Moreover, we highlight the danger of hastily adopting GenAI tools in education without deep consideration of the efficacy, ecosystem-level implications, ethics, and pedagogical soundness of such practices. [ABSTRACT FROM AUTHOR]
Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd 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: Psychology and Behavioral Sciences Collection
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  Data: The promise and challenges of generative AI in education.
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  Data: <searchLink fieldCode="JN" term="%22Behaviour+%26+Information+Technology%22">Behaviour & Information Technology</searchLink>. Jul2025, Vol. 44 Issue 11, p2518-2544. 27p.
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  Data: <searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Data+security%22">Data security</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+ethics%22">Professional ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Learning%22">Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+tests+%26+measurements%22">Educational tests & measurements</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+language+processing%22">Natural language processing</searchLink><br /><searchLink fieldCode="DE" term="%22Autodidacticism%22">Autodidacticism</searchLink><br /><searchLink fieldCode="DE" term="%22Curriculum+planning%22">Curriculum planning</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+assisted+instruction%22">Computer assisted instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher-student+relationships%22">Teacher-student relationships</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+competence%22">Professional competence</searchLink>
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  Data: Generative artificial intelligence (GenAI) tools, such as large language models (LLMs), generate natural language and other types of content to perform a wide range of tasks. This represents a significant technological advancement that poses opportunities and challenges to educational research and practice. This commentary brings together contributions from nine experts working in the intersection of learning and technology and presents critical reflections on the opportunities, challenges, and implications related to GenAI technologies in the context of education. In the commentary, it is acknowledged that GenAI's capabilities can enhance some teaching and learning practices, such as learning design, regulation of learning, automated content, feedback, and assessment. Nevertheless, we also highlight its limitations, potential disruptions, ethical consequences, and potential misuses. The identified avenues for further research include the development of new insights into the roles human experts can play, strong and continuous evidence, human-centric design of technology, necessary policy, and support and competence mechanisms. Overall, we concur with the general skeptical optimism about the use of GenAI tools such as LLMs in education. Moreover, we highlight the danger of hastily adopting GenAI tools in education without deep consideration of the efficacy, ecosystem-level implications, ethics, and pedagogical soundness of such practices. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Behaviour & Information Technology is the property of Taylor & Francis Ltd 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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        Value: 10.1080/0144929X.2024.2394886
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      – Code: eng
        Text: English
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        PageCount: 27
        StartPage: 2518
    Subjects:
      – SubjectFull: Generative artificial intelligence
        Type: general
      – SubjectFull: Data security
        Type: general
      – SubjectFull: Professional ethics
        Type: general
      – SubjectFull: Computer software
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      – SubjectFull: Learning
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      – SubjectFull: Educational tests & measurements
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      – SubjectFull: Natural language processing
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      – SubjectFull: Curriculum planning
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      – SubjectFull: Machine learning
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      – SubjectFull: Professional competence
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              Text: Jul2025
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