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Mastering knowledge: the impact of generative AI on student learning outcomes.

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Title: Mastering knowledge: the impact of generative AI on student learning outcomes.
Authors: Pallant, Jessica L. (AUTHOR), Blijlevens, Janneke (AUTHOR), Campbell, Alexander (AUTHOR), Jopp, Ryan (AUTHOR)
Source: Studies in Higher Education. Apr2026, Vol. 51 Issue 4, p714-735. 22p.
Subjects: Educational outcomes, Mastery learning, ChatGPT, Generative artificial intelligence, Higher education, Test design, Teaching methods, Educational technology
Abstract: Generative AI (GenAI) has had a significant impact across industries since the launch of ChatGPT in late 2022. Much of the focus of existing research in the higher education space has considered the impact GenAI has had on academics and institutions. Conversely, research has been less focused on the impact this technology will have on students. Our research investigates how GenAI impacts student learning outcomes in higher education. We applied a quasi-experimental lens to analyse qualitative data of 192 student reflections and apply quantitative content analysis (QCA). Results indicate that a higher level of learning occurs when students use GenAI to construct and augment knowledge (mastery approach). In contrast, lower-level learning outcomes resulted from using GenAI procedurally without augmenting knowledge (procedural approach). Through a practical lens, the course curriculum can be designed to include GenAI to scaffold students' learning from basic knowledge construction tasks to more complex augmentation of knowledge. Assessment design can be adjusted to promote mastery goal structures, encouraging students to critically engage with GenAI outputs rather than simply reproducing them, fostering optimal learning outcomes. [ABSTRACT FROM AUTHOR]
Copyright of Studies in Higher Education 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: Mastering knowledge: the impact of generative AI on student learning outcomes.
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  Data: <searchLink fieldCode="AR" term="%22Pallant%2C+Jessica+L%2E%22">Pallant, Jessica L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Blijlevens%2C+Janneke%22">Blijlevens, Janneke</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Campbell%2C+Alexander%22">Campbell, Alexander</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jopp%2C+Ryan%22">Jopp, Ryan</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Studies+in+Higher+Education%22">Studies in Higher Education</searchLink>. Apr2026, Vol. 51 Issue 4, p714-735. 22p.
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  Data: <searchLink fieldCode="DE" term="%22Educational+outcomes%22">Educational outcomes</searchLink><br /><searchLink fieldCode="DE" term="%22Mastery+learning%22">Mastery learning</searchLink><br /><searchLink fieldCode="DE" term="%22ChatGPT%22">ChatGPT</searchLink><br /><searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Test+design%22">Test design</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+methods%22">Teaching methods</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+technology%22">Educational technology</searchLink>
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  Data: Generative AI (GenAI) has had a significant impact across industries since the launch of ChatGPT in late 2022. Much of the focus of existing research in the higher education space has considered the impact GenAI has had on academics and institutions. Conversely, research has been less focused on the impact this technology will have on students. Our research investigates how GenAI impacts student learning outcomes in higher education. We applied a quasi-experimental lens to analyse qualitative data of 192 student reflections and apply quantitative content analysis (QCA). Results indicate that a higher level of learning occurs when students use GenAI to construct and augment knowledge (mastery approach). In contrast, lower-level learning outcomes resulted from using GenAI procedurally without augmenting knowledge (procedural approach). Through a practical lens, the course curriculum can be designed to include GenAI to scaffold students' learning from basic knowledge construction tasks to more complex augmentation of knowledge. Assessment design can be adjusted to promote mastery goal structures, encouraging students to critically engage with GenAI outputs rather than simply reproducing them, fostering optimal learning outcomes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Studies in Higher Education 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=192729707
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        Value: 10.1080/03075079.2025.2487570
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        Text: English
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              Text: Apr2026
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