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Artificial Intelligence on Campus: Revisiting Understanding as an Aim of Higher Education.

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Title: Artificial Intelligence on Campus: Revisiting Understanding as an Aim of Higher Education.
Authors: Herman, Jamie (AUTHOR), Lara‐Steidel, Henry (AUTHOR)
Source: Educational Theory. Aug2025, Vol. 75 Issue 4, p603-625. 23p.
Subjects: Artificial intelligence, Higher education, Evaluation methodology, Generative artificial intelligence, Student engagement, ChatGPT, Cognitive development
Abstract: The launch of the powerful generative AI tool ChatGPT in November 2022 sparked a wave of fear across higher education. The tool could seemingly be used to write essays and do other work without students putting in the effort expected of them. In this paper, Jamie Herman and Henry Lara‐Steidel posit a way of addressing the concerns over ChatGPT and increasingly powerful generative AI tools in the classroom by first examining what exactly, if anything, widespread AI use undermines in education. That question, they argue, is logically prior to the question of what to do or how best to embrace new advances in AI technology. They propose that ChatGPT, rather than threatening student cognitive development and effort, reveals a serious flaw in higher education's current aims and assessments: they are directed at knowledge, not understanding. Herman and Lara‐Steidel review the distinction between knowledge and understanding to argue that aiming for the latter requires work and effort from students, ensuring that they develop cognitive agency. They further note that assessments in higher education are typically geared toward measuring knowledge, not understanding, and suggest that this makes them particularly vulnerable to being undermined by AI use, while assessments of understanding do not. Although AI can enhance and aid students in developing understanding, it can neither provide them with understanding nor give the appearance of understanding without student effort. After addressing some salient objections, the authors conclude by outlining avenues for designing understanding‐based assessments in higher education compatible with AI tools such as ChatGPT, and they provide a framework for both understanding and responding to generative AI use in education. [ABSTRACT FROM AUTHOR]
Copyright of Educational Theory 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: Psychology and Behavioral Sciences Collection
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  Data: The launch of the powerful generative AI tool ChatGPT in November 2022 sparked a wave of fear across higher education. The tool could seemingly be used to write essays and do other work without students putting in the effort expected of them. In this paper, Jamie Herman and Henry Lara‐Steidel posit a way of addressing the concerns over ChatGPT and increasingly powerful generative AI tools in the classroom by first examining what exactly, if anything, widespread AI use undermines in education. That question, they argue, is logically prior to the question of what to do or how best to embrace new advances in AI technology. They propose that ChatGPT, rather than threatening student cognitive development and effort, reveals a serious flaw in higher education's current aims and assessments: they are directed at knowledge, not understanding. Herman and Lara‐Steidel review the distinction between knowledge and understanding to argue that aiming for the latter requires work and effort from students, ensuring that they develop cognitive agency. They further note that assessments in higher education are typically geared toward measuring knowledge, not understanding, and suggest that this makes them particularly vulnerable to being undermined by AI use, while assessments of understanding do not. Although AI can enhance and aid students in developing understanding, it can neither provide them with understanding nor give the appearance of understanding without student effort. After addressing some salient objections, the authors conclude by outlining avenues for designing understanding‐based assessments in higher education compatible with AI tools such as ChatGPT, and they provide a framework for both understanding and responding to generative AI use in education. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Educational Theory 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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        Value: 10.1111/edth.70026
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        Text: English
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              Text: Aug2025
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              Y: 2025
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