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Physical Review Physics Education Research
Article . 2024 . Peer-reviewed
License: CC BY
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https://dx.doi.org/10.48550/ar...
Article . 2023
License: arXiv Non-Exclusive Distribution
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Performance of ChatGPT on the test of understanding graphs in kinematics

Authors: Giulia Polverini; Bor Gregorcic;
APC: 1,975.93 EUR

Performance of ChatGPT on the test of understanding graphs in kinematics

Abstract

The well-known artificial intelligence-based chatbot ChatGPT-4 has become able to process image data as input in October 2023. We investigated its performance on the test of understanding graphs in kinematics to inform the physics education community of the current potential of using ChatGPT in the education process, particularly on tasks that involve graphical interpretation. We found that ChatGPT, on average, performed similarly to students taking a high-school level physics course, but with important differences in the distribution of the correctness of its responses, as well as in terms of the displayed “reasoning” and “visual” abilities. While ChatGPT was very successful at proposing productive strategies for solving the tasks on the test and expressed correct reasoning in most of its responses, it had difficulties correctly “seeing” graphs. We suggest that, based on its performance, caution and a critical approach are needed if one intends to use it in the role of a tutor, a model of a student, or a tool for assisting vision-impaired persons in the context of kinematics graphs. Published by the American Physical Society 2024

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Sweden
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Keywords

Other Physics Topics, LC8-6691, Physics Education (physics.ed-ph), Physics, QC1-999, Physics - Physics Education, FOS: Physical sciences, Annan fysik, Special aspects of education

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Top 10%
Top 1%
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