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Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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ChatGPT-4's ability to describe kinematic graphs (datasets)

Authors: Arvidson, Anders; Ghazal, Abdulmasih;

ChatGPT-4's ability to describe kinematic graphs (datasets)

Abstract

This dataset contains the ChatGPT-4 responses generated for the study “ChatGPT-4’s ability to describe kinematic graphs”. The dataset includes prompts and responses for 26 items from the Test of Understanding Graphs in Kinematics (TUG-K), with five independent iterations per item (130 responses in total). The files correspond to the data analysed in the thesis.

Keywords

LLM, Physics education, ChatGPT, Accessibilty, Concept inventories, GPT-4, Kinematics graphs, Large language models, TUG-K

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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!
0
Average
Average
Average