Evidence map›Paper›PMID 37903836›Full record

ArticleScientific reports2023

A large-scale comparison of human-written versus ChatGPT-generated essays.

Steffen Herbold, Annette Hautli-Janisz, Ute Heuer, Zlata Kikteva, Alexander Trautsch

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
48.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 279 citations in OpenAlex.

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  12. How should the advancement of large language models affect the practice of science?Proceedings of the National Academy of Sciences of the United States of America · 2025
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  18. Medical science educator · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Steffen HerboldFaculty of Computer Science and Mathematics, University of Passau, Passau, Germany. steffen.herbold@uni-passau.de.
Annette Hautli-JaniszFaculty of Computer Science and Mathematics, University of Passau, Passau, Germany.
Ute HeuerFaculty of Computer Science and Mathematics, University of Passau, Passau, Germany.
Zlata KiktevaFaculty of Computer Science and Mathematics, University of Passau, Passau, Germany.
Alexander TrautschFaculty of Computer Science and Mathematics, University of Passau, Passau, Germany.
University of Passau · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChatGPT and similar generative AI models have attracted hundreds of millions of users and have become part of the public discourse. Many believe that such models will disrupt society and lead to significant changes in the education system and information generation. So far, this belief is based on either colloquial evidence or benchmarks from the owners of the models-both lack scientific rigor. We systematically assess the quality of AI-generated content through a large-scale study comparing human-written versus ChatGPT-generated argumentative student essays. We use essays that were rated by a large number of human experts (teachers). We augment the analysis by considering a set of linguistic characteristics of the generated essays. Our results demonstrate that ChatGPT generates essays that are rated higher regarding quality than human-written essays. The writing style of the AI models exhibits linguistic characteristics that are different from those of the human-written essays. Since the technology is readily available, we believe that educators must act immediately. We must re-invent homework and develop teaching concepts that utilize these AI models in the same way as math utilizes the calculator: teach the general concepts first and then use AI tools to free up time for other learning objectives.

Identifiers

PMID37903836
PMCPMC10616290
OpenAlexW4388034851

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.