Evidence map›Paper›PMID 40278052›Full record

ArticleJournal of Intelligence2025

Can Generative AI and ChatGPT Break Human Supremacy in Mathematics and Reshape Competence in Cognitive-Demanding Problem-Solving Tasks?

Deniz Kaya, Selim Yavuz

Abstract read
In one paragraph

Article in Journal of Intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Trial
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

2 authors.

Deniz KayaDepartment of Mathematics Education, Faculty of Education, Nevsehir Hacı Bektas Veli University, 50300 Nevsehir, Türkiye.ORCID 0000-0002-7804-1772
Selim YavuzDepartment of Curriculum and Instruction, School of Education, Indiana University Bloomington, Bloomington, IN 47405, USA.ORCID 0009-0005-6816-2422

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the potential of generative artificial intelligence tools in addressing cognitive challenges encountered by humans during problem-solving. The performance of ChatGPT-4o and GPT-4 models in the NAEP mathematics assessments was evaluated, particularly in relation to the cognitive demands placed on students. Sixty NAEP mathematics assessment tasks, coded by field experts, were analyzed within a framework of cognitive complexity. ChatGPT-4o and GPT-4 provided responses to each question, which were then evaluated using NAEP's scoring criteria. The study's dataset was analyzed using the average performance scores of students who answered correctly and the item-wise response percentages. The results indicated that ChatGPT-4o and GPT-4 outperformed most students on individual items in the NAEP mathematics assessment. Furthermore, as the cognitive demand increased, higher performance scores were required to answer questions correctly. This trend was observed across the 4th, 8th, and 12th grades, though ChatGPT-4o and GPT-4 did not demonstrate statistically significant sensitivity to increased cognitive demands at the 12th-grade level.

Indexed as

AI-driven educationChatGPTcognitive loadgenerative artificial intelligencemathematics assessmentNAEPproblem-solving

Identifiers

PMID40278052
PMCPMC12027771

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.