Evidence map›Paper›PMID 41387841›Full record

ArticleBMC oral health2025

The reliability of answers from four different AI chatbots on periodontology theoretical exam questions: an evaluation in dental education.

Cenker Zeki Koyuncuoglu, Ahmet Hamdi Selcuker, Erdem Ozyilmaz

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

3 authors.

Cenker Zeki KoyuncuogluDepartment of Periodontology, Faculty of Dentistry, Istanbul Aydın University, Beşyol Mah. İnönü Cad. No:6 Küçükçekmece, Istanbul, 34295, Türkiye. zekikoyuncuoglu@aydin.edu.tr.ORCID http://orcid.org/0000-0002-5866-5860
Ahmet Hamdi SelcukerDepartment of Periodontology, Faculty of Dentistry, Istanbul Aydın University, Beşyol Mah. İnönü Cad. No:6 Küçükçekmece, Istanbul, 34295, Türkiye.ORCID http://orcid.org/0000-0001-8275-2131
Erdem OzyilmazDepartment of Periodontology, Faculty of Dentistry, Istanbul Aydın University, Beşyol Mah. İnönü Cad. No:6 Küçükçekmece, Istanbul, 34295, Türkiye.ORCID http://orcid.org/0000-0003-0842-4716

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDentistry is a profession affected by modern technology, materials, and societal events like the pandemic, leading to an academic field that continuously evolves in both practice and education. Consequently, advancements include the extensive implementation of digital dentistry, the incorporation of remote instruction into dental training throughout the pandemic, and the investigation of optimal AI integration within the dental profession and education are necessary. This study evaluated the reliability of answers provided by four different major artificial intelligence (AI) chatbot using 125 periodontology exam questions administered between 2018−2023.

methodsThis study used closed-ended questions retrieved from the official archives of the Department of Periodontology, Faculty of Dentistry, Istanbul Aydin University originally included in exams given to 3rd, 4th, and 5th-year students between 2018 and 2023. These questions were then posed to AI chatbots for evaluation. These include 92 of the questions are true/false, 8 are fill-in-the-blank, 22 are multiple-choice, and 3 are calculation questions. Questions were asked to each AI chatbot (ChatGPT-4o mini, ChatGPT-4o, Gemini Advance, and CoPilot Pro) twice, with a one-month interval, and evaluated on a binary scoring system. Before the questions were asked to the AI chatbots, the chat histories and cookies were cleared from the user interfaces, and a previously unused e-mail address was used to log in. The questions were asked one at a time, and the next question was not asked until the previous one was answered. The NCSS (Number Cruncher Statistical System) 2007 (Kaysville, Utah, USA) program was used for statistical analyses. While evaluating the study data, descriptive statistical methods were used. In the comparison of qualitative data across three or more periods, the Cochran’s-Q test was used, and the Mc Nemar test was used for post hoc analyses. Statistical significance level was set at p < 0.01 and p < 0.05 levels.

resultsCoPilot Pro achieved the highest accuracy rate both on Day-0 (73.6%) and after one month (75.2%). When comparing the performance of AI chatbots on Day-0 and Month-1, no statistically significant difference was found. However, GPT-4o mini performed significantly worse than the other three AI chatbots at both time points (p < 0.05). The performance of GPT-4o was the most inconsistent, as 19 questions answered correctly in the first round were answered incorrectly in the second round.

conclusionThe findings underscore the need for critical evaluation of AI tools before their adoption in dental education. While AI chatbots can support dental education, their use should be carefully guided and complemented by clinical experience, critical appraisal of information sources, and academic oversight to ensure professional competence and responsible integration into learning processes.

Indexed as

Artificial IntelligenceEducational MeasurementEducation, DentalPeriodonticsHumansReproducibility of ResultsArtificial intelligenceChatbotsDentalEducationPeriodontics

Identifiers

PMID41387841
PMCPMC12817414

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.