Evidence map›Paper›PMID 36457086›Full record

ArticleBMC medical education2022

Analysis of the effect of an artificial intelligence chatbot educational program on non-face-to-face classes: a quasi-experimental study.

Jeong-Won Han, Junhee Park, Hanna Lee

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07051343 (Effect of Using Artificial Intelligence Chatbot About Electronic Fetal Monitoring on Maternity Nursing Students' Performance), which is not on this map. Cited by 45 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 6 pooled it
44.5field-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.

NCT07051343 naactive not recruitingnot on this mapstarted 2025, after this paper: background citation

Effect of Using Artificial Intelligence Chatbot About Electronic Fetal Monitoring on Maternity Nursing Students' Performance

TypeinterventionalSponsorMansoura UniversityRan2025 to 2025Enrolled84ConditionsArtificial Intelligence (AI), Electronic Fetal Monitoring, Nursing StudentsArmsdesigned artificial intelligence Chatbot education about electronic fetal monitoring, traditional teaching method
3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 6 syntheses or guidelines pooled it, 155 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Jeong-Won HanCollege of Nursing Science, Kyung Hee University, 26 Kyunghee-Daero, Dongdaemun-Gu, Seoul, 02447, Republic of Korea.ORCID http://orcid.org/0000-0002-4893-8327
Junhee ParkCollege of Nursing Science, Dongnam Health University, 50, Cheoncheon-Ro 74Beon-Gil, Jangan-Gu, Suwon-Si, Gyeonggi-Do, 16323, Republic of Korea.
Hanna LeeDepartment of Nursing, Gangneung-Wonju National University, 150 Namwon-Ro, Heungeop-Myeon, Wonju-Si, Gangwon-Do, 26403, Republic of Korea. hannalee@gwnu.ac.kr.ORCID http://orcid.org/0000-0002-9835-4717
Dongnam Health University · KRGangneung–Wonju National University · KRKyung Hee University · KR

Funding

National Research Foundation of Korea(NRF) 2022R1I1A3072862
6 · The paper itself

Abstract

backgroundEducation and training are needed for nursing students using artificial intelligence-based educational programs. However, few studies have assessed the effect of using chatbots in nursing education.

objectivesThis study aimed to develop and examine the effect of an artificial intelligence chatbot educational program for promoting nursing skills related to electronic fetal monitoring in nursing college students during non-face-to-face classes during the COVID-19 pandemic.

designThis quasi-experimental study used a nonequivalent control group non-synchronized pretest-posttest design.

methodsThe participants were 61 junior students from a nursing college located in G province of South Korea. Data were collected between November 3 and 16, 2021, and analyzed using independent t-tests.

resultsThe experimental group-in which the artificial intelligence chatbot program was applied-did not show statistically significant differences in knowledge (t = -0.58, p = .567), clinical reasoning competency (t = 0.75, p = .455), confidence (t = 1.13, p = .264), and feedback satisfaction (t = 1.72, p = .090), compared with the control group; however, its participants' interest in education (t = 2.38, p = .020) and self-directed learning (t = 2.72, p = .006) were significantly higher than those in the control group.

conclusionThe findings of our study highlighted the potential of artificial intelligence chatbot programs as an educational assistance tool to promote nursing college students' interest in education and self-directed learning. Moreover, such programs can be effective in enhancing nursing students' skills in non-face-to face-situations caused by the ongoing COVID-19 pandemic.

Indexed as

COVID-19Students, NursingArtificial IntelligenceHumansLearningPandemicsArtificial intelligenceChatbot programClinical reasoningData processingEducationNursing

Identifiers

PMID36457086
PMCPMC9713176
OpenAlexW4310494163

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.