Evidence map›Paper›PMID 42216152›Full record

ArticleBMC nursing2026

Investigating the associations between AI-Based educational tool utilization, academic procrastination, academic achievement, and time management among nursing students.

Zainab Albikawi, Mohammad Abuadas

Abstract read
In one paragraph

Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zainab AlbikawiFaculty of Nursing, Yarmouk University, Irbid, Jordan. zainab.albikawi@yu.edu.jo.
Mohammad AbuadasFaculty of Nursing, Yarmouk University, Irbid, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe role of artificial intelligence (AI) tools in education has transformed the way students learn and manage their academic tasks. However, health professions education has not sufficiently studied the role of AI tools in procrastination, time management, and academic achievement.

objectivesTo investigate the associations of AI-based educational tools usage, academic procrastination, academic achievement, and time management among undergraduate nursing students.

methodsA cross-sectional study was conducted with a sample of 167 Jordanian undergraduate nursing students. Data was collected through validated scales measuring procrastination (General Procrastination Scale), time management skills (Time Management Questionnaire), and a researcher-developed scale measuring AI-based educational tool usage.

resultsParticipants demonstrated moderate levels of academic procrastination (mean = 58.28 ± 13.00) and time management (mean = 56.86 ± 11.34), alongside a very good academic achievement (GPA mean = 81.25 ± 7.80). Multiple linear regression analysis indicated that AI-based educational tool usage (B = -0.22, p = 0.007) and time management (B = -0.38, p < 0.001) were significant predictors of academic procrastination. AI-based educational tool usage was also a significant predictor of time management (B = 0.24, p = 0.003). In addition, academic achievement was significantly predicted by AI-based educational tools usage (B = 0.24, p = 0.003), time management (B = 0.21, p = 0.007), and study hours (B = 2.85, p = 0.012).

conclusionThe use of AI-based educational tools was significantly associated with better academic performance among nursing students, alongside lower academic procrastination and better time management skills. The incorporation of AI into the learning process for nursing students may support the development of efficient learning habits and positive academic outcomes.

Indexed as

Academic achievementAcademic procrastinationArtificial intelligenceNursing educationTime management

Identifiers

PMID42216152
PMCPMC13430715

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.