Evidence map›Paper›PMID 42486962›Full record

ArticleScientific reports2026

Development and psychometric validation of the AI chatbots acceptance and perception scale for higher education students.

Ashraf Ragab Ibrahim, Mohamed Ali Nemt-Allah

Abstract readValidation Study
In one paragraph

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

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

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.

Ashraf Ragab IbrahimEducational Psychology and Statistics Department, Faculty of Education, Al-Azhar University, Dakahlia, Egypt. AshrafIbrahem.26@azhar.edu.eg.ORCID 0009-0004-6251-4864
Mohamed Ali Nemt-AllahEducational Psychology and Statistics Department, Faculty of Education, Al-Azhar University, Dakahlia, Egypt.ORCID 0009-0001-0908-4648

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid integration of artificial intelligence (AI) chatbots in higher education has transformed student learning experiences and institutional operations, yet comprehensive measurement tools for assessing student usage patterns remain limited. This study presents the development and psychometric validation of the AI Chatbots Usage Scale, a comprehensive instrument measuring perceptual and attitudinal dimensions of AI chatbot acceptance among higher education students. Using a two-phase methodology, the research employed separate samples for Exploratory Factor Analysis (EFA) (n = 374) and Confirmatory Factor Analysis (CFA) (n = 599) among university students aged 17-23 from the Faculty of Education in Egypt. The initial 25-item scale underwent rigorous expert validation and pilot testing before final administration. EFA revealed a four-factor structure comprising Ease of Use, Perceived Usefulness, Trust, and Accessibility, accounting for 42.48% of total variance. CFA demonstrated excellent model fit indices, with the multidimensional model significantly outperforming a unidimensional alternative. Internal consistency reliability was excellent across all factors, with coefficients ranging from 0.731 to 0.928. The validated scale demonstrates strong theoretical alignment with established technology acceptance frameworks while extending traditional models to accommodate AI-specific considerations. These findings provide researchers and educational institutions with a reliable, theoretically grounded instrument for assessing and optimizing AI chatbot implementation in higher education contexts.

Indexed as

Artificial IntelligencePsychometricsStudentsAdolescentFactor Analysis, StatisticalFemaleHumansMaleReproducibility of ResultsSurveys and QuestionnairesUniversitiesYoung AdultArtificial Intelligence chatbotsHigher educationPsychometric assessmentScale validation

Identifiers

PMID42486962
PMCPMC13392293

What OpenQuestion holds

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LicenceCC BY
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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 OpenQuestion graph.