Evidence map›Paper›PMID 42445257›Full record

ArticleFrontiers in psychology2026

Student perceptions of artificial intelligence in higher education: a structural analysis at an Italian university.

Calogero Cammà, Luisa Amenta, Salvatore Battaglia, Ciro Celsa, Giansalvo Cirrincione, Salvatore Contino, Pier Paolo Corso, Salvatore Di Dio, Gabriele Di Maria, Marco Enea and 13 more

Abstract read
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In one paragraph

Article in Frontiers in psychology, 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

23 authors.

Calogero CammàDepartment of Health Promotion, Mother & Child Care, Internal Medicine & Medical Specialties, Gastroenterology & Hepatology Unit, University of Palermo, Palermo, Italy.
Luisa AmentaDipartimento di Scienze umanistiche, University of Palermo, Palermo, Italy.
Salvatore BattagliaDepartment of Economics Business and Statistics, University of Palermo, Palermo, Italy.
Ciro CelsaDepartment of Health Promotion, Mother & Child Care, Internal Medicine & Medical Specialties, Gastroenterology & Hepatology Unit, University of Palermo, Palermo, Italy.
Giansalvo CirrincioneDépartement Electronique-Electrotechnique-Automatique (EEA), University of Picardie Jules Verne, Amiens, France.
Salvatore ContinoDepartment of Engineering, University of Palermo, Palermo, Italy.
Pier Paolo CorsoDipartimento di Fisica e Chimica-Emilio Segré, University of Palermo, Palermo, Italy.
Salvatore Di DioDipartimento di Architettura, University of Palermo, Palermo, Italy.
Gabriele Di MariaDepartment of Health Promotion, Mother and Child Care, Internal Medicine, and Medical Specialties (PROMISE), University of Palermo, Palermo, Italy.
Marco EneaDepartment of Health Promotion, Mother and Child Care, Internal Medicine, and Medical Specialties (PROMISE), University of Palermo, Palermo, Italy.
Adriano FagioliniDepartment of Engineering, Mobile & Intelligent Robots @ Panormus Laboratory (MIRPALab), University of Palermo, Palermo, Italy.
Alessandra FerraroUniversity of Palermo, Palermo, Italy.
Mauro GiuffrèDepartment of Internal Medicine (Digestive Diseases), Yale School of Medicine, New Haven, CT, United States.
Giosuè Lo BoscoDepartment of Mathematics and Computer Science, University of Palermo, Palermo, Italy.
Domenica MatrangaDepartment of Health Promotion, Mother and Child Care, Internal Medicine, and Medical Specialties (PROMISE), University of Palermo, Palermo, Italy.
Roberto PirroneDepartment of Engineering, University of Palermo, Palermo, Italy.
Francesco Maria RaimondiDepartment of Engineering, University of Palermo, Palermo, Italy.
Ilenia TinnirelloDepartment of Engineering, University of Palermo, Palermo, Italy.
Riccardo UccelloUniversity Information Systems Area, University of Palermo, Palermo, Italy.
Marco VaccaroDepartment of Health Promotion, Mother and Child Care, Internal Medicine, and Medical Specialties (PROMISE), University of Palermo, Palermo, Italy.
Caterina VentimigliaDepartment of Law, University of Palermo, Palermo, Italy.
Salvatore VitabileDepartment of Biomedicine, Neurosciences and Advanced Diagnostics (BIND), University of Palermo, Palermo, Italy.
Massimo MidiriDepartment of Biomedicine, Neurosciences and Advanced Diagnostics (BIND), University of Palermo, Palermo, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and aims: The rapid advancement of artificial intelligence (AI) is transforming higher education, yet understanding of student perceptions remains limited. This study investigates the structure of student attitudes toward AI and identifies key predictors among Italian university students. Methods: A cross-sectional survey was administered to 864 students at the University of Palermo (May-June 2025). The questionnaire examined demographics, AI experience, and attitudes using 10 Likert-type items. Data were analyzed using exploratory factor analysis and confirmatory factor analysis. Results: Most students (65.8%) reported superficial AI knowledge, yet 93.6% had used AI applications, predominantly ChatGPT (59.8%). Factor analyses identified two distinct latent constructs: perceived Impact of AI and AI-related Concerns, negatively correlated ( Conclusions: Student attitudes toward AI reflect two distinct dimensions: opportunity recognition and risk awareness, systematically influenced by gender, discipline, and AI experience. Successful implementation requires tailored approaches addressing gender-specific concerns, discipline-specific needs, and promoting direct AI experience.

Indexed as

artificial intelligenceconfirmatory factor analysiseducational technologyfactor analysishigher educationstudent perceptions

Identifiers

PMID42445257
PMCPMC13357671

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.