Perception of AI tool adoption and training: initial validation using GSEM method

Purpose This study develops and validates the “Perception of the Adoption and Training in the Use of Artificial Intelligence Tools in the Profession” instrument, designed to measure Latin American university students' attitudes and perceptions regarding AI training in their professional education across diverse fields. Design/methodology/approach The instrument was administered to 238 students from various disciplines at a Mexican university. Structural validity and reliability were assessed using a generalized structural equation model (GSEM) with quasi-maximum likelihood (QML) to handle data non-normality and analyze latent construct relationships. Findings Results show high internal consistency and validity, with strong correlations between items and constructs of “attitude” and “perception of AI training value.” The study found significant relationships between understanding AI tools and the perceived value of AI training, as well as between this perception and attitudes toward incorporating AI in professional training. Practical implications The instrument helps institutions identify student attitudes and training needs related to AI, enabling tailored curricula and training programs that foster positive AI acceptance, thus preparing students for modern technological challenges. Originality/value This study offers a validated instrument tailored to the Latin American context, addressing a gap in measuring student perceptions of AI in professional training. It serves as a diagnostic tool for educators and policymakers in designing AI-integrated pedagogical strategies that align with student needs.

Authors

Institutions

Publication Details

Journal
Applied Computing and Informatics
Published
2024-12-23
DOI
https://doi.org/10.1108/aci-09-2024-0370
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
1.05
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Perception of AI tool adoption and training: initial validation using GSEM method

José Carlos Vázquez Parra, Carolina Henao-Rodríguez, Jenny-Paola Lis-Gutiérrez, Paloma Suárez-Brito et al.
2 citations
Applied Computing and Informatics
Ethics and Social Impacts of AI
1.05
article

Perception of AI tool adoption and training: initial validation using GSEM method

José Carlos Vázquez Parra, Carolina Henao-Rodríguez, Jenny-Paola Lis-Gutiérrez, Paloma Suárez-Brito, Sergio Palomino-Gámez
article en
2 citations

Abstract

Purpose This study develops and validates the “Perception of the Adoption and Training in the Use of Artificial Intelligence Tools in the Profession” instrument, designed to measure Latin American university students' attitudes and perceptions regarding AI training in their professional education across diverse fields. Design/methodology/approach The instrument was administered to 238 students from various disciplines at a Mexican university. Structural validity and reliability were assessed using a generalized structural equation model (GSEM) with quasi-maximum likelihood (QML) to handle data non-normality and analyze latent construct relationships. Findings Results show high internal consistency and validity, with strong correlations between items and constructs of “attitude” and “perception of AI training value.” The study found significant relationships between understanding AI tools and the perceived value of AI training, as well as between this perception and attitudes toward incorporating AI in professional training. Practical implications The instrument helps institutions identify student attitudes and training needs related to AI, enabling tailored curricula and training programs that foster positive AI acceptance, thus preparing students for modern technological challenges. Originality/value This study offers a validated instrument tailored to the Latin American context, addressing a gap in measuring student perceptions of AI in professional training. It serves as a diagnostic tool for educators and policymakers in designing AI-integrated pedagogical strategies that align with student needs.

Applied Computing and Informatics
Fundación Universitaria Konrad Lorenz (CO), Institute for the Future (US), Tecnológico de Monterrey (MX)
Quality Education
Openalex Percentile: Top 17%
Ethics and Social Impacts of AI
1.05
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.