Survey on Teachers' Perceptions of AI in El Salvador

Published: 17 September 2026| Version 1 | DOI: 10.17632/5mw82yfkdw.1
Contributor:
Mauricio Dagoberto Deleon Villagran

Description

This dataset corresponds to a study on teachers' perceptions regarding Artificial Intelligence (AI) in El Salvador. Data processing was conducted using the quantitative analysis software JASP 0.95.4 and IBM SPSS Statistics 28.0.0.0 (190). The analytical strategy is deployed in three phases: Phase 1 — Sample characterization: Measures of central tendency, dispersion, counts, and percentage distributions of participants' sociodemographic and academic characteristics are provided. Phase 2 — Description of variables of interest: The distribution of item responses is explored through measures of central tendency, dispersion, and shape (skewness and kurtosis), offering an overview of perceptions and response variability. Phase 3 — Internal consistency and inferential tests: Reliability results for the variables of interest are presented using McDonald's Omega. Additionally, association tests are applied: Chi-square test of independence, and between-group comparison tests: Mann-Whitney U.

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Artificial Intelligence, Education, Teaching, Higher Education, Generative Artificial Intelligence

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