AI Adoption and Staff Competencies in Peruvian Basic-Education Institutions

Ninety-eight administrative personnel across 54 institutions in Chimbote, Peru, responded to a structured survey. The dataset contains anonymized Likert-scale responses measuring AI adoption, job competencies, productivity, and autonomy. Researcher Miguel Canchari published the data in April 2026 to support reproducibility in educational administration research.

Use Cases

• Analyze correlations between AI adoption scores (IA1–IA8) and administrative productivity metrics (PA1–PA6).
• Model the influence of job competency variables (CL1–CL6) on decision-making autonomy (ATD1–ATD3) using structural equation modeling.
• Examine the distribution of Likert-scale responses across all variable groups to assess perceptions of digital transformation.
• Compare institutional performance indicators based on aggregated staff responses from the 54 surveyed institutions.

Strengths

• Data is fully anonymized to ensure participant confidentiality.
• All 98 records use consistent 5-point Likert-scale measurement for comparability.
• Dataset is structured for direct use in Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis.

Limitations

• Small sample size of 98 respondents limits statistical power and generalizability.
• Geographic scope is restricted to institutions in Chimbote, Peru, which may not represent other regions.
• Dataset size is 62.7 KB, indicating a limited scope with no longitudinal or time-series component.

Provenance

Source

Miguel Canchari via figshare.

Collection Method

Collected via a structured questionnaire administered to administrative staff.

Freshness

Data was last updated in April 2026, indicating recent collection and publication.

Geography

Chimbote, Peru.