Digital Matthew Effect Data for 724 STEM Students in Ciudad Juárez, Mexico

724 Industrial Engineering student survey responses from public and private universities in Ciudad Juárez, Mexico, collected for a 2026 doctoral thesis. The data, provided by Luis Fernando Alvarez Saucedo, operationalizes the Digital Matthew Effect to examine digital inequalities, gender gaps, and academic AI appropriation. It includes raw data, codebooks, and R scripts for analysis.

Use Cases

• Analyze digital inequality patterns among STEM students based on survey data.
• Investigate gender gaps in technology access and use based on the study's operationalization.
• Model academic appropriation of artificial intelligence based on student survey responses.
• Perform cluster analysis on student profiles based on the described k-means methodology.
• Conduct multinomial logistic regression on factors influencing digital access based on the provided scripts.

Strengths

• Includes 724 anonymized student cases.
• Provides a complete codebook (diccionario_variables_IA.csv) for variable interpretation.
• Contains fully reproducible R scripts for cleaning, statistical tests, and modeling.
• Original survey instrument (Cuestionario_IA_STEM_AlvarezSaucedo_2026.pdf) is included for context.

Limitations

• Column-level documentation is absent from the provided metadata; field semantics must be inferred after download.
• Row count is unknown for individual files, which may limit suitability assessment.
• Data may reflect geographic and temporal bias inherent to a single-city, cross-sectional study from 2026.

Provenance

Source

Luis Fernando Alvarez Saucedo

Collection Method

Survey of 724 Industrial Engineering students from public and private universities.

Freshness

Last updated 2026-05-24 08:15:51; freshness should be verified.

Geography

Ciudad Juárez, Chihuahua, Mexico