In Clas activity for Data Science using the group and across functions.

This project applies basic text mining techniques to instructional feedback narratives from a district dataset. Using tokenization and a simplified embedded sentiment lexicon, I quantified positive and negative language within feedback comments and aggregated results at the anonymized observer level. The goal was to examine variation in tone across observers and demonstrate how sentiment analysis workflows can be applied to educational feedback data in R.

El propósito de esta herramienta es identificar y localizar a las EduCunas del MINEDU y a los servicios Cuna Más del MIDIS, con el fin de optimizar la gestión del acceso y la cobertura de las acciones de formación y monitoreo.