Aprender Tests: Only four provinces showed the best results; data reveals educational levels

Argentina's 2025 Aprender national assessments reveal significant disparities in educational performance across provinces. The City of Buenos Aires, Córdoba, Chubut, and Tierra del Fuego stood out with the highest achievements in Language. In Mathematics, the City of Buenos Aires, Formosa, and Córdoba topped the rankings.

The Ministry of Capital Humano reported an overall improvement in both Language and Mathematics compared to the 2023 evaluations. These results, however, highlight differences not only between provinces but also across different management sectors, socioeconomic levels, and school environments. The assessment, conducted in November 2025, involved 631,366 sixth-graders from 19,414 schools nationwide, representing 84% of the enrolled student population and the highest participation rate since the Aprender tests began in their current format in 2016.

Language assessments showed that 76.9% of students reached satisfactory or advanced performance levels, with 44.1% in the satisfactory category and 32.8% in the advanced. Basic performance was recorded by 18.2%, while 4.9% fell below the basic level, marking the lowest percentage since the 2013 National Evaluation Operation (ONE). In Mathematics, 55% of students achieved satisfactory or advanced levels (39.9% satisfactory, 15.1% advanced), with 24.8% at a basic level and 20.2% below basic.

Notably, the improvement was not uniform. While Buenos Aires City, Córdoba, Chubut, and Tierra del Fuego showed the highest average scores in Language, Misiones, Santiago del Estero, Tucumán, Catamarca, and Chaco registered the lowest. The report also points out that the students evaluated began first grade in 2020, during the COVID-19 pandemic, experiencing significant disruptions to in-person schooling. Their primary education was completed during the recovery phase of face-to-face classes, a trajectory the ministry considers relevant for interpreting the results, though it cautions against attributing outcomes to single policies or factors.