A machine learning-based adaptive platform is associated with cognitive improvements in Peruvian secondary school students: a quasi-experimental study

A quasi-experimental study conducted in Peruvian secondary schools indicates that a machine learning-based adaptive educational platform is associated with cognitive improvements in students. Compared to traditional teaching methods, students utilizing the platform showed enhanced performance across attention, memory, reasoning, and comprehension.

Why it matters

This research highlights the potential of machine learning to significantly enhance cognitive learning outcomes, offering a data-driven approach to personalized education. The findings suggest that adaptive technological interventions can be a critical tool for improving educational efficacy and student development globally.

Key insights

• The research employed an applied, quantitative, quasi-experimental design.
• The study involved 56 fourth-grade secondary students in Piura, Peru.
• An experimental group (n=30) used an ML-based adaptive platform, while a control group (n=26) received traditional teaching.
• Cognitive learning was assessed across four dimensions: attention, memory, reasoning, and comprehension.
• Assessments were conducted via pretest and posttest exams over three consecutive weeks for each topic.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1938135