Application of artificial intelligence for the detection of educational needs and the personalization of evaluation processes

Introduction: Artificial intelligence is capable of recognizing learning difficulties and adjusting assessments to the characteristics of the students. Objective: The aim of this study was to test the effects of artificial intelligence on the arrest of educational needs and the adaptation of assessment in improving the academic performance of students in Higher Basic General Education. Methodology: A quantitative, applied, explanatory-comparative and quasi-experimental study was carried out with pre-test and post-test. The population was 240 students and the sample was 148. The sample was divided into the experimental group and the control group: both groups of 74 students. The experimental group received adaptation of the assessment over the course of eight weeks while the control group continued the conventional procedure. Simulated data were used to structure the analytical model. Results: The experimental group improved 17.8 points in performance compared to the control group (6.3 points) with a large effect (d = 1.42). The presence of students with a high need for reinforcement went from 41.9% to 10.8% and satisfactory mastery increased to 63.5%. Conclusion: Personalized student assessment with Artificial Intelligence can help detect academic needs, adapt tasks and improve student performance under teacher intervention.