In the 2018 Programme for International Student Assessment (PISA), 15-year old Filipino students ranked last in reading proficiency among all countries/territories, with only 19% meeting the minimum (Level 2) standard. It is important to understand the different factors that contribute to the low reading performance and proficiency of these students, specifically the interventions that may help address this learning problem. Based on the result of a study using machine learning approaches, specifically binary classification methods, to identify the variables that best predict low (Level 1b and lower) vs. higher (Level 1a or better) reading proficiency using the Philippine PISA data, 20 variables that discriminated low reading proficiency students were identified. The results reflect aspects of the students’ psychosocial experiences at home, the classroom, and in the schools that relate to their poor reading proficiency. The results point to how interventions to address poor reading proficiency need to go beyond the curriculum and instructional interventions. What is needed are localized interventions that try to improve the psychosocial experiences of students in school, and that involve stakeholders from the local communities.
