DLSU-AKI Policy Brief, Volume VII, No. 17
Mitigating Emissions Associated With the Production of Traded Goods
BRAc RN 2021-01
Shedding Light on Bank Deposits in Philippine Provinces
Modernizing VAT in the Digital Economy
Nature-Based Policies Towards Green Recovery: Mitigating the Impacts of Climate Change and Future Disease Outbreaks

PIDS WB 2021-1104
Assessing the Philippines' Performance in Meeting the ASEAN Economic Community Vision 2025
PIDS WB 2021-1103
Examining The Health Impacts Of The COVID-19 Pandemic In The Philippines
ILS 30th Anniversary Video
PIDS WB 2021-1102
Evaluating the Pantawid Pamilyang Pilipino Program's Payment System
Publication Detail
DLSU-AKI Working Paper Series 2021-11-075 : Using Machine Learning Approaches to Explore Non-Cognitive Variables Influencing Reading Proficiency in English Among Filipino Learners Final Report

Filipino students ranked last in reading proficiency among all countries/territories in the Programme for International Student Assessment (PISA) 2018, with only 19% meeting the minimum (Level 2) standard. It is imperative to understand the range of factors contributing to low reading proficiency, specifically variables that can be the target of interventions to help the students with poor reading proficiency. We used 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 from a nationally representative sample of 15-year-old students. Several binary classification methods were applied, and the best classification model was derived using support vector machines (SVM), with 81.2% average test accuracy. The 20 variables with the highest impact in the model were identified and interpreted using the socioecological perspective of development and learning. These variables included students’ home-related resources and socioeconomic constraints, learning motivation and mindsets, reading classroom experiences with teachers, reading self-beliefs, attitudes and experiences, and social experiences in the school environment. The results were discussed with reference to the need for a system perspective to address poor proficiency that requires interconnected interventions that go beyond the students’ reading classroom.

DLSU - Angelo King Institute for Economic and Business Studies
Authors Keywords
Lucas, Rochelle, I.; Cordel II, Macario, O.; Teves, Jude Michael, M.; Yap, Sashmir, A.; Chua, Unisse, C.; Bernardo , Allan, B. I. ; education; machine learning; motivation; PISA; reading proficiency; non-cognitive variables; support vector machines; growth mindset; reading self-concept; bullying; school connectedness; Programme for International Student Assessment ;
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Published in 2021 and available in the De La Salle University - Angelo King Institute for Economic and Business Studies (Room 223, St. La Salle Hall, 2401 Taft Avenue, Manila 0922 or Downloaded 13 times since November 08, 2021
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