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Profiling low-proficiency science students in the Philippines using machine learning.

Allan B I Bernardo1, Macario O Cordel1, Marissa Ortiz Calleja1

  • 1De La Salle University, Manila, Philippines.

Humanities & Social Sciences Communications
|May 16, 2023
PubMed
Summary
This summary is machine-generated.

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Filipino students struggle with science literacy, ranking near last in PISA 2018. Machine learning identified key factors like reading strategies and home environment impacting low science achievement, suggesting new reform targets.

Area of Science:

  • Educational Psychology
  • Science Education
  • Data Science

Background:

  • Filipino students consistently demonstrate low performance in international science literacy assessments.
  • The Programme for International Student Assessment (PISA) 2018 results placed Filipino learners second to last among 78 participating countries in science literacy.
  • Identifying factors contributing to low achievement is crucial for effective science education reform in the Philippines.

Purpose of the Study:

  • To utilize machine learning to analyze student questionnaire data from PISA 2018.
  • To identify the key factors associated with the poorest-performing Filipino students in science literacy.
  • To inform targeted interventions and policy recommendations for science education reform.

Main Methods:

Keywords:
EducationPsychology

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  • Application of machine learning approaches, specifically the random forest classifier, to PISA 2018 student data.
  • Utilizing Shapley Additive Explanations (SHAP) to determine the importance of various predictive variables.
  • Analysis focused on identifying students vulnerable to very low science achievement.

    • Main Results:

    • The random forest classifier model demonstrated high accuracy and precision in identifying low-performing students.
    • Fifteen variables were identified as most significant in predicting low science proficiency.
    • Key factors included metacognitive awareness of reading strategies, social experiences, aspirations, pride in achievement, and family/home factors (parental characteristics, ICT access).

    Conclusions:

    • Personal and contextual factors significantly influence science literacy achievement, extending beyond traditional instructional and curricular elements.
    • The findings underscore the need for a holistic approach to science education reform in the Philippines.
    • Implications for policy and program development are suggested to address identified contributing factors.