Preparation, Practice, and Beliefs : A Machine Learning Approach to Understanding Teacher Effectiveness
This paper uses machine learning methods to identify key predictors of teacher effectiveness, proxied by student learning gains linked to a teacher over an academic year. Conditional inference forests and the least absolute shrinkage and selection...
Main Authors: | , , |
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Language: | English |
Published: |
World Bank, Washington, DC
2021
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Subjects: | |
Online Access: | http://documents.worldbank.org/curated/undefined/737101636989604541/Preparation-Practice-and-Beliefs-A-Machine-Learning-Approach-to-Understanding-Teacher-Effectiveness http://hdl.handle.net/10986/36600 |
Summary: | This paper uses machine learning
methods to identify key predictors of teacher effectiveness,
proxied by student learning gains linked to a teacher over
an academic year. Conditional inference forests and the
least absolute shrinkage and selection operator are applied
to matched student-teacher data for math and Kiswahili from
grades 2 and 3 in 392 schools across Tanzania. These two
machine learning methods produce consistent results and
outperform standard ordinary least squares in out-of-sample
prediction by 14–24 percent. As in previous research,
commonly used teacher covariates like teacher gender,
education, experience, and so forth are not good predictors
of teacher effectiveness. Instead, teacher practice (what
teachers do, measured through classroom observations and
student surveys) and teacher beliefs (measured through
teacher surveys) emerge as much more important. Overall,
teacher covariates are stronger predictors of teacher
effectiveness in math than in Kiswahili. Teacher beliefs
that they can help disadvantaged and struggling students
learn (for math) and they have good relationships within
schools (for Kiswahili), teacher practice of providing
written feedback and reviewing key concepts at the end of
class (for math), and spending extra time with struggling
students (for Kiswahili) are highly predictive of teacher
effectiveness. As is teacher preparation on how to teach
foundational topics (for both Math and Kiswahili). These
results demonstrate the need to pay more systematic
attention to teacher preparation, practice, and beliefs in
teacher research and policy. |
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