How sensitive are the evaluations of a school's effectiveness to the selection of covariates in the applied value‑added model?

There is no final consensus regarding which covariates should be used (in addition
to prior achievement) when estimating value-added (VA) scores to evaluate
a school’s effectiveness. Therefore, we examined the sensitivity of evaluations of
schools’ effectiveness in math and language achievement to covariate selection in
the applied VA model. Four covariate sets were systematically combined, including
prior achievement from the same or different domain, sociodemographic and sociocultural
background characteristics, and domain-specific achievement motivation.
School VA scores were estimated using longitudinal data from the Luxembourg
School Monitoring Programme with some 3600 students attending 153 primary
schools in Grades 1 and 3. VA scores varied considerably, despite high correlations
between VA scores based on the different sets of covariates (.66 < r < 1.00).
The explained variance and consistency of school VA scores substantially improved
when including prior math and prior language achievement in VA models for math
and prior language achievement with sociodemographic and sociocultural background
characteristics in VA models for language. These findings suggest that prior
achievement in the same subject, the most commonly used covariate to date, may
be insufficient to control for between-school differences in student intake when estimating
school VA scores. We thus recommend using VA models with caution and
applying VA scores for informative purposes rather than as a mean to base accountability
decisions upon.