Fast‐Tracks in Mathematics: Accelerated Learning, Self‐Selection or Teacher Bias?

This study examines high-achieving students in Norwegian lower secondary schools who follow accelerated learning trajectories in mathematics, so-called fast-tracks. It asks whether and how fast-tracks improve high-achieving students' learning and performance. The analyses rely on high-quality administrative register data from Norway covering all students who graduated from 2010 to 2017. The results show that fast-track students outperform regular students in mathematics. They are overrepresented with top school grades, so effects are often underestimated using standard methods. To address ceiling effects in grades, we apply Tobit regression and a novel use of correlated-random effects (Mundlak model), embedding fixed-effects and instrumental-variable approaches within nonlinear Tobit models. The results suggest that (1) the fast-tracks improve the students' learning, and (2) the students are selected and self-selected, based on prior performance and background characteristics. When comparing teacher-set grades versus exam grades set by anonymous, randomly assigned examiners, the results suggest that (3) teachers give fast-track students even better grades than regular students. One plausible explanation is that teachers perceive or label fast-track students as more talented than other students. The findings, in particular, suggest that Norwegian teachers compensate disadvantaged fast-track students who originate from homes with limited parental educational resources.