Do Algorithms Homogenize Students’ Achievements in Secondary School Better Than Teachers’ Tracking Decisions?

Abstract

Two objectives guided this research. First, this study examined how well teachers’ tracking decisions contribute to the homogenization of their students’ achievements. Second, the study explored whether teachers’ tracking decisions would be outperformed in homogenizing the students’ achievements by statistical models of tracking decisions. These models were akin to teachers’ decisions in that they were based on the same information teachers are supposed to use when making tracking decisions. It was found that the assignments of students to the different tracks made either by teachers or by the models allowed for the homogenization of the students’ achievements for both test scores and school marks. Moreover, the models’ simulations of tracking decisions were more effective in the homogenization of achievement than were the tracking decisions, if the students assigned to the different tracks were at the center of the achievement distribution. For the remaining students, there was no significant difference found between teachers’ tracking decisions and the models’ simulations thereof. The reason why algorithms produced more homogeneous groups was assumed to be due to the higher consistency of model decisions compared to teacher decisions.