Selecting Teachers in Indonesia: Predicting Teacher Performance using Pre-Employment Information

Abstract

A wave of teacher retirement in Indonesia provides an opportunity to replace them with better-performing teachers. We study whether teacher candidates’ screening tests into Pendidikan Profesi Guru (PPG) or Teacher Professional Education, a postgraduate education programme in Indonesia, can predict their performance at the end of the programme and in an actual classroom situation at the beginning of their teaching career. Using administrative data of 1,291 primary school teacher candidates, we find that admission criteria, including undergraduate grade point average (GPA), online admission tests, and interview scores, can predict a candidate’s performance on their knowledge and teaching practice exams at the end of their education programme. A one standard deviation higher online admission test score is associated with a 0.30 standard deviation higher score in the knowledge examination. Teacher candidates with a one standard deviation higher interview score perform 0.07 standard deviation better on the teaching practice examination. For teacher candidates with one standard deviation higher undergraduate GPA, their knowledge examination performance is 0.15–0.17 standard deviation higher on average, and their teaching practice exam score is 0.06-0.07 standard deviation higher on average. We then estimate the predictive ability of the admission criteria on student learning outcomes in numeracy and literacy, which uses 1,530 randomly sampled students taught by 114 teacher candidates. We find no evidence that the selection criteria predicted student learning in a meaningful way. Our results contribute to a nascent body of research on the selection of teachers using ex-ante criteria to identify effective teachers in developing countries.

Publication
In RISE Working Paper Series
Emilie Berkhout
Emilie Berkhout
PhD Candidate

Specialized in impact evaluations in low- and middle-income countries.