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

Monitoring, Evaluation and Learning

RISE Programme in Indonesia studies 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.

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This is one of a series of working papers from RISE—the large-scale education systems research programme supported by the UK’s Department for International Development (DFID), Australia’s Department of Foreign Affairs and Trade (DFAT), and Bill & Melinda Gates Foundation.

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Author 
Asri Yusrina
Luhur Bima
Daniel Suryadarma
Emilie Berkhout
Author(s)
Daniel Suryadarma
Emilie Berkhout
Editor(s) 
Translator(s) 
Research Area 
National
Research Topic 
Keywords 
teacher selection
teacher education
admission criteria
student learning outcomes
Publication Type 
Working Paper