Can the Teacher Professional Education Admission Criteria in Indonesia Predict Teacher Performance?

Studies find that effective teachers raise student test achievement and lead to higher future earnings for the students (Chetty et.al, 2014; Hanushek, 2011). Teacher selection and the criteria used in making the selection are important because they aim to identify such effective teachers. Identifying teachers with such potential is relatively more cost-effective than other policies applied after the teachers have teaching jobs (Klassen and Kim, 2019; Hobson et al., 2010). Many studies focus on selecting teachers based on the information collected at the time of hire to predict student outcomes (Jacob et al., 2018; Hill et al., 2012; Staiger and Rockoff, 2010). Other studies identify potentially effective teachers even before they become teachers. Those studies use information from teacher education programme admission criteria to predict teacher candidates’ success in the programme (Heinz, 2013; Casey and Child, 2011; Caskey et al., 2001). Among teacher selection criteria, studies identified predictors of subsequent performance including undergraduate grades, written tests, interviews, and teaching practice. In developing countries, studies on teacher selection are virtually non-existent. We found two studies that focus on the selection of teachers during hiring. Both use candidates’ screening tests results to predict student learning outcomes (Araujo et al., 2020; Cruz-Aguayo et al., 2017). However, we did not find studies in developing country contexts that focus on selection of teachers into education programmes or how the admission criteria relate to student learning outcomes. Whether focusing on selecting teachers during their education programme or as they go through the recruitment process, studies on teacher selection across countries have the same underlying question: Will the criteria be able to identify effective teachers? The idea of teacher selection to improve the quality of the teaching force is appealing. For instance, in high performing countries in PISA, like Japan and Korea, where there are many teacher colleges (Ingersoll, 2007) and the most prevalent teacher employment is civil-service, great attention is paid to the quality of selection into teacher education programmes (OECD, 2018). Teacher selection is arguably more critical in developing countries. In most developing countries, the entry into teacher education programmes lacks selectivity and teacher qualifications tend to be set lower compared to other professional jobs (Béteille and Evans, 2019). Across all developing countries, a larger number of teachers are employed and account for most of the education spending, but their effect on student outcomes is small (ADB, 2021; Crawfurd and Pugatch, 2021). This suggests the need for more attention to policies such as the selection of teachers and criteria used to identify those best suited to teach in the classroom. In Indonesia, where the teacher recruitment system lacks a strong mechanism to ensure quality (Huang et al., 2020) and the teacher in-service training has not been effective (Revina et al., 2020), a potential way to improve the pool of teachers is through enhanced selection of individuals who will become teachers. We specifically question whether we can predict a teacher’s performance using information available when they were a teacher candidate. Admission criteria for teacher education are presumably intended to identify candidates who have the greatest likelihood of being able to do well in the academic programme and ultimately in the classroom as a professional. The identification of criteria that predict teacher subsequent performance would give policy makers a stronger understanding of where programme improvement may be needed.