Smarter teachers, smarter pupils Smarter teachers, smarter pupils? Some new evidence from Sub-Saharan Africa Nadir Altinok a, Manos Antonisis b, Phu Nguyen-Van c a BETA, University of Lorraine b Global Education Report Team, UNESCO c BETA, CNRS & University of Strasbourg ASSA, Chicago, January 6-8, 2017

Teacher knowledge & student performance Clear evidence about teacher knowledge as a key determinant of student learning. But very few information is available about which specific observable characteristics of teachers can account for this impact (Rockoff, 2004 ; Rivkin, Hanushek, Kain, 2005 ; Aaronson, Barrow, Sander, 2007). Most analyzed variables: teacher education and experience Teachers' academic skills measured by scores on achievement tests is the most significantly correlated with student achievement (Wayne, Youngs, 2003; Eide, Goldhaber, Brewer, 2004; Hanushek, Rivkin, 2006). The analysis of the effects of teacher test scores on pupil achievement was mainly conducted in developed countries.

Outline Previous literature Main contributions Methodology Data and variables Results Conclusion

Literature Previous studies: Hanushek (1971; 1992), Summers and Wolfe (1977), Murname and Phillips (1981), Ehrenberg and Brewer (1995), Ferguson and Ladd (1996), Rowan, Chiang, and Miller (1997), Ferguson (1998), and Rockoff et al. (2011). Studies focused on developing countries: Harbison and Hanushek (1992) in rural Northeast Brazil; Tan, Lane, and Coustère (1997) in the Philippines, Bedi and Marshall (2002) in Honduras, Santibanez (2006) in Mexico, Behrman, Ross, and Sabot (2008) in rural Pakistan; Marshall (2009) for Guatemala; Metzler and Woessmann (2012) in Peru. Few papers on Sub-Saharan Africa: Bonnet (2009) combined both teachers' knowledge and behaviour using SACMEQ II data. However, the relationship only had two control variables, potentially leading to biased estimates. Shepherd (2013) found that teacher knowledge improves student achievement in the wealthiest quintile of schools in South Africa.

Literature Most papers based on developing countries likely suffer from bias due to omitted student and teacher characteristics and non-random sorting of students and teachers. In this study, we propose to evaluate the effect of teacher subject knowledge on student achievement for eight Sub-Saharan African countries which took part to SACMEQ III assessment in 2007. SACMEQ (Southern and Eastern Africa Consortium for Monitoring Educational Quality) is an assessment which includes 15 Sub-Saharan African countries (most of them are anglophone countries).

Contributions of the study The hypothesis that teacher subject knowledge has a similar affect among countries is wrong since very large differences can be found among African countries regarding their education and the distribution of teacher knowledge => We specify the hypothesis of country-specific teacher quality. Teacher subject knowledge effect depends on specific conditions like low school resources, high teacher absenteeism or low performance of teachers in ‘core skills’ (i.e. skills which are taught to pupils) : If absenteeism is high, the teacher effect is low in most countries. Teachers with high scores are not necessarily high performers. It depends on ‘knowledge transferability’: for the group of pupils who are taught by teachers who perform very well in ‘core skills’, the teacher effect is strongly positive.

Methodology  

Methodology  

Methodology  

Data SACMEQ includes 15 countries: Botswana, Kenya, Lesotho, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, United Republic of Tanzania, United Republic of Tanzania (Zanzibar), Uganda, Zambia and Zimbabwe. SACMEQ survey: pupils and teachers' skills in reading & mathematics. The SACMEQ III data were collected using a stratified two-stage cluster sample design. The math and reading teachers of the three largest classes in each school were tested.

Data The teacher and pupil tests used different sets of items but the two tests had some common items (20 and 13 common items for the reading test and the mathematics test respectively). The separate subject-specific tests in SACMEQ III allow for an encompassing measurement of teacher subject knowledge in two specific subjects. Both student and teacher tests in both subjects were scaled using Rasch modeling: All test scores are placed on a common scale with mean 500 and standard deviation 100 across students participating in SACMEQ III. In order to test our identification strategy, we not only need comparable data for both teacher and student subject knowledge, but also classes taught from the same teacher.

Data Mauritius excluded because of no available test on teachers. In some countries, teachers for mathematics are different from teachers for reading. This difference appears to be systematic in some countries. The proportion of pupils who are taught by the same teacher on both subjects in 6th Grade varies greatly between SACMEQ countries. Same teacher for the two subjects in 8 countries: Botswana, Lesotho, Malawi, South Africa, Swaziland, Uganda (min. 7%), Zambia, and Zimbabwe (max. 92%).

Data Student performance: Teacher performance: Top countries in reading: Tanzania and Seychelles Top countries in mathematics: Kenya and Tanzania Teacher performance: Top country in reading: Seychelles Top country in mathematics: Kenya Control variables: student gender, student 1st language, urban area, private school, complete school, teacher gender, teacher’s university degree. # observations: 317 (Zambia)-3142 (Botswana); 14952 (whole Sacmeq).

Data

Data

Results (1) (2) (3) (4) (5) Unrestricted model Restricted model     (1) (2) (3) (4) (5) Unrestricted model Restricted model Fixed-effect model Maths Reading Maths+Reading SACMEQ 0.002 0.016 0.017 0.010 (0.83) (0.21) (0.89) (0.19) (0.36) Botswana 0.000 -0.010 0.001 -0.005 (0.99) (0.62) (0.97) (0.59) (0.76) Lesotho -0.040 -0.050 -0.043 -0.047 -0.045 (0.27) (0.23) (0.10)* Malawi 0.064 0.137 0.066 0.135 0.103 (0.37) (0.02)** (0.03)** South Africa 0.074 0.072 0.070 (0.12) (0.11) Swaziland 0.036 -0.039 0.084 n.a. (0.57) (0.24) Uganda 0.096 0.319 0.348 (0.50) (0.05)** (0.46) Zambia 0.018 0.034 0.015 0.027 (0.56) (0.17) Zimbabwe 0.004 -0.029 0.005 -0.031 (0.79) (0.74)

Results Heterogenous effects: Female students vs male students; Female teachers vs male teachers; Rural vs urbal areas; Mother/father with university degree or not; Wealthiest schools vs schools with poor socio-economic background All countries considered: Female teachers (+) No clear pattern about the effect of teacher quality among individual countries Student gender, teacher gender, school’s socio-economic levels (+/-) Possible nonlinear effect of teacher quality and ‘ability matching’ between sub-samples

Results Teacher/student ability matching matters: Absenteeism: - Low performing teachers & low performing students: - Smart teachers & low performing student: + High performing teachers & high performing students: + Absenteeism: - ‘Core items’: + (more in reading than in math) Robustness check: use STOC (same teacher one classroom) sample to eliminate potential bias from teacher sorting between classrooms.

Conclusion Analysis on SACMEQ data (14 Sub-Saharian countries; 8 countries for ‘same teacher’; 5 countries for ‘same teacher one classroom’) Low evidence for teacher quality effect: Lack of reliable data (Cronbach’s alpha lower than 0.5) Teacher subject knowledge effect is heteregenous across countries. Country heterogeneity: absenteeism, knowledge transferability (lack of knowledge on ‘core skills’) Results are robust to within-school teacher sorting effect.