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Inefficiency in the education system means schooling is not learning. Assessment of learning
crises requires value-added estimates using repeated data on a nationally representative sample
of children of each of the member countries. At present, such estimates are available only for a
handful of OIC countries such as Pakistan, Afghanistan and Bangladesh (Asadullah and
Chaudhury 2015; Asadullah, Alim and Hossain 2018; Asim and Asadullah 2018). This involves
cross-sectional data to construct learning profile, an empirical relationship between years of
schooling completed and basic competencies. Although many OIC countries today participate in
international assessments such as EGRA, TIMSS, PISA, PIRLS and SACMEQ, these surveys assess
students at a point in the school cycle. While TIMSS test children in grades 4 and 8, very few OIC
countries participate in grade 4 version. In case of PISA, the survey population is 15 year old
adolescents. However countries differ in terms of schooling cycle and age at first enrolment. This
causes variation among participating children in terms of grade enrolled at the time of the
assessment. In PISA 2012 data, sample children are reported to be enrolled in grades 7 – 12 at
the time of the test. Figure 2.6 takes advantage of this and constructs the grade-learning profile.
Again, these are far from ideal as the sample size corresponding to lower and upper grades is
very small and lacks representation. However, this is true for OIC as well as non-OIC and OECD
sample. There is a noticeable learning gap between OIC and non-OIC countries at all grades. In
other words, children from participating OIC countries are behind their peers from OECD
countries at all points in the secondary schooling cycle. An average OIC child from grade 7
sample is 50 points behind a child from the participating OECD sample. Interestingly, a similar
gap prevail vis-à-vis non-OECD countries though it is more systematic up to grade 10.OIC
countries are behind their peers from OECD countries at all points in the secondary schooling
cycle. An average OIC child from grade 7 sample is 50 points behind a child from the
participating OECD sample. Interestingly, a similar gap prevails vis-à-vis non-OECD countries
though it is more systematic up to grade 10.
2.1.2. Input Quality and Expenditure on Education
This section analyzes data on education quality in terms of inputs such as student teacher ratio
(PTR), proportion of certified teachers and government expenditure. Figure 2.7 plots data on
PTR by average per capita income level of OIC, OECD and other non-OECD countries for whom
data is available. In the case of most OECD countries, there are around 20 students per teacher
in primary as well as secondary education. In contrast, only a small proportion of OIC countries
maintains a PTR below 20. The relatively high PTR in the majority of OIC countries reflect the
lack of resources (shortage of schools, classrooms as well as teachers). There is a poverty
connection in the sense that income-rich countries such as Qatar, Kuwait, Saudi Arabia and
Bahrain have favorable PTR compared to economically poor member states, particularly African
member countries. Similarly, upper-middle income countries such as Turkey, Malaysia and
Kazakhstan also have a PTR of around 20. This pattern is most pronounced in the case of PTR in
primary schools. At the same time, the part of the variation also reflects demographic
differences. Older OIC countries are seeing a decline in the country’s youth population because
of early demographic transition which has led to a dramatic reduction in class size. In some OIC
countries, their youthful population along with the inflow of refugees has put pressure on
classrooms and teachers.