Page 126 - Štremfel, Urška, and Maša Vidmar (eds.). 2018. Early School Leaving: Contemporary European Perspectives. Ljubljana: Pedagoški inštitut.
P. 126
ear ly school leaving: contempor ary european perspectives
learning. Making benchmarking charts a reliable source for policy learning
calls for their in-depth contextualisation. Well-developed national infor-
mation systems for gathering information on ESLers are a precondition for
this. They (should) not only consist of comparable statistical data but also
other (qualitative and quantitative) information that helps to understand
the phenomenon in detail (e.g. Thematic Working Group, n.d.). Hordosy
(2014) reports that the big differences in national information systems (e.g.
student registers, national or regional surveys) have so far allowed little
room for making comparisons across Europe. Given that “first experienc-
es in countries applying more advanced data collection systems show that
high-quality monitoring is very useful in maximising the reduction in ESL”
(European Commission, 2016), these could provide an unexploited source
of more in-depth policy learning and an even more positive trend of reduc-
ing it at the EU level.
Why do they learn?
Policy learning helps in controlling uncertainty by enabling changes to be
understood and to thereby construct scenarios and predictions in an ever
changing environment. In terms of the factors that catalyse policy learning
and explain why policy learning occurs in the first place, two sets of factors
can be identified: a) factors at the individual level, which include looking
for solutions to policy problems, controlling uncertainty, achieving indi-
vidual and collective goals and searching for the truth; b) structural fac-
tors, which include time-related factors that stimulate policy learning (an
election period, economic crisis, regime transformation, a period of lack of
success, a period of uncertainty), political culture, the institutional struc-
ture of a country, special characteristics of public policy and organisation-
al competence (e.g. Bennet & Howlett, 1992).
The motives for policy learning in the form of policy experimentation
for dealing with ESL within the TITA project can be explained by the great
complexity of the ESL policy problem and the consequences it holds for in-
dividuals, nation states and EU society as a whole, along with the already
established infrastructure for multi-professional cooperation in participat-
ing countries (France, Luxembourg, Switzerland). Experiences of the lead-
ing partner (France) with social experimentations in the ESL field clear-
ly also represent an important factor explaining the EU’s interest in policy
learning in the TITA setting.
126
learning. Making benchmarking charts a reliable source for policy learning
calls for their in-depth contextualisation. Well-developed national infor-
mation systems for gathering information on ESLers are a precondition for
this. They (should) not only consist of comparable statistical data but also
other (qualitative and quantitative) information that helps to understand
the phenomenon in detail (e.g. Thematic Working Group, n.d.). Hordosy
(2014) reports that the big differences in national information systems (e.g.
student registers, national or regional surveys) have so far allowed little
room for making comparisons across Europe. Given that “first experienc-
es in countries applying more advanced data collection systems show that
high-quality monitoring is very useful in maximising the reduction in ESL”
(European Commission, 2016), these could provide an unexploited source
of more in-depth policy learning and an even more positive trend of reduc-
ing it at the EU level.
Why do they learn?
Policy learning helps in controlling uncertainty by enabling changes to be
understood and to thereby construct scenarios and predictions in an ever
changing environment. In terms of the factors that catalyse policy learning
and explain why policy learning occurs in the first place, two sets of factors
can be identified: a) factors at the individual level, which include looking
for solutions to policy problems, controlling uncertainty, achieving indi-
vidual and collective goals and searching for the truth; b) structural fac-
tors, which include time-related factors that stimulate policy learning (an
election period, economic crisis, regime transformation, a period of lack of
success, a period of uncertainty), political culture, the institutional struc-
ture of a country, special characteristics of public policy and organisation-
al competence (e.g. Bennet & Howlett, 1992).
The motives for policy learning in the form of policy experimentation
for dealing with ESL within the TITA project can be explained by the great
complexity of the ESL policy problem and the consequences it holds for in-
dividuals, nation states and EU society as a whole, along with the already
established infrastructure for multi-professional cooperation in participat-
ing countries (France, Luxembourg, Switzerland). Experiences of the lead-
ing partner (France) with social experimentations in the ESL field clear-
ly also represent an important factor explaining the EU’s interest in policy
learning in the TITA setting.
126
