Martina Vukasovic, research fellow, University of Oslo Equity and quality in transitions in education: Evidence (gaps) and some inputs for policy development.

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Presentation transcript:

Martina Vukasovic, research fellow, University of Oslo Equity and quality in transitions in education: Evidence (gaps) and some inputs for policy development 6-7 December 2011, Belgrade

Outline Transitions in education –What is meant by them? –Why are they important? –How can they affect equity and quality? Some data about education transitions in Serbia Policy inputs

Transitions in education (1) Any shift from one level of education to another –Between different levels: e.g. from primary to secondary education –Between different years e.g. from first to second year of studies Transitions marked by two processes –Assessment –Selection Impact of transitions on equity and quality depends on the nature of assessment and consequences of selection (e.g. tracking)

Transitions in education (2) Assessment may seem neutral at the first glance so why should it affect equity? –From early age students from lower SEB score less on various assessment tests (grades in school, entrance exams for secondary or higher education etc) –Tests can be biased in various ways (e.g. in favour of majority mother tongue) Some animals are more equal than others –Although seems neutral and (completely) meritocratic in essence disregards starting inequalities –Some groups experience multiple disadvantage Importance of economic, cultural and social capital

Transitions in education (3) Selection – in essence two processes: –“System” choosing the students –Parents and/or students choosing their education Increasing quality vs. decreasing equity? –“System” wants to pair students and schools in the best way possible (e.g. “best and brightest in best schools”) –Parents and/or students want to maximise their returns

Example: transition from SE to HE (1) Criteria: –grades from secondary education –entrance exam scores Purpose of entrance exams to create a level playing field? Possible sources of problems with equity: –grades correlated with SEB Disadvantage accumulated through previous stages of education –special entrance exam preparation courses Available to those with ability to pay and attend

Example: transition from SE to HE (2) Possible consequences for equity –Students with lower SEB can not access HE or access less prestigious HE institutions or fields –Students with lower SEB can not get into the state funded quota

Some data (1) Transition from PE to SE – combining PISA and TIMSS (see Babin, Pantic, Vukasovic 2009) Type of secondary school correlated with education of parents –64.4% of students in 3 year SE has education of parents at ISCED < 3; compared to 4.4% of students in 4 year academic SE (gimnazija) –51.9% of students in 4 year academic SE has education of parents at ISCED 5A or 5B; compared to 12.1% of students in 3 year SE

Some data (2) Grades in PE, SE entrance exams scores, as well as PISA test scores correlated with education of parents (Spearman’s rho) VI gradeVII grade VIII grade E. exam math E. exam lang. PISA math PISA reading Education of parents

Some data (3) Transition from SE to HE (see Vukasovic 2007) –Students with better educated parents tend to end up in academic HEI –Students with better educated parents tend to end up in the state funded quota Progress through HE (see Vukasovic 2007) –Those with better educated parents overrepresented in higher years of higher education

Some data (4)

Some data (5) Estimated that 45% of students drop out (pre Bologna) Indications that some students do not complete the HE initially chosen –Average age at enrolment for total student population approx. 1 year lower then average age at enrolment for graduates (in the programme they graduated from)

Data problems Incomplete data bases for different stages of education –Sometimes data categories no longer relevant Not possible to combine data even within one stage of education –E.g. SV20 (enrolment into HE) and SV50 (graduation from HE) do not match in terms data collected or in terms of time covered No automatic linkages between data bases

Some policy inputs Sort out data! Strengthen the cross-sectoral linkages in terms of development of policy Adequate attention to all policy instruments (e.g. financing regulation and legislation often clash)