NESIS Regional Centre, UNESCO Harare - Zimbabwe

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Presentation transcript:

NESIS Regional Centre, UNESCO Harare - Zimbabwe From Theory, Data Analysis to Causal Inference National Education Statistical Information Systems Systèmes d’Informations Statistiques sur l’Education In this presentation, I will explain the strategy, structures and processes of development of capacity of National Education Statistical Information Systems”in Sub-Saharan Africa. Its objective is the development of sustainable institutional capacity to provide policy-relevant statistical services in Africa. As the World Bank representative said, it is an area characterised by ”30 years of failure”, an area where no single agency has been able to solve. With Sweden as the lead agency, the Working Group on Education Statistics was formed within the ADEA and, with UNESCO as the host agency, NESIS was initiated as a pilot project with three pilot countries, Ethiopia, Zambia and Zimbabwe. The initial NESIS core team consisted of only two persons. Since then, NESIS has grown into a region-wide programme, direcly supported by 11 agencies and over 40 participating African countries. In the meantime, UNESCO Division of Statistics has been replaced by the new UIS and the NESIS strategy has become an important part of its capacity-building component of its programme. NESIS Regional Centre, UNESCO Harare - Zimbabwe www.unesco.org/nesis 19 November 2001

The Objective: Set your own learning goals Beginners: no statistics & no policy analysis eye-opener, awareness of the the two fields Intermediate: only statistics or policy analysis Learn to relate statistics and policy analysis Advanced: both statistics and policy analysis Apply policy framework to statistics Apply tools of statistics to policy analysis

Expected outputs Focus on policy issue area Draft possible explanatory models Data matrix design Design analysis scheme Descriptive statistics on selected variables Data transformation, index construction Evaluation of validity and reliability Relational data analysis Evaluation of the explanatory models Interpretation of the results with reference to the policy issue(s)

Set your own expected results Data Beginner Intermediate Advanced Own Getting acquainted with methods and tools in analysing own data Starting knowledge & tools to take-off for continued learning through doing it. Beginning of a policy study for further elaboration Demo Getting acquainted with methods and tools of analysis Ideas & examples to be applied for a policy study

Geometry = Trigonometry = Psychometrics = Economics = Statistics = ? Introduction Geometry = Trigonometry = Psychometrics = Economics = Statistics = ?

Statistics: accounting/ measurements of the State Land ownership Population Production Taxes Conscriptions Welfare state: distribution of Housing Education Health Etc.

Capacity for policy formulation and management Administration Decision Mobilization Evaluation Implementation Capacity building must aim at the central functions of the policy cycle. The leaderships’ ability to make informed decisions and issue sensible directives. The management’s ability to make optimal usage of available resources for implementation. Education is a service industry, in which the main clients are the learners. One must think in terms of customer service. All functions must ultimately serve customer satisfaction in terms of fulfilling the customers’ learning needs. Ultimately, the rationale for capacity building is to make a positive impact on the teaching-learning process. Explain the right and left side control mechanisms in terms of efficiency and effectiveness with regard to impact. Monitoring TL Impact Efficiency Effectiveness

Policy cycle Formulation – defining goals, identifying target groups and setting targets Decision – “authoritative allocation of values” Mobilization – resources delivered to system development Implementation – systems development benchmark indicators Monitoring – systems performance benchmark indicators Assessment – systems outputs and outcomes impact Informed, intelligent policy requires information on distribution, trends, contrasts and progress benchmark indicators with regard to policy target groups and targets. Formulation – Policy formulation involves defining goals, identifying target groups and setting targets It seeks to answer “Who wants or needs what, when and how? From who to whom, when and how?” These questions may be answered by individual favour-seekers or by other forms of conflict resolution. Scientific surveys of voter preferences, household living standards, labour market, health and nutrition, educational attainment and consumer preferences are examples of common approach in democratic and transparent societies. Decision – Government decisions are said to be “authoritative allocation of values”, For example, the government may declare its intention to provide learning opportunities to the target groups or pass a legislation Mobilization – Some government decisions are followed by mobilisation of resources. How much was actually delivered to system development works? Implementation – systems development benchmark indicators What system parts (eg. Schools for the rural poor) are implemented and what parts are not implemented (eg. Teachers for the rural poor)? Monitoring – systems performance benchmark indicators What system parts are functioning optimally, effectively, efficiently? Assessment – systems outputs and outcomes impact What target groups got what, how much, when and how?

Analytic capacity-building The role of data analysis in policy analysis