UIS light DQAF for administrative data and other UIS CD tools

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UIS light DQAF for administrative data and other UIS CD Marc Bernal, UIS Regional Advisor for SSA 3 rd SDG 4 TCG meeting Montréal, 1 st June 2017

Summary content Light DQAF DQA CapED UIS CD UIS Light DQAF for administrative data Rational Characteristics UIS DQA for the CapED program (capacities assets and needs) Data mapping Admin data (Light DQAF) Household Surveys Learning assessments Finance data UIS Capacity Development Tools Across the full CD cycle 2

Institutional environment Prerequisites of quality Integrity UIS Light DQAF for administrative data: Rational procedures Methodological soundness Accuracy and reliability results Serviceability Accessibility A DQAF is a tool to assess the context in which data are produced Verifies how data are produced against fundamental principals of official statistics and internationally accepted standards Based on UIS DQAF long experience Initially developed by IMF for economic data Adapted to education data by UIS and World Bank Series of improvements Contextualisation to a country-led assessment process Part of the UIS Capacity development approach Training Learning by doing Strengthening country ownership 3 One only data source type Administrative data (classically coming from school registries)

One only data source type: administrative data from school registries 4

Institutional environment Policy and legal framework Adequacy of resources Relevance 5 UIS Light DQAF for administrative data: Characteristics processes Sound Methodology Accuracy and reliability outputs Periodicity and timeliness Consistency Accessibility and clarity Restructuring Same basic framework hierarchy (Dimensions, Subdimensions, items) scoring 3 pillars (according to Fund principles & CoP) Streamlined Eliminate duplicates (merge similar concepts e.g.: Basis for recording and Archiving of source data) from 140 to 45 items Non ambiguous evidence led (Kept only items which can clearly be assessed upon evidence) Provide scoring guidance to reduce subjective scoring Extract data gaps outside the framework (data mapping tool / scope) Additional to assess the consistency of available data (among data sets, data sources and historical series) Part of a tool kit Within the DQAF itself (user manual, scoring guidance, interview guides, resources inventory, consistency check ) Within the SDG 4 context - Developed in the context of the CapED project (national indicator framework, data mapping, other data sources DQA)

Institutional environment Policy and legal framework Adequacy of resources Relevance 6 The CapED DQA tool kit processes Sound Methodology Accuracy and reliability outputs Periodicity and timeliness Consistency Accessibility and clarity SDG4 indicators framing tool Helps countries analyse their ESP in light of SDG4 Identify gaps and make recommendations for alignment Identify existing and potential indicators Data mapping / data source mapping Helps identifying data gaps, possible improvement in planned data collection and suggestions for new data collections exercises DQA existing data source School administrative data Learning assessments (GAML): Assessment of Data Quality Processes (ADQP) Household surveys Finance data Institutional environment Relevance processes Sound Methodology outputs Periodicity and timeliness Accessibility and clarity

UIS Capacity Development Experience Based on field and HQ teams experience Capacity Building (SCB) program Under EU funding CB for EFA 11 countries Posting regional and cluster advisors in UNESCO Offices Up to 18 staff in Arab states, SSA, LAC, Asia Continued projects under UNESCO Offices management, UIS scientific orientations and oversight, funding by partners / countries Pacific Capacity Building Project Under DFAT funding 6 countries DQAF + action plans for fund mobilization Web-based lighter DQAF for other countries 7

UIS Capacity Development Approach Step 1: Engage Stakeholder on Capacity Development Institutionalization of processes; CD governing principles: National Ownership, Separation between decision making and implementation (Fundamental Principle of Master plan), Coordination of partners and with existing initiatives Step 2: Assess Capacity Assets and Needs Policy review and indicators needs; Data mapping and Data quality assessments Step 3: Formulate a capacity development response Produce recommendations from assessments; Develop national CD strategy UNDP CD five-step process cycle Step 4: implement a CD response Institutional; Organizational; Technical; Individual capacities needs response Step 5: Evaluate capacity development 8

UIS Capacity Development Tools Step 1: Engage Stakeholder on Capacity Development Education data platform (TOR, inter-ministerial note) Integration in NSDS Step 2 : Assess Capacity Assets and Needs Indicators framing tool Data mapping tool DQA for admin data, HHS, Finance data Assessment of Data Quality Processes (ADQP) for learning assessments Step 3 : Formulate a capacity development response Guidelines for developing a NSDES Draft NSDES structure 9

UIS Capacity Development Tools (Cont.) Step 4: implement a CD response Institutional: Examples / good practices: EMIS Policy, acts Organizational: Technical: Individual : EMIS life cycle management and quality assurance Software development Data collection form design Database modelling and system design Data quality control reports design and production Support to international reporting Education finance data analysis and National Education Accounts Comparing and combining administrative data and other data sources 10 Step 5 : Evaluation RBM imbedded in NSDES Role of the education data platform

UIS light DQAF for administrative data and other UIS CD Marc Bernal, UIS Regional Advisor for SSA m.bernal@unesco.org Learn more: http://uis.openplus.ca/gaml/ Thank you!