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UIS Data gathering mechanisms

UIS Data gathering mechanisms. Said Voffal Kampala, 6 May 2008. Outline. Surveys on education and timetable What are the major issues facing data quality? UIS data processing Work with countries: essential issue to improve data quality

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UIS Data gathering mechanisms

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  1. UISData gathering mechanisms Said VoffalKampala, 6 May 2008

  2. Outline • Surveys on education and timetable • What are the major issues facing data quality? • UIS data processing • Work with countries: essential issue to improve data quality • Sources of the discrepancies between national and international data

  3. How does UIS collect the education data? UIS compiles data from the Ministries of Education (or sometimes the national statistical offices) show the questionnaire. Survey on statistics of education OECD EUROSTAT

  4. How does UIS collect literacy data? • UIS Survey on Literacy Statistics completed by national statistical offices • Three potential sources a the national level: 1. National population and housing censues 2. National sample surveys 3. International sample surveys such as UNICEF’s Multiple Indicator Cluster Surveys (MICS)

  5. Data Timeliness :improvements • UIS publishes international education data for a given school year between 15-20 months after the end of that school. • Data for the school year ending in 2006 published in March 2008 • UIS is implemented a rolling data release: Data for each will be disseminated as soon as they are ready

  6. How does UIS ensure comparability? • ISCED to classify programmes • Ensuring that the entire country, all educational institutions and groups are included in the data • Population estimates from the United Nations Population Division • GDP and GNP estimates from the World Bank

  7. Quick overview of UIS procedures related to the data processing

  8. Cleaning process • Review of data • Determining/footnoting the coverage of the questionnaire • Adjusting for ISCED • Revision of error reports and correction of mistakes • Feedback to country statisticians

  9. Cleaning process (cont’d) • Comparison of data to available time series and other sources of data (for example national publications, household surveys) • Revision of resulting indicators by UIS and countries The cleaning process ends with the estimation of missing data (only if necessary)…

  10. Why do we estimate data? • To have a COMPLETE set of data both in terms of the intended coverage of the questionnaire and the data item concerned • To have COMPARABLE data across all countries • To avoid too many footnotes • To produce regional and global indicators

  11. How do we estimate? • Encourage country to make an estimate (best position) • All publishable estimates are always based on reported data (for the previous years) • Standardized procedures to produce the estimates

  12. Validity and reliability: Countries and agencies review • Countries received a personalized data and indicators report: • Formula of calculating indicators included • Identify and resolve problems • Respond to our queries • Receive comments on our estimates • Inform the results before publishing • Data are also sent to international agencies (World Bank, UNSD, UNDP, Pole de Dakar)

  13. Calendar of data dissemination for SURVEY 2007 Not for publication For revision and comments Countries Preliminary November 2007 For publication: WB-WDI Incomplete: No WEI/OECD Provisional December 2008 More complete GED 2008, website and agencies (example: MDG) Revised March 2008 Most complete data Final web release including all revisions and updates Final Sept/Oct 2008

  14. Sources of discrepancies between national and international indicators • Indicator 2.1: Total net primary enrolment ratio: Two main issues: • Different definition of primary education at national and international level (like in Ethiopia, Kenya and Malawi) • Difference in coverage: Both under and over coverage (private education, geographic coverage)

  15. Indicator 2.1: use of different definition • Some countries may use different methodology than the one used internationally to calculate the indicator. • Children of the primary age but enrolled in lower secondary education should be included as well

  16. Demographic data used to calculate indicator 2.1 • Nationnally: national estimates • Internationnally: UN Population Division estimate • Experience shows that there might be a very significant difference between the two sources

  17. Indicator 2.2: Survival to primary last grade Sources of discrepancy (same as indicator 21.): • Different definition of primary education at national and international level (like in Ethiopia, Kenya and Malawi) 2. Difference in coverage: Both under and over coverage (private education, adult education, geographic coverage)

  18. Indicator 2.2: calculation method • Internationally: the reconstructed cohort method based flow rates (repetition, drop out, promotion) • Nationally: should be the same . UNESCO has an Excel based template which countries can use

  19. Indicator 2.3: literacy rate of 15-24 years old No discrepancy is expected between national and international data as both refers to the same statistics. • Any difference between data published at national and international is only be due to use of data from a different survey.

  20. Data Dissemination • Global Education Digest: flagship UIS publication on Education • CD-ROM: complete series for most of the data and indicators produced by the UIS • WEB site: http://www.uis.unesco.org • Data requests • International organizations, agencies, NGOs, universities, researchers, media. • Other thematic reports • Out-of-School Children • Teachers and Educational Quality: Monitoring Global Needs for 2015 • Working papers

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