31 July 2009

Global Education Digest 2009

Cover of "The State of the World's Children 2009"The UNESCO Institute for Statistics (UIS) has published the 2009 edition of its annual Global Education Digest. The GED presents the latest statistics on pre-primary, primary, secondary and tertiary education, education finance, literacy and educational attainment. The statistical tables contain data for more than 200 countries and territories. In addition to national data, the tables offer global values and regional values for the Arab States, Central and Eastern Europe, Central Asia, East Asia and the Pacific, Latin America and the Caribbean, North America and Western Europe, South and West Asia, and Sub-Saharan Africa.

The analytical chapter that precedes the statistical tables is dedicated to a different topic every year. The analytical chapter in the GED 2009 explores global trends in higher education, including levels of participation, fields of study, student mobility, and tertiary education finance. The tables with time series data from 1970 to 2005 that were introduced in the previous GED are limited to data on tertiary education this year. The GED 2008 also contained time series tables on primary and secondary education.

The data from the GED are available free of charge at the UIS Data Centre. To access the statistical tables, click on "Predefined Tables" and then "Education". For most indicators, the GED only lists data for one or two years, whereas the Data Centre provides annual statistics from 1999 to 2008. The Data Centre also offers time series data for selected primary, secondary and tertiary education indicators from 1970 to 2005.

References
  • UNESCO Institute for Statistics (UIS). 2009. Global education digest 2009: Comparing education statistics across the world. Montreal: UIS. (Download PDF, 7.0 MB)
  • UNESCO Institute for Statistics (UIS). 2008. Global education digest 2008: Comparing education statistics across the world. Montreal: UIS. (Download PDF, 6.3 MB)
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Friedrich Huebler, 31 July 2009 (edited 19 September 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/07/ged.html

09 May 2009

Achievement gap between black and white students in the United States

Two previous articles on this site presented data on disparities in school attendance by ethnicity, language or religion from 17 nationally representative household surveys. Net attendance rates among the least disadvantaged groups are up to 1.7 times higher than net attendance rates among the most disadvantaged groups at the primary level of education and up to 6 times higher at the secondary level of education.

Similar gaps in access to education and in student achievement exist in the United States. The National Center for Education Statistics has published the most recent findings of its National Assessment of Educational Progress, a long term study of student achievement, in the report NAEP 2008 Trends in Academic Progress. The results of the periodic assessments by the NCES demonstrate a persistent achievement gap between black and white students.

Figure 1 summarizes the results of 12 reading assessments over the period 1971 to 2008. For each assessment, the average reading scores of black and white students aged 9, 13 and 17 years are plotted in the graph. The shaded area indicates the achievement gap between black and white students. For 2004, two scores are shown for each group because the assessment format was revised in that year. The reading scores in 1971 and 2008 are also listed in Table 1.

Figure 1: Average reading scores of black and white students, 1971-2008
Trendlines with reading scores of black and white students in the United States between 1971 and 2008
Data source: NAEP 2008 Trends in Academic Progress, p. 14-15.

Black and white students of all ages achieved higher reading scores in 2008 than in previous years. In 1971, 9-year-old white students had an average score of 214 and black students in the same age group scored 170 on average. In 2008, the average score of 9-year-olds was 228 for white students and 204 for black students. As a result, the score gap between black and white 9-year-olds fell from 44 in 1971 to 24 in 2008. For 13-year-old students the score gap fell from 39 to 21 over the same period and for 17-year-olds it fell from 52 to 29.

Closer inspection of the data reveals that most of this reduction in the achievement gap occurred during the 1970s and 1980s. Since the 1990s, the gap between black and white students has remained relatively stable. Although the reading scores of black students continue to improve, they no longer grow fast enough to close the gap with white students.

Table 1: Average reading scores of black and white students, 1971 and 2008
Year Age Average reading score Score gap
Black White
1971 9 years 170 214 44
2008 9 years 204 228 24
1971 13 years 222 261 39
2008 13 years 247 268 21
1971 17 years 239 291 52
2008 17 years 266 295 29
Data source: NAEP 2008 Trends in Academic Progress, p. 14-15.

The NAEP report shows a similar achievement gap between black and white students in the area of mathematics. In addition, there is a similar but smaller gap between white and Hispanic students in reading and mathematics. In spite of long-running efforts to improve the education system for all parts of the population, minority students consistently lag behind white students in the United States.

Reference
  • Rampey, Bobby D., Gloria S. Dion, and Patricia L. Donahue. 2009. NAEP 2008 Trends in Academic Progress. Washington: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. (Download PDF file, 1.1 MB)
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Friedrich Huebler, 9 May 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/05/usa.html

05 April 2009

New version of programs to integrate Stata and external text editors

Version 3.1 of the rundo and rundolines programs to integrate Stata and external text editors has been released. The new version corrects a bug in version 3 of the rundo program, which had pointed to the wrong INI file. As a result of this bug, changed settings in rundo.ini had no effect on the execution of the program. Version 3.1 also updates the code of the rundo and rundolines programs to version 10.1 of Stata. Older versions of Stata are still supported.

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Friedrich Huebler, 5 April 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/04/stata.html

15 March 2009

Disparities in secondary school attendance by ethnicity, language or religion

Members of ethnic, linguistic or religious minorities face barriers to access to education in many countries. In an article on primary school attendance by ethnicity, language or religion the presence of such disparities was demonstrated with data from Multiple Indicator Cluster Surveys. The MICS are nationally representative household surveys supported by UNICEF that collect data on school attendance and other household member characteristics. In the most recent round of MICS surveys, carried out in 2005 and 2006, 17 countries collected data on school attendance by ethnicity, language or religion: Albania, Belize, Gambia, Georgia, Guinea-Bissau, Guyana, Kazakhstan, Kyrgyzstan, Lao PDR, Macedonia, Montenegro, Serbia, Sierra Leone, Thailand, Togo, Uzbekistan, and Viet Nam.

The school attendance data from the MICS surveys can be used to generate an education parity index that measures relative disparity across different groups of disaggregation, as described in the article on primary school attendance. To calculate the index, the attendance rate of the group with the lowest value is divided by the attendance rate of the group with the highest value. The result is a value between 0 and 1, where 1 means that children from different ethnic, linguistic or religious groups have the same secondary school attendance rate. Values closer to 0 indicate increasing disparity.

As an example, Thailand collected data on school attendance that can be linked to the mother tongue of the household head. The secondary school net attendance rates (NAR) for two groups of children identified in the 2005-06 MICS data are shown in Table 1.

Table 1: Secondary school attendance in Thailand
Mother tongue of household head
Secondary NAR (%)
Thai 81.2
Other language 65.8
Total 79.8
Data source: MICS 2005-06.

Among children from households whose head speaks Thai, the secondary NAR is 81.2 percent. Among children from households headed by someone with a different mother tongue, the secondary NAR is 65.8 percent. The secondary school parity index for Thailand is then calculated as follows.

Secondary school parity index = Lowest secondary NAR / Highest secondary NAR

= Secondary NAR of speakers of another language /
   Secondary NAR of speakers of Thai

= 65.8 / 81.2

= 0.81

The parity index is a relative, not an absolute measure of disparity. The value 0.81 means that the secondary NAR of speakers of another language is, relatively speaking, 19 percent below the secondary NAR of Thai speakers. The absolute gap between children from the two groups is 15.4 percent, the difference between 81.2 and 65.8.

The secondary school parity index for all 17 countries with data is shown in Figure 1. The index ranges from a high of 0.98 in Viet Nam to a low of 0.17 in Serbia. The low value for Serbia is explained by extremely low secondary school attendance among the Roma ethnic group. The secondary school NAR for Roma children is 14.8 percent, compared to 85.9 percent for Serbians and 88.6 percent for children from other ethnic groups. In addition to Serbia, six other countries have index values at or below 0.5: Lao PDR, Macedonia, Guinea-Bissau, Togo, Belize, and Montenegro. In these countries, children from the most advantaged ethnic, linguistic or religious group have secondary school net attendance rates that are at least twice as high as the attendance rates of children from the most disadvantaged group. In Viet Nam, Kazakhstan, Albania, and Uzbekistan, on the other hand, disparities in access to secondary education are relatively small.

Figure 1: Secondary school parity index: School attendance by ethnicity, language or religion
Bar graph showing secondary school parity index in 17 countries
Data source: MICS 2005-2006.

The attendance rates used to calculate the secondary school parity index are summarized in Table 2. The table also shows whether the national agencies that implemented a survey chose ethnicity, language or religion to identify minorities. A comparison with data on primary school attendance makes clear that disparities at the secondary level of education are much larger than disparities at the primary level, where the parity index for the same group of countries has a range from 0.59 to 0.99.

Table 2: Disparities in secondary school attendance by ethnicity, language or religion
Country Year Characteristic Primary NAR (%) Parity index
Min. Max.
Albania 2005 Religion 77.1 83.7 0.92
Belize 2006 Language 36.9 79.2 0.47
Gambia 2006 Ethnicity 27.5
48.2 0.57
Georgia 2005 Ethnicity 69.0
90.6 0.76
Guinea-Bissau 2006 Language 4.3
13.8 0.31
Guyana 2006 Ethnicity 56.0
81.1 0.69
Kazakhstan 2006 Language 90.8
96.0 0.95
Kyrgyzstan 2006 Language 79.3
92.4 0.86
Lao PDR 2006 Language 10.0
45.6 0.22
Macedonia 2005 Ethnicity 17.4
73.7 0.24
Montenegro 2005 Ethnicity 46.5
92.9 0.50
Serbia 2005 Ethnicity 14.8 88.6 0.17
Sierra Leone 2005 Religion 17.8 24.4 0.73
Thailand 2005-06 Language 65.8
81.2 0.81
Togo 2006 Ethnicity 22.9
53.1 0.43
Uzbekistan 2006 Language 87.1
95.4 0.91
Viet Nam
2006 Ethnicity 93.8
95.7 0.98
Data source: MICS 2005-2006.

Data source
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Friedrich Huebler, 15 March 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/03/elr2.html