CHER 2011 University of Iceland Reykjavík Iceland June 24 th -26 th

CHER 2011University of Iceland Reykjavík

Iceland June 24th-26th

Is there an invariance in educational expansion?Jón Torfi Jónasson

[email protected] http://www.hi.is/~jtj/

School of Education, University of Iceland

mailto:[email protected]

http://www.hi.is/~jtj/

Jón Torfi Jónasson - CHER 2011 Iceland 2

Schofer, E., & Meyer, J. W. (2005). The Worldwide Expansion of Higher Education in the Twentieth Century. American Sociological Review 70, 898-920.

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Based on Fig. 1 in Schofer and Meyer 2005The growth of the world tertiary student population relative to

population

The preamble

• Growth of education• Credentialism• The question of robustness, invariance

• The dependent variables– Registration at a certain level of education– Degrees awarded– Students entering the education– Controlling for population changes; cohort corrections

• The independent variables– Cultures– Gender– Age– Social groups


The story of the analysis

• The growth of education in Iceland, both university entrance examination and university enrolment

• Comparison with the other Nordic countries for upper secondary educationJón Torfi Jónasson. (2003). Does the state expand schooling? A a study based on five Nordic countries. Comparative Education Review, 47(2), 160-183.

• Green, Thomas F., David P. Ericson, and Robert Seidman. Predicting the behavior of the Educational System: Syracuse University Press, 1980, showed that growth of high school education in the US is predicable; can be shown to be essentially exponential (JTJ).

• An example of the Icelandic situation


Jón Torfi Jónasson - CHER 2011 Iceland

Higher education: enrolment in Iceland 1911-1970

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All Icelandic university students in Iceland and abroad as % of average of 20-24 yr cohorts

Exponential trend. All Icelandic university students in Iceland and abroad as % of average of 20-24 yr cohorts based on the years 1911-1970



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Higher education: enrolment in Iceland 1911-1970-2010

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Source: Statistics Iceland

But what about “very different” systems?

• Consider the HE systems in the US and Japan as examples.

• First the US then Japan. • The method.

1. Consider the enrolment in HE in the growth period after the second war, which is often considered to show growth attached to optimism and belief in education. Many writers refer to the explosion in educational attendance during this period.2. Consider what would be predicted on the basis of prior developments i.e. for the first part of the 20th century using the exponential fit.3. Consider then what would be predicted for the rest of the 20th century.



Higher education: enrolment in the US 1900-2008

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Growth rates in US higher education 1900-2008. The explosive growth rates after World War II in perspective

Males and females corrected for cohort 1940-1970



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Growth rates in US higher education 1900-2008. Actual growth compared to the 1900-1939 exponential and logistic predictions


USA 1900-1939 Males and females exponential prediction

USA 1900-1939 Males and females. S-logistic Limit 700

Expon. (Males and females corrected for cohort 1900-1939)



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Higher education: enrolment in Japan 1900-2004

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Growth rates in Japanese higher education 1900-2004. Actual growth compared to the 1900-1939 exponential and logistic predictions




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Japan 1900-1939 Males and females. S-logistic Limit 700



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USA Males corrected for cohort 1900-2008

USA Females corrected for cohort 1900-2008

Gender, degrees and age, first some data from Iceland

• The period 1997-2009; ISCED 5, graduations from university• Based on data from Statistics Iceland

• First age and gender



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Iceland: Graduation rates of diffeerent age groups, corrected for cohort size

Females 25-29 years

Females 22-24 years

Males 25-29 years

Females 30-34 years

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Females 35-39 years

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Ave

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age groups, corrected for cohort size, 1997-2009

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The Swedish case; Gender, degrees and age:

• Three graphs

– 1. The basics: The fit of the exponent, an example for 25 year old males and females graduating from 3-3,5 year degree courses

– 2. The fit of the exponent, for ages between 24 and 39 males and females graduating from 3-3,5 year degree courses

– 3. The same as previous but now with the fit of the exponents for males and females graduating from 3-3,5 year degree courses and 4-4,5 degree courses

Based on data graciously provided by Statistics Sweden in May and June 2011.



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The proportion of the 25 year old cohort graduating with a 3-3,5 year degree during 1978-2010, shown separately for males and females

3 - 3,5 år män 25 år

3 - 3,5 år kvinnor 25 år

Expon. (3 - 3,5 år män 25 år)

Expon. (3 - 3,5 år kvinnor 25 år)


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Sweden: Growth exponents for graduation at different ages corrected for cohort size for the period 1978-2010

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3 - 3,5 years Males


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Sweden: Growth exponents for graduation at different ages corrected for cohort size for the period 1978-2010


4 - 4,5 years Males


3 - 3,5 years Males

Different social groups

• Consider the three groups in the US, the hispanics, the blacks and the white.

– Note the growth rate for each– Note the gender differences– Note the similarities between the groups, in terms of

• Gender growth rates• and the differences between the gender



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Percentage of 25- to 29-year-olds who completed a bachelor’s degree or higher, by race/ethnicity and sex: 1971–2009

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Percentage of 25- to 29-year-olds who completed a bachelor’s degree or higher, by race/ethnicity and sex: 1971–2009

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Completions. 25-29 year olds. Growth rates US 1971-2009(0,02 indicates approx 2% growth) White

male female Ratio female/male

Completed some college 0,009 0,021 2,3Completed bachelor degree or higher 0,007 0,023 3,3

Blackmale female Ratio

female/maleCompleted some college 0,020 0,026 1,3Completed bachelor degree or higher 0,017 0,023 1,3

Hispanicmale female Ratio

female/maleCompleted some college 0,008 0,027 3,6Completed bachelor degree or higher 0,005 0,029 5,8

Conclusions

We find • similar, robustness• similar long-term trends• similar gender similarites• similar gender differences

• across cultures• social groups• age groups


Conclusions

In order to understand the mechanisms of growth• we should look at the gender effects• but especially the age effects• and the effects and trends within different degrees

• e.g. low growth rates for certain ages for males may only tell a very small part of the story

• we suggest that essentially the same patterns are pretty universal and thus there is some important invariance over cultures and social groups

• we can expect massive growth over the next decades very much as hitherto



The growth of the world tertiary student population relative to total population in the 20th century: number of

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The predicted growth of the world tertiary student population relative to total population: number of students

per million inhabitants

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World population 20096.790 million

Growth of 4% 5%HE students 2000 100 100 million

2010 150 163 million2020 220 265 million2030 324 432 million2040 480 704 million2050 710 1146 million

Thank you

Kærar þakkir


Documents

CHER 2011 University of Iceland Reykjavík Iceland June 24 th -26 th