How can strengthening national education systems improve enrollment rates?

Education system strength – How can the governments invest in improving national higher education systems to achieve higher enrolment rates?

By Andreas Chrysanthou

Stimulating the national higher education system and understanding the implications of relevant policies and investment is crucial for national governments to improve the overall enrolment rates of local and international students. The QS Higher Education System Strength Rankings compares national performance in four categories: System strength, access to higher education, flagship performance and economic context. While educational policies focus mostly on highlighting a country’s flagship institution and improving overall rankings (system strength), access of the local population to higher education institutions[1] and sufficient financial support (economic context)[2] could be equally important in achieving higher enrolment rates. Given an equal weight for each of the abovementioned categories, the average education system score per EU country can be estimated:

As it can be observed in the above figure, North-Western EU countries score above the EU average (UK, Germany, France, Netherlands), while South-Eastern regions score far below the average (Estonia, Ukraine, Poland, Greece). But what makes several EU regions suffer from low education system strength and how can it be improved? Our research attempts to analyse two possible relationships between national statistics and education system scores[3]:

 

  1. The effect of national poverty rates on the access to higher education.
  2. The effect of the total number of universities within a country on economic context

 

The following figure examines the effect between the abovementioned interrelated variables including national poverty rates[4] and university access scores:

The particularly low access scores for several countries including Ukraine, Estonia, Russia, Greece and Poland can be partially explained by the high poverty of the abovementioned countries; because of the negative relationship between the two variables. On the contrary, the best performing countries such as UK, Germany, France and Netherlands entail some of the lowest poverty rates in the EU, while Spain and Italy have an outstanding performance with respect to access scores despite the higher-than-average poverty rates. Lastly, despite the lower poverty rates of Portugal, the country continues to perform below the EU average concerning access to education.

A second cause for the inequality between national education system scores within the EU can be examined between the number of higher education institutions and the economic context scores, since a higher number of institutions might further divide the government’s financial support amongst the universities. The following figure examines the abovementioned effects between the two variables:

Surprisingly, the number of universities within a country has a positive effect on the economic context score of its national universities. It is expected that higher government funding could result in establishing more universities, however it would be more difficult for the government to financially sustain a higher number of HEIs: UK, Germany, France and Russia, with many higher education institutions receive a higher financial support per institution from the government, while Estonia, Norway, Czech Republic, Greece and Austria, with much less universities receive less governmental funding per institution. It would be important no to forget that such countries have limited funding to support their universities. The Netherlands, Spain and Italy also receive sufficient financial support while the number of universities remains below the EU average, while Ukraine and Poland score much lower on the economic context while having a higher-than-average number of universities.

 

So far, we have identified that poverty rates and the total number of higher education institutions within a country are some of the causes for the large gap between South-Western and North-Eastern EU countries with respect to higher education system scores. Therefore, one question remains – Which are the target areas of improvement in national education systems for governments to achieve an increase in FTE student enrolments and attract more international students?

 

Based on Statistics

A statistical analysis including 116 EU universities within 21 countries is performed in 2 OLS regression models[i] to examine the effects of the education system strength variables on the number of FTE students and the number of internationals per institution. The following results highlight the main variables affecting the number of FTE enrolments (model 1) and international students (model 2):

Model 1: Variables affecting the number of FTE students per university

  • Improving the System Score (Rankings) by 1%, increases the numbers of FTE students per institution by 1.84%.
  • The effect of improving access scores is stronger as poverty rates increase. In fact, improving access at the highest ranked universities within a country will decrease FTE students per institution by 8% (due to higher concentration of students in the best performing universities). However, the effect becomes positive for poverty rates higher than 14.25%, and continues to increase by 1.147% per 1% increase in poverty rates.
  • The effect of improving economic context scores is stronger as the number of universities increase. More specifically, improving the economic performance of the highest ranked universities within a country by 1% decreases FTE students per institution by 3.7% (due to higher concentration of students in the best performing universities). However, the effect is positive if the number of HEIs within the country is more than 270 (close to the EU average); and keeps increasing slightly (0.000098%) per additional university. Additionally, the effect of improving the economic performance increases as rankings increase.
  • Flagship scores have an insignificant effect on the numbers of FTE students.

Model 2: Variables affecting the number of International students per university

  • Improving the access score by 1% increases the numbers of international students per institution by 4.6%.
  • Improving the system score (Rankings) by 1% increases the numbers of international students per institution by 1.5%.
  • improving the economic performance of the highest ranked universities within a country by 1% decreases international students per institution by 2.8%.
  • Flagship scores have an insignificant effect on the numbers of international students.

So…Where to invest?

Overall, it can be concluded that the idea of promoting a “flagship” institution does not improve enrolment rates overall, while more focus should be given on improving access in countries with high poverty rates, while improving the rankings of local institutions.

Lastly, it can be assumed that government investment in higher education brings positive results only when the supply of higher education is sufficient (as indicated by the number of HEIs per country); otherwise it might result in a higher concentration of students in highly ranked

[1] Indicated by the number of places available within the top 500 ranked universities, divided by the square root of a country’s population.

[2] Indicated by the national overall rankings score, factored against the national GDP per capita for the country in question.

[3] Weighted average of access, economic, flagship and system scores: https://www.topuniversities.com/system-strength-rankings/methodology

[4] Indicated by the ratio of the population which receives income below the poverty line; taken as half of the median household income of the total population.

[i] Explanatory variables included: QS World rankings 2018, Citations per faculty, academic reputation, total & international university staff, education system scores (4 variables), interaction effects between rankings and education system scores (4 variables), poverty rates, number of universities per country, interaction effect between poverty rates and access scores, interaction effects between number of universities and economic scores, university density (Total area / # of HEIs), dummy variables for UK, Nordic, Western EU and Eastern EU regions. 

 

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