Liechtenstein - Tertiary education, academic staff (% female)

Tertiary education, academic staff (% female) in Liechtenstein was 37.29 as of 2019. Its highest value over the past 8 years was 37.29 in 2019, while its lowest value was 26.61 in 2011.

Definition: Tertiary education, academic staff (% female) is the share of female academic staff in tertiary education.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/)

See also:

Year Value
2011 26.61
2012 30.17
2013 30.63
2014 33.67
2015 34.45
2016 35.00
2017 36.61
2019 37.29

Development Relevance: The share of female teachers shows the level of gender representation in the teaching force. A value of greater than 50% indicates more opportunities or preference for women to participate in teaching activities. Women teachers are important as they serve as role models to girls and help to attract and retain girls in school.

Other Notes: Data retrieved via API in March 2019. For detailed information on the observation level (e.g. National Estimation, UIS Estimation, or Category not applicable), please visit UIS.Stat (http://data.uis.unesco.org/).

Statistical Concept and Methodology: The share of female academic staffs in tertiary education is calculated by dividing the total number of female academic staffs at tertiary level of education by the total number of academic staffs at the same level, and multiplying by 100. Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).

Aggregation method: Weighted average

Periodicity: Annual

Classification

Topic: Education Indicators

Sub-Topic: Inputs