Germany DE: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Female: % Cumulative data was reported at 25.306 % in 2022. This records an increase from the previous number of 24.831 % for 2021. Germany DE: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Female: % Cumulative data is updated yearly, averaging 20.690 % from Dec 2010 (Median) to 2022, with 13 observations. The data reached an all-time high of 25.306 % in 2022 and a record low of 0.730 % in 2011. Germany DE: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Female: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

In 2022, Canada had the highest share of adults with a university degree, at over 60 percent of those between the ages of 25 and 64. India had the smallest share of people with a university degree, at 13 percent of the adult population. University around the world Deciding which university to attend can be a difficult decision for some and in today’s world, people are not left wanting for choice. There are thousands of universities around the world, with the highest number found in India and Indonesia. When picking which school to attend, some look to university rankings, where Harvard University in the United States consistently comes in on top. Moving on up One of the major perks of attending university is that it enables people to move up in the world. Getting a good education is generally seen as a giant step along the path to success and opens up doors for future employment. Future earnings potential can be determined by which university one attends, whether by the prestige of the university or the connections that have been made there. For instance, graduates from the Stanford Graduate School of Business can expect to earn around 250,000 U.S. dollars annually.

In the winter semester 2024/25, around 2.87 million students were enrolled in German universities. This was a slight decrease compared to the previous year, but still around 250,000 more than ten years ago, demonstrating that higher education is becoming a more popular option for people in Germany. Students at German universities The majority of students in Germany are studying to get a bachelor’s degree, however, a significant growing number of students also go on to do a master’s degree. German universities offer students the opportunity to study a wide range of subjects - humanities as well as sciences. The most popular subjects to study among German students in recent years have been law, economics, and social sciences, followed by engineering. Although there are different institutions at which students in Germany can pursue higher education, most students opt to study at a university or university of applied sciences. These types of institutions also offer the most courses for students to choose from. Private universities As well as having state-funded universities, there are also private universities in Germany. As the name suggests, this means that they are not funded by the state, and therefore students must pay the fees for each semester themselves. This model of higher education is more similar to the one found in England or the U.S. Despite the higher tuition fees, the most popular university in Germany is currently a private one, suggesting that there are possibly some advantages to paying more for your education. It is important to note that comparatively only a very small percentage of students attend private universities. This is likely since they are more expensive, and shows the importance of keeping university affordable so that everyone can have the opportunity to pursue further education.

Germany DE: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Male: % Cumulative data was reported at 33.311 % in 2022. This records a decrease from the previous number of 33.453 % for 2021. Germany DE: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Male: % Cumulative data is updated yearly, averaging 29.980 % from Dec 2010 (Median) to 2022, with 13 observations. The data reached an all-time high of 33.453 % in 2021 and a record low of 1.708 % in 2013. Germany DE: Educational Attainment: At Least Bachelor's or Equivalent: Population 25+ Years: Male: % Cumulative data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Social: Education Statistics. The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.;UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed April 5, 2025. https://apiportal.uis.unesco.org/bdds.;;

******* was the European country with the highest share of graduates in 2024, with almost **** of those aged between 15 and 64 having a degree. On the contrary, only ** percent of the population aged 15 to 64 in ********************** hold a tertiary education title.

The system of social indicators for the Federal Republic of Germany - developed in its original version as part of the SPES project under the direction of Wolfgang Zapf - provides quantitative information on levels, distributions and changes in quality of life, social progress and social change in Germany from 1950 to 2013, i.e. over a period of more than sixty years. With the approximately 400 objective and subjective indicators that the indicator system comprises in total, it claims to measure welfare and quality of life in Germany in a differentiated way across various areas of life and to monitor them over time. In addition to the indicators for 13 areas of life, including income, education and health, a selection of cross-cutting global welfare measures were also included in the indicator system, i.e. general welfare indicators such as life satisfaction, social isolation or the Human Development Index. Based on available data from official statistics and survey data, time series were compiled for all indicators, ideally with annual values from 1950 to 2013. Around 90 of the indicators were marked as "key indicators" in order to highlight central dimensions of welfare and quality of life across the various areas of life. The further development and expansion, regular maintenance and updating as well as the provision of the data of the system of social indicators for the Federal Republic of Germany have been among the tasks of the Center for Social Indicator Research, which is based at GESIS, since 1987. For a detailed description of the system of social indicators for the Federal Republic of Germany, see the study description under "Other documents".
Indicators for the area of life “education”

The data on the area of life “education” is made up as follows:

Participation in education and educational opportunities: Access to the elementary area [second level]; Children in kindergartens; Provision rate in child day care for children under three years old; Participation in education in lower secondary education [second level]; School attendance of 13-year-olds by school type; School success in lower secondary education [second level]; School leavers without a secondary school diploma; School success in upper secondary education [second level]: High school graduate rate; Participation in tertiary education [second level]: Student quota of 20 to 30 year olds; Equal opportunities in tertiary education [second level]: Student entry rate for university studies; Entry rate for university/technical college studies; Further training [second level]: VHS course occupancy per 100 inhabitants; Participation rate for the entire further training; Participation rate in general and political further training; Participation rate in continuing professional education; Participation rate of continuing vocational training among employed people; Qualification [first level]: Language competence [second level]: Proportion of population with foreign language skills; IT competence [second level]: Proportion of population with computer skills; Quality of school education [second level]: Proportion of students with a lack of mathematical competence; Proportion of students with poor reading skills; Proportion of students with a lack of scientific competence; Vocational training [second level]: Share of population with apprenticeship/skilled training; Proportion of the population with vocational training; Proportion of the population with a technical college education; Proportion of the population with a university degree; Effectiveness [first level]: Unemployment rate: people without training; Unemployment rate: university graduates; Organization and costs of the education system [first level]: Public/private sector ratio [second level]: Proportion of high school students in public schools to all high school students; Costs of the education system [second level]: Share of public budget expenditure on education; public/private financing of studies; Financing the studies; Subjective preservation and evaluation of education [first level]: Satisfaction with training.

The concept of the ‘age-specific attendance rates’ is used in this study as indicator for the population’s attendance at education. This indicator eliminates the effects of demographic influences in temporal and regional comparisons. In this concept the long-term development of school and univeristy attendance is analyzed by relating the age-grouped number of pupils and students to the population of the same age cohort.

First the development of the pupils’ and students’ number and the main features of the demographic development are represented. The development of the age-specific attendance rates of separate age cohorts shows the effect of changes caused by school-reorganization (for example the reorganization of the school years or the implementation of new educational establishments). Furthermore, this development suggests the comparison of the attendence development between different educational institutions an within the same institition between different age cohorts.

The results of the calculations for the age cohort of the 13-year-olds is of particular interest, because in this age group the school attendance is compulsory for all children and the alloction of the children to the different school-types in Germany (elementary school or rather ‘Hauptschule’, mid-level secondary school or rather ‘Real-Schule’, grammar school or rather ‘Gymnasium’) is completed.

The age-specific attendance rates at the grammar schools (‘Gymnasium’) of the 18-year-olds could be seen as a rough indicator for the population’s participation at advanced education.

Comparisons of the age-specific attendance rates of boys and girls at school and of men and women at vocational education and universities respectively shows, that the participation of girls and women has increased.

Afterwards the passage thru the edicational system of the birth-cohorts 1940, 1946, 1950, 1960, and 1970 is analysed.

Topics:

Datatables in HISTAT:

A. Absolute Number: resident population, pupils, and students (1950-1987).

B. Age-specific attendance rates by kind of school (1952-1987). (6-year-olds, 10-year-olds, 13-year-olds, 16-year-olds, 18-year-olds, 22-year-olds, 26-29-year-olds).

C. Age-specific attedance rates at university (Portion of female students, percentage of students, students at the age of 22, 26 and 29 by sex).

D. Age-specific attendance rates at education by birth-cohorts. (Birth-cohorts: 1940, 1946, 1950, 1960 and 1970 by kind of school and by kind of universities).

E. Age-specific attendance rates at education by German Federal States (=Bundesländer).

In 2023, around 20 percent of the population with a migrant background had a secondary or elementary school education. 38.5 percent had some type of university degree.

Open Science in (Higher) Education – data of the February 2017 survey

This data set contains:

• Full raw (anonymised) data set (completed responses) of Open Science in (Higher) Education February 2017 survey. Data are in xlsx and sav format.
• Survey questionnaires with variables and settings (German original and English translation) in pdf. The English questionnaire was not used in the February 2017 survey, but only serves as translation.
• Readme file (txt)

Survey structure

The survey includes 24 questions and its structure can be separated in five major themes: material used in courses (5), OER awareness, usage and development (6), collaborative tools used in courses (2), assessment and participation options (5), demographics (4). The last two questions include an open text questions about general issues on the topics and singular open education experiences, and a request on forwarding the respondent’s e-mail address for further questionings. The online survey was created with Limesurvey[1]. Several questions include filters, i.e. these questions were only shown if a participants did choose a specific answer beforehand ([n/a] in Excel file, [.] In SPSS).

Demographic questions

Demographic questions asked about the current position, the discipline, birth year and gender. The classification of research disciplines was adapted to general disciplines at German higher education institutions. As we wanted to have a broad classification, we summarised several disciplines and came up with the following list, including the option “other” for respondents who do not feel confident with the proposed classification:

• Natural Sciences
• Arts and Humanities or Social Sciences
• Economics
• Law
• Medicine
• Computer Sciences, Engineering, Technics
• Other

The current job position classification was also chosen according to common positions in Germany, including positions with a teaching responsibility at higher education institutions. Here, we also included the option “other” for respondents who do not feel confident with the proposed classification:

• Professor
• Special education teacher
• Academic/scientific assistant or research fellow (research and teaching)
• Academic staff (teaching)
• Student assistant
• Other

We chose to have a free text (numerical) for asking about a respondent’s year of birth because we did not want to pre-classify respondents’ age intervals. It leaves us options to have different analysis on answers and possible correlations to the respondents’ age. Asking about the country was left out as the survey was designed for academics in Germany.

Remark on OER question

Data from earlier surveys revealed that academics suffer confusion about the proper definition of OER^[2]. Some seem to understand OER as free resources, or only refer to open source software (Allen & Seaman, 2016, p. 11). Allen and Seaman (2016) decided to give a broad explanation of OER, avoiding details to not tempt the participant to claim “aware”. Thus, there is a danger of having a bias when giving an explanation. We decided not to give an explanation, but keep this question simple. We assume that either someone knows about OER or not. If they had not heard of the term before, they do not probably use OER (at least not consciously) or create them.

Data collection

The target group of the survey was academics at German institutions of higher education, mainly universities and universities of applied sciences. To reach them we sent the survey to diverse institutional-intern and extern mailing lists and via personal contacts. Included lists were discipline-based lists, lists deriving from higher education and higher education didactic communities as well as lists from open science and OER communities. Additionally, personal e-mails were sent to presidents and contact persons from those communities, and Twitter was used to spread the survey.

The survey was online from Feb 6^th to March 3^rd 2017, e-mails were mainly sent at the beginning and around mid-term.

Data clearance

We got 360 responses, whereof Limesurvey counted 208 completes and 152 incompletes. Two responses were marked as incomplete, but after checking them turned out to be complete, and we added them to the complete responses dataset. Thus, this data set includes 210 complete responses. From those 150 incomplete responses, 58 respondents did not answer 1st question, 40 respondents discontinued after 1st question. Data shows a constant decline in response answers, we did not detect any striking survey question with a high dropout rate. We deleted incomplete responses and they are not in this data set.

Due to data privacy reasons, we deleted seven variables automatically assigned by Limesurvey: submitdate, lastpage, startlanguage, startdate, datestamp, ipaddr, refurl. We also deleted answers to question N^o 24 (email address).

References

Allen, E., & Seaman, J. (2016). Opening the Textbook: Educational Resources in U.S. Higher Education, 2015-16.

First results of the survey are presented in the poster:

Heck, Tamara, Blümel, Ina, Heller, Lambert, Mazarakis, Athanasios, Peters, Isabella, Scherp, Ansgar, & Weisel, Luzian. (2017). Survey: Open Science in Higher Education. Zenodo. http://doi.org/10.5281/zenodo.400561

Contact:

Open Science in (Higher) Education working group, see http://www.leibniz-science20.de/forschung/projekte/laufende-projekte/open-science-in-higher-education/.

[1] https://www.limesurvey.org

[2] The survey question about the awareness of OER gave a broad explanation, avoiding details to not tempt the participant to claim “aware”.

In the winter semester of 2023/2024, which starts in the autumn, there were 405,492 students enrolled in Bavarian universities. North Rhine-Westphalia boasted the highest university student numbers among German federal states, with approximately 717,963 students.

In 2022, Canada had the greatest number of international students compared to their entire higher education population, with nearly ** percent of students being international. Australia followed with a share of ** percent of the students being international, while the United Kingdom ranked third.

The number of university students in the Netherlands grew annually, with enrollment especially increasing between 2019 and 2021. In 2022, ******* students were registered at universities around the country. The largest share of these students was studying degrees related to behavior and social sciences, at around ******. By comparison, roughly ***** students were enrolled in a teaching program.  Internationalization of higher education    The growth in the number of university students is mostly the result of an increased number of international students finding their way to the Netherlands. In the last decade, the number of enrolled international students more than doubled. Whereas in 2008 less than ****** international students were studying in the Netherlands, by 2018 this had grown to just under ******.  Netherlands especially popular among German students    In the academic year 2018/2019, over ****** German students were enrolled at universities in the Netherlands. Germans formed by far the largest international student community in the country. In 2018/2019, the number of German students in the Netherlands was nearly twice as large as the second, third and fourth-largest communities (Italian, Chinese and Belgian students) combined.