Publications

Unfortunately, there is no result available for this search combination

18. Sozialerhebung.

Middendorff, E., & Hoffstätter, U. (2019).
18. Sozialerhebung. Daten und Methodenbericht zur Studierendenbefragung 2006 (Version 1.0.0). Hannover: fdz.DZHW.
Abstract

The 18th Social Survey is part of the series of studies on the economic and social condition of student life in Germany, which exists since 1951. It is a cross-sectional survey that is usually conducted every three years. The core of the Social Survey includes questions on access to higher education, structural characteristics of studies and the course of studies, the social and economic situation (financing of studies, cost of living, gainful employment, housing situation), topics relating to the fields of activity of the Studentenwerke as well as socio-demographic characteristics. The data from the 18th Social Survey provide a snapshot [...] Full abstract: https://doi.org/10.21249/DZHW:ssy18:1.0.0

beeinträchtigt studieren – best2.

Birkelbach, R. (2019).
beeinträchtigt studieren – best2. Daten- und Methodenbericht zur Studierendenbefragung 2016/17 (Version 1.0.0). Hannover: fdz.DZHW.

Entwicklung und Betrieb eines Metadatenmanagementsystems für Forschungsdaten aus dem Bereich der Hochschul- und Wissenschaftsforschung - Lessons Learned.

Stephan, K., & Reitmann, R. (2019).
Entwicklung und Betrieb eines Metadatenmanagementsystems für Forschungsdaten aus dem Bereich der Hochschul- und Wissenschaftsforschung - Lessons Learned. In B. Mittermaier (Hrsg.), Forschungsdaten sammeln, sichern, strukturieren. 8. Konferenz der Zentralbibliothek, Forschungszentrum Jülich, 4.-6. Juni 2019. Proceedingsband (S. 39-55). Jülich: Forschungszentrum Jülich Gmbh, Zentralbibliothek.

Hinweise zur Codierung fehlender Werte in der Aufbereitung quantitativer Daten. Version 1.0.

Verbund Forschungsdaten Bildung (Hrsg.) (2019).
Hinweise zur Codierung fehlender Werte in der Aufbereitung quantitativer Daten. Version 1.0. fdbinfo Nr. 6.

DZHW-Absolventenpanel 2005.

Baillet, F., Franken, A., Weber, A. (2019).
DZHW-Absolventenpanel 2005. Daten-und Methodenbericht zu den Erhebungen der Absolvent(inn)enkohorte 2005 (1., 2. und 3. Befragungswelle) (Version 2.0.0). Hannover: fdz.DZHW.

21. Sozialerhebung.

Becker, K., Baillet, F., & Weber, A. (2018).
21. Sozialerhebung. Daten- und Methodenbericht zu der Erhebung der wirtschaftlichen und sozialen Lage der Studierenden 2016. Daten- und Methodenbericht (Version 1.0.0). Hannover: fdz.DZHW.
Abstract

The 21st Social Survey is part of a survey series regarding the economic and social situation of students conducted since 1951 by the German National Association for Student Affairs (DSW) as part of their social survey. The Social Survey is a cross-sectional study which is usually carried out every three years. Key components of the study include access to higher education, structural aspects of the course and progress of studies, the economic and social situation (financing of studies, living expenses, employment, housing conditions) as well as topics in the field of activity of the German National Association for Student Affairs and socio-demographic characteristics. [...] Full abstract: https://doi.org/10.21249/DZHW:ssy21:1.0.0

A Fast Algorithm Based on Apriori Algorithms to Explore the Set of Repetitive Items of Large Transaction Data.

Ghofrani, J., Mohseni M., & Bozorgmehr, A. (2018).
A Fast Algorithm Based on Apriori Algorithms to Explore the Set of Repetitive Items of Large Transaction Data. ICCDA 2018 Proceedings of the 2nd International Conference on Compute and Data Analysis, 13-19. https://doi.org/10.1145/3193077.3193089
Abstract

Parallel data mining is utilized to improve the performance of analyzing large databases within a reasonable time frame. Exploring associative rules is an important task in data mining with various practical applications that can be used to explore knowledge in the form of a set of repetitive items or associative rules. Parallel algorithms divide the data superficially and then using different distribution approach, like data distribution, candidate and numerical candidate distribution, extract the set of repetitive items, and ultimately explore strong association laws. In this paper, a parallel algorithm is proposed to explore the collection of repetitive items from big and dense transaction databases.

DZHW-Pro­mo­vier­ten­pa­nel 2014.

Brandt, G., de Vogel, S., Jaksztat, S., Teichmann, C., Lange, K., Scheller, P., Vietgen, S. (2018).
DZHW-Pro­mo­vier­ten­pa­nel 2014. Methoden- und Datenbericht (Version 2.0.0). Hannover: fdz.DZHW.
Abstract

The DZHW Panel Study: Careers of PhD Holders 2014 is a panel study of the DZHW concerning the careers of doctoral graduates. The study analyses how the formal context as well as the learning and development conditions that PhD graduates experienced during their doctorate studies influence the transition into employment and the further development of their professional career, both within as well as outside academia. The basic population comprises all persons who obtained a doctorate degree from a higher education institution with the right to award doctorates in Germany in the examination year of 2014. [...] Full abstract: https://doi.org/10.21249/DZHW:phd2014:2.0.0

DZHW PhD Panel 2014.

Brandt, G., de Vogel, S., Jaksztat, S., Teichmann, C., Lange, K., Scheller, P., Vietgen, S. (2018).
DZHW PhD Panel 2014. Methoden- und Datenbericht (Version 2.0.0). Hannover: fdz.DZHW.
Abstract

The DZHW Panel Study: Careers of PhD Holders 2014 is a panel study of the DZHW concerning the careers of doctoral graduates. The study analyses how the formal context as well as the learning and development conditions that PhD graduates experienced during their doctorate studies influence the transition into employment and the further development of their professional career, both within as well as outside academia. The basic population comprises all persons who obtained a doctorate degree from a higher education institution with the right to award doctorates in Germany in the examination year of 2014. The panel is designed as a census in order to generate [...] Full abstract: https://doi.org/10.21249/DZHW:phd2014:2.0.0

A conceptual framework for clone detection using machine learning.

Ghofrani, J., Mohseni M., & Bozorgmehr, A. (2018).
A conceptual framework for clone detection using machine learning. 2017 IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI). http://dx.doi.org/10.1109/KBEI.2017.8324908
Abstract

Code clones can happen in any software project. One of the challenges is that, code clones come in various forms which makes them hard to detect using standard templates. Due to this variety in structure and form of semantically similar clones, machine learning techniques are required to detect them. Recently in many domains, e.g., natural language processing, deep neural networks drew a lot of attention due to their accuracy. In this paper, we exploit the results of some convolutional neural networks for code summarization to find the code clones. We use the generated descriptions for two code snippets as a metric to measure the similarities between them. We propose a vector similarity measure to calculate a similarity indicator between th

DZHW-Absolventenpanel 2009.

Baillet, F., Franken, A., & Weber, A. (2017).
DZHW-Absolventenpanel 2009. Daten- und Methodenbericht zu den Erhebungen der Absolvent(inn)enkohorte 2009 (1. und 2. Befragungswelle). Hannover: fdz.DZHW.

DZHW Graduate Panel 2009.

Baillet, F., Franken, A., & Weber, A. (2017).
DZHW Graduate Panel 2009. Methoden- und Datenbericht. Hannover: fdz.DZHW.
Abstract

The DZHW Graduate Panel 2009 is part of the DZHW Graduate Survey Series, which compiles information on study, career entry, career development and further qualifications of higher education graduates using standardised surveys. The first Graduate Panel was created in 1989. Since then, every fourth graduate year (cohort) has been surveyed. For each graduate cohort, a series of survey waves are carried out, with each wave occurring at differing time intervals following the completion of degree. The DZHW Graduate Panel 2009 comprises the sixth graduate cohort of the survey series. Similar to the 2005 cohort, the study phase of the 2009 cohort is defined by the transformation [...] Full Abstract: https://doi.org/10.21249/DZHW:gra2009:1.0.1

Panelausfall in der Studierendenkohorte des Nationalen Bildungspanels. Analyse des Ausfallprozesses zwischen der ersten und zweiten telefonischen Befragung.

Liebeskind, U., & Vietgen, S. (2017).
Panelausfall in der Studierendenkohorte des Nationalen Bildungspanels. Analyse des Ausfallprozesses zwischen der ersten und zweiten telefonischen Befragung. NEPS Working Paper No. 70. Bamberg, Deutschland: Leibniz-Institut für Bildungsverläufe, Nationales Bildungspanel.

DZHW-Studienberechtigtenpanel 2008.

Daniel, A., Hoffstätter, U., Huß, B., Scheller, P. (2017).
DZHW-Studienberechtigtenpanel 2008. Methoden- und Datenbericht (Version 1.0.0). Hannover: fdz.DZHW.

DZHW Panel Study of School Leavers with a Higher Education Entrance Qualification 2008.

Daniel, A., Hoffstätter, U., Huß, B., Scheller, P. (2017).
DZHW Panel Study of School Leavers with a Higher Education Entrance Qualification 2008. Methoden- und Datenbericht (Version 1.0.0). Hannover: fdz.DZHW.
Abstract

The DZHW Panel Study of School Leavers 2008 is part of the School Leavers panel series of the DZHW, which records information on post-school educational and career paths of school leavers with a higher education entrance qualification. For every graduate year (cohort) a series of survey waves are carried out with each wave occurring at a different time before and after graduation, implemented as a combined cohort-panel-design. The Panel Study of School Leavers 2008 comprises the 17th cohort of the survey series with three survey waves. In contrast to preceding cohorts, the study phase of the 2008 cohort is defined by the implementation of the two-cycle degree programme [...] Full Abstract: https://doi.org/10.21249/DZHW:gsl2008:1.0.0

Contact

David Broneske
Dr. David Broneske Acting Head +49 511 450670-454
Karsten Stephan
Dr. Karsten Stephan Deputy Head +49 511 450670-415

Projects

All research area projects

Staff

All research area staff

Publications

All research area publications

Presentations and conferences

All research area presentations and conferences