Publications

DZHW publishes its research findings in renowned academic journals, at national and international conferences and in its own publishing formats. An overview of publications and lectures produced by DZHW staff can be seen below. You can open individual publication formats separately using the menu in the left-hand column.

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Anomaly detection algorithms: Comparative analysis and explainability perspectives.

Darab, S., Allipilli, H., Ghani, S., Changaramkulath, H., Koneru, S., Broneske, D., & Saake, G. (2023).
Anomaly detection algorithms: Comparative analysis and explainability perspectives. In D. Benavides-Prado et al. (Hrsg.), Data Science and Machine Learning, 21st Australasian Conference, AusDM 2023, Auckland, New Zealand, December 11–13, 2023, Proceedings (S. 90-104). Singapore: Springer Nature.

Ausstattungs-, Kosten- und Leistungsvergleich Künstlerische Hochschulen 2021. Grunddaten und Kennzahlen der Hochschule für Musik und Theater Hamburg.

Sanders, S. (2023).
Ausstattungs-, Kosten- und Leistungsvergleich Künstlerische Hochschulen 2021. Grunddaten und Kennzahlen der Hochschule für Musik und Theater Hamburg. Hannover: DZHW (nicht zur Veröffentlichung vorgesehen).

Forschung im Team: Kooperationsvorhaben erfolgreich meistern.

Hückstädt, M. (2023).
Forschung im Team: Kooperationsvorhaben erfolgreich meistern. (DZHW Brief 04|2023). Hannover: DZHW. https://doi.org/10.34878/2023.04.dzhw_brief

The Long and Winding Road to Excellence: The German Case.

Möller, T., & Hornbostel, S. (2023).
The Long and Winding Road to Excellence: The German Case. In M. Yudkevich, P. G. Altbach, & J. Salmi (Hrsg.), Academic Star Wars: Excellence Initiatives in Global Perspective (S. 177-201). Cambridge, Massachusetts: The MIT Press. https://doi.org/10.7551/mitpress/14601.003.0012

Die Studierendenbefragung in Deutschland: best3.

Steinkühler, J., Beuße, M., Kroher, M., Gerdes, F., Schwabe, U., ... & Buchholz, S. (2023).
Die Studierendenbefragung in Deutschland: best3. Studieren mit einer gesundheitlichen Beeinträchtigung. Hannover: DZHW.

Dropout intent of students with disabilities.

Rußmann, M., Netz, N., & Lörz, M. (2023).
Dropout intent of students with disabilities. Higher Education (online first). https://doi.org/10.1007/s10734-023-01111-y
Abstract

We examine the mechanisms explaining the dropout intentions of students with disabilities by integrating Tinto’s model of student integration, the student attrition model, the composite persistence model, and insights from social stratification research. Overall, our results highlight the importance of considering both students’ integration into higher education and their private resources for understanding student-group-specific dropout intent.

Ausstattungs‐, Kosten‐ und Leistungsvergleich Universitäten 2022. Grunddaten und Kennzahlen Universität Bielefeld.

Winkelmann, G. (2023).
Ausstattungs‐, Kosten‐ und Leistungsvergleich Universitäten 2022. Grunddaten und Kennzahlen Universität Bielefeld. Hannover: DZHW (nicht zur Veröffentlichung vorgesehen).

The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys.

Höhne, J. K., Kern, C., Gavras, K., & Schlosser, S. (2023).
The sound of respondents: predicting respondents’ level of interest in questions with voice data in smartphone surveys. Quality & Quantity, International Journal of Methodology, 57(6). https://doi.org/10.1007/s11135-023-01776-8
Abstract

Web surveys completed on smartphones open novel ways for measuring respondents’ attitudes, behaviors, and beliefs that are crucial for social science research and many adjacent research fields. In this study, we make use of the built-in microphones of smartphones to record voice answers in a smartphone survey and extract non-verbal cues, such as amplitudes and pitches, from the collected voice data. This allows us to predict respondents’ level of interest (i.e., disinterest, neutral, and high interest) based on their voice answers, which expands the opportunities for researching respondents’ engagement and answer behavior. [...] Full abstract: https://doi.org/10.1007/s11135-023-01776-8

Internationale Wissenschaftlerinnen und Wissenschaftler an deutschen Hochschulen: Von der Postdoc-Phase zur Professur (InWiDeHo).

Jaudzims, S., & Oberschelp, A. (2023).
Internationale Wissenschaftlerinnen und Wissenschaftler an deutschen Hochschulen: Von der Postdoc-Phase zur Professur (InWiDeHo). Eine Analyse von Herausforderungen und Gelingensbedingungen. DAAD-Studien. Bonn: DAAD.
Abstract

In Germany, only a few international academics have succeeded in gaining access to a university professorship. This is evident on an international scale, but also in comparison with other academic staff at universities. The InWiDeHo research project investigated whether and, if so, which obstacles exist for international academics in the transition from postdoc to professorship. The report presents the core findings and recommendations for action of the qualitative study, for which international postdocs and newly appointed professors as well as members of university management were interviewed as part of expert interviews. Group discussions were also held with university staff.

Spezifische Bedarfe von wissenschaftlich Tätigen aus dem Ausland sollten stärker berücksichtigt werden.

Jaudzims, S., & Oberschelp, A. (28. November 2023).
Spezifische Bedarfe von wissenschaftlich Tätigen aus dem Ausland sollten stärker berücksichtigt werden [Blogbeitrag]. Abgerufen von https://www.wissenschaft-weltoffen.de/de/2023/11/28/spezifische-bedarfe-von-wissenschaftlich-taetigen-aus-dem-ausland-sollten-staerker-beruecksichtigt-werden/

Data Mesh for Managing Complex Big Data Landscapes and Enhancing Decision Making in Organizations.

Azeroual, O., & Nacheva, R. (2023).
Data Mesh for Managing Complex Big Data Landscapes and Enhancing Decision Making in Organizations. In L. Gruenwald, E. Masciari, C. Rolland, & J. Bernardino (Hrsg.), Proceedings of the 15th International Conference on Knowledge Management and Information Systems (KMIS 2023) (S. 202-212). Rome, Italy: SciTePress, Science and Technology Publications, Lda. https://doi.org/10.5220/0012195700003598

WISHFUL - Website extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage.

Shahania, S., Spiliopoulou, M., & Broneske, D. (2023).
WISHFUL - Website extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage. In Delir Haghighi, P. et al. (Hrsg.), Information Integration and Web Intelligence (iiWAS 2023) (S. 20-26). Cham: Springer. https://doi.org/10.1007/978-3-031-48316-5_3
Abstract

Extracting information from diverse websites is increasingly important, especially for analyzing vast data sets to detect trends, gain insights. By studying job ads, researchers can monitor employer demand shifts, assisting policymakers in aiding affected workers and industries. However, extraction faces challenges like varied website formats, dynamic content, and duplicate data. This study introduces a method for extracting data from diverse private university websites involving keyword identification, website categorization, and extraction pipelines.

Ausstattungs‐, Kosten‐ und Leistungsvergleich Universitäten 2022. Grunddaten und Kennzahlen Universität Rostock.

Winkelmann, G. (2023).
Ausstattungs‐, Kosten‐ und Leistungsvergleich Universitäten 2022. Grunddaten und Kennzahlen Universität Rostock. Hannover: DZHW (nicht zur Veröffentlichung vorgesehen).

WGTDISTRIM: Stata module to trim extreme sampling weights (version 1.0.0) [Stata-ado].

Lang, S., & Klein, D. (2023).
WGTDISTRIM: Stata module to trim extreme sampling weights (version 1.0.0) [Stata-ado]. Hannover: Github.
Abstract

wgtdistrim trims extreme sampling weights using the weight distribution approach suggested by Potter (1990). The reciprocal of the sampling weights are assumed to follow a (scaled) beta distribution. The parameters of the beta distribution are estimated from the sampling weights and the trimming levels (cut-offs) are computed for the specified percentiles. Sampling weights that are more extreme than the specified percentiles are trimmed to these percentiles and the excess is distributed equally among the untrimmed sampling weights so that the sum of the trimmed sampling weights equals the sum of the untrimmed sampling weights. This process is repeated a specified number of times (or until the trimmed sampling weights do no longer change).

Does the higher education experience affect political interest, efficacy, and participation? Comparing dropouts to graduates and ‘non-starters’.

Mishra, S., Klein, D., & Müller, L. (2023).
Does the higher education experience affect political interest, efficacy, and participation? Comparing dropouts to graduates and ‘non-starters’. European Journal of Higher Education. https://doi.org/10.1080/21568235.2023.2276853

Contact

Anja Gottburgsen
Dr. Anja Gottburgsen +49 511 450670-912