Die strukturelle Verankerung von Berufungsbeauftragten an deutschen Universitäten. Walther, L., & Schwartz, E. (2022). Die strukturelle Verankerung von Berufungsbeauftragten an deutschen Universitäten. Beiträge zur Hochschulforschung, 44(4), 58-79.
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Gibt es eine Unwucht bei der Finanzierung von Hochschulen und außeruniversitären Forschungseinrichtungen? Speiser, G. (2022). Gibt es eine Unwucht bei der Finanzierung von Hochschulen und außeruniversitären Forschungseinrichtungen? die hochschule, 2022 (1–2), 152-166.
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Besonders belastet und kurz vor dem Abbruch? Nicht-traditionelle Studierende zu Beginn der COVID-19-Pandemie. Becker, K., & Brändle, T. (2022). Besonders belastet und kurz vor dem Abbruch? Nicht-traditionelle Studierende zu Beginn der COVID-19-Pandemie. Zeitschrift für Hochschulentwicklung, , 17(4), 155-173 (online first). http://dx.doi.org/10.3217/zfhe-17-04/8
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Warum brechen nicht-traditionelle Studierende häufiger ihr Studium ab? Eine Dekompositionsanalyse. Dahm, G. (2022). Warum brechen nicht-traditionelle Studierende häufiger ihr Studium ab? Eine Dekompositionsanalyse [Sonderheft]. Zeitschrift für Hochschulentwicklung, 17(4)(Hochschulzugang und Studium nicht-traditioneller Studierender: Die Situation in Österreich, Deutschland und der Schweiz), 111-132. https://doi.org/10.3217/zfhe-17-04/06
Abstract
Non-traditional students in higher education drop out more often than traditional students. To understand this difference more clearly, this paper examines differences between the two groups with regard to sociodemographic characteristics, study contexts and life circumstances, as well as individual assessments of prospects of academic success and the costs and returns of studying. A decomposition analysis shows that student age and study context are two factors that have a particularly strong significance for the higher tendency of non-traditional students to drop out. This paper suggests ways in which theoretical models for explaining educational decisions could be adapted with regard to the special group of non-traditional students.
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Editorial: Hochschulzugang und Studium nicht-traditioneller Studierender: Die Situation in Österreich, Deutschland und der Schweiz. Freitag, W. K., Kerst, C., & Ordemann, J. (2022). Editorial: Hochschulzugang und Studium nicht-traditioneller Studierender: Die Situation in Österreich, Deutschland und der Schweiz. In W. K. Freitag, C. Kerst, & J. Ordemann (Hrsg.), Hochschulzugang und Studium nicht-traditioneller Studierender: Die Situation in Österreich, Deutschland und der Schweiz (S. 9-21). Graz: Verein Forum Neue Medien in der Lehre Austria. https://doi.org/10.3217/zfhe-17-04/01
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Datenzugang. Hoffstätter, U., & Linne, M. (2022). Datenzugang. Einführung in das Thema Zugang zu Daten der Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften in Forschungsdatenzentren. KonsortSWD Working Paper 2022 (4). Berlin: Konsortium für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften (KonsortSWD). https://www.doi.org/10.5281/zenodo.7347064
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Exploiting views for collaborative research data management of structured data. Broneske, D., Wolff, I., Köppen, V., & Schäler, M. (2022). Exploiting views for collaborative research data management of structured data. In Y.-H. Tseng, M. Katsurai, & H. N. Nguyen (Hrsg.), ICADL 2022: From born-physical to born-virtual: Augmenting intelligence in digital libraries. (S. 360-376). Cham: Springer (online first). https://doi.org/10.1007/978-3-031-21756-2_28
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The effects of response burden – collecting life history data in a self-administered mixed-device survey. Carstensen, J., Lang, S., & Cordua, F. (2022). The effects of response burden – collecting life history data in a self-administered mixed-device survey. Journal of Official Statistics, 38(4), 1069-1095. https://doi.org/10.2478/jos-2022-0046
Abstract
Collecting life history data is highly demanding and therefore prone to error since respondentsmust retrieve and provide extensive complex information. Research has shown that responseburden is an important factor influencing data quality. We examine whether increases indifferent measures of response burden in a (mixed-device) online survey lead to adverseeffects on the data quality and whether these effects vary by the type of device used (mobileversus non-mobile).
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Competency requirements in research information management and reporting: evidence from a national survey in Germany. Schelske, S., & Thiedig, C. (2022). Competency requirements in research information management and reporting: evidence from a national survey in Germany. Procedia Computer Science (211), 141-150. https://doi.org/10.1016/j.procs.2022.10.186
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Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS. Azeroual, O., Schöpfel, J., Ivanovic, D., & Nikiforova, A. (2022). Combining Data Lake and Data Wrangling for Ensuring Data Quality in CRIS. In M.-A. Sicilia, P. de Castro, S. Vancauwenbergh, E. Simons, & O. Ognjen (Hrsg.), 15th International Conference on Current Research Information Systems (S. 3-16). Dubrovnik, Croatia: Procedia Computer Science. https://doi.org/10.1016/j.procs.2022.10.171
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UCRP-miner: Mining patterns that matter. Darrab, S., Broneske, D., & Saake, G. (2022). UCRP-miner: Mining patterns that matter. In IEEE Institute of Electrical and Electronic Engineers (Hrsg.), Proceedings of the 5th International Conference on Data Science and Information Technology (DSIT) (S. 1-7). New York, United States: IEEE. https://doi.org/10.1109/DSIT55514.2022.9943880
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Research Information Systems and Ethics relating to Open Science. Schöpfel, J., Azeroual, O., & de Castro, P. (2022). Research Information Systems and Ethics relating to Open Science. In M.-A. Sicilia, P. de Castro, S. Vancauwenbergh, E. Simons, & O. Ognjen (Hrsg.), 15th International Conference on Current Research Information Systems (S. 36-46). Dubrovnik, Croatia: Procedia Computer Science. https://doi.org/10.1016/j.procs.2022.10.174
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Tell me why it’s fake: Developing an explainable user interface for a fake news detection system. Shahania, S., Purificato, E., & William De Luca, E. (2022). Tell me why it’s fake: Developing an explainable user interface for a fake news detection system. In CEUR Workshop Proceedings (Hrsg.), Proceedings of the 3rd Italian Workshop on Explainable Artificial Intelligence (XAI.it 2022). Udine, Italy: CEUR.
Abstract
In this paper, we present the design and development of an explainable user interface for a fake news
detection system. The problem of distinguishing real from fake articles gained a lot of popularity in
the last few years, mainly due to the soaring diffusion of social networks and internet bots as means
for propaganda and disinformation sharing. By leveraging various explainability methods, i.e. feature
importance, partial dependence plots and SHAP values, we aim to show how the combination of different
techniques embedded in an interactive user interface can lead to enhance trust in a detection system for
a non-expert user, such as a fact-checker or a content manager. Through several examples, we describe
all the explainability component
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Legal aspects and data protection in relation to the CRIS system. Zendulková, D., & Azeroual, O. (2022). Legal aspects and data protection in relation to the CRIS system. In M.-A. Sicilia, P. de Castro, S. Vancauwenbergh, E. Simons, & O. Ognjen (Hrsg.), 15th International Conference on Current Research Information Systems (S. 17-27). Dubrovnik, Croatia: Procedia Computer Science. https://doi.org/10.1016/j.procs.2022.10.172
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Drawbacks of Normalization by Percentile Ranks in Citation Impact Studies. Donner, P. (2022). Drawbacks of Normalization by Percentile Ranks in Citation Impact Studies. Journal of Library and Information Studies, 20(2), 75-93.
Abstract
This paper discusses drawbacks of the percentile rank method for citation impact normalization which have hitherto been neglected in the bibliometrics literature. The transformation of citation counts to percentile ranks changes ratio scale data into ordinal scale data, for which the notions of the ratio between two values and of the magnitude of a difference between two values are not defined – a substantial loss of information. This distorts citation data particularly severely because the differences between citation counts adjacent in order in publication sets are greater for more highly cited publications and because highly cited publications are more scarce than non-highly cited ones. [...]
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