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<jats:title>Abstract</jats:title><jats:p>The Open Science movement is gaining tremendous popularity and tries to initiate changes in science, for example the sharing and reuse of data. The new requirements that come with Open Science poses researchers with several challenges. While most of these challenges have already been addressed in several studies, little attention has been paid so far to the underlying Open Science practices (OSP). An exploratory study was conducted focusing on the OSP relating to sharing and using data. 13 researchers from the Weizenbaum Institute were interviewed. The Weizenbaum Institute is an interdisciplinary research institute in Germany that was founded in 2017. To reconstruct OSP a grounded theory methodology (Strauss in Qualitative Analysis for Social Scientists, Cambridge University Press, Cambridge, 1987) was used and classified OSP into open production, open distribution and open consumption (Smith in Openness as social praxis. First Monday, 2017). The research shows that apart from the disciplinary background and research environment, the methodological approach and the type of research data play a major role in the context of OSP. The interviewees’ self-attributions related to the types of data they work with: qualitative, quantitative, social media and source code. With regard to the methodological approach and type of data, it was uncovered that uncertainties and missing knowledge, data protection, competitive disadvantages, vulnerability and costs are the main reasons for the lack of openness. The analyses further revealed that knowledge and established data infrastructures as well as competitive advantages act as drivers for openness. Because of the link between research data and OSP, the authors of this paper argue that in order to promote OSP, the methodological approach and the type of research data must also be considered.</jats:p>

<ns3:p>Research that investigates respective researchers’ engagement in Open Science varies widely in the topics addressed, methods employed, and disciplines investigated, which makes it difficult to integrate and compare its results. To investigate current outcomes of Open Science research, and to get a better understanding on well-researched topics and research gaps, we aimed at providing an openly accessible overview of empirical studies that focus on different aspects of Open Science in different scientific disciplines, academic groups and geographical regions. In this paper, we describe a data set of studies about Open Science practices retrieved following a PRISMA approach to compile a literature review. We included studies from the Scopus and Web of Science databases with keywords relating to Open Science between the years 2000 and 2020, as well as a snowball search for relevant articles. Studies that did not investigate any aspect of Open Science, or weren’t peer-reviewed were excluded, resulting in a total of 695 remaining studies.<ns3:italic> </ns3:italic>The data set was collaboratively annotated to ensure intercoder reliability of the coded data.</ns3:p>

<jats:p>How can Knowledge In/Equity be addressed in qualitative research by taking the idea of Open Science into account? Two projects from the Open Science Fellows Programme by Wikimedia Deutschland will be used to illustrate how Open Science practices can succeed in qualitative research, thereby reducing In/Equity. In this context, In/Equity is considered as a fair and equal representation of people, their knowledge and insights and comprehends questions about how epistemic, structural, institutional and personal biases generate and shape knowledge as guidance. Three questions guide this approach: firstly, what do we understand by In/Equity in the context of knowledge production in these projects? Secondly, who will be involved in knowledge generation and to what extent will they be valued or unvalued? Thirdly, how can data be made accessible for re-use to enable true participation and sharing?</jats:p>

Der Beitrag beschäftigt sich mit dem Gebrauch von sogenannten Open Educational Resources (OER) innerhalb der deutschsprachigen Soziologie. OER sind Lehr-und Lernmaterialien, die öffent-lich und frei von Kosten zugänglich sind sowie unter einer offenen Lizenz stehen, die es erlaubt, das Material frei zu nutzen, zu vervielfältigen und zu bearbeiten. Um diese Form der Bereitstellung von Lehr-und Lernmaterial zu fördern, sind im deutschen Sprachraum in den letzten Jahren verschie-dene digitale Infrastrukturen entstanden, die an einzelnen Hochschulstandorten, aber auch hochschulübergreifend Lehrenden zur Verfügung stehen, um dort ihr Material zu veröffentlichen. Es wurden 37 dieser Repositorien untersucht. Darüber hinaus wurde auch die Videoplattform YouTube nach soziologischem Lehr-und Lernmaterial durchforstet. Der Beitrag stellt den Zeitverlauf und die Akteur:innen der OER-Veröffentlichungen dar. Anschließend soll mithilfe eines praxistheoretischen Vokabulars die Lehre innerhalb der Soziologie aufgeschlüsselt und ein möglicher Bezug zu den empirischen Ergebnissen hergestellt werden.

<jats:p>In diesem Beitrag wird die ‚What Works‘-Debatte in der Sozialen Arbeit um die zentrale Frage nach Wirkfaktoren erweitert. Der empirische Nachweis von Wirkfaktoren in sozialarbeiterischen Interventionen ist bis heute ein Desiderat. Vor dem Hintergrund der Realist Evaluation werden in diesem Beitrag relevante Wirkfaktoren (Kontexte und Mechanismen) herausgearbeitet. Datengrundlage stellt eine Onlinebefragung von 200 fallführenden Fachpersonen in vier sozialarbeiterischen Handlungsfeldern in der deutschsprachigen Schweiz dar (Arbeitsintegration, Bewährungshilfe, Schuldnerberatung, Sozialhilfe). Die Ergebnisse verweisen auf signifi kante Wirkfaktoren von erfolgreichen Interventionen, u.a. Arbeitsstile der Fachpersonen und Verhaltensmerkmale der Klient(inn)en und können in einem allgemeinen Wirkungsmodell mit handlungsfeldübergreifenden Outcomes verdichtet werden. Diese Erkenntnisse leisten einen Beitrag zur Professionalisierung der Sozialen Arbeit sowie zur Konstruktion von Wirkungsmodellen und sollen zukünftige weitere Forschungsvorhaben in diese Richtung anregen.</jats:p>

<jats:p>Academics may actively respond to the expectations of the academic status market, which have largely been shaped by the World University Rankings (WURs). This study empirically examines how academics’ citation patterns have changed in response to the rise of an “evaluation environment” in academia. We regard the WURs to be a macro-level trigger for cementing a bibliometric-based evaluation environment in academia. Our analyses of citation patterns in papers published in two higher education journals explicitly considered three distinct periods: the pre-WURs (1990–2003), the period of WURs implementation (2004–2010), and the period of adaption to WURs (2011–2017). We applied the nonparametric Kaplan–Meier method to compare first-citation speeds of papers published across the three periods. We found that not only has first-citation speed become faster, but first-citation probability has also increased following the emergence of the WURs. Applying Cox proportional hazard models to first-citation probabilities, we identified journal impact factors and third-party funding as factors influencing first-citation probability, while other author- and paper-related factors showed limited effects. We also found that the general effects of different factors on first-citation speeds have changed with the emergence of the WURs. The findings expand our understanding of the citation patterns of academics in the rise of WURs and provide practical grounds for research policy as well as higher education policy.</jats:p>

Due to the Corona crisis, German Higher Education Institutions had to close their campuses in March and lecturers had to teach online. To understand how the Corona crisis affected students, first this article explains the structural and social inequalities in the German higher education system, using Tinto's (1975; 1997) student engagement theory. Second, the concept of Bergman-Rosamond et al. (2020) is used to analyze the challenges that Corona has raised for students, including current surveys. We found that the closure of the social space campus (and the Corona crisis as a whole) particularly hit hard those students who had previously been affected by (intersectional) inequality. Therefore, to lessen the specific challenges associated with the ad hoc transition to digital studying, the creation of a digital community of learning can help. We demonstrate how such a community can be created by the example seminar, "Digital practices: an autoethnographic observation". During the seminar, students recorded their digital technology use in a journal, and we analyzed the diary entries using the collaborate autoethnography method. The seminar example shows that this method is well suited for the development of a community of learning as it not only places students in the spotlight but as students work together on a topic they get to know each other, and a basis of trust is created through peer-feedback. Therefore, it was important to have a digital space (in this case Mahara) where the exchange could take place. The continuous insight into the students’ "learning status" enabled the lecturer to promote the learning and provide individual assistance for the students.

Through co-occurrence analysis of 1139 documents (1964-2018) we identified trends in the discussions about the implementation of student teaching evaluation (SET). We found that: (1) Attention to SET originated in the US in the 1970s, spreading to German-speaking countries in the mid-1990s and continuing in China and Latin America in the early 2000s. (2) SET is commonly viewed as a control tool deserving methodological improvement, while bias is debated in the US. We also found local trajectories: (3) Whereas in the US and Latin America SET is primarily seen as a management tool, German-speaking and Chinese authors reflect more on improving teaching. Chinese scholars consider SET a valid instrument for state control associated with artificial intelligence. Also, (4) SET is commonly used in medical education in the US and the German-speaking region and in physical education in China. We conclude that SET is discussed cross-nationally but affected by national path dependencies.

<jats:p>Openness in science and education is increasing in importance within the digital knowledge society. So far, less attention has been paid to teaching Open Science in bachelor’s degrees or in qualitative methods. Therefore, the aim of this article is to use a seminar example to explore what Open Science practices can be taught in qualitative research and how digital tools can be involved. The seminar focused on the following practices: Open data practices, the practice of using the free and open source tool “Collaborative online Interpretation, the practice of participating, cooperating, collaborating and contributing through participatory technologies and in social (based) networks. To learn Open Science practices, the students were involved in a qualitative research project about “Use of digital technologies for the study and habitus of students”. The study shows the practices of Open Data are easy to teach, whereas the use of free and open source tools and participatory technologies for collaboration, participation, cooperation and contribution is more difficult. In addition, a cultural shift would have to take place within German universities to promote Open Science practices in general.</jats:p>

<jats:p>Ausgehend von den fünf Schulen von Open Science von Fecher und Friesicke (2014) findet in diesem Beitrag eine Reflexion eines qualitativen Open Science-Forschungsprojektes statt. Mit der Reflexion wird der Offenlegung und Transparenz, die Open Science-Projekten immanent ist, entsprochen. Es soll aber auch zukünftigen Forscherinnen und Forschern, die überlegen ein Open Science Projekt zu starten, dabei helfen mögliche Hürden aber auch Lösungswege zu antizipieren. Als Reflexionsbeispiel dient das Projekt «Nutzung digitaler Medien und Habitus von Studierenden», das auf folgenden fünf Ebenen betrachtet wird: Ebene der Wissensproduktion; Ebene der freien Zugänglichkeit von Wissen; Ebene der Infrastruktur; Ebene der kollaborativen Forschung und Ebene der Impakt-Messung.</jats:p>

Apart from teaching, research and service to society, since 2015 higher education systems and institutions in Europe have faced an additional expectation – to respond to the largely unexpected yet nevertheless growing demand for higher education by refugees. This study explores system and organizational level responses to such environmental pressures in Germany and Flanders, both affluent systems, but different in terms of size, attractiveness as destination and the extent to which their languages are widely spoken. Relying primarily on document analysis and interviews, the study highlights three elements of policy dynamics: policy styles, main drivers, and extent of involvement of non-state actors. While, as expected, in both systems the dynamics were re-active, solution-driven, and with strong involvement of non-state actors, contrary to expectations both countries responded primarily in a bottom-up manner. The study provides a conceptual tool and a first empirical insight into this novel phenomenon.

This article examines the normative roots of criteria used for the accreditation of study programs in German higher education based on the orders of worth framework by Boltanski and Thévenot (On justification. Economies of worth, Princeton University Press, Princeton, 2006). From 1999 to 2017, the criteria have been subject to continuous efforts of legitimation, especially by the German Länder, which are in charge of public higher education in Germany. The empirical analysis shows that industrial (e.g., ‘standardization’), civic (e.g., ‘gender justice and equal opportunities’), and civic-industrial (e.g., ‘employability’) codings are the core of accreditation criteria. The normativity of these criteria constitutes accreditation as a technical arrangement running (a) a structural program (e.g., qualifications of academic teachers, modularization of study programs, and quality management) and (b) a political program (e.g., diversity of students and system of studies). Based on the empirical analysis, it is concluded that X does not stand for the accreditation of quality X. X stands for the accreditation of X qualities for specific normative purposes via the higher education accreditation regime.