Edited by Mandy Schiefner-Rohs, Sandra Hofhues and Andreas Breiter
Please submit your abstract until 31. July 2020 at https://www.medienpaed.com/about/submissions ein. Please also find the author guidelines there.
Call for Papers as PDF
Topic
Governance by numbers (Grek 2009; Hartong 2016) as well as the quantification of the social (Mau 2017) seem to have become a new paradigm for education policy and education administration. (Inter-)national school achievement tests, school inspections or (university) rankings are exemplary forms of educational governance with and through data or figures (for the school e.g. Altrichter 2010). Whereas data on learners and their performance has been generated primarily in the past, further data sources are being tapped explicitly or implicitly in the course of digitisation: Just think of learning software, which often serves as an explicit data source for research and practice design, or of the implicit “digital footprints” (or traces) that we all leave behind in software products and which can in principle be accessed from different sides. When data sets are linked together, Learning Analytics often plays a role against the background of the discussions about individualisation and digitisation - although this tendency is therefore viewed critically in the educational environment (e.g. Büching et al. 2019; Allert, Asmussen, and Richter 2018).
All the examples mentioned ultimately aim one thing: to optimize teaching and learning through data, numbers and, most recently, algorithms. The concept of datafication therefore takes up this target perspective in discourse. It exposes with all its might what is understood by data as visible tendencies in education, but especially in the context of school: Thus, on the one hand, digitisation there has led to a condensed, highly complex process of communication and interdependence management of people in their contexts of action. The social itself becomes an objectification of communicative action (Knoblauch 2017) and is to a large extent data-based and/or -controlled. On the other hand, new data-based practices are emerging that can be analysed, described, observed and reflected upon in schools in particular and in educational organisations in general. Moreover, data are increasingly being generated automatically as reference points for individual or collective, implicit or explicit decisions, so that the social is pointed to individual data points, numerical or threshold values and/or indices. Prietl and Houben (2018) even speak of a data society because of this obvious reduction of complexity.
From a media education perspective, data, figures and algorithms are used to raise various research perspectives and to ask questions of design, especially in the school context. They are settling in the educational organisations themselves, for example, by asking about the concrete structures of provision and measures in dealing with the data society in schools. They raise questions about interdisciplinary research and development in the school context, when only the interplay of (media) pedagogy and computer science can answer research questions in the field (e.g. Breiter and Jarke 2019). Moreover, there are many reasons for cooperation, but also for demarcations between politics, administration, educational organizations and people, and between data production and consumption (see Hartong 2016). (Inter-)nationally, the growing importance of social surveying practices, datafication and algorithms in the education sector can be followed (e.g. Boyd and Crawford 2012; Espeland and Stevens 2008; van Dijk 2014; Kitchin 2016; Selwyn 2016; Knox et al. 2019).
Translated with www.DeepL.com/Translator (free version) Data, so much can be gathered from discourse so far, describe not only social realities –they create or change them as a result of their mere availability or orientation to them. Thus, a behavioral control through algorithms can already be observed (e.g. Manolev, Sullivan, and Slee 2019), which is also (not only) to be reflected in media education. Contrary to naive assumptions, software or data infrastructures are not neutral - social relations and inequalities are technically inscribed in them (Dalton and Thatcher 2014; Fuller 2008; Kitchin and Lauriault 2014; Lachney, Babbitt, and Eglash 2016, Hartong 2020).
With the present call for papers we would like to give space to the above questions and discussions - be it on the level of theoretical reflections or concrete concepts or on the level of empirical studies. The following topics are of particularly interest:
Students and the automated measurement of their learning progress: Increasingly, (administration-oriented) school information systems are becoming compulsory due to school legislation. Data integration with learning management systems often allows the linking of learning levels, learning paths etc. with other data. The digital data collected for the systems and stored and processed in them can be used for short- to long-term decisions regarding the learning status of students. Examples from the USA and the UK show that the composition of classes or communication with parents can be “optimised”. School administration software, timetabling, electronic class books and/or digital tests etc. therefore pose ethical challenges by applying new power and control techniques as a result of data-based schools. On the research side, in contrast to other countries (e.g. UK, NL, USA), there are also gaps in Germany that need to be identified in the form of theoretical and conceptual contributions.
Auspicious promises of individualised learning opportunities: Learning Analytics with the promises of individualisation and personalisation of learning can be found in the educational context of schools as well as in other educational sectors, including teacher training, higher education or further education. In all areas, the data generated there can be linked with others, at least in principle – they thus allow “predictions” of an unimagined breadth. For example, the combination of data from learning management systems with geo-based data on the location of learners would make it possible to make predictions about learning success, as is already done for students, in order to determine their academic success (continued by Hartong 2019). The limitations of such promises and predictions as well as the roles of the (teaching) persons involved in them need to be examined.
Increasing measurement of organizational performance: In recent years, more and more data has been generated and evaluated in schools from the perspective of school development in order to generate knowledge about the strengths and weaknesses of individual schools and schools in comparison (e.g. Maag Merki and Altrichter 2010; Thiel et al. 2019). From this perspective, too, school information systems hold potential and reveal ambivalences, which, in conjunction with other systems, offer an in-depth look at school administration and organizational learning of individual schools or several schools. Implications are also to be assumed here, for example for organized learning processes or collective arrangements of organizing and learning in schools.
Self-optimization in the context of self-tracking: The independent collection and evaluation of data using one‘s own devices, some of which are worn on the body, opens up an ambivalent field between new educational experiences on the one hand and self-technologies on the other hand (e.g. Damberger 2019), which must be considered from a media-pedagogical research perspective. In addition, different devices allow self-tracking from the subjects (Gapski 2015; Damberger and Iske 2017; Biermann and Verständig 2017; Dander 2017, 2018; Rode and Stern 2019; von Felden 2020) and a form of self-empowerment. The ambivalences and limits inherent in this are to be named specifically for the context of school, insofar as these technologies of the self (Foucault 1993) are used there.
Approaches and forms of (school) data education. Since digitization leads to a changed way of dealing with cultural objects and the formation of new practices, alternative approaches to cultural education as well as data as media education are offered. From a media education perspective, alternative approaches to data formation (e.g. through artistic-aesthetic forms and/or theatre) should therefore be examined and considered in the design of schools (most recently Rat für kulturelle Bildung 2019; Jörissen 2019). While concepts of data literacies that are desired in terms of educational policy and economics are primarily information science and/or method-oriented and focus on individual subjects and areas, it is precisely the connections to traditional concepts of media competence and media education that need to be worked out from an emancipatory and critical perspective (e.g. Niesyto 2018).
The Special Issue thus summarises the question of how the ambivalent field between optimisation and surveying or between freedom and immaturity is manifested by data validation (not only) in schools. It is based on two premises: Firstly, an increasing relevance of different data is assumed, which also has an impact on the design of education (processes). Secondly, the issue assumes that this process affects all those involved in educational institutions. Data validation is thus becoming an increasing part of organisational culture and educationally motivated organisational development processes, which also include data-based communication structures, team development and knowledge management requirements. This results in a current need for research and reflection: the generation of data and its extraction in the context of schools must be critically discussed. In addition, the implications of this for educational processes as well as for research on them need to be reflected upon. Thus, the process of data validation also facilitates the further development of empirical research methods, which, in view of the large number of implicit data-based decisions in particular, require greater attention (see Mayerl and Zweig 2016, Fromme et al. 2020). Finally, there is an ongoing need to position itself as a school for processes of datafication.
Contributions
This call for submissions is interested in those contributions and submissions that address comprehensive and overarching questions of datafication with a closer or broader relation to the school and that address these questions from the perspective of media education. The aim is to highlight a currently highly relevant but so far little studied topic. Both theoretical-conceptual and empirical contributions are welcome. The following questions can be used as examples to tie in with the above-mentioned topics:
- Students and the automated measurement of their learning progress: What are the multilateral benefits of school information systems? Which applications in connection with data validation are seen in schools? Which scenarios for research and investigation of these are currently conceivable and will be in the future? What are the implications of the increasing aggregation of data for the learning of students and the educational activities of teachers? How does datafication change pedagogical practices?
- Promising promises of individualized learning opportunities: What significance do data have in the everyday life of teachers and (school) management? How does the relationship between individualised, data-based learning offers and collective learning processes change in schools? What implications do data have for aspects of social inequality and educational disadvantage in and of schools?
- Measurement of organisational action: How can software development be in line with organisational development? What are the special features of data-based administration and learning systems in general and school information systems in particular? What is the relationship between digitised New Public Management and data-driven school improvement? How can data possibly change teaching and organisational cultures?
- Self-optimization in the light of self-tracking: Which data practices can be observed in schools and educational organizations? How can they be explained? What implications do they have for participation and educational processes in schools?
- Access and forms of (school) data formation: Which groups of people are addressed by data and media education in schools? Which images of human beings are drawn with the help of data education in schools? How does the educational organisation school talk about data retrieval? What do teachers, management personnel, pedagogical staff or learners themselves know about their data-supported educational organisation? What procedures are identified for taking data protection into account and for dealing with algorithmic bias?
We invite scientists, educational practitioners and media educators, to submit abstracts of up to 1200 characters in electronic form by 31.07.2020 at: https://www.medienpaed.com/about/submissions. The editors will inform about the preliminary acceptance of the contribution by 15.09.2020.
Full texts must be submitted by 01.01.2021 and will then be reviewed in a double-blind peer-review. Contributions should be written according to the instructions for manuscript submission (http://www.medienpaed.com/about/submissions#authorGuidelines).
Submission
Via:
https://www.medienpaed.com/about/submissions
Deadline for abstracts: 31 July 2020
Publication:
Special issue of the journal MedienPädagogik
Note:
Please prepare full texts to timely submit upon notification.
Contributions submitted in English or German should be original and should not be under consideration elsewhere. The total character count should be less than 40.000 characters (including spaces, without abstract, and without references). A narrative abstract of 150–200 words briefly describes the main issues, significant results and conclusions. Contributions must be submitted with an English and German title and abstract.
Editors
- Mandy Schiefner-Rohs (TU Kaiserslautern)
- Sanda Hofhues (Universität zu Köln),
- Andreas Breiter (ifib and Universität Bremen)
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