What is your digital daily habit
The creeping process of digitization of universities
"Without the universities themselves being aware of it, they have become data and software-driven institutions. This means they use complex software systems in many areas in which large amounts of data are generated without this data (apart from research) being subjected to an evaluation become." Dr. Hubertus Neuhausen, Director of the University and City Library Cologne and member of the ad-hoc AG “Higher Education for the Digital Age in the European Context”, explains his view of the influence of gradual digitization on processes at universities.
1) Digitization and universities
If you look at complex organizations such as universities, there are a multitude of perspectives on how they can be viewed meaningfully and profitably. In this article, the term digitization is mainly used in connection with processes. When one speaks of the digitization of universities, it means that the essential processes of a university such as teaching and research as well as the operation of an extensive infrastructure are increasingly being carried out with the help of software, data and the necessary hardware. The complexity of these software systems continues to increase. At first glance, that sounds very trivial, downright banal, but this development has a significant impact on our everyday lives as well as on the everyday life of universities.
We usually do not notice these changes. They happen gradually and creep into the daily routine. The economist Richard Baldwin describes this process as "iPhone infiltration": Over the years, the iPhone has gradually expanded its range of services. We have built these services bit by bit into our everyday life, such as the online calendar, the mail function, the text messaging, the podcast and music app, etc., because they are very convenient and useful. Many people now feel helpless without their smartphone. Our behavior has changed significantly over the years without us even realizing this process as such (Baldwin, 2019 pp. 196-197). The thesis of this article is that - mutatis mutandis - it happened in the same way in universities.Image: [https://unsplash.com/photos/ewGMqs2tmJI Nathan Dumlao]
In a college there is usually three different "business areas" that follow different "logics":
- Academic teaching or training can be understood - very simply - as a "process business": Former students go through a clearly structured course of courses and leave the university as newly graduated academics.
- Scientific research can be understood - also very simply - as a "solution shop": A specific scientific question or problem is examined until a solution is found.
- Substantial infrastructures are necessary for universities to be able to provide teaching and research at all: They need administrations and they own properties. They operate libraries, computer centers and facilities such as university sports. A whole series of sub-organizations and a large number of employees are necessary for the university to function at all. One could speak of a “facilitated network” here - analogous to a fitness studio, the equipment of which can be used for a monthly fee.
Due to a habit that is almost 200 years old, we no longer perceive these three areas separately in a university (Christensen, 2012 min. 69-72). They interact with each other to a high degree and are mutually dependent.
2) Universities as "software landscapes"
Each of these three business areas digitizes itself in very different ways:
- In research, alongside the classic media of books and journals, software and data are increasingly appearing as results of research efforts. Big data analyzes and simulations are becoming legitimate research methods. Large software-based devices that produce large amounts of data, e.g. in the area of gene sequencing, are changing the research landscape. Even the humanities are taking energetic steps in this direction with the digital humanities (Expert Commission for Research and Innovation, 2019 p. 95-6; Deutsche Forschungsgemeinsschaft, 2018 p. 12-14; Gilch et al., 2019 p. 43-46; RfII - Rat für Information Infrastructures, 2016 pp. 9-18).
- To the extent that academic teaching implies research-based learning, digital instruments and methods penetrate university teaching. In addition to the classic teaching formats of lectures and seminars, there are new digital forms such as the inverted classroom (Gilch et al., 2019 pp. 49-54; Handke, 2014; Nacken, 2017).Image: [https://unsplash.com/photos/466ENaLuhLY Markus Spiske]
- A large part of the infrastructure is meanwhile implemented with the help of software systems, e.g. in the area of research management with research information systems (FIS), in the area of teaching and studies with campus management systems and e-learning platforms, in the area of administration with comprehensive administrative software as provided by SAP (Thillosen, 2017 min. 19-24).
Through this process, universities (also) become technical ecosystems (Hechler & Pasternack, 2017). Despite its disruptive character, the entire process of digitization as such is very rarely looked at and reflected upon by universities. A real discussion only takes place on the subject of digital teaching. Without the universities themselves noticing, they have become data and software-driven institutions. This means that they use complex software systems in many areas in which large amounts of data are generated without this data (apart from research) being subjected to an evaluation.
As a rule, these software tools have been introduced through the initiatives of interest groups to meet a specific need, or project funds are available that can be used for a specific occasion. Most of these initiatives were not embedded in an overarching strategy. This created a software landscape in many universities that consists of "silos"which are usually only very superficially linked. This means that there is a complex ecosystem of software that is not well integrated (Expert Commission for Research and Innovation, 2019 pp. 101-102; Hechler & Pasternack, 2017 pp. 10-14).
3) University as a specific type of organization and its effects on the different digitization speeds in the three "business areas"
All universities try to become like the few internationally outstanding top universities (Harvard and Stanford, Oxford and Cambridge, the ETH Zurich). Without making it explicit, universities in Germany also behave in the same way, not least in the excellence competition (Heine, 2019; Wiarda, 2016). The ideal is the research-oriented university with strong third-party funding, which trains its students close to research and, if possible, to become active scientists themselves (doctorate, habilitation). The research university is the guiding star for the university system, on which the entire system aligns itself in a competition for bigger and better, e.g. when the universities of applied sciences endeavor to obtain the right to award doctorates (Christensen & Eyring, 2011 p. XIX-XXX and 3-30; Willets, 2017 p. 3-4 , 36-39).
Image: [https://unsplash.com/photos/e3Uy4k7ooYk Davide Cantelli] If one considers universities as a specific type of organization, then universities have a much lower cohesion or a much lower degree of integrated structure than it appears from the outside . Clark Kerr, President of the University of California from 1958-1967, aptly described universities as "a series of faculty entrepreneurs held together by a common grievance over parking" (quoted from Willets, 2017, p. 34). Universities can be understood as a collection of science and research entrepreneurs and small businesses (projects, chairs and institutes)who want to prove themselves optimally and be successful in the great competition for career opportunities, financial resources and prestige, which is also science (Schimank, 2005 pp. 148-149).
This results in a number of consequences that are also very relevant for the different dynamics and speeds in the digitization of universities:
- The members of the university management were or are themselves successful science entrepreneurs, and they are elected by science entrepreneurs (Roessler, 2019; Symanski, 2012; Wiarda, 2019a). Decisions by university management are mainly made from this perspective: In a university's structure of priorities, research, especially cutting-edge research, has the highest priority.
- In all areas that their research concerns, the science entrepreneurs are highly agile and also integrate disruptive developments such as those resulting from digitization with the greatest willingness. As a result, research is digitizing at a very high speed: For example, the efforts within the framework of the National Research Data Infrastructure (NFDI) or the Medical Informatics Initiative should be mentioned here (Expert Commission Research and Innovation, 2019 p. 95-96; Deutsche Forschungsgemeinsschaft, 2018 p. 12- 14; Gilch et al., 2019 pp. 43-46).
- Because the same science entrepreneurs not only do research, but also teach and manage the university within the framework of self-administration, they permanently live in a state of structural overload. Therefore, questions of teaching, infrastructure and their digitization have a significantly lower priority and there is not the same agility in these areas as in research. In order to deal with their own resources economically, scientists * in the areas of teaching and infrastructure are often structurally conservative (Expert Commission Research and Innovation, 2019 p. 97-98; Gilch et al., 2019 p. 46-55; Persicke & Friedrich, 2016 p. 35-38).
In surveys, university management assigns great importance to the topic of digitization, but more intensive engagement with these questions has only begun in recent years (Expert Commission for Research and Innovation, 2019 p. 92-94; Gilch et al., 2019 p. 41-42, 63 -64, 98-100; Persicke & Friedrich, 2016 p. 38; Schmid, Lutz, Radomski, & Behrens, 2017 p. 23-30). Even if Chief Information Officers have increasingly been deployed in universities in recent years, university management often lacks a “digital” perspective, i.e. an awareness that digitization requires profound changes in all areas of universities.
In a somewhat pointed way, one can say that the digitization of universities is not just a technical project, i.e. the introduction of technical systems. It also requires a significant cultural change and extensive organizational development in the entire university system. A study has shown that at least three “digital savvy board members” are required in commercial enterprises in order to generate a sustainable and company-wide digital perspective on the board of a company (Weill, Apel, Woerner, & Banner, 2019). At this point it should not be diminished what has so far also been outstandingly achieved by the management of the universities in the field of digitization at many locations. But if you consider how the heads of university management are usually recruited, a "digital savvy“Rectorate or Presidium are more likely to be the exception (Rienhoff, 2017 Min. 24.26-25.55; Roessler, 2019; Wiarda, 2019a, 2019b).Image: [https://unsplash.com/photos/eMP4sYPJ9x0 Sharon McCutcheon]
Three "laws" of digital technology are already having an enormous transformative effect:
- Moore's Law: Since 1965, the performance of a computer chip has doubled approximately every 18 months.
- Gilder's Law: The rate at which data can be transferred is higher than the growth in the performance of processors in computers (Moore's Law). That has not proven to be entirely true, but the almost explosive increase in transmission performance has made the enormous access rates, for example on social networks or YouTube, possible in the first place.
- Varian's Law: From time to time new technologies emerge which provide a comprehensive set of components and new products can be created through repeated combinations of these components. Once these components are there, they set off a technology boom in which innovators work their way through the possibilities.
These “laws” are still in effect. This means that digitization will continue to advance at a high speed and a great dynamic of change will continue to affect our daily lives, the world of work and economic processes, and last but not least, universities (Baldwin, 2019, pp. 89-102; Friedman, 2016 Pp. 19-117). One consequence is that first in England, but increasingly also in Germany, the discussion begins about the extent to which universities are adequately preparing their graduates for a digitized world of work (e.g. Meyer-Guckel, Klier, Kirchherr & Winde, 2019; University UK, 2018).
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