European Journal of Higher Education IT 2020-1

The role of information technology within higher education is changing radically with the progress of digital transformation. This implies significant changes in several areas. The focus has typically been in business change, in processes, and in modern digital technology. However, cultural aspects have recently been identified as the most important road blocker for organisations to take digital transformation forward. We have also seen how significant external events, such as the Covid-19 pandemic, can accelerate and redirect change at the cultural level.

This paper investigates the required cultural changes for digital transformation in the context of Higher Education. Firstly, we identify seven cultural elements that need to be addressed to cope with the change. Secondly, we provide a template that allows institutions to find the best approach for managing cultural change when introducing digital technologies. The template consists of four key areas: (1) reviewing the vision and the strategy, (2) managing change proactively and continuously, (3) navigating your way in the changing landscape, and (4) solving issues on the spot.

The goal of this paper is to introduce aspects of transfer (the third mission) into the digital infrastructure of a higher education institution (HEI). While there is little visibility of transfer characteristics in discussions on digital infrastructure, the political importance of this topic is growing. Therefore, our approach is to extend the infrastructure of HEIs with features from modern data analytics. We identified sources relevant for transfer and visualize them in a dashboard. As a first step, we designed descriptive or diagnostic components for the different fields of transfer. Building on this, next steps towards predictive components are discussed.

“Digitalisation” is a ubiquitous theme at every university. Since by now literally all aspects of university work and life depend on IT and, in particular, on data, the availability and persistence of data and data services is essential. As trivial as this appears, scientific users need to rely on the availability of their data and data stores, either for using previously stored data or to run experiments that generate new data. This includes all aspects, from the availability to persistency.

Since in many cases access to the data happens in a tiered IT setup, there is no way of “direct” access to the data but a suitable – often server-based – software stack has to be up and running as well. Plus, it’s not “a” software stack but a vast multitude. Therefore, the mentioned requirements go beyond bitstream preservation but include the infrastructure to access the information.

In addition, the justified expectation of all users is an (almost) 24×7-availability of services, and, in particular, an assured persistency of once-stored data. So, data services have to be invisible in the sense that they are expected to be ubiquitously and continuously available. Any “visibility” can be regarded as a disturbance of this expectation.

To cope with this combination of amounts of data, level of expectation, and technical multitude and a concurrent steady growth in all of these dimensions, a consortium of universities in North-Rhine Westphalia currently runs a project to develop structures for joint, university-spanning services for safe data storage and high storage and server availability.

In this paper we report on a model and experiences in designing digital higher education. Our case is Aalto Online Learning—an Aalto University wide strategic initiative for educational development. Since the kickstart in the year 2016, our activities have been to create online and blended learning experience designs, related learning materials and media, and as its foremost ambition, to transform and improve the educational setting and structures of the university and beyond. Instead of starting from a single platform or technology with all of its constraints, Aalto Online Learning starts from ideas to improve learning, and selects or develops a design to bring the idea to reality in an agile and collaborative activity. We have evaluated the whole process—from the call for idea proposals to funding, design, development and dissemination at courses—via nine consecutive rounds from early 2016 to early 2020. To overcome identified challenges in each round, we have clarified the model, introduced new training and production approaches, identified and ran online learning theme groups, and developed innovative tools and platforms. The model has been used to identify learning improvement ideas and to develop them into solutions for over 240 courses at Aalto University.

Social media platforms or other online services are often used for learning by students. Thereby, they (consciously or unconsciously) disclose personal information and metadata which are frequently used as part of business models. Even if universities provide similar services or innovative adaptive learning spaces, students seem to be rather restrained in sharing data. This hinders personalization and adaptation. There even seems to be a general problem with privacy attitudes stated in questionnaires and actual privacy behavior (“informational privacy paradox”). In order to investigate this gap, a preliminary study was conducted. The goal was to investigate the inner attitude of students towards the disclosure of personal data to commercial and non-commercial university services utilizing a so-called Implicit Association Test (IAT) based on the trust dimension. The results of the study show that there seems to be a moderate implicit positive attitude towards the university. Also, the impact of technology affinity on this implicit preference on trust was investigated. Here, only a slight tendency for a difference between the groups of technology affine and not affine students could be found. An exploratory data analysis showed a significant difference on the degree of the implicit preference towards the university regarding the enthusiasm for technology.