Refine
Has Fulltext
- yes (5) (remove)
Document Type
- Postprint (4)
- Monograph/Edited Volume (1)
Is part of the Bibliography
- yes (5)
Keywords
- digital learning (2)
- COVID-19 (1)
- Innovation (1)
- Innovationsprozess (1)
- KMU (1)
- Open Innovation (1)
- SME (1)
- TAM (1)
- advances in teaching and learning technologies (1)
- capabilities (1)
Vorliegender Leitfaden ist eines der Ergebnisse des Forschungsprojekts „Open Innovation in Life Sciences“ (OIL), das von Mai 2008 bis April 2011 an der Universität Potsdam durchgeführt wurde. Er nimmt für sich in Anspruch, gerade Innovationsmanager in kleinen und mittleren Unternehmen (KMU) der Pharmaindustrie bei der Einführung des Open Innovation Managements zu unterstützen. Zielsetzung des Forschungsprojekts war es, (1) die Chancen und Risiken von Open Innovation unter besonderer Berücksichtigung der Anforderungen von Pharma-KMU zu analysieren und (2) daraus abgeleitet ein Konzept zur Implementierung von Open Innovation bei Pharma-KMU zu entwickeln. Der Ausgangspunkt des Projektes war die Erkenntnis, dass die Life Sciences-Branche im Allgemeinen und die Pharmaindustrie im Besonderen durch eine steigende Komplexität der Innovationsprozesse und eine zunehmende Tendenz zu Kooperationen gekennzeichnet ist. Vor diesem Hintergrund eröffnet gerade der Open Innovation-Ansatz für die Pharmabranche neue Gestaltungs- und damit Wachstumsmöglichkeiten. Open Innovation – definiert als die planvolle Öffnung der Innovationsprozesse und die strategische Einbindung des Unternehmensumfelds – wird dabei als zentraler Erfolgsfaktor für die Innovationsfähigkeit beschrieben.
Recent research suggests that design thinking practices may foster the development of needed capabilities in new digitalised landscapes. However, existing publications represent individual contributions, and we lack a holistic understanding of the value of design thinking in a digital world. No review, to date, has offered a holistic retrospection of this research. In response, in this bibliometric review, we aim to shed light on the intellectual structure of multidisciplinary design thinking literature related to capabilities relevant to the digital world in higher education and business settings, highlight current trends and suggest further studies to advance theoretical and empirical underpinnings. Our study addresses this aim using bibliometric methods—bibliographic coupling and co-word analysis as they are particularly suitable for identifying current trends and future research priorities at the forefront of the research. Overall, bibliometric analyses of the publications dealing with the related topics published in the last 10 years (extracted from the Web of Science database) expose six trends and two possible future research developments highlighting the expanding scope of the design thinking scientific field related to capabilities required for the (more sustainable and human-centric) digital world. Relatedly, design thinking becomes a relevant approach to be included in higher education curricula and human resources training to prepare students and workers for the changing work demands. This paper is well-suited for education and business practitioners seeking to embed design thinking capabilities in their curricula and for design thinking and other scholars wanting to understand the field and possible directions for future research.
With the latest technological developments and associated new possibilities in teaching, the personalisation of learning is gaining more and more importance. It assumes that individual learning experiences and results could generally be improved when personal learning preferences are considered. To do justice to the complexity of the personalisation possibilities of teaching and learning processes, we illustrate the components of learning and teaching in the digital environment and their interdependencies in an initial model. Furthermore, in a pre-study, we investigate the relationships between the learner's ability to (digital) self-organise, the learner’s prior- knowledge learning in different variants of mode and learning outcomes as one part of this model. With this pre-study, we are taking the first step towards a holistic model of teaching and learning in digital environments.
Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.