Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen


Dennerlein Sebastian, Pammer-Schindler Viktoria, Maitz Katharina, Ebner Markus, Getzinger Günter, Ebner Martin

TEL Marketplace – A Sandpit- and Co-Design-informed Innovation Process for Implementing TEL Research in Higher Education

International Conference on Human-Centered Digitalization - Workshop: Innovating Digital Education and Skills in Different Cultures, on a Global Scope and in an Interdisciplinary Context , 2019

Innovating digital education in a sustainable manner requires a human-centered approach. Perspectives of all relevant stakeholders must be respected in a responsible innovation process to address actual problems in teaching as well as learning and increase acceptance of a Technology-Enhanced-Learning (TEL) solution. In higher education, this requires an interdisciplinary iterative co-design process including researchers, teachers, students and all other university institutions and their representatives being affected by the digital teaching and/or learning innovation. We suggest an innovation process called TEL Marketplace following the idea of a sandpit or idealab. First, it offers a place for exchange in form of a f2f-marketplace, where researchers present their TEL innovations for discussion, problem-mapping and team formation with lecturers and students. Second, a two-step process takes place consisting of a competitive call for the distribution of funding among the submissions and a cooperative innovation phase for co-creation of the TEL solutions in the selected innovation-teams before implementing and evaluating them in university courses. For the cooperative innovation process, we developed a “University Innovation Canvas” that serves as a boundary object for the interdisciplinary innovation-teams and triggers reflection about important factors to be respected for a sustainable implementation. Thereby, the canvas represents a ‘living document’ evolving alongside the innovation process and allowing for targeted feedback and support. The end of the TEL Marketplace represents the beginning of the next iteration. Previously funded projects provide input for new projects and, at the same time, can apply for another round of funding with new goals. The maturity of the developed innovations then informs the decision for continuation or standardization. The TEL Marketplace, therefore, aims at leveraging existing research results and establishing a living community of practice, whilst preventing to fund “research for the sake of research” and reaching punctual impact, only.

Adolfo Ruiz Calleja, Dennerlein Sebastian, Kowald Dominik, Theiler Dieter, Lex Elisabeth, Tobias Ley

An Infrastructure for Workplace Learning Analytics: Tracing Knowledge Creation with the Social Semantic Server

Journal of Learning Analytics, Society for Learning Analytics Research (SoLAR), UTS ePress , 2019

In this paper, we propose the Social Semantic Server (SSS) as a service-based infrastructure for workplace andprofessional Learning Analytics (LA). The design and development of the SSS has evolved over 8 years, startingwith an analysis of workplace learning inspired by knowledge creation theories and its application in differentcontexts. The SSS collects data from workplace learning tools, integrates it into a common data model based ona semantically-enriched Artifact-Actor Network and offers it back for LA applications to exploit the data. Further,the SSS design promotes its flexibility in order to be adapted to different workplace learning situations. Thispaper contributes by systematizing the derivation of requirements for the SSS according to the knowledge creationtheories, and the support offered across a number of different learning tools and LA applications integrated to it.It also shows evidence for the usefulness of the SSS extracted from four authentic workplace learning situationsinvolving 57 participants. The evaluation results indicate that the SSS satisfactorily supports decision making indiverse workplace learning situations and allow us to reflect on the importance of the knowledge creation theoriesfor such analysis.

Breitfuß Gert, Fruhwirth Michael, Pammer-Schindler Viktoria, Stern Hermann, Dennerlein Sebastian

The Data-Driven Business Value Matrix - A Classification Scheme for Data-Driven Business Models

32nd Bled eConference, University of Maribor, Faculty of Organizational Sciences, HUMANIZING TECHNOLOGY FOR A SUSTAINABLE SOCIETY JUNE 16 – 19, 2019, BLED, SLOVENIA,, Andreja Pucihar, PhD, et al., University of Maribor Press, Bled, Slovenia, 2019

Increasing digitization is generating more and more data in all areas ofbusiness. Modern analytical methods open up these large amounts of data forbusiness value creation. Expected business value ranges from process optimizationsuch as reduction of maintenance work and strategic decision support to businessmodel innovation. In the development of a data-driven business model, it is usefulto conceptualise elements of data-driven business models in order to differentiateand compare between examples of a data-driven business model and to think ofopportunities for using data to innovate an existing or design a new businessmodel. The goal of this paper is to identify a conceptual tool that supports datadrivenbusiness model innovation in a similar manner: We applied three existingclassification schemes to differentiate between data-driven business models basedon 30 examples for data-driven business model innovations. Subsequently, wepresent the strength and weaknesses of every scheme to identify possible blindspots for gaining business value out of data-driven activities. Following thisdiscussion, we outline a new classification scheme. The newly developed schemecombines all positive aspects from the three analysed classification models andresolves the identified weaknesses.
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