Information on individual educational components (ECTS-Course descriptions) per semester
|Degree programme:||Master Sustainable Energy Systems|
|Type of degree:||FH Master´s Degree Programme|
|Winter Semester 2021|
|Course unit title||Research Project: Business Informatics|
|Course unit code||800101022901|
|Language of instruction||German / English|
|Type of course unit (compulsory, optional)||Elective|
|Semester when the course unit is delivered||Winter Semester 2021|
|Teaching hours per week||4|
|Year of study||2021|
|Number of ECTS credits allocated||Second Cycle (Master)|
|Number of ECTS credits allocated||6|
|Name of lecturer(s)||Martin DOBLER|
|Prerequisites and co-requisites|
Participating students must have an interest in scientific processes and research in general. In addition, the students have to work independently, especially when defining research questions relevant to them, to active participation in the elaboration of the content that contributes to solving the research questions.
Prerequisites for the participation are, beforehand, an application to the coach of the research project and an accompanying discussion before the beginning of the course in order to identify possible topics and interests. For the AI topic basic programming knowledge is required.
This research project relates to the current BI research projects KMUDigital i4Production and DataKMU and also refers to the completed research projects iCargo and EURIDICE.
Numerous initiatives, (research) projects and teaching programs at the international, EU and regional levels are currently dealing with the so-called Digital Transformation, i.e. the change from traditional business activities, processes and competencies to fully or partially digitalized models and forms of organization in which significant innovations can be achieved in the short term and, from a strategic perspective, also in the longer term. Digital transformation is a motor for a wide range of processes in society - including industry - and is ultimately aimed at moving away from traditional, rigid ways of thinking in order to shape the future strategically in a targeted manner according to predefined goals with the help of ICT (information and communication technologies).
The learning results of this module are partitioned.
On the one hand, students will learn to apply scientific (applied) research questions. This includes the formulation of research questions, selection of the research method - from qualitative to quantitative methods to the use of specific, relevant IT tools -, presentation of the research contents in presentations or publications and the execution of a research process (theses, falsification, experiments, etc.).
On the other hand, students will learn about the content of current research projects at the Research Centre Business Informatics (BI). Topical overlaps with other research centres are quite possible. The module also provides students with an international environment for science. On the one hand by a diverse team in the BI, on the other hand by the inclusion of a large number of cooperation partners within the consortium projects of the BI in the (EU) foreign country.
The detailed, scientific learning results are documented individually with the students before the start of the course as part of the formulation of the research questions.
|Planned learning activities and teaching methods|
Activation: The students take responsibility for the research and learning process by introducing their own perspectives in the jointly discussed research map (context) and raising questions. They should be able to incorporate their own ideas into the research question.
The module is a research project within the framework of the module library - see also description of the context study format.
|Assessment methods and criteria|
The criteria for the assessment will be clarified individually with the students in a preliminary interview and defined within the scientific context.
For the evaluation, the project results and quality of the scientific approach are used. Any scientific publication or in-house presentations (overlapping with other Research Centres or within the Research Centre) are included in the assessment.
An assessment of the final presentation of the project results rounds off the assessment criteria.
This module constitutes the second cycle of the module "Research Project: Process Engineering" which has been started under the same title in the precedent summer term.
In addition, the research project also offers the possibility of a scientific publication (conference or journal) in cooperation with the FZ BI.
|Recommended or required reading|
* O. Ganschar, et al., „Produktionsarbeit der Zukunft-Industrie 4.0“. D. Spath (Ed.). Stuttgart: Fraunhofer Verlag (2013).
* European Communities. Europe 2020 – “A strategy for smart, sustainable and inclusive growth”, Communication from the European Commission. Brussels, Belgium. Available online at ec.europa.eu/europe2020
* M. Huschebeck, et al., “Intelligent Cargo Systems Study (ICSS): Impact assessment study on the introduction of intelligent cargo systems in transport logistics industry”, European Communities (2009)
* M. Dobler and J. Schumacher, “Towards a Pan-European Ecosystem for Intelligent Cargo”, Proceedings of 9th ITS European Congress 2013, Dublin, Ireland (2013)
* B. Holtkamp, S. Steinbuss, and Heiko Gsell, “Towards a Logistics Cloud”, Proceedings of the Sixth International Conference on Semantics Knowledge and Grid (SKG) 2010 (2010).
* M. Huschebeck, et al., “Intelligent Cargo Systems Study (ICSS): Impact assessment study on the introduction of intelligent cargo systems in transport logistics industry,” European Communities (2009)
* K. Ashton, “That Internet of Things Thing: In the real world, things matter more than ideas”, RFID Journal.
* D. Evans, “The Internet of Everything: How More Relevant and Valuable Connections Will Change the World” (2012), available online at www.cisco.com/web/about/ac79/docs/innov/IoE.pdf
* G. Halbritter, T. Fleischer, and C. Kupsch, "Strategien für Verkehrsinnovationen. Umsetzungsbedingungen – Verkehrstelematik – internationale Erfahrungen” (2008), Edition Sigma, Berlin.
* P. Ballon, et al., “Future Internet Public Private Partnership: Towards FI-PPP Innovation and Business Ecosystems”, available at: www.fi-ppp.eu/white-paper-published-on-fi-ppp-innovation-and-business-ecosystems/
Introductory Literature for AI:
* S. Russel and P. Norvig, "Artificial Intelligence: A Modern Approach", Pearson, 2020, ISBN 978-9-13-461099-3
* F. Provost and T. Fawcett, "Data Science for Business", O'Reilly, 2013, ISBN 978-1-44-93-6132-7
* I. Goodfellow et al., "Deep Learning", MIT Press, 2017, ISBN 978-0-262-03561-3
* C. Monar, "Interpretable Machine Learning", Leanpub, 2018
* R. S. Sutton and A. G. Barto, "Reinforcement Learning: An Introduction", MIT Press, 2018, ISBN 978-0-262-35270-3
* G. James et al., "An Introduction to Statistical Learning, Springer 2013, ISBN 978-1-4614-7137-0
|Mode of delivery (face-to-face, distance learning)|
The topic is split into didactic sections.