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First year Business Administration students tend to regard themselves as “non-computer scientists” and often have a lack of motivation about taking IT courses in general, either because they perceive them as too technical, too difficult or somewhat irrelevant. In an attempt to counteract this perception and increase the levels of engagement and willing attendance to class, we decided to flip the traditional lecture model and develop a new teaching and learning approach for the IT Fundamentals course using an open source Enterprise Resource Planning (ERP) system as the platform from which to draw the various underlying IT concepts and through which the relevant competences can be acquired.
This paper describes the implementation process of this new contextualized learning framework “IT via ERP” and the changes in the didactical methods to support it.
The need for the logistics sector to timely respond to the increasing requirements of a globalised and digitalised world relies greatly on the com- petences and skills of its labour force. It becomes therefore essential to reinforce the cooperation between universities and business partners in the logistics and supply chain management fields across the European region and to build a logistics knowledge cluster supported by a communication and collaboration platform to foster continuous learning, skill acquisition and experience sharing anytime anywhere. In this paper we focus on designing the conceptual and technical framework for a communication and collaboration platform with the aim to establish the communication pipelines between the partner institutions, facilitating user interactions and exchange, leading to the creation of new knowledge and innovation in the logistics field. This framework is based on the requirements of the three main stakeholders: students, lecturers and companies, and consists of four functional areas defined according to the platform opera- tional requirements. A working prototype of the platform was developed using the Moodle learning management system and its core tools to determine its applicability and possible enhancement requirements. In the next stages of the project some additional tools like a knowledge base and the integration of the partners’ learning management systems to form the logistics knowledge cluster will be implemented.
Dos and Don’ts im Dashboard-Design: Wie Eyetracking-Verfahren bei der Datenvisualisierung helfen
(2016)
In this paper we present the concept of the "KI-Labor Südbaden" to support regional companies in the use of AI technologies. The approach is based on the "Periodic Table of AI" and is extended with both new dimensions for sustainability, and the impact of AI on the working environment. It is illustrated on the basis of three real-world use cases: 1. The detection of humans with lowresolution infrared (IR) images for collaborative robotics; 2. The use of machine data from specifically designed vehicles; 3. State-of-the-art Large Language Models (LLMs) applied to internal company documents. We explain the use cases, thereby demonstrating how to apply the Periodic Table of AI to structure AI applications.
Fallstudien sollen theoretische Lerninhalte zu Konzepten von Business Intelligence und Data Warehousing veranschaulichen und in einen praxisnahen Kontext bringen. Außerdem sollen Studierende umsetzungsorientierte Kompetenzen mit praxisrelevanten Systemen erwerben. Um diese Kompetenzen abzuprüfen und um die Auseinandersetzung mit Software und Konzepten zu vertiefen, haben sich Projekte als Ergänzung zu Fallstudien und Klausuren vielfach bewährt. Der Vortrag stellt dar, welche Möglichkeiten Dozierende im Rahmen der vom UCC zur Verfügung gestellten Plattform SAP Data Warehouse Cloud (SAP DWC) haben, um studentische Projekte zu Data Warehousing und Analytics durchzuführen. Der Autor berichtet über seine Erfahrung aus der Betreuung von über 30 Projekten mit SAP DWC aus verschiedenen Studiengängen seit 2020. Neben einer Übersicht über die von Studierenden gewählten Themen werden ausgewählte Projektergebnisse vorgestellt. Außerdem wird auf den Modus der Durchführung sowie existierende systemseitige Limitationen eingegangen. Für Dozierende, die mit ihren Studierenden eigene Projekte erfolgreich durchführen möchten, werden konkrete Hinweise und Maßnahmen dargestellt.
This paper describes the concept and some results of the project "Menschen Lernen Maschinelles Lernen" (Humans Learn Machine Learning, ML2) of the University of Applied Sciences Offenburg. It brings together students of different courses of study and practitioners from companies on the subject of Machine Learning. A mixture of blended learning and practical projects ensures a tight coupling of machine learning theory and application. The paper details the phases of ML2 and mentions two successful example projects.