Fachtagung Verwaltungsinformatik FTVI, Fachtagung Rechtsinformatik FTRI

Mathematical modeling describes the processes being performed by people who try to solve real world problems mathematically or who try to solve mathematical word problems. The literature on mathematical modeling is based on the so-called modeling cycle (Blum, 2003), which consists of five substages, that describe the course of the problem-solving process. As a first step (Structuring), the problem situation is being understood by the modeler and the most crucial elements of the problem are identified. The modeler then translates those elements to a mathematical language (Mathematising), where they are now presented in the form of equations, numbers, operators and symbols, i.e. in the form of a mathematical model. In the third step (Solving), the model is used to come to a mathematical solution to the problem, which in the next step (Interpretation) is then re-translated into real-world information and gives an answer to the question that has been raised in the problem. The last step describes the Validation of the whole problem-solving process. If the modeler comes to the conclusion that his solution is wrong or not optimal, the modeling cycle starts from the beginning. The modeling cycle functions as a descriptive model of modeling processes, because it describes how modeling is carried out by students. On the other hand, it also functions as a normative model, because it makes prescriptions on how one should behave, when solving problems mathematically. However, there do not exist any empirical studies to prove neither the descriptive nor the normative character of the modeling cycle. This thesis shows, that the suitability as a descriptive model can only be affirmed with restrictions. Validation could not be observed in any of the subjects taking part in the first study and the sequence of the remaining four processes also diverged from the theoretically postulated order. A revised version of the modeling cycle as a recursive model is therefore proposed. In the second study, the suitability as a normative model was explored, by separately assessing the four processes Structuring, Mathematising, Solving and Interpretation with newly designed items. The four scales were validated with several criteria, one of them the ability to solve modeling tasks, which confirms the normative function of the modeling cycle. In order to help promote modeling competency in young learners, it is necessary to find ways for diagnosing modeling competency as early as at the end of primary school. By generating items for the four sub-competencies Structuring, Mathematising, Solving and Interpretation a basis has been founded to do this in an objective, reliabel and valid way.

The novel mobile application csxPOI (short for: collaborative, semantic, and context-aware points-of-interest) enables its users to collaboratively create, share, and modify semantic points of interest (POI). Semantic POIs describe geographic places with explicit semantic properties of a collaboratively created ontology. As the ontology includes multiple subclassiffcations and instantiations and as it links to DBpedia, the richness of annotation goes far beyond mere textual annotations such as tags. With the intuitive interface of csxPOI, users can easily create, delete, and modify their POIs and those shared by others. Thereby, the users adapt the structure of the ontology underlying the semantic annotations of the POIs. Data mining techniques are employed to cluster and thus improve the quality of the collaboratively created POIs. The semantic POIs and collaborative POI ontology are published as Linked Open Data.

Innovation can help a forward-looking company to rise up very quickly, furthermore, innovative products and services bring a company to a stage where it can win new segments of customers and be ahead of the competition. For their innovation process, the companies can distinguish between open and closed innovation. In this case, we will focus on open innovation and how companies share their innovation processes for the benefit of the company. They use information and innovation systems to define their innovation process, as well as, track innovative ideas and the phase of their development. There are always pros and cons when it comes to open innovation processes in an organization. We will try to look at certain examples in the business world to illustrate how good or bad an open innovation process can be for a company. In this Bachelor thesis, we will try to point out the essential criteria for an open innovation process and illustrate companies which have used open innovation processes. In some cases it went successfully and for some companies it went unsuccessfully.

In der aktuellen Hochschullandschaft findet man hauptsächlich die Unterrichtsform des Frontalunterrichts. Das bedeutet, der Lehrende hält während der Vorlesungszeit einen monologartigen Vortrag über den Unterrichtsstoff. Hierbei nehmen die Studenten nur passiv am Geschehen teil bzw. protokollieren das vom Professor Vorgetragene um es später zu Hause eigenständig nachzuarbeiten. E-Learning hingegen lässt den Lernenden aktiv Einfluss darauf nehmen, wie und in welchem Tempo er Lehrinhalte bearbeitet. In dieser Studienarbeit soll ein E-Learning-Kurs für den Themenbereich der Computergrafik erstellt werden. Die Arbeit besteht aus drei Teilen. Neben dieser schriftlichen Ausarbeitung habe ich einen E-Learning-Kurs mit Hilfe des Learning Management Systems WebCT1erstellt und hierfür zwei Applets erstellt, die Übungsaufgaben zu den Themen Koordinatentransformationen und Szenegraphen erstellen.