Renate Strazdina

Quality of study programs: an ecosystems perspective

The quality of study programs is one of the issues that are essential in the turbulent global environment universities nowadays operate in. Quality may be considered in terms of different quality standards trying to follow their guidelines formally and practically. This paper takes a different view of the quality issue with respect to the study programs in the field of engineering, namely, the quality of the study program is considered from the ecosystem perspective and value exchange between different members of the ecosystem is taken as a central object of interest in defining and supporting the high quality of the program. While analysis of value exchange and detection of changes in the value provision and request are not a natural part of the university teaching process, appropriate models and support systems can help to understand the value exchange process in the educational ecosystem. The understanding of the value exchange process, in turn, helps to identify and monitor knowledge requirements for developing high quality study programs.

Knowledge Requirements Monitoring System: Advantages for Industry and University

Nowadays, graduates have a wide range of opportunities when they are thinking about their further education and it is difficult to choose whether it would be better to go one way or another. One of the most important drivers for the final decision is whether the study program chosen can lead to a good and interesting job in the future. That means that Universities have to reflect the answer to this question in the description of the study programs, but in order to do this they have to know what the main requirements from the Industry are. This paper, building upon the previous research showing that a knowledge requirements monitoring system and the processes behind it can improve the quality of study programs, focuses on application of the monitoring system for extracting and representing industrial requirements using skill frameworks and direct and indirect course and topic rating systems.

Statistical Analysis for Supporting Inter-Institutional Knowledge Flows in the Context of Educational System

Inter-institutional networks become more and more important for today’s organizations. Despite mostly business-oriented organizations recognizing the possibilities that come with these networks, academic and educational systems are a typical example of inter-institutional network, and viewing these institutions as elements of a single network would yield positive results for all the parties. However, there is almost no research on the educational system as an inter-institutional network, especially in information system development education. The purpose of this chapter is to consider the education system as an inter-institutional network and to define the feedbacks existing within it in order to improve the network’s overall performance. Besides this the purpose is to find the data sets required for feedbacks analysis and appropriate methods for data analysis.

Configurative Alignment of Business and Application Services: A Work Systems Perspective

There are different ways of defining business and IT alignment. On one end it is possible to look at the alignment from the strategic perspective; on another end we can go down to the small granularity manual and software functions to see how they are related via human-computer interfaces. In this paper we take a work systems perspective in addressing the alignment between business and IT. In particular, we consider service systems by describing the services at several levels of granularity where they can be instantiated in manual, semi-automatic, and automatic modes of functioning. This perspective helps to address some design challenges for flexible work systems that require intention- and situation-dependent alignment between human and artificial work to manage multiple options of heterogeneous service configurations. The proposed alignment approach is illustrated by education demand and offer correspondence monitoring services.

Change Management for Fractal Enterprises

Change management is an important process enabling the definition of a successful enterprise strategy and operations—especially in a turbulent environment. A number of methodologies are available for change management; however none of those is designed specifically for fractal systems. Taking into consideration self-similarity; self-organization, goal-orientation, and dynamics and vitality of fractal systems, change management in such systems obviously requires organizational procedures that take account of the distinct properties of fractal systems. The purpose of this research is to define a change management methodology that would allow administering change management in fractal systems in general and apply it to a specific change situation when the primary object of the change is an information system of a fractal enterprise.

Capabilities and Challenges of Contemporary Service Based Monitoring Systems

New technology developments have opened opportunities to obtain more data from more sources as well as to handle a larger variety of forms of data. This, in turn, raises the interest in data and information monitoring in different business and engineering contexts. Thus monitoring systems obtain the role of subsystems in contemporary information and knowledge systems. Taking into consideration the quest for agility of business and information systems, the flexibility offered by service systems motivates the consideration of service based monitoring systems. In this paper capabilities and challenges of service based monitoring systems are discussed by considering several issues of analysis.