Jüngling, Stephan

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Jüngling, Stephan

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A human aptitude test for object-oriented programming in the context of AI and machine learning

2020, Jüngling, Stephan, Telesko, Rainer, Dornberger, Rolf

Many current IT systems are implemented based on the object-oriented (OO) programming paradigm, which over more than two decades has proved to be one of the most successful mechanisms for code re-use and the most powerful extension mechanisms used in many software components and systems. Combined with a solid understanding of business principles and good communication skills, OO is still considered to be one of the core skills in the design of platforms and systems that drive our current IT landscape. The self-evaluation test, which we developed as an early indicator for prospective Business Information Technology (BIT) students, revealed insights about the skill level of beginners and serves as a starting point to reflect on abstraction skills in the context of the current digitalization and the increase in artificial intelligence (AI) components. The article explains the relevance of OO thinking on different levels of abstraction in the context of the lifecycle of current system architectures and provides an outlook on how these abstraction skills can be re-used when switching from an OO development paradigm into a new area where AI and machine learning will steadily increase their influence on the overall design of software systems.

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Towards an assistive and pattern learning-driven process modeling approach

2019, Laurenzi, Emanuele, Hinkelmann, Knut, Jüngling, Stephan, Montecchiari, Devid, Pande, Charuta, Martin, Andreas, Martin, Andreas, Hinkelmann, Knut, Gerber, Aurona, Lenat, Doug, van Harmelen, Frank, Clark, Peter

The practice of business process modeling not only requires modeling expertise but also significant domain expertise. Bringing the latter into an early stage of modeling contributes to design models that appropriately capture an underlying reality. For this, modeling experts and domain experts need to intensively cooperate, especially when the former are not experienced within the domain they are modeling. This results in a time-consuming and demanding engineering effort. To address this challenge, we propose a process modeling approach that assists domain experts in the creation and adaptation of process models. To get an appropriate assistance, the approach is driven by semantic patterns and learning. Semantic patterns are domain-specific and consist of process model fragments (or end-to-end process models), which are continuously learned from feedback from domain as well as process modeling experts. This enables to incorporate good practices of process modeling into the semantic patterns. To this end, both machine-learning and knowledge engineering techniques are employed, which allow the semantic patterns to adapt over time and thus to keep up with the evolution of process modeling in the different business domains.

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Checking the students aptitude for a bachelor program: experiences with a web-based tool

2018, Jüngling, Stephan, Telesko, Rainer, Reber, Andreas

Research Abstract: Checking the student’s aptitude for a Bachelor program: Experiences with a Web-based tool Research Objectives: In autumn 2014 the Bachelor program „Business Information Technology (BIT)” has been launched. BIT is about the application of information technology in business with the focus on building information systems. Since several terms, it can be observed that a considerable number of students faces difficulties in modules related to programming and mathematics at the beginning of the study. In order to monitor the aptitude of the program for beginners a project was launched with the aim to develop a method and a web-tool supporting the self-assessment related to indispensable competencies in the BIT program. Methodology: The aptitude test - built with Google Forms - currently consists of 31 predefined multiple choice questions and calculates an overall aptitude value and single aptitude values for the main categories logical and analytical thinking, understanding algorithms and abstract thinking. The questions are taken from well-established test systems like ELIGO-System, BOMAT, CASA etc. and are typically solved within less than 45 minutes. The students can check their suitability for the study programme by comparing their overall aptitude value with a given threshold. First test runs conducted with the tool confirm the validity of the aptitude test. The future scope will involve more students and deal with an analysis of concrete weaknesses that can be used as input to adapt the settings of programming and mathematics modules.

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Towards AI-based solutions in the system development lifecycle

2020, Jüngling, Stephan, Peraic, Martin, Martin, Andreas, Martin, Andreas, Hinkelmann, Knut, Fill, Hans-Georg, Gerber, Aurona, Lenat, Doug, Stolle, Reinhard, van Harmelen, Frank

Many teams across different industries and organizations explicitly apply agile methodologies such as Scrum in their system development lifecycle (SDLC). The choice of the technology stack, the programming language, or the decision whether AI solutions could be incorporated into the system design either is given by corporate guidelines or is chosen by the project team based on their individual skill set. The paper describes the business case of implementing an AI-based automatic passenger counting system for public transportation, shows preliminary results of the prototype using anonymous passenger recognition on the edge with the help of Google Coral devices.It shows how different solutions could be integrated with the help of rule base systems and how AI-based solutions could be established in the SDLC as valid and cost-saving alternatives to traditionally programmed software components.

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Leverage white-collar workers with AI

2019, Jüngling, Stephan, Hofer, Angelin, Martin, Andreas, Hinkelmann, Knut, Gerber, Aurona, Lenat, Doug, Clark, Peter

Based on the example of automated meeting minutes taking, the paper highlights the potential of optimizing the allocation of tasks between humans and machines to take the particular strengths and weaknesses of both into account. In order to combine the functionality of supervised and unsupervised machine learning with rule-based AI or traditionally programmed software components, the capabilities of AI-based system actors need to be incorporated into the system design process as early as possible.

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Combining symbolic and sub-symbolic AI in the context of education and learning

2020, Telesko, Rainer, Jüngling, Stephan, Gachnang, Phillip, Martin, Andreas, Hinkelmann, Knut, Fill, Hans-Georg, Gerber, Aurona, Lenat, Doug, Stolle, Reinhard, van Harmelen, Frank

Abstraction abilities are key to successfully mastering the Business Information Technology Programme (BIT) at the FHNW (Fachhochschule Nordwestschweiz). Object-Orientation (OO) is one example - which extensively requires analytical capabilities. For testing the OO-related capabilities a questionnaire (OO SET) for prospective and 1st year students was developed based on the Blackjack scenario. Our main target of the OO SET is to identify clusters of students which are likely to fail in the OO-related modules without a substantial amount of training. For the interpretation of the data the Kohonen Feature Map (KFM) is used which is nowadays very popular for data mining and exploratory data analysis. However, like all sub-symbolic approaches the KFM lacks to interpret and explain its results. Therefore, we plan to add - based on existing algorithms - a “postprocessing” component which generates propositional rules for the clusters and helps to improve quality management in the admission and teaching process. With such an approach we synergistically integrate symbolic and sub-symbolic artificial intelligence by building a bridge between machine learning and knowledge engineering.

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Innovation potential for human computer interaction domains in the digital enterprise

2018, Jüngling, Stephan, Lutz, Jonas, Korkut, Safak, Jäger, Janine, Dornberger, Rolf

This chapter summarizes a historic overview of some iconic examples of human computer interaction devices and focuses on a human computer interaction paradigm which is based more on human language. Human language is by far the most utilized means of conscious communication between humans whereas the mouse and keyboard are the dominant means to store and process information in computers. This chapter elaborates on the main challenges related to human language, as well as on ideas showing how human language, written or spoken, is embedded in different application scenarios. Built on this premise this chapter presents ideas for today’s digitalized enterprises, which seem to disregard the fact that the latest technological advancements enable different ways of interacting with computerized systems, and that current interaction methods are bound to constraints of half a century ago. Given today’s computational power, the engineers of former decades would not have had to invent intermediary interaction devices such as the mouse, if direct manipulation with touch screen or natural language processing had been possible. The possibilities for modern enterprises to overcome the restrictions of interaction devices from the past are considered.