Jüngling, Stephan

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Jüngling
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Stephan
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Jüngling, Stephan

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2018 - 20203
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Autor:in: Telesko, Rainer × Enddatum: 2022 × Hochschule: Hochschule für Wirtschaft × Institut: Institut für Wirtschaftsinformatik ×

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  • Vorschaubild nicht verfügbar
    Publikation
    A human aptitude test for object-oriented programming in the context of AI and machine learning
    (Springer, 2020) Jüngling, Stephan; Telesko, Rainer; Dornberger, Rolf [in: New trends in business information systems and technology. Digital innovation and digital business transformation]
    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.
    04A - Beitrag Sammelband
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    Publikation
    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 [in: Proceedings of the AAAI 2020 Spring Symposium on Combining Machine Learning and Knowledge Engineering in Practice (AAAI-MAKE 2020)]
    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.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    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.
    06 - Präsentation