A human aptitude test for object-oriented programming in the context of AI and machine learning
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2020
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04A - Book part
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New trends in business information systems and technology. Digital innovation and digital business transformation
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97-111
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Springer
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Cham
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Abstract
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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978-3-030-48331-9
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English
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Yes
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Published
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Closed
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Citation
Jüngling, S., & Telesko, R. (2020). A human aptitude test for object-oriented programming in the context of AI and machine learning. In R. Dornberger (Ed.), New trends in business information systems and technology. Digital innovation and digital business transformation (pp. 97–111). Springer. https://doi.org/10.1007/978-3-030-48332-6_7