발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.3] A Software Engineering Education for Machine Learning Based Systems |
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| 논문투고자 |
Young-Taek Jin |
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| 논문내용 |
Modern software systems are increasingly integrating components driven by machine learning technology, harnessing its power to enrich various functionalities such as recommendation engines, anomaly detection, classification tasks, and predictive modeling. These software systems, which incorporate machine learning elements, bear distinctive attributes compared to their conventional counterparts. Regardless, it is of utmost importance that these machine learning-based systems uphold the qualities and standards expected of effective and reliable software. From a software engineering viewpoint, there have been numerous challenges in creating and managing these machine learning-based systems. Many literature reviews, and case analyses have offered certain solutions to address these hurdles. Nonetheless, various literatures and case studies have not been reported for software engineering education that help students adapt to the fast-paced evolution of diverse machine learning development environments. Moreover, traditional software engineering education has often overlooked the unique facets of machine learning development. Consequently, education that encapsulates the synergies and differences between these two arenas is yet to be fully realized. The objective of this paper is to bridge this gap. To achieve this, the study brings forward principles and teaching experiences related to the development of machine learning-based systems as part of the software engineering curriculum. |
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