Data processing is a central topic of computer science and hence also in secondary computer science education, which includes strategies for storing, managing and retrieving data. In the context of Big Data, this field changes tremendously: established ideas, such as avoiding redundancies and storing data in a persistent and consistent way, are dropped in order to speed up the access to distributed stored data as well as its availability. Furthermore, with the rapidly growing impact of data processing on everyone’s daily life, computer science education needs to address these aspects as well as their social and ethical implications, such as privacy issues. This paper points out the major challenges that arise from the outlined developments by evaluating whether database concepts and examples commonly used in CS education need to be updated.
CITATION STYLE
Grillenberger, A., & Romeike, R. (2014). Big data – challenges for computer science education. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8730, 29–40. https://doi.org/10.1007/978-3-319-09958-3_4
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