Abstract
In this chapter, contextualisation is discussed with particular emphasis to the delivery of data science courses and programmes. Data science has seen a significant increase in popularity due to its applications to business and academic related fields. Data is being continuously created and therefore, it is crucial to create methods, frameworks and implementations to extract, assess and utilise actionable information for data. Data is, and will be, the new currency. As a consequence, data science must be embedded in the curricula from an early age. The objective of contextualisation includes the integration of learning with various topics and disciplines, to provide meaning. VR/AR technologies can further enhance contextualisation within data science, due to their ability to engage and interact with users.
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Trovati, M. (2023). Contextualisation in Data Science. In: Carter, J., O'Grady, M., Rosen, C. (eds) Higher Education Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-031-29386-3_7
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