
This chapter focuses on teaching and learning of data science. We address this topic in this Guide of teaching computer science since data science is an emerging discipline that computer science is one of its basic components and, accordingly, the two fields have some overlaps. In this chapter we take into consideration the fact that not all the students, who study the MTCS course, are familiar with data science, and, therefore, unlike other chapters, this chapter does include some explanations about what data science is as well as its knowledge structure. We dedicate special attention to the pedagogy of data science, highlighting both the learners’ perspective and the teachers’ perspective. To avoid too abstract and vague description of the teaching and learning processes of data science in high school, we present an example of a data science program for high school. In the activities presented to the students in this chapter, we aim to highlight the opportunities that the teaching of data science opens to the students, as data science is an emerging field that its pedagogy is still in its initial development stages. At the same time, the activities highlight the relevance of data science to the teaching of computer science in order to deliver the message that the teaching processes of the two fields can mutually contribute to each other.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
