Gør som tusindvis af andre bogelskere
Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.
Ved tilmelding accepterer du vores persondatapolitik.Du kan altid afmelde dig igen.
The widespread availability of big data, machine learning, and computational power has amplified the relevance of data in our day-to-day lives. For example, it is almost impossible to make it through a day without reading the news, scrolling through Facebook, or reading a policyreport that does not generate data or reference or result from data-informed decision-making. As a result, mathematics policy reforms and curriculum developers have begun exploring how data science can be introduced at the K-12 level (e.g., Gould et al. 2016) . At the same time, secondary mathematics teachers have reported feeling uncomfortable with their knowledge about statistics content and practices (Batanero et al., 2011; Franklin et al., 2015). This may be partially attributed to how the statistical education of pre-service mathematics teachers (PSMTs) is often mathematics-oriented (Burill & Biehler, 2011), although mathematics and statistics are two distinct fields. This
Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.
Ved tilmelding accepterer du vores persondatapolitik.