Anthony Harradine's research while affiliated with Prince Alfred College and other places

Publications (3)

Chapter
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During the past several years, we have conducted a number of instructional interventions with students aged 12 – 14 with the objective of helping students develop a foundation for statistical thinking, including the making of informal inferences from data. Central to this work has been the consideration of how different types of data influence the...
Chapter
Full-text available
Ideas of statistical inference are being increasingly included at various levels of complexity in the high school curriculum in many countries and are typically taught by mathematics teachers. Most of these teachers have not received a specific preparation in statistics and therefore, could share some of the common reasoning biases and misconceptio...
Article
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In current curriculum materials for middle school students in the US, data and chance are considered as separate topics. They are then ideally brought together in the minds of high school or university students when they learn about statistical inference. In recent studies we have been attempting to build connections between data and chance in the...

Citations

... To continue the development of visualization and measure of distribution, we introduce a new signal and noise process, based on contexts of production (Konold and Harradine 2014). For example, students attempt to manufacture "candies" of a standard size out of clay. ...
... Early instruction on sampling attempts to develop the foundations for this kind of knowledge and the associated abilities by addressing the concept of representativeness, which is grounded in embracing random sampling methods and acknowledging the representative power of a sample based on a sufficiently large sample size. However, even if this teaching is already quite restrictive when referring to key ideas of sampling in relation to inference (Harradine et al., 2011), the specialized research literature reveals that these notions are not trivial to students and that applying this knowledge outside the classroom is especially complicated. This is a big concern for reaching a main goal of statistical literacy: being able to interpret and critically evaluate statistical information, datarelated arguments, or stochastic phenomena found in diverse contexts (Gal, 2002). ...
... The preparation process that both students and teachers went through while learning probability and statistics was insufficient (Koparan, 2019;Rodríguez-Alveal, Díaz-Levicoy & Vásquez, 2018). Philosophical debates around the meaning of probability, certain features of probabilistic reasoning, students' misconceptions and difficulties, and the growing diversity of technological resources reveal that teachers need special preparation to teach probability Konold, et al., 2007;Rodríguez-Alveal, Díaz-Levicoy & Vásquez, 2018). While textbooks provide some examples, some texts offer a very narrow view of probability concepts or a single approach to probability. ...