Research on Uncertainty

Pratt, Dave; Kazak, Sibel

doi:10.1007/978-3-319-66195-7_6

Cited by 24 publications

(12 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Although working with high school students, Chance et al (2004) and Saldanha and Thompson (2002) recommend having learners repeat the sampling process and compare multiple sample results to foster an understanding of the sample process. Other recommendations for the design of the intervention would be to take an approach that integrates CK and PCK (Groth, 2017), have learners conduct statistical investigations themselves (Garfield & Ben-Zvi, 2008), use hands-on activities (Canada, 2006;Pratt & Kazak, 2018), use simulation activities to illustrate sampling variability (Garfield & Ben-Zvi, 2008;Mills, 2002) and keep descriptive analyses as simple as possible to facilitate focusing on the relevant concepts to be learned (Arnold, Pfannkuch, Wild, Regan, & Budgett, 2011).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

The development of informal statistical inference content knowledge of pre-service primary school teachers during a teacher college intervention

et al. 2018

View full text Add to dashboard Cite

Teachers who engage primary school students in informal statistical inference (ISI) must themselves have good content knowledge of ISI (ISI-CK). However, little is known about how college education for pre-service teachers can contribute to the development of their ISI-CK. To address this shortcoming, we used a case study to investigate ISI-CK development in a class of 21 pre-service primary school teachers who participated in a short intervention (180 min). Based on qualitative and quantitative analyses of the pretest, posttest and intervention data, the results suggest that most participants acknowledged it is possible to make uncertain inferences. An assignment to search the media for inferential claims seemed to create awareness regarding inference and the need to distinguish between a sample and a population. A simulation involving random sampling and varied sample size probably increased the participants' knowledge of sampling variability and random sampling. No development was seen in the participants' knowledge about sufficient sample sizes. The statistical investigation conducted by the participants during a model lesson may have strengthened their awareness of ISI, but it also revealed that many participants continued to favour distributed sampling over random sampling. Further research on belief formation with regard to data as evidence, sampling methods and the expression of uncertainty in the context of ISI is needed.Educ Stud Math (2018) 99:217-234 https://doi

show abstract

Section: Theoretical Backgroundmentioning

confidence: 99%

The development of informal statistical inference content knowledge of pre-service primary school teachers during a teacher college intervention

et al. 2018

View full text Add to dashboard Cite

show abstract

“…For the media, this perspective of mathematics provides credibility for propositions and arguments in a seemingly unbiased fashion (Himmelstein, 2014 ). Similarly, in typical mathematics and statistics curricula, students learn that levels of probability associated with the occurrence of events are always quantifiable, that is, the chance of uncertain events can be accurately calculated and represented numerically (Pratt & Kazak, 2018 ). The uses of StaMPs in media items about the pandemic, however, often involve notions of vagueness and risk .…”

Section: Discussionmentioning

confidence: 99%

Welcome to the era of vague news: a study of the demands of statistical and mathematical products in the COVID-19 pandemic media

Gal

Geiger

2022

Educ Stud Math

View full text Add to dashboard Cite

In this article, we report on a typology of the demands of statistical and mathematical products (StaMPs) embedded in media items related to the COVID-19 (coronavirus) pandemic. The typology emerged from a content analysis of a large purposive sample of diverse media items selected from digital news sources based in four countries. The findings encompass nine categories of StaMPs: (1) descriptive quantitative information, (2) models, predictions, causality and risk, (3) representations and displays, (4) data quality and strength of evidence, (5) demographics and comparative thinking, (6) heterogeneity and contextual factors, (7) literacy and language demands, (8) multiple information sources, and (9) critical demands. We illustrate these categories via selected media items, substantiate them through relevant research literature, and point to categories that encompass new or enhanced types of demands. Our findings offer insights into the rich set of capabilities that citizens (including both young people and adults) must possess in order to engage these mass media demands, critically analyze statistical and mathematical information in the media, evaluate the meaning and credibility of news reports, understand public policies, and make evidenced-informed judgments. Our conclusions point to the need to revise current curricular frameworks and conceptual models (e.g., regarding statistical and probability literacy, adult numeracy), to better incorporate notions such as blended knowledge, vagueness, risk, strength of evidence, and criticality. Furthermore, more attention is needed to the literacy and language demands of media items involving statistical and mathematical information. Implications for further research and educational practice are discussed.

show abstract

“…On one hand, type m respondents thought that random events are naturally equiprobable, even when they are not (Lecoutre, 1992). This is perhaps related to the representativeness heuristic: it denotes judging the likelihood of an event according to how well such event represents some aspects of the parent population or how it matches the system that generated it, which is the case of m thinkers (Kustos & Zelkowski, 2013;Pratt & Kazak, 2018). They focused on the random process, which appeared clearly in their description: 'both situations imply random experiments, and [the] outcomes have the same chance to occur, regardless of any conditions'.…”

Section: Characteristics Of Mathematically Oriented Thinkers [M = M and M* Reasoning]mentioning

confidence: 99%

Reasoning under uncertainty within the context of probability education: A case study of preservice mathematics teachers

Elbehary

2021

Pythagoras

View full text Add to dashboard Cite

Interpreting phenomena under uncertainty stands as a substantial cognitive activity in our daily life. Furthermore, in probability education research, there is a need for developing a unified model that involves several probabilistic conceptions. From this aspect, a central inquiry has been raised through this study: how do preservice mathematics teachers (PSMTs) reason under uncertainty? A multiple case study design was operated in which a purposive sample of PSMTs was selected to justify their reasoning in two probabilistic contexts while their responses were coded by NVivo, and corresponding categories were developed. As a result, PSMTs’ probabilistic reasoning was classified into mathematical (M), subjective (S), and outcome-oriented (O). Besides, several biases emerged along with these modes of reasoning. While M thinkers shared equiprobability and insensitivity to prior probability, the prediction bias and the belief of Allah’s willingness were yielded among S thinkers. Also, the causal conception spread among O thinkers.

show abstract

Research on Uncertainty

Cited by 24 publications

References 67 publications

The development of informal statistical inference content knowledge of pre-service primary school teachers during a teacher college intervention

The development of informal statistical inference content knowledge of pre-service primary school teachers during a teacher college intervention

Welcome to the era of vague news: a study of the demands of statistical and mathematical products in the COVID-19 pandemic media

Reasoning under uncertainty within the context of probability education: A case study of preservice mathematics teachers

Contact Info

Product

Resources

About