A deep structure model of students' statistical misconceptions

Mevarech, Zemira R.

doi:10.1007/bf00368237

Cited by 89 publications

(70 citation statements)

References 13 publications

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“…Both of these topics were typically found in earlier curriculum documents associated with procedures for calculating means and probabilities. In the 1980s Pollatsek, Lima and Well (1981) and Mevarech (1983) demonstrated student difficulty with weighted averages, as did Strauss and Bichler (1988) with the general properties of the mean. Mokros and Russell (1995) identified the dilemma of representativeness for averages and Cai (1995and Cai ( , 1998 revealed difficulties with the notion of mean due to students' failure to work the algorithm backward.…”

Section: Measuring Student Understandingmentioning

confidence: 91%

Explaining Student Achievement: the Influence of Teachers’ Pedagogical Content Knowledge in Statistics

Callingham

Carmichael

Watson

2015

Int J of Sci and Math Educ

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Abstract:Statistics is an increasingly important component of the mathematics curriculum. StatSmart was a project intended to influence middle-years students' learning outcomes in statistics through the provision of appropriate professional learning opportunities and technology to teachers. Participating students in Grade 5/6 to Grade 9 undertook three tests, a pre-test, a post-test and a longitudinal retention test over a period of two years. Their teachers completed a survey that included items measuring pedagogical content knowledge (PCK) for teaching statistics. Despite the development of valid instruments to measure both student and teacher content knowledge and teachers' PCK, linking teachers' knowledge directly to students' learning outcomes has proved elusive. Multi-level modeling of results from 789 students for whom there were three completed tests and measures from their teachers indicated that students' outcomes were influenced positively by their initial teacher's PCK. Extended participation of teachers in the project also appeared to reduce negative effects of changing teachers.

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Section: Measuring Student Understandingmentioning

confidence: 91%

Explaining Student Achievement: the Influence of Teachers’ Pedagogical Content Knowledge in Statistics

Callingham

Carmichael

Watson

2015

Int J of Sci and Math Educ

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“…Watson and Moritz (2000) looked at how elementary through high school students' understanding of average changes over time. Undergraduate college students have also been shown to have tenuous understanding of the mean: Pollatsek, Lima, and Well (1981) documented undergraduates' difficulties in determining weighted means, and Mevarech's (1983) study cited their dilemmas in identifying situations in which the mean algorithm had been incorrectly applied. A recent study of pre-service elementary school teachers rated nearly half of them as having an understanding of mean and median that was limited to computational procedures (Groth & Bergner, 2006).…”

Section: Introductionmentioning

confidence: 99%

Students' Misconceptions in Interpreting Center and Variability of Data Represented via Histograms and Stem-and-Leaf Plots

Cooper

Shore

2008

Journal of Statistics Education

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This paper identifies and discusses misconceptions that students have in making judgments of center and variability when data are presented graphically. An assessment addressing interpreting center and variability in histograms and stem-and-leaf plots was administered to, and follow-up interviews were conducted with, undergraduates enrolled in introductory statistics courses. Assessment items focused upon comparing the variability of two data sets of common range represented by bell-shaped histograms on a common scale, computing measures of center from data extracted from graphs, and in comparing the relative location of the mean and median on a histogram from skewed data. Students' misconceptions often stemmed from their difficulty in maintaining understanding of the data that are being represented graphically.

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“…Indeed, there is a body of interdisciplinary research that indicates that students tend to have confusions and difficulties with a variety of topics in statistics (Garfield and Ahlgren, 1988;Shaughnessy, 1992). It has been found that students hold misconceptions relating to fundamental statistical concepts, such as the mean and correlation (Mevarech, 1983;Morris, 1997). Research in computer-based learning has looked at how the computer can be used effectively to address students' statistical misconceptions and help students come to understand key statistical ideas (Cumming and Thomason, 1995;Morris, 1998).…”

Section: Introductionmentioning

confidence: 99%

Active learning of statistics: a case study

Morris

Scanlon

2000

ALT-J

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Research at the Open University has investigated students' learning of statistical concepts and how information technology can be effectively used to support this process. Previous empirical work has looked at psychology students' misconceptions relating to correlation and how computer-based learning environments can be used to address these. This paper reports on the findings from a qualitative study that investigated students' learning collaboratively from a multimedia application called ActivStats.

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A deep structure model of students' statistical misconceptions

Cited by 89 publications

References 13 publications

Explaining Student Achievement: the Influence of Teachers’ Pedagogical Content Knowledge in Statistics

Explaining Student Achievement: the Influence of Teachers’ Pedagogical Content Knowledge in Statistics

Students' Misconceptions in Interpreting Center and Variability of Data Represented via Histograms and Stem-and-Leaf Plots

Active learning of statistics: a case study

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