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Lonneke Boels; Alex Lyford; Arthur Bakker; Paul Drijvers – Frontline Learning Research, 2023
Many students persistently misinterpret histograms. Literature suggests that having students solve dotplot items may prepare for interpreting histograms, as interpreting dotplots can help students realize that the statistical variable is presented on the horizontal axis. In this study, we explore a special case of this suggestion, namely, how…
Descriptors: Data Interpretation, Interpretive Skills, Statistical Distributions, Graphs
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Saskia Schreiter; Markus Vogel – Educational Studies in Mathematics, 2025
The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center,…
Descriptors: Eye Movements, Statistical Distributions, Data Interpretation, Data Analysis
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Lonneke Boels; Arthur Bakker; Wim Van Dooren; Paul Drijvers – Educational Studies in Mathematics, 2025
Many students persistently misinterpret histograms. This calls for closer inspection of students' strategies when interpreting histograms and case-value plots (which look similar but are different). Using students' gaze data, we ask: "How and how well do upper secondary pre-university school students estimate and compare arithmetic means of…
Descriptors: Secondary School Students, Learning Strategies, Data Interpretation, Graphs
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Dunn, Peter K.; Marshman, Margaret – Australian Mathematics Education Journal, 2021
This is the fourth in a series of statistical articles for mathematics teachers. In this article, the authors discuss topics in General Mathematics in Unit 2 Topic 1 (Univariate data analysis and the statistical investigation process) and topics in Essential Mathematics, Unit 2 Topic 1 (Representing and comparing data).
Descriptors: Mathematics Education, Mathematics Instruction, Data Analysis, Graphs
Lewis, Felicia Wider – ProQuest LLC, 2016
This thesis examined middle school students' current understanding of variability using a constructed response item assessment question. Variability is an essential concept in the teaching and learning of statistics. However, many students have difficulty with the concept of variability especially when constructing boxplots. Using a framework…
Descriptors: Middle School Students, Knowledge Level, Statistics, Mathematical Concepts
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Lem, Stephanie; Kempen, Goya; Ceulemans, Eva; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim – International Journal of Science and Mathematics Education, 2015
Box plots are frequently misinterpreted and educational attempts to correct these misinterpretations have not been successful. In this study, we used two instructional techniques that seemed powerful to change the misinterpretation of the area of the box in box plots, both separately and in combination, leading to three experimental conditions,…
Descriptors: Mathematical Concepts, Mathematics Instruction, Teaching Methods, Graphs
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Schild, Anne H. E.; Voracek, Martin – Research Synthesis Methods, 2015
Research has shown that forest plots are a gold standard in the visualization of meta-analytic results. However, research on the general interpretation of forest plots and the role of researchers' meta-analysis experience and field of study is still unavailable. Additionally, the traditional display of effect sizes, confidence intervals, and…
Descriptors: Graphs, Visualization, Meta Analysis, Data Interpretation
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Lem, Stephanie; Onghena, Patrick; Verschaffel, Lieven; Van Dooren, Wim – Educational Psychology, 2013
Recent studies have shown that the interpretation of graphs is not always easy for students. In order to reason properly about distributions of data, however, one needs to be able to interpret graphical representations of these distributions correctly. In this study, we used Tversky's principles for the design of graphs to explain how 125…
Descriptors: Graphs, Data Interpretation, College Freshmen, Design
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Mullenex, James L. – Mathematics Teacher, 1990
Describes a five-number summary which is a display of the minimum value, lower quartile, median, upper quartile, and maximum value. Indicates how to draw box plots as graphical representations of a five-number summary. (YP)
Descriptors: Data Analysis, Data Interpretation, Graphs, Mathematics Materials
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Brown, Richard; Davis, Gretchen – Mathematics Teacher, 1990
Presents an activity considering whether a difference exists in the age of Oscar winners. Describes how to draw a stem plot and a box plot as an example of implementing the recommendations of the NCTM Standards. Provides tables showing the name, movie titles, and ages of the Oscar winners since 1928. (YP)
Descriptors: Data Analysis, Data Interpretation, Graphs, Mathematics
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Davis, Gretchen – Mathematics Teacher, 1990
Describes classroom activities and shows that statistics is a practical tool for solving real problems. Presents a histogram, a stem plot, and a box plot to compare data involving class enrollments. (YP)
Descriptors: Data Analysis, Data Interpretation, Graphs, Mathematics