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Examining Middle School Students' Statistical Thinking While Working In A Technological Environment, Melissa Arnold Scranton

Theses and Dissertations

Examining Middle School Students' Statistical Thinking

While Working in a Technological Environment

Melissa Arnold Scranton

The purpose of this study was to gain a better understanding of how students think in a technological environment. This was accomplished by exploring the differences in the thinking of students while they worked in a technological environment and comparing this to their work in a paper and pencil environment. The software program TinkerPlots: Dynamic Data Exploration (Konold & Miller, 2005), a construction tool that middle school students use for data analysis was the technological environment. In both environments, types of critical, creative, and statistical …

Examining Introductory Students’ Attitudes In A Randomization-Based Curriculum, Joshua Ryan Beemer

Statistics

Student attitudes regarding introductory statistics courses are not always the most positive. The purpose of this research is to utilize the Survey of Attitudes Toward Statistics to evaluate introductory statistics students’ attitudes pre- and post course. Furthermore, comparisons of attitudes within different introductory course curricula across institutions will be made. Various components within the survey, such as difficulty, value, and interest, will be assessed in order to determine where students’ attitudes are affected the most and how they are correlated with other variables such as current GPA and curriculum taught. The outcomes for these models look at demographic predictors that …

Descriptive Statistical Attributes Of Special Education Datasets, Valerie Felder

Wayne State University Dissertations

ABSTRACT

Descriptive Statistical Attributes of Special Education Data Sets

by

VALERIE FELDER

December 2013

Advisor: Dr. Shlomo Sawilowsky

Major: Educational Evaluation and Research

Degree: Doctor of Philosophy

Micceri (1989) examined the distributional characteristics of 440 large-sample achievement and psychometric measures. All the distributions were found to be nonnormal at alpha = .01. Micceri indicated three factors that might contribute to a non-Gaussian error distribution in the population. The first factor is subpopulations within a target population. The second factor is ceiling effects and the third factor is treatment effects that may change the location parameter, variability, or shape of the …