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# Conference Paper

• ### Forming small class groups using multidimensional scaling.

In college courses that use group work to aid learning and evaluation, class groups are often selected randomly or by allowing students to organize groups themselves. This article describes how to control some aspect of the group structure, such as increasing schedule compatibility within groups, by forming the groups using multidimensional scaling. Applying this method in an undergraduate statistics course has resulted in groups that have been more homogeneous with respect to student schedules than groups selected randomly. For example, correlations between student schedules increased from a mean of 0.29 before grouping to a within-group mean of 0.50. Further, the exercise motivates class discussion of a number of statistical concepts, including surveys, association measures, multidimensional scaling, and statistical graphics.

• ### Graduate students and their use of statistical knowledge in educational psychology.

This work describes the use of statistics made by graduate students in the field of Educational Psychology at the National Pedagogical University, when writing their theses or dissertations in support of their candidature for a degree of professional qualification. The results show that, in general, the thesis writers used statistical analyses when their investigation required them; however, it was found that students mainly have the following difficulties: a) their choice of a suitable statistical test concerning their objective of research; b) the way of interpreting data; c) selection of the design consistent with their objectives; d) in their comprehension of the meaning of some statistical concepts; e) in their decision use of charts or graphs. Finally the work concludes by discussing the pertinence of the contents, strategies and procedures of instruction and evaluation of courses in statistics.

• ### SATS at Ball State University: Approaches and attitudes.

SATS survey data collected from three introductory statistics courses - college algebra-based, college calculus-based, and a high school AP course. Instructors of these courses also completed a questionnaire concerning their approach to a 1st course in statistics. What are the similarities and differences in the students' attitudes to each instructor's approach?

• ### Assessing statistical reasoning through project work.

New technologies involve a reformulation of statistical teaching contents and methodology and, at the same time, reinforce the need for a deeper training of students, including developing students' statistical reasoning. In this work we evaluate the statistical reasoning ability acquired by health sciences students from the analysis of their final undergraduate projects.

• ### An explanation of student performance using hierarchical linear model for schools in Pernambuco, Brzil.

The hierarchical linear models or multilevels were developed for analysis of data which possess group structure, that is, a structure hierarchy which takes in account the data variability inside and among each hierarchical level. By using data analysis from SAEPE (2002 Educational Evaluation System of Pernambuco), hierarchical models (MH) are presented with two levels of evaluation in mathematics and Portuguese language classes applied to the 4th and 8th grades students of fundamental teaching and to the students 3rd grade students medium teaching. The results in this modeling are more appropriate due to data group structure. A comparison between multiple regression models and hierarchical models shows a better performance of the second model.

• ### A hierarchy of tertiary students' consideration of variation.

In this study a hierarchy of consideration of variation was developed from students' responses to a questionnaire given at the beginning of a tertiary introductory statistics course. The hierarchy was then used to code responses to the same questionnaire post-study. Comparison of student performances showed that the development of consideration of variation differs with the context of the question. The proposed hierarchy could provide a basis for a more general hierarchy of consideration of variation that is applicable across a variety of tasks. It also supports educators in identifying the level of a student's consideration of variation, providing direction for teaching and learning activities that will help that consideration develop.

• ### Understanding high school students' ideas about probability: Some findings from Fiji.

This paper reports on data from a large study which explored form five (14 to 16-year-olds) students' ideas in statistics (probability, descriptive statistics, graphical representations, investigations). This paper discusses the ways in which students made sense of probability tasks obtained from the individual interviews. The findings revealed that many of the students used strategies based on beliefs, prior experiences and intuitive strategies. Additionally, in some cases the meaning intended by myself on the interview tasks was not that constructed by the students. As a result, students constructed responses based on these unintended interpretations. While students showed more competence on the formal item, they were less competent on the question involving an everyday context. This inconsistency could be due to contextual or linguistic issues. The paper concludes by suggesting some implications for further research.

• ### Identifying content knowledge for teaching statistics.

The purpose of the study reported herein was to identify important aspects of statistical knowledge needed for teaching in the middle school grades. A systematic study of the current literature, including state and national standards, was conducted to identify these important aspects and to measure the degree of emphasis or importance suggested for the content. Results show that state and national standards differ greatly in their expectations of what topics in data analysis and statistics students and teachers should master. The variation is also large in the degree of emphasis given to the content. The majority of the documents analyzed suggest giving greater emphasis to the selection and proper use of graphical data representation and measures of center and spread. Additionally teachers' standards also suggest as important the proper selection and use of teaching strategies and inference of students' understanding from their work and discourse.

• ### Using business-style cases in an introductory statistics course.

Most institutions of higher learning in the United States offer introductory statistics courses in a variety of flavors. Integration of the subject-specific concepts with the basic applied statistical techniques should be the primary goal of these flavored courses. Solely lecture-based traditional instruction method is not suitable to satisfying this objective. We argue for the incorporation of business-style cases into the introductory statistics curriculum using Constructivist learning theory and the notion of the "liberal arts" education. A typical business case setup is presented and its compatibility with an introductory statistics course is assessed. Finally, a sample business-style case for the application of the simple linear regression is provided.

• ### YSTATTEST: A system for automated online test creation and correction.

Using exclusively open-source software, we have developed and implemented an online testing system dubbed YStatTest. This system allows instructors to create homework, quizzes, and exams by querying a database containing question templates. A template is selected based on such elements as keywords, categories, and historical difficulty. Numerical values, data, and correct answers for each question template are randomly generated upon exam creation. Thus, although two students may receive identical templates, they will likely differ in placement on the exam and most assuredly in the data and numerical values associated with the question. We discuss the impact this testing system has had upon student learning and highlight future planned development for our software.