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An Investigation Of Eighth Grade StudentsYolcu, Ayse 01 June 2012 (has links) (PDF)
The purpose of this study was to investigate the statistical literacy of 8th grade students and their attitudes towards statistics. Moreover, the relationship between their statistical literacy and attitudes towards statistics was examined.
The study was conducted in Yenimahalle district of Ankara in the Spring semester of 2011-2012 academic year. The sample of this study was obtained through cluster random sampling. Nine schools were randomly selected for the study. A total of 1074 eighth grade students in these schools participated. The scales used in the data collection were Statistical Literacy Test (SLT) adapted from Probability Attitudes Scale previously developed for Turkish students (Bulut, 1994) and Attitude towards Statistics Questionnaire (ATSQ) developed by the researcher based on Watson&rsquo / s (1997) three tier framework.
The analysis of the mean scores of statistical literacy in terms of content domains revealed that although sample, graphs, and chance contents had closer mean scores to each other which was around moderate value / average, inference, and variation content domains had lower mean scores.
A one-way within subjects ANOVA indicated that there were significant differences between Tier 1, Tier 2 and Tier 3 aspects of statistical literacy. The pairwise comparisons indicated that students performed lowest in third tier of statistical literacy where students were required to evaluate inappropriate statistical claims. Although, students performed slightly higher in the first tier where they showed their ability in understanding statistical terminology / their performance was the highest in the second tier which was interpreting statistical claims in context.
Eighth grade students&rsquo / attitudes towards statistics were positive with a mean score of 3.52 in five point scale. The correlation analysis indicated that there were positive and significant relationship between students&rsquo / attitudes towards statistics and statistical literacy scores.
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Statistical reasoning at the secondary tertiary interfaceWilson, Therese Maree January 2006 (has links)
Each year thousands of students enrol in introductory statistics courses at universities throughout Australia, bringing with them formal and informal statistical knowledge and reasoning, as well as a wide range of basic numeracy skills, mathematical inclinations and attitudes towards statistics, which have the potential to impact on their ability to develop statistically. This research develops and investigates measures of each of these components for students at the interface of secondary and tertiary education, and investigates the relationships that exist between them, and a range of background variables. The focus of the research is on measuring and analysing levels and abilities in statistical reasoning for a range of students at the tertiary interface, with particular interest also in investigating their basic numeracy skills and how these may or may not link with statistical reasoning allowing for other variables and factors. Information from three cohorts in an introductory data analysis course, whose focus is real data investigations, provides basis for the research. This course is compulsory for all students in degree programs associated with all sciences or mathematics. The research discusses and reports on the development of questionnaires to measure numeracy and statistical reasoning and the students' attitudes and reflections on their prior school experiences with statistics. Students' attitudes are found to be generally positive, particularly with regard to their self-efficacy. They are also in no doubt as to the links that exist between mathematics and statistics. The Numeracy Questionnaire, developed to measure pre-calculus skills relevant to an introductory data analysis course which emphasises real data investigations, demonstrates that many students who have completed a basic algebra and calculus senior school subject struggle with skills which are in the pre-senior curricula. Direct examination of the responses helps to understand where and why difficulties tend to occur. Rasch analysis is used to validate the questionnaire and assist in the description of levels of skill. General linear models demonstrate that a student's numeracy score depends on the result obtained in senior mathematics, whether or not the student is a mathematics student, gender, whether or not higher level mathematics has been studied, self-efficacy and year. The research indicates that either the pre-senior curricula need strengthening or that exposure to mathematics beyond the core senior course is required to establish confidence with basic skills particularly when applied to new contexts and multi- step situations. The Statistical Reasoning Questionnaire (SRQ) is developed for use in the Australian context at the secondary/tertiary interface. As with the Numeracy Questionnaire, detailed examination of the responses provides much insight into the range and features of statistical reasoning at this level. Rasch analyses, both dichotomous and polychotomous, are used to establish the appropriateness of this instrument as a measuring tool at this level. The polychotomous, Rasch partial credit model is also used to define a new approach to scoring a statistical reasoning instrument and enables development and application of a hierarchical model and measures levels of statistical reasoning appropriate at the school/tertiary interface. General linear models indicate that numeracy is a highly significant predictor of statistical reasoning allowing for all other variables including tertiary entrance score and students' backgrounds and self-efficacy. Further investigation demonstrates that this relationship is not limited to more difficult or overtly mathematical items on the SRQ. Performance on the end of semester component of assessment in the course is shown to depend on statistical reasoning at the beginning of semester as measured by the partial credit model, allowing for all other variables. Because of the dominance of the relationship between statistical reasoning (as measured by the SRQ) and numeracy on entry, some further analysis of the end of semester assessment is carried out. This includes noting the higher attrition rates for students with less mathematical backgrounds and lower numeracy.
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How Attitudes towards Statistics Courses and the Field of Statistics Predicts Statistics Anxiety among Undergraduate Social Science Majors: A Validation of the Statistical Anxiety ScaleO'Bryant, Monique J. 08 1900 (has links)
The aim of this study was to validate an instrument that can be used by instructors or social scientist who are interested in evaluating statistics anxiety. The psychometric properties of the English version of the Statistical Anxiety Scale (SAS) was examined through a confirmatory factor analysis of scores from a sample of 323 undergraduate social science majors enrolled in colleges and universities in the United States. In previous studies, the psychometric properties of the Spanish and Italian versions of the SAS were validated; however, the English version of the SAS had never been assessed. Inconsistent with previous studies, scores on the English version of the SAS did not produce psychometrically acceptable values of validity. However, the results of this study suggested the potential value of a revised two-factor model SAS to measure statistics anxiety. Additionally, the Attitudes Towards Statistics (ATS) scale was used to examine the convergent and discriminant validities of the two-factor SAS. As expected, the correlation between the two factors of the SAS and the two factors of the ATS uncovered a moderately negative correlation between examination anxiety and attitudes towards the course. Additionally, the results of a structural regression model of attitudes towards statistics as a predictor of statistics anxiety suggested that attitudes towards the course and attitudes towards the field of statistics moderately predicts examination anxiety with attitudes towards the course having the greatest influence. It is recommended that future studies examine the relationship between attitudes towards statistics, statistics anxiety, and other variables such as academic achievement and instructional style.
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