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Descriptors:
Test Format; Test Items; Item Analysis; Goodness of Fit; Statistics; Item Response Theory; Sample Size; Test Length

Abstract:
Empirical information regarding performance of model-fit procedures has been a persistent need in measurement practice. Statistical procedures for evaluating item fit were applied to real test examples that consist of both dichotomously and polytomously scored items. The item fit statistics used in this study included the PARSCALE's G[squared], Orlando and Thissen's (2000) S - [chi][squared] and S - G[squared], and Stone's (2000) [chi][squared*] and G[squared*]. The results of this study indicated that the fit of an individual item was affected by the choice of model-fit analyses. The performance of fit indices appeared to vary depending on item response theory (IRT) model mixtures used for calibration, sample size, and test length. In terms of consistency among the fit indices, the statistics based on the same approach (e.g., S - [chi][squared] and S - G[squared] ) showed considerably higher agreement in detecting misfitting items than the statistics based on different approaches (e.g., S - [chi][squared] and [chi][squared*]). Consistent and inconsistent findings compared to previous research are discussed along with practical implications. (Contains 3 tables and 1 figure.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Video Technology; Probability; Mathematics Instruction; Statistics; Mathematics; Mathematics Education; Elementary Education; Mathematics Teachers; Middle School Teachers; Elementary School Mathematics; Elementary School Teachers

Abstract:
The purpose of this study is to examine prospective mathematics specialists' engagement in an instructional sequence designed to elicit and develop their understandings of random processes. The study was conducted with two different sections of a probability and statistics course for K-8 teachers. Thirty-two teachers participated. Video analyses within a collaborative course design were used to support a teaching experiment about teachers' conceptions of random processes. In particular, teachers were asked whether the outcomes of "Rock-Paper-Scissors" (RPS) are generated randomly or not, were presented with a definition for random selection, and were asked to come to a conclusion about RPS. Teachers struggled to reconcile the equality of winning outcomes for each player with the potential for human interference in the process of generating outcomes. Ultimately, teachers concluded the outcomes were not generated randomly, but encountered a variety of unexpected obstacles along the way. (Contains 2 figures and 3 tables.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Foreign Countries; Item Response Theory; Statistics; Data Analysis; Goodness of Fit; Psychometrics; Test Items; Measurement Techniques

Abstract:
We investigate the performance of three statistics, R [subscript 1], R [subscript 2] (Glas in "Psychometrika" 53:525-546, 1988), and M [subscript 2] (Maydeu-Olivares & Joe in "J. Am. Stat. Assoc." 100:1009-1020, 2005, "Psychometrika" 71:713-732, 2006) to assess the overall fit of a one-parameter logistic model (1PL) estimated by (marginal) maximum likelihood (ML). R [subscript 1] and R [subscript 2] were specifically designed to target specific assumptions of Rasch models, whereas M [subscript 2] is a general purpose test statistic. We report asymptotic power rates under some interesting violations of model assumptions (different item discrimination, presence of guessing, and multidimensionality) as well as empirical rejection rates for correctly specified models and some misspecified models. All three statistics were found to be more powerful than Pearson's X [superscript 2] against two- and three-parameter logistic alternatives (2PL and 3PL), and against multidimensional 1PL models. The results suggest that there is no clear advantage in using goodness-of-fit statistics specifically designed for Rasch-type models to test these models when marginal ML estimation is used. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Grade 6; Grade 7; Grade 8; Gifted; Career Education; Science Careers; Data Analysis; Insurance; Insurance Occupations; Natural Disasters; Risk Assessment; Graphs; Mathematics Instruction; Mathematics Skills; Mathematical Concepts; Probability; Statistics; Statistical Analysis; Class Activities; Mathematics Activities; Worksheets; Lesson Plans; Instructional Materials; Visual Aids; Teaching Guides; Academic Standards; National Standards; Relevance (Education); Reprography; Seismology; Weather

Abstract:
"Shake, Rattle, & Roll" is a new program developed by The Actuarial Foundation with Scholastic, provides dynamic real-world math content designed to build student skills while showing students the relevance of math to understanding their world and planning for their future. Math skills are increasingly important for students. According to the U.S. Department of Labor, computer and mathematical science occupations, are projected to add 967,000 jobs and grow fastest among the professional groups by 2014. [A poster that accompanies this teaching guide can be viewed and/or retrieved at: http://www.actuarialfoundation.org/pdf/Poster.pdf.] Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Psychometrics; Intellectual Disciplines; Periodicals; Statistics; Researchers; Role

Abstract:
In this paper, I will review some aspects of psychometric projects that I have been involved in, emphasizing the nature of the work of the psychometricians involved, especially the balance between the statistical and scientific elements of that work. The intent is to seek to understand where psychometrics, as a discipline, has been and where it might be headed, in part at least, by considering one particular journey (my own). In contemplating this, I also look to psychometrics journals to see how psychometricians represent themselves to themselves, and in a complementary way, look to substantive journals to see how psychometrics is represented there (or perhaps, not represented, as the case may be). I present a series of questions in order to consider the issue of what are the appropriate foci of the psychometric discipline. As an example, I present one recent project at the end, where the roles of the psychometricians and the substantive researchers have had to become intertwined in order to make satisfactory progress. In the conclusion I discuss the consequences of such a view for the future of psychometrics. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Undergraduate Students; Marketing; Business Administration Education; Majors (Students); Statistics; Mathematics Anxiety; Measures (Individuals); Factor Structure; Multivariate Analysis; Factor Analysis; Gender Differences; College Credits; Internship Programs; College Curriculum; College Instruction; Teacher Student Relationship; Computer Uses in Education

Abstract:
Marketing students are known as less likely to have an affinity for the quantitative aspects of the marketing discipline. In this article, we study the reasons why this might be true and develop a parsimonious 20-item scale for measuring quantitative affinity in undergraduate marketing students. The scale was administered to a sample of business majors at a midsized university. The scale developed yielded a four-factor solution: Confidence, Enjoyment, Marketability, and Importance. Using multivariate analysis of variance, we test whether there are significant differences in quantitative affinity by gender, major, internship completion, class standing, and class completion. The findings suggest that marketing majors are less likely to enjoy the quantitative aspect of their major, but on completing a marketing research course their appreciation for the importance of quantitative tools increases. Internship completion has no effect on the undergraduate marketing students' quantitative affinity. Our study complements extant literature by providing a parsimonious scale for assessing quantitative affinity specially adapted to the marketing students and analyzing the characteristics associated with students' scores. Suggested teaching strategies, based on the findings, are included. (Contains 2 tables and 1 figure.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Factor Analysis; Computer Assisted Instruction; Outcomes of Education; Public Health; Problem Based Learning; Teaching Methods; Electronic Learning; Online Courses; Feedback (Response); Comparative Analysis; Case Studies; Computer Mediated Communication; Longitudinal Studies; Questionnaires; Interviews; Tutors; Statistics; Graduate Students; Masters Programs

Abstract:
This case-study compared traditional, face-to-face classroom-based teaching with asynchronous online learning and teaching methods in two sets of students undertaking a problem-based learning module in the multilevel and exploratory factor analysis of longitudinal data as part of a Masters degree in Public Health at Maastricht University. Students were allocated to one of the two study variants on the basis of their enrolment status as full-time or part-time students. Full-time students (n = 11) followed the classroom-based variant and part-time students (n = 12) followed the online asynchronous variant which included video recorded lectures and a series of asynchronous online group or individual SPSS activities with synchronous tutor feedback. A validated student motivation questionnaire was administered to both groups of students at the start of the study and a second questionnaire was administered at the end of the module. This elicited data about student satisfaction with the module content, teaching and learning methods, and tutor feedback. The module coordinator and problem-based learning tutor were also interviewed about their experience of delivering the experimental online variant and asked to evaluate its success in relation to student attainment of the module's learning outcomes. Student examination results were also compared between the two groups. Asynchronous online teaching and learning methods proved to be an acceptable alternative to classroom-based teaching for both students and staff. Educational outcomes were similar for both groups, but importantly, there was no evidence that the asynchronous online delivery of module content disadvantaged part-time students in comparison to their full-time counterparts. (Contains 1 table.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Decision Making; Basic Vocabulary; Data; Accountability; Guidelines; Evaluation; Measures (Individuals); Statistics; Statistical Significance; Reliability; Validity; Criterion Referenced Tests; Norm Referenced Tests

Abstract:
The concept of teacher accountability assumes teachers will use data-driven decision making to plan and deliver appropriate and effective instruction to their students. In order to do so, teachers must be able to accurately interpret the data that is given to them, and that requires the knowledge of some basic concepts of assessment and statistics. This article will provide the classroom teacher with the basic vocabulary of assessment and clear descriptions of these concepts to facilitate their use of assessment data to develop effective instruction. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Foreign Countries; Subcultures; Mathematics Curriculum; Educational Change; Educational Innovation; Curriculum Implementation; Statistics; Mathematics Instruction; Teacher Attitudes; Educational Policy; Semi Structured Interviews; Secondary School Teachers; Case Studies

Abstract:
Implementing educational innovations is far more complex than the straightforward execution of policy prescriptions. The diversity in implementation variants reflects an inherent tension between stabilizing and change-driven processes in school organizations. This article tries to capture this complexity by focusing on how individual and collective processes of sense-making, as well as the actual structural factors (e.g., subcultures, roles and positions) and processes (e.g., legitimation) in the school, mediate implementation practices. Drawing on data from semi-structured interviews, this article reports on an exploratory study into the perceptions and implementation of the new statistics curriculum by secondary school teachers in Flanders (Belgium). (Contains 3 tables.) Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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Descriptors:
Cognitive Mapping; Cognitive Structures; Knowledge Base for Teaching; Preservice Teachers; Data Analysis; Statistics; Mathematics Education; Preservice Teacher Education

Abstract:
This report describes a model for mapping cognitive structures related to content knowledge for teaching. The model consists of knowledge elements pertinent to teaching a content domain, the nature of the connections among them, and a means for representing the elements and connections visually. The model is illustrated through empirical data generated as prospective teachers were in the process of developing knowledge for teaching nominal categorical data analysis. During a course focused on the development of statistical knowledge for teaching, the prospective teachers analyzed statistical problems, descriptions of children's statistical thinking, and related classroom scenarios. Their analyses suggested various types of knowledge structures in development. In some cases, they constructed all knowledge elements targeted in the course. In many cases, however, their knowledge structures had missing, incompatible, and/or disconnected elements preventing them from carrying out recommendations for teaching elementary nominal categorical data analysis in an optimal manner. The report contributes to teacher education by drawing attention to prospective teachers' learning needs, and it contributes to research on teachers' cognition by providing a method for modeling their cognitive structures. Note:The following two links are not-applicable for text-based browsers or screen-reading software. Show Hide Full Abstract

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