Literature Index

Displaying 2271 - 2280 of 3326
  • Author(s):
    Audy Salcedo
    Year:
    2014
    Abstract:
    This study presents the results of the analysis of a group of teacher-made test questions for statistics courses at the university level. Teachers were asked to submit tests they had used in their previous two semesters. Ninety-seven tests containing 978 questions were gathered and classified according to the SOLO taxonomy (Biggs & Collis, 1982) and to the definitions of statistical literacy, statistical reasoning and statistical thinking (delMas, Ooms, Garfield & Chance, 2007). Results suggest a strong preference for questions that address the evaluation of cognitive abilities in the lower levels of the taxonomies used. Reflections as to the implications of these results for the teaching and evaluation of statistics courses are presented.
  • Author(s):
    Jill Newton, Leslie Dietiker and Aladar Horvath
    Year:
    2008
    Abstract:
    This analysis of the K-8 statistics standards in 41 United States of America (USA) state documents that include grade level expectations (GLEs) is timely given the increased need for statistical literacy as the quantity of available data around us grows. This analysis endeavors to answer the question: What are K-8 students in the USA expected to know and be able to do with regard to statistics as represented in the state standards documents? The study was framed using the four process components outlined in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: (1) formulate questions, (2) collect data, (3) analyze data, and (4) interpret results (Franklin et al., 2007). Among other findings, the analysis highlights two major types of knowledge expected in the documents, the knowledge expected to "do" each of the four processes and the knowledge expected to "understand" and/or "evaluate" the processes.
  • Author(s):
    Scheaffer, R. L.
    Editors:
    Brunelli, L., & Cicchitelli, G.
    Year:
    1993
    Abstract:
    The development of a data-driven curriculum for high school mathematics appears to be in line with the needs of students to see more motivation and application within the mathematics classroom and to develop important skills to carry beyond the classroom. The revised curriculum under development is designed to raise the quantitative literacy off all students as it builds connections among mathematics, science, and technology. It models a new approach to the teaching of mathematics, the approach required by the NCTM Standards, as it emphasizes hands-on activities for students and discovery of concepts through data. Technology in the form of graphing calculators and computers is an integral part of the teaching and learning style being promoted through these materials and workshops. This project attempts to connect topics of importance in a modern mathematics curriculum to a modern view of statistical science for the purpose of enhancing student interest and skills in both areas.
  • Author(s):
    Russell, S. J., & Corwin, R. B.
    Year:
    1989
    Abstract:
    A unit of study that introduces collecting, representing, describing, and interpreting data is presented. Suitable for students in grades 4 through 6, it provides a foundation for further work in statistics and data analysis. The investigations may extend from one to four class sessions and are grouped into three parts: "Introduction to Data Analysis"; "Learning About Landmarks in the Data"; and "A Project in Data Analysis." An overview of the investigation, session activities, dialogue boxes, and teacher notes are included in each investigation. The major goals developed in each part of this guide are: (1) describing the shape of the data; (2) defining the way data will be collected; (3) summarizing what is typical of the data; (4) making quick sketches of the data; (5) inventing ways to compare two sets of data; (6) representing data first through sketches, then through a presentation graph or chart; (7) using the median as a landmark in the data; (8) understanding that the median is only one landmark in the data; and (9) experiencing all the stages of a data analysis investigation. Attached are 10 student sheets. (KR)
  • Author(s):
    David L. Neumann, Michelle Hood, and Michelle M. Neumann
    Year:
    2009
    Abstract:
    Humor has been promoted as a teaching tool that enhances student engagement and learning. The present report traces the pathway from research to practice by reflecting upon various ways to incorporate humor into the face-to-face teaching of statistics. The use of humor in an introductory university statistics course was evaluated via interviews conducted with a random sample of 38 students. Responses indicated that humor aided teaching by providing amusement, breaking up content, bringing back attention, lightening the mood, increasing motivation, reducing monotony, and providing a mental break. Students that were already motivated and interested in statistics derived less benefit from humor, finding it at times irrelevant and distracting. The selective use of humor is recommended in teaching statistics, particularly for students that hold negative attitudes towards the subject.
  • Author(s):
    Schwarz, C. J.
    Year:
    1997
    Abstract:
    StatVillage is a hypothetical city based on real data that is suitable as a teaching aid for an introductory class in survey sampling. It uses a World Wide Web-based interface to allow the students to actively select sampling units; it then returns the corresponding data for further analysis. The underlying data are actual census records extracted from public use microdata files.
  • Author(s):
    Amy L. Phelps
    Year:
    2012
    Abstract:
    Service-learning can mean different things and look quite different in varying statistics curricula that may include undergraduates, graduates, majors and non-majors across a wide array of higher institutions. The terms community engagement, volunteerism, community-based projects and service-learning are tossed around on various institutions‟ websites. The purpose of this article is two-fold. First is to provide an historical review of the evolution of service-learning activities to try to unify and define the terminology as one might use this pedagogy for statistics instruction. Second is to present some examples of how a first and second course in business statistics can step up from service-learning and move up the continuum towards reaping the reciprocal benefits of SERVICE-LEARNING (SL). In this article, service learning (note the omission of a hyphen) is a valued classroom service activity that separates the activity from the learning goals of the class, while service-learning (note the presence of a hyphen) is a teaching methodology in which the service and learning goals are carefully given equal weight in the development of the project so that classroom goals and service outcomes enhance each other providing a reciprocal experience for all participants (Sigmon 1994). When this careful design is a “method of teaching through which students apply newly acquired academic skills and knowledge to address real-life needs in their own communities” (ASLER 1994), SL unifies what students are currently learning in the classroom with the service they are simultaneously providing in the community. Careful design opens the door to provide opportunities of SL in an introductory, non-majors statistics class.
  • Author(s):
    Stephen Gorard and Patrick White
    Year:
    2017
    Abstract:
    In their response to our paper, Nicholson and Ridgway agree with the majority of what we wrote. They echo our concerns about the misuse of inferential statistics and NHST in particular. Very little of their response explicitly challenges the points we made but where it does their defence of the use of inferential techniques does not stand up to scrutiny. Their statements are either contradictory, agreement ‘dressed up’ as disagreement, appeals to authority, semantic slights of hand, or irrelevant to our original claims. It is not clear why such a response was needed.
  • Author(s):
    Derry, S. Levin, J. R., Schauble, L.
    Year:
    1995
    Abstract:
    Literacy and informed decision making in an uncertain world require the ability to reason statistically. However, research indicates that, although conceptions of statistics and probability have steadily advanced within scientific and mathematical communities, adults in mainstram American society cannot think probabilistically or statistically about important societal issues. This problem is addressed through implementation and evaluation of a novel statistics course for students who are teachers or are considering a career in teaching. The course is designed to help students use statistical concepts as tools for social reasoning within simulations of real-world problem situations. The course is unique because of its connections with the community and its commitment to achieving a high degree of authenticity through simulations of realistic social problem solving.
  • Author(s):
    Antonio Carlos de Souza, Celi Espasandin Lopes, and Débora de Oliveira
    Year:
    2014
    Abstract:
    This paper presents discussions on stochastic education in early childhood, based on two doctoral research projects carried out with groups of preschool teachers from public schools in the Brazilian cities of Suzano and São Paulo who were participating in a continuing education program. The objective is to reflect on the analysis of two didactic situations related to the learning of statistics in mathematics classes. The results show evidence of the mathematics learning of the teachers who teach mathematics in early childhood. They also highlight the mathematical and statistical relations that children are able to establish when carrying out stochastic activities included in their childhood context.

Pages

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education