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Webinars

  • Discovery Projects in Statistics: Implementation Strategies and Examples of Student Projects

    Brad Bailey & Dianna Spence, University of North Georgia
    Tuesday, February 18, 2014 - 12:00pm
    In this presentation we will discuss student-directed discovery projects in statistics, which are intended as the means through which statistical content is taught to the students. In particular, we will delineate the purpose and scope of a project covering linear regression analysis and another project covering comparisons with basic t-tests. We will describe curriculum materials developed to help instructors facilitate such projects and provide the web address where these materials can be accessed. We will give examples of how instructors use the curriculum materials to guide students through the projects' stages. In particular, the materials can be used to provide the students with clear information about the project requirements and what activities the students are expected to be engaged in during each phase of the student-directed projects. These projects are truly student-directed in that the students select their own research topic, define their own variables, and devise and carry out their own data collection plan before analyzing and interpreting their data. The students report their results in two forms: a written report is provided to the instructor and a brief formal presentation is made before the rest of the class. In both formats, the students report the findings of their research project, as well as explain why they chose the particular research topic, explain how they gathered, organized and analyzed the data and list any short-comings they perceive in their own project. Our presentation will include specific examples of projects that students have conducted. Finally, we will also discuss the rationale for assigning such projects, including the potential benefits of such projects - benefits suggested by both prior and on-going research - and possible factors mediating those benefits.
  • Strategies for successful implementation of collaborative student assessment in face-to-face and online statistics classes

    Audbjorg Bjornsdottir, University of Minnesota
    Tuesday, February 11, 2014 - 12:00pm
    This presentation will be about collaborative tests, where students are allowed to work together during the exam. It will include a review about the effectiveness and different formats of collaborative tests along with successful strategies for implementing them in face-to-face and online statistics classes.
  • Primarily Statistics: Developing an Introductory Statistics Course for Pre-service Elementary Teachers

    Jennifer L. Green, Montana State University and Erin E. Blankenship, University of Nebraska-Lincoln
    Tuesday, January 21, 2014 - 3:30pm
    We developed an introductory statistics course for pre-service elementary teachers. In this webinar, we will describe the goals and structure of the course, as well as the assessments we implemented. Overall, the course aims to help pre-service teachers recognize the importance of statistics in the elementary curriculum, as well as the integral role they, as teachers, can play in a student's entire statistical education.
  • Investing in the Next Generation through Innovative and Outstanding Strategies (INGenIOuS): Report of outcomes from a recent workshop

    A. John Bailer, Miami University
    Tuesday, January 14, 2014 - 12:00pm
    The need for a larger proportion of the workforce to enter well equipped with mathematics and statistics skills has been acknowledged in a number of recent reports. To address this need, action must be taken by all stakeholders involved in preparing students for 21st century workforce demands. A collaboration of mathematics and statistics professional societies recently culminated in a workshop focused on identifying strategic steps that might be taken to dramatically increase the flow of mathematical sciences professionals into the workforce pipeline.
  • Does My Baby Really Look Like Me? Using Tests for Resemblance to Teach Topics in Categorical Data Analysis

    Amy G. Froelich & Dan Nettleton, Iowa State University
    Tuesday, November 19, 2013 - 12:00pm
    Many new parents have heard claims of a striking resemblance between them and their babies. As parents ourselves, we were skeptical of such claims so we devised a study to objectively answer the question "Does my baby really look like me?" In this webinar, we will present a study to test whether neutral observers perceive a resemblance between a parent and a child. We will demonstrate the general approach with two parent/child pairs (Amy and her daughter and Dan and his son) using survey data collected from introductory statistics students serving as neutral observers. We will then present ideas for incorporating the study design process, data collection, and analysis into different statistics courses.
  • The "Core Concepts Plus" Paradigm for Creating an Electronic Textbook for Introductory Business and Economic Statistics

    M. Ryan Haley, University of Wisconsin Oshkosh
    Monday, November 18, 2013 - 12:00pm
    This paper describes a textbook -development paradigm that has the flexibility to meet the specific needs of a department, college, and surrounding business community, while simultaneously lowering costs for students, facilitating the transition from intro-level to mid- and upper-level courses, preserving professor-specific preferences over course content and structure, increasing the quality and uniformity of the curriculum, overcoming difficulties of traditional rental programs, enhancing the professional development and teaching ability of professors, and improving student learning outcomes.
  • Updating the Guidelines for Undergraduate Programs in Statistics

    Nicholas J. Horton, Amherst College
    Tuesday, November 12, 2013 - 12:00pm
    Undergraduate study of statistics has been growing in recent years, with the number of students completing stats majors in the United States doubling in the past 5 years. At the same time, the amount and complexity of data being collected increases almost without bound. What should students completing undergraduate majors, minors or concentrations in statistics learn in order to help analyze this flood of information? The American Statistical Association endorsed guidelines in this area in 2000, and a workgroup is now considering what needs to be changed and amplified from the earlier report and supporting materials. In this webinar, participants will hear more about the process, learn about and identify key issues to be considered, and have the opportunity to make suggestions about areas and topics to explore.
  • Making the Grade: A Cross-National Analysis of Teacher Training on Student Achievement Across 52 Nations

    Natalie Bold, Seattle University
    Tuesday, October 22, 2013 - 12:00pm
    There has been an increasing number of school systems which are being held accountable for student performance, however there has not been a corresponding emphasis on school and teacher preparation with which to achieve these standards. Previous studies have shown the variation in teacher preparation both within and between countries. Many studies have shown that teachers are a major factor in predicting student achievement and academic success (Hattie 2008). And yet, to date there has been a lack of cross-national focus on the preparatory programs of educators and available data is sparse. I would like to help bring new attention to the importance of quality teacher training. My paper provides a broad comparison of national education systems, including teacher preparation requirements. I explore this topic by analyzing the performance of students in over 50 countries who participated in the 2006 and 2009 PISA (Program for International Student Assessment). I will demonstrate that high-quality teacher training is related to student achievement and learning and suggests that improving teacher training might contribute to local and national growth and development.
  • Distinguishing Between Binomial, Hypergeometric, and Negative Binomial Distributions

    Jacqueline Wroughton, Northern Kentucky University
    Tuesday, October 15, 2013 - 12:00pm
    In this webinar I will discuss the development and assessment of an activity used in an introductory calculus-based statistics course to distinguish between these three discrete distributions. Students from the assessment were students in one of these courses.
  • Which Traits Attract Women: Appearance, Intelligence, Wealth, or Strength?

    Nathan Tintle & Joshua Nymeyer, Dordt College
    Thursday, September 26, 2013 - 4:00pm
    "Which Traits Attract Women: Appearance, Intelligence, Wealth, or Strength?" was the first place winner of the Undergraduate Statistics Class Project Competition. Project mentor, Nathan Tintle of Dordt College, will briefly discuss the class assignment underlying the project and how he handles the project and the competition. Joshua Nymeyer, Dordt College, the team leader from the this class project will present their work.

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