Teaching Of Introductory Statistics Research Articles

The Teaching of Introductory Statistics: Results of a National Survey

The Statistics Teaching Inventory (STI) was designed to assess the teaching practices of U.S.-based, college-level introductory statistics instructors in a variety of institutions and departments. This instrument has now been updated to reflect current trends and recommendations in statistics education. In this study, we used the STI to examine the current state of the curricular and instructional practices being used by U.S.-based, college-level introductory statistics instructors. We explore the extent to which instructors report that their introductory statistics courses are aligned with recommended practices as outlined by the 2016 GAISE College Report. Data were collected from a sample of college-level U.S.-based, college-level introductory statistics instructors. Results based on 228 usable responses indicated that instructors, by-and-large, tended to be following the GAISE recommendations, especially related to content. However, courses may not yet be aligned with newer content recommendations (e.g., provide students opportunities to work with multivariate data), and there is still a large percentage of instructors that are not embracing student-oriented pedagogies and assessment methods. Supplementary materials for this article are available online.

Using R as a Simulation Tool in Teaching Introductory Statistics

The use of computer simulations in the teaching of introductory statistics can help undergraduate students understand difficult or abstract statistics concepts. The free software environment R is a good candidate for computer simulations since it allows users to add additional functionality by defining new functions. In this paper, we illustrate how computer simulations with R are used in statistics classrooms and student homework assignments by examples. These examples include sampling distributions and the central limit theorem, the t-distributions, confidence intervals, hypothesis testing, regression analysis and nonparametric tests.

TheRStudent Companion

I believe there is a fairly broad consensus that the teaching of introductory statistics often shortchanges the students. Course use unmotivating examples are unmotivating, principles are reduced to mere formulas, and even the word statistics evokes an image of tedious computation. Though it evoked controversy, I side with Xiao-Li Meng’s comments (Meng 2009) that the teaching of AP Statistics generally suffers from such problems.

Elaboration of Statistics Learning Objects for Mobile Devices

Mobile learning (m-learning) allows a person to study using a mobile computer device anywhere and anytime. In this work we report the elaboration of learning objects for the teaching of introductory statistics using cellular phones.

Using research papers as a tool in teaching introductory statistics

The introductory course in statistics has traditionally been taught as a collection of computationally intensive activities. In recent years, many statisticians have become involved in the reform movement in statistical education aimed at the teaching of introductory statistics. Those interested in reform want to emphasize statistical thinking and understanding and help students appreciate the role of statistics in the scientific process and in life. This paper suggests using research papers from refereed journals to illustrate how different statistical concepts are used together in scientific inquiry. In addition, it is hoped that students will see the value and relevance of statistics in their own lives and careers through examining research in their own areas of interest.

Teaching Students Inferential Statistics: A "Tail" of Three Distributions

THERE IS LITTLE question that fundamental concepts of statistics are quintessentially abstract (Watts 1991:290). As a result, the teaching of introductory statistics can be as frustrating as it is satisfying. It is frustrating in the sense that a complete understanding of statistical principles generally exceeds that which can be taught in a single semester. It is satisfying because the instructor is left with the creative task of finding mathematically intelligible ways of teaching students the many concepts associated with quantitative research. Teaching statistics is also challenging because the fundamental concepts that are introduced at the beginning of the course serve as the foundation for understanding inferential tests that occur later in the semester. The fundamental concepts associated with inferential techniques-such as the sampling distribution--are particularly important to students in introductory social statistics because these concepts help them understand how social scientists use a single sample to make generalizations about a larger population. As many of those who teach introductory social statistics would agree,

Training in the law of large numbers and everyday inductive reasoning: a replication, with implications for statistics course design

This study investigated the effect of a previously successful lesson in the law of large numbers on the everyday inductive reasoning of 64 Australian higher education students with humanities and science backgrounds. It also tested one aspect of Reigeluth's Elaboration Theory of Instruction. Word problems were used to test reasoning. The results closely replicated several of Fong, Krantz and Nisbett's findings with American subjects and supported Reigeluth's Theory, although they raise a question about the effectiveness of formal statistics course training in the local population. A possible salience or demand effect, and the interaction between moral development and the willingness to generalise statistical heuristics are discussed. Several new approaches to the teaching of introductory statistics are suggested.