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In this article, we explore the drivers of students' success in a first-year university statistics course. Using a unique sample from Westminster International University in Tashkent, we discover that student engagement with their studies is reflected in their class attendance and in the use of online resources, which continue to play an important role in their academic performance. Moreover, we discovered that socio-demographic factors such as age, gender, marital status, employment, and language of instruction of prior schooling are significant in explaining student academic outcomes. These factors have important policy implications for both the university and the broader national level. [ABSTRACT FROM AUTHOR]

College instructors often provide students with only summative evaluations of their work, typically in the form of exam scores or paper grades. Formative evaluation, such as classroom assessment techniques (CATs), are more rare in higher education and provide an ongoing evaluation of students' progress. In this article, the author summarizes the use of CATs in an undergraduate introductory statistics course and present data indicating that students believed CATs increased their understanding of material and benefited their academic performance. With minor revision, these CATs can be effectively used in other disciplines. [ABSTRACT FROM AUTHOR]

The goal of this study was to validate measures and assess the effects of collaborative group-learning methods in real classrooms on 3 specific dependent variables: feelings of campus connectedness, academic classroom community, and effective group processing (2 factors). Confirmatory factor analyses were conducted to evaluate a 4-factor model. Using hierarchical linear modeling techniques, results indicated that campus connectedness and collaborative learning (compared with no collaborative learning) predicted positive academic classroom community. For classes using more formal cooperative group work, campus connectedness and group processing--evaluation predicted positive academic classroom community. Suggestions for further applications of the measures are discussed. [ABSTRACT FROM AUTHOR]

Focuses on the origins, concepts and pedagogy of statistics as a separate academic discipline. Definitions of statistics; Discussions of disciplinary boundaries; Educational reform views on inclusion of statistics topics in school mathematics in 20th century; Impact of curricular and pedagogic factors on uniformity of discipline.

Sex, drugs, and rock & roll are topics that arouse almost universal interest among students. We use that interest to motivate the learning of statistical thinking in our first-year Introduction to Statistical Methods course. We have designed a class survey that uses randomized responses. Each person does his/her own randomization with a pair of colored dice. This engages the students in the gathering and analyzing of sensitive data about his/her class in such a way that no individual's personal information is divulged. The survey gives the students a concrete situation where randomization removes the motivation to give false answers to sensitive questions. Instead, the "false" answers come into the data by the randomization which has a known probability structure, so the students can extract estimates of the class proportions without knowing any individual's personal information. This reinforces the message that statistical methods can only be relied on to give meaningful results when there is some known random structure underlying the data. [ABSTRACT FROM AUTHOR]

Focuses on a study which presented a guide for training Bachelor of Science (BS) statisticians from prospective employers. Information on the statistics degree; Methods used in the study; Positions and major job responsibilities suited for BS statisticians.

Deals with a study which discussed the curriculum guidelines for the Bachelor of Science degrees in statistical science in the United States. Historical background of the study; State of undergraduate programs in statistics; Recommendations for the statistics curriculum.

The following three articles are the results of papers presented and discussed at a symposium entitled "Improving the Workforce of the Future: Opportunities in Undergraduate Education," held August 12-13, 2000, in Indianapolis, IN. This symposium was sponsored by the American Statistical Association through its Undergraduate Statistics Education Initiative. The first article was the keynote address at the symposium. The latter two articles are position papers that were developed in part through discussions among representatives from liberal arts colleges, research universities, industry, and government at a May 1999 meeting at the ASA Headquarters and a subsequent April 2000 workshop in Alexandria, VA. This workshop was partially supported by the National Science Foundation. Other position papers based on symposium discussions are being developed and are scheduled to appear in the Journal of Statistical Education. [ABSTRACT FROM AUTHOR]

The Advanced Placement Statistics course, first offered in 1997 after more than 12 years of planning, allows high school students who pass an examination to receive college credit for a statistics course taken at their high school. In its third year 25,240 students took this examination, and 57% "passed." The three-hour exam consists of both multiple choice and free response questions, which cover the four sections of the AP Statistics syllabus: data exploration, study design, probability distributions through simulation, and inference. Although some problems remain, both students and teachers find the course to be challenging and valuable. [ABSTRACT FROM AUTHOR]

Comments on the articles written by James J. Higgins and Robert V. Hogg on statistical programs for the undergraduate statistics major. Status of statistics as an undergraduate discipline; Need for an identity for the undergraduate discipline; Use of continuous quality improvement (CQI) on statistics programs; Response from Higgins and Hogg.

Highlights results of a survey conducted by the Conference Board of the Mathematical Sciences on undergraduate programs in the United States. Enrollment in statistics courses; Number of bachelor's degrees with a major in statistics; Breakdown of full-time and part-time faculty members.

Presents several classroom demonstrations that have encouraged student involvement in the undergraduate course in decision theory and Bayesian statistics at the Columbia University in New York City. Principles of decision analysis; Subjective probability intervals and calibration; Utility of money and risk-aversion.

Attempts to imagine plausible futures on the state of statistics teaching at the university level at the end of the 20th century. Responses of the authors on the effect of technology on statistics; Ways of helping students learn more about statistics; Criticism directed at higher education.

Focuses on the challenges in teaching short statistics courses by the Department of Statistics at the University of Florida from 1991 to 1994. Reduced state funding for education; Necessity of coming up with external sources of funding; Development of a program called `Week of Short Courses' which was used to generate additional revenue.

Suggests issues and explores problems that must be considered in any substantial overhaul of statistics curricula in graduate programs. Introduction of cross-disciplinary training; Renewed emphasis on the undergraduate education; Example of an ideal statistics curricula.

Comments on the efforts of academicians to change the statistics curricula in graduate programs. Faculty selection as the biggest step in making good curriculum decisions; Necessity of changes in the statistic profession.

Comments on the efforts of academicians to change the statistics curricula in graduate programs from the point of view of an educational psychologist. Need for the faculty to be aware of teaching and learning techniques; Course work and experience on teaching as requisites for graduate students in statistics.

Proposes a graduate curriculum for the ideal statistics department. Includes computing; Data analysis; Data collection; Design of experiments; Inferences; Probability theory; Statistical consulting.

Describes an approach in teaching introductory statistics to undergraduates. Explanation of statistical formula; Feedbacks; Importance of rapport.