This 5-year study of graduating seniors at Elon University ( n = 2,058) evaluates the impacts of experiential learning depth (amount of time commitment) and breadth (number of different types of experiences) on student outcomes. Data on study abroad, undergraduate research, internships, service, and leadership experiences were pulled from cocurricular transcripts and paired with responses to the National Survey of Student Engagement. Both depth and breadth were associated with acquiring a broad general education, writing clearly and effectively, contributing to the welfare of communities, relationships with faculty and administration, and desire to attend the same institution. Depth (but not breadth) was associated with higher order thinking (synthesis and application) in the senior year, as well as overall educational experience. Breadth (but not depth) was associated with working effectively with others and better relationships with other students. Overall, key learning outcomes desired for a college student are driven by both experiential learning depth and breadth.

No abstract

This five-year study of graduating seniors at Elon University (n=1,858) compared student outcomes measured by the National Survey of Student Engagement across five study abroad groups:  no study abroad, semester, short-term (3-week), two short-terms, and semester plus short-term.  Both short-term and semester programs were positively associated with how students rate their overall educational experience and whether they would attend the same institution again. However, students who participated in semester programs reported better outcomes in numerous categories: contributing to class discussion, including diverse perspectives in discussions and assignments, synthesis of ideas, less rote memorization of course material, empathy,acquiring a broad general education,critical thinking,and working effectively with others.  There was less compelling evidence of better outcomes from a second short-term program or one taken in addition to a semester program.  Overall, short-term programs clearly have value, but semester programs are associated with significantly better outcomes overall.

This article presents the results of a case study from one professor's experience teaching an introductory statistics course. The goal of this study was to better understand student perceptions of engagement in a statistics course. Voluntary, self-reported data were collected daily for students to evaluate the engagement level of the class that day, and students also identified activities that they considered engaging. A final survey was administered at the end of the semester to provide a holistic, retrospective measure of engagement in the course and to collect feedback on various questions related to perceptions of engagement. Results indicate variation in student engagement scores and variation in engagement scores across the semester indicating some influence of class activity on perceptions of engagement. Perceptions of engagement are contextualized with students' comments from the daily surveys. Associations between engagement and final course grade were also investigated. Student perceptions of engagement were also compared to the professor's perception of engagement for students.

Nonparametric estimators of component and system life distributions are developed and presented for situations where recurrent competing risks data from series systems are available. The use of recurrences of components’ failures leads to improved efficiencies in statistical inference, thereby leading to resource-efficient experimental or study designs or improved inferences about the distributions governing the event times. Finite and asymptotic properties of the estimators are obtained through simulation studies and analytically. The detrimental impact of parametric model misspecification is also vividly demonstrated, lending credence to the virtue of adopting nonparametric or semiparametric models, especially in biomedical settings. The estimators are illustrated by applying them to a data set pertaining to car repairs for vehicles that were under warranty.

This article explores the use of online survey software to collect data from students during class to efficiently use class time. Several example activities for an introductory statistics classroom are considered. We also discuss utilization of online survey software for other purposes such as collecting assessment information and student preferences related to statistics projects.

This paper examines the use of a randomization-based activity to introduce the ANOVA F-test to students. The two main goals of this activity are to successfully teach students to comprehend ANOVA F-tests and to increase student comprehension of sampling distributions. Four sections of students in an advanced introductory statistics course participated in this study. When the topic of ANOVA was introduced, two sections were randomly assigned to participate in a traditional approach (one for each instructor), while the other two sections participated in a randomization-based method. Students were administered a pre-test and a post-test that asked them to apply hypothesis testing concepts to a new scenario. Students also responded to some basic conceptual questions. This study showed mixed results related to students' understanding of the logic of inference, but the activity utilized shows some promising gains in student understanding of sampling distributions.

The purpose of this research is to better understand the role of statistics in teaching and research by faculty from all disciplines and their perceptions of the statistical preparation of their students. This study reports the findings of a survey administered to faculty from seven colleges and universities regarding the use of statistics in teaching and research with undergraduate students. The introductory statistics course serves as a foundation for statistical methods that students learn and use in classes within numerous other disciplines. Information was collected from faculty on how students can be better prepared in the introductory statistics class to use statistics in other disciplines. Findings from this paper imply that statistics is being widely used in a variety of disciplines but also suggest that cooperative communication and transitional second courses in statistics be implemented. This paper also highlights the varied statistical techniques that faculty members teach in their courses and mentor in student research projects and statistical experiences.