Large Introductory Statistics Research Articles

How to use academic and digital fingerprints to catch and eliminate contract cheating during online multiple-choice examinations: a case study

Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination of unique academic and digital fingerprints, and identified students who used virtual private networks (VPNs) to protect their online identity. There were two forms of cheating – posting questions and waiting for responses from tutors, and looking for questions that had already been solved. We found that 165 questions from these examinations were posted by 10 different students, but that the most common form of cheating was searching for answers that had already been posted. This paper discusses these patterns of Chegg usage, the consequences of not catching cheating early on, and how students reacted to being caught. Also provided are R and Python code that readers may use to identify cheating students in their own courses.

A Randomized Study to Evaluate the Effect of a Nudge via Weekly E-mails on Students’ Attitudes Toward Statistics

Can a “nudge” toward engaging, fun, and useful material improve student attitudes toward statistics? We report on the results of a randomized study to assess the effect of a “nudge” delivered via a weekly E-mail digest on the attitudes of students enrolled in a large introductory statistics course taught in both flipped and fully online formats. Students were randomized to receive either a personalized weekly E-mail digest with course information and a “nudge” to read and explore interesting applications of statistics relevant to the weekly course material, or a generic course E-mail digest with the same course information, and no “nudge.” Our study found no evidence that “nudging” students to read and explore interesting applications of statistics resulted in better attitudes toward statistics. Supplementary materials for this article are available online.

Utilizing Peer Review and Revision in STEM to Support the Development of Conceptual Knowledge Through Writing

While many STEM faculty believe Writing-to-Learn to be an effective instructional tool, instructional barriers such as the time and effort required to provide substantive feedback to their students limit the use of writing in STEM classrooms. Incorporating peer review and revision into the writing process can help mitigate these barriers while additionally supporting the learning process. This study presents an analysis of a Writing-to-Learn assignment that incorporates peer review and revision into a large introductory statistics course, where this study specifically focused on whether engaging with these processes results in changes in how students write about the content targeted by the assignment. Our results demonstrate that students made content-focused revisions between drafts that increased the amount of content they explained correctly. Additionally, our study provides evidence that students benefit from reading peers’ work in a content-focused peer review and revision process. Overall, this study shows that incorporating peer review and revision into writing assignments focused on developing content knowledge provides students with substantive feedback and enhances students’ conceptual learning.

Assessing student learning and knowledge transfer using principles of team-based learning and bridge assignments in large introductory statistics classes.

Assessing student learning and knowledge transfer using principles of team-based learning and bridge assignments in large introductory statistics classes.

Class attendance and learning outcome

This paper presents new evidence on the dynamic treatment effects of class attendance on academic performance. The analysis is based on a dataset from a large introductory statistics course and a dynamic modeling framework of Ding and Lehrer (Rev Econ Stat 92(1):31–42, 2010). The course had seven progressive assessments spread across a thirteen-week semester. Assessment test scores were matched to individual student attendance records. We use a panel dataset to study the dynamic interactions over time and between learning activities including lectures and tutorials, while accounting for reverse causality and self-selection without resorting to instruments for attendance or discontinuity design. Class attendance is found to have a test score return rate of 1.3 percentage points per lecture and 1 percentage point per tutorial. For both lecture and tutorial attendances, the contemporaneous effect dominates the lagged effect, with the effects accumulating over time. We also find a substitution rather than complementarity effect between lecture attendance and tutorial attendance, but the former has a stronger effect on test scores than the latter. Our results also show these effects are stronger for under-performing students.

Two Learning Activities for a Large Introductory Statistics Class

In a very large Introductory Statistics class, i.e. in a class of more than 300 students, instructors may hesitate to apply active learning techniques, discouraged by the volume of extra work. In this paper two such activities are presented that evoke student involvement in the learning process. The first is group peer teaching and the second is an in-class simulation of random sampling from the discrete Uniform Distribution to demonstrate the Central Limit Theorem. They are both easy to implement in a very large class and improve learning.

Using Cooperative Learning in a Large Introductory Statistics Class

This article discusses one active learning technique, cooperative learning, that can be used in large classes. This technique requires that students be divided into learning teams. A method for quickly dividing a large class of students into learning teams is presented. Two examples of cooperative learning exercises used in an introductory statistics class are given. These serve as illustrations of the type of cooperative learning exercises that can be assigned in a large class. In particular, these exercises were used in a class of 195 students. Preliminary findings by the instructor of the advantages of using cooperative learning exercises are discussed.

Enhancing Statistics Education with Expert Systems: More than an Advisory System

This article reports on the results of two studies that investigated the effectiveness of different uses of expert systems in large introductory statistics classes. Three groups of students were co...

Increasing Student Participation in Large Introductory Statistics Classes

Abstract Traditionally, a large class in elementary statistics is taught by having the instructor lecture for the class period with little interaction from the students. This article considers an approach for teaching a large elementary statistics class that encourages student involvement. Comments and evaluations from the students who took a class using this approach are examined.

Increasing Student Participation in Large Introductory Statistics Classes

Increasing Student Participation in Large Introductory Statistics Classes