Integrating Quality Control Concepts into the Introductory Business Statistics Course

Statistics courses are frequently perceived by tertiary students as extremely difficult and anxiety-inducing, negatively impacting student outcomes and experiences. To address this, the present study considered worked example videos (where an instructor demonstrates the solution to a problem while narrating the process) as a blended learning approach for enhancing an introductory business statistics course taken by 2265 students over three semesters. Impact was evaluated with video usage, academic performance, and student survey data. Students heavily utilised worked example videos before assessment deadlines, frequently employing active learning strategies during their engagements. Improvements in academic performance and course satisfaction were observed compared to previous cohorts. This demonstrates worked example videos are well-suited to large-enrolment courses due to their highly scalable capacity to deliver timely support for learning, which individuals can tailor to their diverse needs.

Because statistical analysis requires the ability to use mathematics, students typically are required to take one or more prerequisite math courses prior to enrolling in the business statistics course. Despite these math prerequisites, however, many students find it difficult to learn business statistics.In this study, we use an ordered probit model to analyze the impact of alternative prerequisite math course sequences on the grade performance of 1,684 business and economics statistics students at a large Midwestern university. In addition, we show how imposing a minimum grade requirement of C- for the math prerequisite course would influence student success in the business statistics course. Although several studies have examined the impact of different math skills, our study is the first to provide a detailed analysis of the impact of different prerequisite math course sequences on student performance in business statistics. We demonstrate that, other things the same, taking more math credit hours, taking math courses that emphasize calculus, and imposing a minimum grade of C- on the prerequisite math course have significant positive impacts on student grade performance in the business and economics statistics course.

Aim/Purpose: The main aim of the research is to examine the performance of second language English speaking students enrolled in the Business Statistics course and to investigate the academic performance of students when taught under the constructivist and non-constructivist approaches in a classroom environment. Background: There are different learning theories that are established based on how students learn. Each of these theories has its own benefits based on the different type of learners and context of the environment. The students in this research are new to the University environment and to a challenging technical course like Business Statistics. This research has been carried out to see the effectiveness of the constructivist approach in motivating and increasing the student engagement and their academic performance. Methodology : A total of 1373 students were involved in the quasi-experiment method using Stratified Sampling Method from the year 2015 until 2016. Contribution: To consider curriculum adjustments for first year programs and implications for teacher education. Findings: The t-test for unequal variances was used to understand the mean score. Results indicate students have high motivation level and achieve higher mean scores when they are taught using the constructivist teaching approach compared to the non-constructivist teaching approach. Recommendations for Practitioners: To consider the challenges faced by first year students and create a teaching approach that fits their needs. Recommendation for Researchers: To explore in depth other teaching approaches of the Business Statistics course in improving students’ academic performance. Impact on Society : The constructivist approach will enable learning to be enjoyable and students to be more confident. Future Research: The research will assist other lectures teaching Business Statistics in creating a more conducive environment to encourage second language English speaking students to overcome their shyness and be more engaged.

[This Proceedings paper was revised and published in Informing Science: the International Journal of an Emerging Transdiscipline (InfoSci)] Aim/Purpose: The main aim of the research is to examine the performance of second language English speaking students enrolled in the Business Statistics course and to investigate the academic performance of students when taught under the constructivist and non-constructivist approaches in a classroom environment. Background: There are different learning theories that are established based on how students learn. Each of these theories has its own benefits based on the different type of learners and context of the environment. The students in this research are new to the University environment and to a challenging technical course like Business Statistics. This research has been carried out to see the effectiveness of the constructivist approach in motivating and increasing the student engagement and their academic performance. Methodology: A total of 1373 students were involved in the quasi-experiment method using Stratified Sampling Method from the year 2015 until 2016. Contribution: To consider curriculum adjustments for first year programs and implications for teacher education. Findings: The t-test for unequal variances was used to understand the mean score. Results indicate students have high motivation level and achieve higher mean scores when they are taught using the constructivist teaching approach compared to the non-constructivist teaching approach. Recommendations for Practitioners : To consider the challenges faced by first year students and create a teaching approach that fits their needs. Recommendation for Researchers: To explore in depth other teaching approaches of the Business Statistics course in improving students’ academic performance. Impact on Society: The constructivist approach will enable learning to be enjoyable and students to be more confident. Future Research: The research will assist other lectures teaching Business Statistics in creating a more conducive environment to encourage second language English speaking students to overcome their shyness and be more engaged.

Most homework sets in statistics courses are constructed so that students concentrate or “mass” their practice on a certain topic in one problem set. Distributed practice homework sets include review problems in each set so that practice on a topic is distributed across problem sets. There is a body of research that points to the efficacy of distributed practice for developing a variety of skills from word recall to surgical techniques. A trial was conducted in several sections of a business statistics course where students were randomly assigned to either have massed practice homework sets or distributed practice homework sets. The two groups were then compared on the course assessments. The results show some evidence for the efficacy of distributed practice homework sets, although this effect may be modified significantly by the instructor or by a Hawthorne effect.

The purpose of this study was to measure the comprehension of basic mathematical skills of students enrolled in statistics classes at a large regional university, and to determine if the scores earned on a basic math skills test are useful in forecasting student performance in these statistics classes, and to determine if students’ basic math skills have changed over time. The results showed that 22 percent of the students’ final grades in business statistics courses were explained by their scores on this skills test. These findings may be of use to statistics faculty in identifying students who experience difficulties in these courses in the future. The current students’ scores were compared to scores from a test previously given to students in 1992/1993. The students from the first group had significantly higher scores than the current group of students.

This paper describes changing the way a business statistics course is taught through the use of just-in-time teaching methods. Implementing this method allowed for more time in the class to be spent focused on problem solving, resulting in students being able to handle more difficult problems. Students’ perceptions of the just-in-time assignments were overall positive.

After witnessing a steady decline and increased variability in students' performance in Business Statistics over several years, it was clear there was need for a change in how students were engaged in the course. In this case study, we examine the use of a mix of technologies that were introduced in an attempt to improve student engagement and students' performance in terms of average course mark, grade performance, and failure rate. Learning technologies utilized over time include Facebook groups to create a learning common, live streaming tutorial over YouTube, flipping the classroom, polling software, electronic bulletin boards and interactive learning platforms such as Cengage MindTap. Our findings seem to suggest that the use of technology enhanced learning tools resulted in an improvement in mean course mark, grade performance and failure rate when compared to periods when the teaching method was purely didactic and used the traditional lecturebased methodology.

This paper describes how to incorporate data from a randomized controlled trial in rural Uganda into teaching an undergraduate business statistics course. The semester-length classroom exercise includes discussions and brainstorming sessions, which allow students to imagine how they would execute a field experiment and analyze the data. Students become familiar with one data set as they use it to supplement textbook examples of hypothesis testing, analysis of variance applications, and simple linear regression. The article discusses the background of the sustainability challenge of 2.8 billion people in the world cooking with solid fuels, the rollout and schedule of integrating field-experiment data into the classroom, and student evaluations of the exercise. The target audience is undergraduate statistics students and/or instructors interested in demonstrating how textbook statistics are used to better understand a real-world sustainability challenge.

In this 2011 investigation, a modified Delphi technique was introduced to determine whether an informed group of post-secondary online faculty and students could arrive at a consensus regarding the importance of previously recognized verbal immediacy behaviors. Two expert panels were presented with Gorham’s (1988) Verbal Immediacy Scale and tasked with determining those behaviors perceived as being the most important in the online learning venue. The result of the study confirmed that a consensus of opinion between online students and faculty is indeed possible, albeit resulting in a new iteration of Gorham’s scale. A discussion of the findings suggests that further consideration for the development of an updated version of a verbal immediacy scale specific to online instructional behaviors may be warranted.

Business statistics courses are not typically popular, and students often find the examples and textbook problems tedious and irrelevant. In this article, the author describes a pedagogy project that keeps students interested and working effectively in a large class. Through a student survey, the author gathered data on students' university experience and demographics. The class used the Statistical Package for the Social Sciences (SPSS) data set for demonstration of a range of statistical techniques. The student survey instrument and data set provided examples and problems for each of the major topics of the course. Student comments and performance demonstrated the project's positive results.

The ability to conduct and correctly interpret the results of hypothesis tests is one of the most important skills that students can acquire in the introductory statistics course. Unfortunately, it is also one of the most difficult skills for them to learn.' Although this problem is widely recognized, textbook authors disagree about the best approach to use for conducting one-tailed hypothesis tests. In a recent survey of introductory business and economics statistics textbooks, we found that about half use the simple null hypothesis approach and about half use the composite null hypothesis approach for one-tailed hypothesis tests.2 Whereas both approaches are valid, the composite null hypothesis approach requires a more detailed statistical explanation than does the simple null hypothesis approach. Unfortunately, most textbooks that use the composite null hypothesis approach eschew the relevant explanation and use, instead, an explanation suitable only for the simple null hypothesis approach.

A First Course in Business Statistics

In this investigation of student performance in introductory business statistics classes, the authors performed two separate controlled studies to compare performance in (a) distance-learning versus traditionally-delivered courses and (b) multiplechoice versus problem-solving tests. Results of the first study, based on the authors' several semesters of experience teaching the course in both distance-learning and traditional formats, show that the distance-learning students did not fare as well as those taking the course in the traditional format. The results of the second study, in which a common set of students took both multiple-choice and written exams in the same semester, showed no significant difference in performance.

In this chapter we present a model for using case studies for the core of an undergraduate theoretical statistics course. These case studies have more depth than most examples found in typical mathematical statistics texts. Each case study provides a real-world question to be addressed as well as background information on the question, data to address the problem, and suggestions for investigating the problem. An important goal is to encourage and develop statistical thinking. This chapter provides both a sample case study on quality control and analysis of variance and a directed project on experimental design that includes a discussion of how we have changed the class to fit these activities into the course. In essence, the case studies become the centerpiece of the course, and as a result, the curriculum, lectures, and assignments are significantly different from a traditional mathematical statistics course.