Undergraduate Business Statistics Course Research Articles

Postsecondary students’ understanding of statistics through story-based tasks

This paper is based on a study that explored a pedagogical approach consisting of interactive story-based tasks used in a first-year undergraduate business statistics course. It addresses the types of understanding students developed for selected statistics topics. Participants were undergraduate business majors required to take the course. Data consisted of the students’ work with the four story-based tasks. Findings suggest that interactive story-based tasks have the potential to be a worthwhile pedagogical approach to support students’ understanding of several statistics concepts at various levels of understanding, but further research is needed to better understand the pedagogical approach needed for adult learners to better implement these tasks to support the deepest level of understanding for all concepts.

How Are Students Learning in a Business Statistics Course? Evidence from Both Direct and Indirect Assessment

This paper studies how both direct and indirect assessment outcomes can determine how students are learning different concepts in business statistics. We explore connections between the outcomes from the two assessment approaches and how different student characteristics and background factors impact these two methods of assessment. The results based on a sample of 64 students enrolled in an undergraduate business statistics course at a large public university designated as a minority-serving institution show some similarities and some differences among the two types of assessment outcomes and the insights they provide about overall student learning in the course. Furthermore, factors like gender and background grade point average are seen to impact both direct and indirect assessment results, whereas others such as the type of business concentration and student status only impact one type of assessment. Finally, we show that some indirect assessment outcomes can predict direct assessment outcomes while controlling for demographic and other background variables.

Forecasting Students’ Final Exam: Results Using Multiple Regression Analysis in an Undergraduate Business Statistics Course

This paper discusses the development of a multiple regression model to predict the final examination marks of students in an undergraduate business statistics course. The marks of a sample of 366 students in the Winter 2017 semester were used to fit the regression model. The final model contained three predictor variables namely two test marks and the homework assignment mark. The marks of another 194 students from Winter 2018 were used to validate the model. The model validation showed that it can be used for future cohorts of students for prediction. The two main objectives of the study were to use the model as a teaching tool in class and to use the model to predict final examination marks of future students.

A Web-based Matrix Organizer for Chunked Multimedia Course Content

This study presents a web-based matrix organizer that houses multi-media course content, including videos and infographics, for an undergraduate business statistics course. Content is “chunked” into microlessons explaining the “When, What and How” of several statistical techniques. An observational study was conducted to evaluate satisfaction with the tool and how the tool influenced learning. Results show that students felt the tool was easy to use and helped them organize and learn information. Some evidence suggests users have higher perceived learning and grades than non-users. The structure can be used for other courses; recommendations for implementing similar systems are presented.

Improving Student Performance in an Undergraduate Business Statistics Course Using Technology Enhanced Learning

Improving Student Performance in an Undergraduate Business Statistics Course Using Technology Enhanced Learning

Some Suggestions for Teaching Undergraduate Business Statistics Courses

Student anxiety is high in many business statistics courses. Often, students fail in these courses because they rely highly on grades rather than on meaningful learning. Instructors also feel the pressure because their students do not attempt to learn deeply. I taught Quantitative Methods courses for a number of years in a University in Ontario, Canada. In this paper, I have critically analyzed some of the challenges that instructors face in teaching these courses and suggested some solutions based on an educational point of view. Continuous assessment, portfolio construction, and improving the efficiency of instructor evaluations are three key suggestions for consideration.
 As these challenges are common to most undergraduate courses in business statistics, the suggestions would mainly help to raise student motivation, encourage students to learn deeply, and increase instructor efficiency.

Using Financial Investment Measures to Proactively Engage Students in the Introductory Business Statistics Course

ABSTRACTTypically, the core-required undergraduate business statistics course covers a broad spectrum of topics with applications pertaining to all functional areas of business. The recently updated American Statistical Association's GAISE (Guidelines for Assessment and Instruction in Statistics Education) College Report once again stresses the pedagogical importance of topic and application relevancy in an increasingly data-centered world. To this end, only two introductory textbooks have incorporated some financial investment measures (Sharpe ratio and beta coefficient) in the teaching of numerical descriptive measures and simple linear regression analysis, respectively, while a few others include them as real-data application exercises at the end of their respective chapters. Although this latter coverage is in compliance with GAISE College Report recommendations on the importance of using relevant real data applications in the teaching of introductory business statistics, it forgoes an opportunity to provide more detailed discussion within the text itself and add value to a business student's learning. Given that all business students will have an opportunity to learn about financial investment, regardless of their functional area major, this paper offers a more proactive use of these and other financial investment measures as part of the current, traditional course or as part of a suggested dedicated introductory business statistics course for finance majors.

Components of a Flipped Classroom Influencing Student Success in an Undergraduate Business Statistics Course

ABSTRACTAn instructor transformed an undergraduate business statistics course over 10 semesters from a traditional lecture course to a flipped classroom course. The researcher used a linear mixed model to explore the effectiveness of the evolution on student success as measured by exam performance. The results provide guidance to successfully implement a flipped classroom course. The largest improvements were achieved by replacing face-to-face lecture with active learning exercises and using quizzes to verify student engagement with offline materials. Using conditional release of course materials to encourage homework completion also provided a significant benefit to students who missed class often.

An Empirical Investigation of the Conception Focused Curriculum: The Importance of Introducing Undergraduate Business Statistics Students to the “Real World”

ABSTRACTContinuing pressures are being placed on undergraduate business education to alter curriculum content and delivery. The anticipated product of these changes is a graduate that is capable of performing the higher order thinking skills needed to navigate a constantly changing, global business environment. This article describes the implementation of a conception‐focused curriculum in an undergraduate business statistics course that has guided students to become masters of the discipline through conception learning and real world problem solving. The sample of 125 students shows that students exposed to the conception‐focused curriculum perceived themselves as being higher order learners and global citizens. Recommendations are provided for other educators to implement this approach in their classrooms and suggestions made for future research.

Enhancing An Undergraduate Business Statistics Course: Linking Teaching And Learning With Assessment Issues

This paper examines several ways in which teaching effectiveness and student learning in an undergraduate Business Statistics course can be enhanced. First, we review some key concepts in Business Statistics that are often challenging to teach and show how using real data sets assist students in developing deeper understanding of the concepts. Second, the paper examines some ways that typical learning issues faced by students taking such a course can be effectively addressed. Third, the paper describes how assessing what knowledge of statistics is retained after formal coursework is completed can provide both a rich source of feedback to improve Business Statistics courses themselves and to strengthen undergraduate business programs, in general.

A Study of the Effectiveness of Web‐Based Homework in Teaching Undergraduate Business Statistics

ABSTRACTWeb‐based homework (WBH) Technology can simplify the creation and grading of assignments as well as provide a feasible platform for assessment testing, but its effect on student learning in business statistics is unknown. This is particularly true of the latest software development of Web‐based tutoring agents that dynamically evaluate individual students' skill level and purport to respond with appropriate, targeted teaching to improve learning efficiency. In this article, we compare traditional, textbook‐based homework assignments with three systems of WBH for undergraduate business statistics courses: ALEKS, PH Grade Assist, and custom‐made online quizzes in Blackboard. These systems represent a range of media from artificial intelligence–based tutoring to instructor‐controlled objective testing. Using a common assessment test, we compare the performance of students taught with these different systems. Our study finds, as we anticipated, that student performance depends significantly upon teacher experience and student academic competence. Once these factors are controlled for, however, the technique used to deliver homework makes little difference in student success. In contrast to other published research, we do not find any advantage to automated tutoring and identify some limitations of this approach based on both instructor and student feedback.

Teaching Business Statistics With Real Data To Undergraduates And The Use Of Technology In The Class Room

In this paper an attempt is made to highlight some issues of interpretation of statistical concepts and interpretation of results as taught in undergraduate Business statistics courses. The use of modern technology in the class room is shown to have increased the efficiency and the ease of learning and teaching in statistics. The importance of using real data in examples and exercises in class room teaching is emphasized.

A Comparison of Student Persistence and Performance in Online and Classroom Business Statistics Experiences

ABSTRACTAs universities extend their distance education offerings to reach more time‐ and place‐bound students, the degree to which online students are successful, as compared to their classroom counterparts, is of interest to accreditation review boards and others charged with assessment. Teaching faculty use information about the effectiveness of their instruction to evaluate and improve the learning experience. By comparing persistence and performance measures from the author's five semesters of online and traditional sections of a required undergraduate business statistics course, this paper provides evidence that while there are significant differences in persistence between the two cases, accomplishment of the learning objectives, as measured by the final grade in the course for those students who persist, is independent of the mode of instruction.

Business Statistics Education: Content and Software in Undergraduate Business Statistics Courses

This study surveyed 500 institutions of higher education in the United States for data on their course content and software use. In undergraduate Business Statistics I courses, the most prevalent topics covered were data analysis, probability, sampling distributions, estimation, means and hypothesis testing; the most popular software by far was Minitab. In Business Statistics II courses, regression analysis, hypothesis testing, time series, and forecasting are most important. Minitab, SAS, Execustat, and ASP were the prevailing software. Most schools of business require both Business Statistics I and II for all students. We present further findings regarding course requirements and content.

Undergraduate Business Statistics: A Survey of Topics and Teaching Methods

Participants in the annual conferences on “Making statistics more effective in schools of business” have made recommendations for improving the teaching of statistics in schools of business. To determine what is being taught and how it is being taught in terms of these recommendations, we surveyed professors teaching undergraduate business statistics courses. We found that hypothesis testing receives the greatest share of coverage and quality control the least. Computers are not used in one quarter of the courses, and lecturing is still the dominant teaching method. When asked for a wish list of changes, professors most often listed greater use of computers and more relevant data.