Identifying Addressable Impediments to Student Learning in an Introductory Statistics Course

Abstract

palocssw@jmu.edu} U sing performance data on a common test instrument administered to more than 4,000 business statistics students studying under 16 different instructors over a period of 6.5 years, we identify areas of consistent student weakness. In addition to verifying difficulties found by earlier researchers, we document a fundamental problem in students' ability to reason with cumulative probabilities, a problem with implications for solving problems with both discrete and continuous distributions. Our performance data also suggest that it may be useful to view statistics problems using a taxonomy based more on solution procedure than on traditional statistics topics. We employ a new methodology based on cluster analysis to identify areas where the observed student difficulties may be particularly addressable. Finally, we offer some preliminary findings on how these problems may be addressed with practical teaching suggestions based on the approaches employed by our more successful instructors.

Multiattempt Quizzes in an MBA‐Level Statistics Course

“…Results seemed to indicate that the videos were viewed more heavily by students with lower quantitative skills, as indicated by Math ACT scores. Stevens and Palocsay (2012) analyzed test results from a common final exam in an introductory statistics course taught by 16 different instructors and given to more than 4,700 students. They identified specific technical issues that students struggle with, such as reasoning with cumulative probabilities.…”

STRATA: A Spreadsheet Tool for Multidimensional Analysis of Operations Research/Management Science Assessment Test Data

“…• Assessment of student performance demonstrating effectiveness of using a measurable-quantity translation method to formulate LP models (Stevens and Palocsay 2004) • Pre-and posttesting of both actual and perceived knowledge for MBA students in six competency areas of business statistics (descriptive/graphical analysis, probability, statistical inference) and MS (LP, decision analysis, quality control) (Price and Randall 2008) • Percentages of correct responses on final exam questions in online business statistics and MS MBA courses to measure application and interpretation of inferential procedures and mathematical formulation and Excel implementation of a network LP model (Sebastianelli and Tamimi 2011) • Teaching notes describing an MBA assignment integrating regression analysis, simulation modeling, and decision trees for a location decision with sample assessment results Klingenberg 2012• Cluster analysis of test results in business statistics to identify the most difficult learning objectives and those where instruction had a positive impact (Stevens and Palocsay 2012) • Test instrument with empirical findings for a two-decision business scenario requiring LP model formulation, graphical solution, and written interpretation (Williams et al 2016).…”

Reflections on Sustainability Issues in Learning Object Development

“…However, the challenges of engaging business students with quantitative and statistical topics are well documented, see for example Stevens and Palocsay (2012) and Carroll and White (2017). Business students often feel that analysis and statistics are boring and not relevant to the real-world.…”