Work

Teaching binary logistic regression modeling in an introductory business analytics course

Year: 2022

Type: article

Abstract: There is an increasing demand to introduce Introductory Business Analytics (IBA) courses into undergraduate business education. Many real‐world business contexts require predictive analytics to understand the determinants of a dichotomous outcome; hence, IBA courses should include binary logistic regression analysis. This article provides our reflective discussions on the design of learning activities and assessments to assist business students in learning binary logistic regression in an IBA course. Data on student engagement and learning outcomes are used to shed light on the impacts of teaching logistic regression on student learning and experience. Notably, students opt to focus their assessment work more on logistic regression than on multiple regression analysis, showing the potential attraction of students toward binary logistic regression analysis. We also observed several challenges, mainly related to the use of Excel, that require special attention from instructors.

Source: Decision Sciences Journal of Innovative Education

DOI: 10.1111/dsji.12274

Authors: Viet‐Ngu Hoang, Justin Watson

Institutions: Queensland University of Technology, Vietnam National University, Hanoi, VNU International School

Language: English

Topic: Management and Marketing Education

Subfield: Management of Technology and Innovation

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $2,550