Objectives and curriculum for a graduate business analytics capstone: Reflections from practice. (12th July 2022)

• Record Type: Journal Article
• Authors: Anand, Tej; Mitchell, Daniel
• Is Part Of: Decision sciences journal of innovative education. Volume 20:Number 4(2022)
• Page Start: 235
• Page End: 245
• Publication Date: 2022-07-12
• Subjects: business analytics -- capstone -- artificial intelligence/machine learning -- course design; Business education -- Periodicals; 658.00711
• DOI: 10.1111/dsji.12272
• Languages: English
• ISSNs: 1540-4595

Abstract

Abstract: Many higher education institutions have responded to the significant shortage of professionals with strong analytical expertise by offering graduate programs in business analytics and data science. These programs are typically designed to be practitioner focused and many of them offer a Capstone course that gives students the opportunity to conduct a real‐world analytics project. In this article, we describe the innovative design of a Capstone course offered to cohorts of approximately 110 graduate students in the business school at the University of Texas, Austin. This course is designed to deliver self‐directed and experiential learning from interacting with business stakeholders and successfully completing team‐based, business analytics projects within a commercial firm using the firm's data. The course design includes student and sponsor engagement, the formation of diverse balanced project teams, matching of teams with projects, and scaffolding, which includes consistent structured mentoring, team reflections, interim deliverables and in‐class learning for practical skills not covered elsewhere in the curriculum. This course has now been offered successfully to two cohorts. In this article, we will also describe changes made for the second cohort related to team formation, project matching, mentoring and in‐class learning. These changes were based on feedback from the first cohort.