Decision Sciences-Journal of Innovative Education最新文献

This article presents a project that uses a business context to introduce students to a multiphase approach to analytics while relying primarily on an introductory Excel course for prerequisite knowledge. A range of analytics techniques—including Excel Pivot tables and charts, regression trend lines, and linear programming—are combined into an integrative project. Using a customer orders database, student groups took on the role of category management teams assigned to analyze product sales, pricing, and costs to create an optimized purchase plan to replenish inventory. The instructor-guided project was employed in a sophomore-level introductory business intelligence course positioned within an undergraduate business core curriculum. Based on the context and level, such a project could be used in a business core course such as fundamentals of business, marketing, operations/supply chain management, information systems, or business analytics.

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.

Firms desire graduates capable of executing current and future business practices, many of which revolve around data. To meet those needs, we shifted the orientation of our required information systems course from technology to data. Instead of a survey of information systems, students learn the data acquisition–preparation–mining–presentation process in an information-systems setting. The scope of the revised undergraduate introductory course includes decision trees, Bayesian classifiers, and clustering; it uses Microsoft's Excel, Access, SQL Server, Power BI, and SQL Server Analysis Services to reveal the basics of data analytics to students. Students have welcomed the change and understand that the course material directly applies to what they will experience as working professionals. Similarly, employers have appreciated the change and tell us that our graduates are better prepared to perform data analysis with minimal training.

Failure has an important role to play in learning how to navigate highly uncertain organizational environments. But “failing fast” just for its own sake may in fact undermine learning if not set up or handled correctly. Using failure-based pedagogy, including generative failure, whole-person learning, and entrepreneurial thinking, an MBA course was designed and experienced by 48 students in three instances. Structured around a novel guiding framework of “brains, bravery, and belief,” the course has resulted in highly impactful learning for students. Student experiments are typically based around either exploring an entrepreneurial idea, developing or enhancing a particular skill, or applying skills and knowledge to help improve a societal problem. In each case, students are supported but also challenged to go beyond their comfort zones and encounter some intelligent failure in the journey. Regular reflection on their experiences, both from a cognitive and an affective perspective, is an essential element built into the course experience. The course, which itself was an experiment and not without its own instructive failures, is now an essential part of the MBA experience.

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.

Project management (PM) work readiness requires preparation beyond the knowledge of concepts and best practices to develop and practice soft skills needed for successful project management. This article proposes a methodology that combines real-world practitioner tools, PM processes, and a Microsoft Excel-based PM Simulator to create a “messy” project environment for students to apply concepts supported by soft skill practice. This methodology addresses a gap in classroom strategies focusing on soft skill development via practice rather than knowledge conveyance for PM education. Faculty provides a project case study for students to plan and execute, starting with charter development and carrying through project execution. This article illustrates one potential case study, but any project planning case study can be used with the PM Simulator as long as the project plan from the case has fewer than 100 individual tasks (PM Simulator constraint). Faculty can control complexity to prevent unwinnable and overly easy scenarios preventing students from becoming frustrated or bored, each a potential learning roadblock. The simulation of an unpredictable project environment occurs as students are faced with challenges that they must assess and overcome. Two pilot implementations successfully demonstrated that students learned to create incremental project artifacts such as charters, project plans, status reports, and learned schedule versus budget-balancing concepts.