Project Summary:
In this GLE project, students from both DePaul and National Chung Cheng University collaborate to work on a fraud detection data analytics case provided by KPMG. Due to the unstructured nature of the case, students will need to define the objectives and scope of the project, design and execute the analyses by considering different possible scenarios and explanations, highlight key findings and provide recommendations. The project not only emphasizes the communicational, cultural, and educational differences in the data driven decision making processes but also highlight local institutional contexts and technology preferences that can influence the decisions.
Project Length:
Technology Tools Used:
- Zoom
- Whatsapp
- Google Slides
- Google Docs
- Line
- Teams
- Google Meet
Interaction Mode:
Learning Outcomes:
- Students learned to evaluate quality of evidence when addressing the objectives and consider possible alternatives.
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Students learned to communicate effectively, need to take into account intercultural differences and local institutional context.
- Students learned to logical conclusion and reasoning by taking into account the decision contexts.
Faculty Feedback:
“Through the GLE project, students have demonstrated the skills needed when working with a global team, which is a must in today’s business environment.” ~ David Wang
“It was incredibly rewarding to see them embrace new perspectives and develop a deeper understanding of audit issues through AI-based solutions in these exchanges. The collaborative projects and discussions not only enhanced their academic knowledge but also fostered critical thinking, technological skills, and cultural awareness. This experience has reinforced the importance of accounting and auditing education and its impact on preparing students for a diverse and interconnected world.” ~ Jack Huang
David Wang
Institution: DePaul University
Discipline: Accounting
Course name: Audit Analytics
Shi-Ming Huang
Institution: National Chung Cheng University
Discipline: Accounting
Course name: Computer Analytics