XBRL data is volumous, which is both a benefit, but also a hurdle for students who are newer to data extraction. You can overcome this hurdle by providing students with a highly structured case, like the one presented below.
Spotlight Case:
How can XBRL data be used to detect changes in unreserved loan losses.
Author: Christine Cheng, Univrsity of Mississippi; Marc Cussatt, Clemson University; Holly Hawk, Clemson University
Inspiration: Media article link by Campbell Pryde
Time Requirement:
This case can be completed in one 75 minute class. Alternatively, students can use the video resources to complete the case outside of class, reserving more time for in-class discussion of the case.
Technology Requirements:
Students can gather the XBRL data for this case through XBRL Filed Data Spreadsheet Add-In for Microsoft Excel or Google Sheets or the XBRL-US Python package from Cheng et al. (2024). Other resources for XBRL data exreaction are provided in How do I get XBRL data?
Learning Objectives:
- Introduction to XBRL and the use of XBRL for decision making
- Exposure to XBRL tags
- Exposure to XBRL spreadsheet add-in and/or Python Wrapper
- Effective Data Visualization
- Effective Communication
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