This paper proposes a model to integrate data analytics into current undergraduate accounting curricula across existing courses rather than offering a stand-alone data analytics course. One of the advantages of curriculum integration is that students are introduced to data analysis in a progressive or sequential way. Furthermore, such an approach typically does not require additional credit hours to reflect the changes made to the accounting curriculum to introduce the emerging technologies used in the accounting profession. The model proposes course learning outcomes (CLOs) related to the data analytics applications linked to specific levels of study and accounting courses. In addition, teaching materials including the main textbook, supplemental reading materials, and case studies are mapped across accounting courses. This model is expected to be beneficial for accounting educators and members of curriculum committees when updating an accounting curriculum to include data analytics.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Accounting analytics
- Accounting curriculum
- Big data
- Data analytics