A model to integrate data analytics in the undergraduate accounting curriculum

Amer Qasim, Hussein Issa, Ghaleb A. El Refae, Alexander J. Sannella

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)31-44
Number of pages14
JournalJournal of Emerging Technologies in Accounting
Volume17
Issue number2
DOIs
StatePublished - Sep 1 2020

All Science Journal Classification (ASJC) codes

  • Accounting
  • Computer Science Applications

Keywords

  • Accounting analytics
  • Accounting curriculum
  • Big data
  • Data analytics

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