arbiter
JournalsAccount

Data Analytics in the financial statement audit: Assessing its active learning effects on student performance

Ouadie Akaaboune et al.

Accounting Educators Journal2020article
ABDC B
Weight
0.43

Abstract

The purpose of this study is to determine the impact that completing a data analytics (DA) assignment has on student learning in a financial statement audit course. The growing implementation of DA in financial auditing, the need for those entering the profession to possess higher order thinking skills, and the ability to perform analysis tasks makes our study timely and relevant. Two groups of students are compared for their exam performance in a financial statement audit course, with one group completing an IDEA assignment after the first exam and other not doing so. Results show that student performance on the second and third exams improved for those who completed the assignment but there was no similar improvement for those who did not. Our results suggest that there is value in using DA in a financial statement auditing course. This should be appealing both to accounting education and to the audit profession due to the implication that graduates would be better prepared to meet the growing demands for higher order thinking and DA skills.

2 citations

Cite this paper

@article{ouadie2020,
  title        = {{Data Analytics in the financial statement audit: Assessing its active learning effects on student performance}},
  author       = {Ouadie Akaaboune et al.},
  journal      = {Accounting Educators Journal},
  year         = {2020},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Data Analytics in the financial statement audit: Assessing its active learning effects on student performance

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.43

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.21 × 0.4 = 0.08
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.