Abstract
Context Statistical testing to arrive at
decision-making-intel useful in setting the risk-level for the audit-client has
been a PCAOB best-practices-staple for many years. Initially, such
inferential-profiles required auditing students to be able to calculate all the
component-parts of the inferential tests—e.g., Means, Correlations, Standard
Deviations, and a-Rejection Regions to mention a few—in forming the
required inferential-intel. Recently, the pendulum has swung to the other
extreme; now there are software platforms that accept data and spew-out results
with little contextual guidance. Both
are the Bain of Pedagogic-sensibilities in the STEM-context. Deliverable In this research report, a
normative pedagogic Decision Support System [DSS] is offered that: (i) is
initialized Ex-Ante by the a-priori specification of the nature of
the particular audit-context so as to form an indication as to the risk-level
of the audit-client and so to justify the related audit-testing needed—this is
termed the Anchoring-Phase, (ii)
then the random-sampling results are collected and are made available to the
auditor—this is termed the Ex-Post-Phase,
(iii) in this Ex-Post-phase the inference-platform selected Ex-Ante is often changed—this is termed
the Conditioning-Phase, and (iv)
then the inference-results are presented by the DSS and used in the calibration
of the risk-level of the audit. Research
Question Does the Ex-Post Conditioning-Phase result in a change
in the inferential-protocol selected by the auditor in the Ex-Ante-Phase? If so, this would be considered a violation of the logic
of the standard inferential model that is based upon the Ex-Ante selection of the inference-platform. In a debrief with the
students using the DSS, the DSS-results-profile was used as the
instructional-platform to better understand the correct application of the
inferential-profile that is used to inform the auditor. A second instructional
aspect is that the DSS is VBA-programed to provide numerous guidance alerts
that are focused on inappropriate testing aspects that can be elected but that
are inconsistent with the standard inferential logic. Discussion of these
aspects seem to enhance understanding of inferential testing. Additionally, a
few of the “programmatic issues” that are currently inherent in using
Excel[2019]™ to create certain inference-profiles are addressed. The DSS
corrects for these Excel-issues. This
DSS is offered as an illustration of the pedagogic benefits of inferential
training enabled by using course specific software modeled on the requirements
of the inferential model. The DSS, a VBA open-access modular platform, is
available as a download without cost or restrictions on its use either
academically or professionally.