International Journal of

Business & Management Studies

ISSN 2694-1430 (Print), ISSN 2694-1449 (Online)
DOI: 10.56734/ijbms
Inferential Decision Support Systems: Pedagogic Enhancements for Delivering Statistical-components in an Auditing Course


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.