How can CA(SA) university students be better prepared for the SAICA training programme: A focus on relational and decision-making skills

Kotze, Ruhan

How can CA(SA) university students be better prepared for the SAICA training programme: A focus on relational and decision-making skills

Master Thesis

2022

Abstract

Purpose: This study investigates the extent to which aspirant CA(SA)s perceive how the academic programme is, and should be, developing relational and decision-making (RDM) skills. There has been extensive criticism that these skills are insufficiently developed in accounting students, an unfortunate reality which, consequently, hinders their expected performance during the SAICA training programme. Research method: A questionnaire was distributed to 103 aspirant CA(SA)s (of which 44 responded) working at one of the largest audit firms globally and currently in their 1st to 3rd year of the SAICA training programme. The questionnaire consisted of three main questions focusing on the respondents' perception of the academic programme. Findings: The majority of the respondents perceive that almost all of the RDM skills are developed to an intermediate or advanced level during the academic programme. However, respondents also perceive that the academic programme should place greater focus on developing certain RDM skills, such as relationship-building; professional scepticism and teamwork, to an advanced level, to maximise performance during the training programme. Lastly, the case study method, a teaching method by academics, resulted in the highest response rate for assisting in developing RDM skills. Originality and value: The study is the first to research RDM skills development, as defined within the new SAICA Competency Framework, during the South African academic programme. Furthermore, the findings of this study could assist SAICA in identifying RDM skills development shortcomings and whether the academic or training programme providers should bear more responsibility for developing certain skills.