AbstractsBusiness Management & Administration

Training of multidisciplinary greenhouse gas assurance engagement teams to improve analytical procedures task performance

by Tri Ramaraya Koroy

Institution: University of New South Wales
Department: Accounting
Year: 2015
Keywords: Analytical procedures; Multidisciplinary teams; Training; Analogical encoding; Collaborative learning; Team mental models
Record ID: 1066822
Full text PDF: http://handle.unsw.edu.au/1959.4/54410


The demand for assurance on greenhouse gas (GHG) emissions has increased due to growing concerns about climate change and the introduction of new legislation and emissions trading schemes in many countries. GHG assurance engagements necessitate the involvement of practitioners from accounting and non-accounting disciplines to form multidisciplinary teams (MDTs). Focusing on training intervention, this thesis investigates whether two training techniques drawn from the educational and cognitive psychology literature, analogical encoding and collaborative learning, are effective in improving individual and MDT performance in conducting a complex analytical procedures task commonly completed in GHG assurance engagements. Analogical encoding is a technique that facilitates encoding of knowledge by comparing two worked examples simultaneously whereas collaborative learning refers to a technique that encourages learners to work together to facilitate discussion and understanding when learning new tasks. The thesis employs a between-subjects experiment using postgraduate students (as surrogates for novice practitioners) to examine the research hypotheses. The study finds that for complex tasks such as the analytical procedures task, a combination of analogical encoding and collaborative learning techniques leads to the highest learning outcomes for individuals and teams. At the individual level, these results suggest that the combination of the two techniques allows simultaneously the reduction in cognitive load, facilitation of deep processing, and development of knowledge structures during learning thereby facilitating improved performance. At the team level, the combined techniques facilitate team member familiarity and sharing of workload, resulting in enhanced process gains. These processes enable team members to perform effective and efficient hypothesis generation and objective evaluation of hypotheses (i.e., less biased towards the inherited hypothesis), which in turn increases the likelihood that they will select the correct causal hypothesis. An analysis was also conducted on the role of team member cognitive structures (i.e., the manner in which knowledge that is important to team functioning is mentally organised, represented, and distributed within the team) and reveals that the two training techniques do not affect all measures of team member cognitive structures and these constructs do not mediate all the relationships between team training inputs and team performance.