Incase: Simulating Experience to Accelerate Expertise Development by Knowledge Workers

Arnold, Vicky; Collier, Philip A.; Leech, Stewart A.; Sutton, Steve G.; Vincent, Andrew

doi:10.1002/isaf.1337

Cited by 11 publications

(6 citation statements)

References 44 publications

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“…Testing of the Theory of Technology Dominance has also been at the core of what is recognised as the INSOLVE project (Arnold et al ., , ,b, , , , ). Insolvency professionals were targeted to get into a high‐risk environment with highly specialised professionals.…”

Section: Auditing and Assurancementioning

confidence: 99%

The changing technological environment and the future of behavioural research in accounting

Arnold

2016

Accounting & Finance

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In an era where the pace of change continues to escalate, behavioural research provides an ongoing avenue for explaining the likely effects of emergent changes on decision-making by providers, users and assurers of accounting information, and for providing ex ante enlightenment for policy-makers. The purpose of this discussion is to identify contemporary changes affecting the accounting environment, discuss the potential impact to individual and organisational decision-making, and explore how behavioural research can be utilised to examine these changes. Specifically, this discussion focuses on the impact that technological changes have had on financial reporting, external auditing and managerial accounting, with an eye towards the potential for these changes to radically alter the future of accounting and auditing research. This article is based on my plenary speech at the 2013 AFAANZ Annual Conference held in Perth, Australia. I thank both Sue Wright and David Lont, presidents of AFAANZ, for giving me the opportunity to synthesise research on the impact of technology on accounting, and to present that discussion in this forum. Over the past twenty years, I have had the opportunity to work with some of the finest academics in the world, either directly as my coauthors or indirectly through involvement in their PhD thesis work. Most of these academics are from the AFAANZ community -people like Stewart Leech at the University of Melbourne, Phil Collier formerly at the University of Melbourne, Carlin Dowling formerly at the University of Melbourne, Mohamed Elbashir and Habib Mahama both formerly at Australian National University, Poh Sun Seow, a graduate of University of Melbourne, now at Singapore Management University, and Jake Rose at Victoria University in New Zealand. These people and their work have profoundly influenced my thinking and my research about the impact of technology on the accounting domain. I would like to thank Steve Sutton for his invaluable help in preparing both the plenary speech and writing this article.© 2016 AFAANZ Accounting and Finance 58 (2018) 315-339

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Section: Auditing and Assurancementioning

confidence: 99%

The changing technological environment and the future of behavioural research in accounting

Arnold

2016

Accounting & Finance

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“…Researchers have been studying the impact of AI and its predecessor technologies on work processes and employee wellbeing since the late 1980s. A series of studies focused on the negative effects of knowledge support systems and artificial intelligence on workers’ wellbeing, and their learning, growth, and development (Arnold & Sutton, 1998; Arnold et al, 2004; 2006; 2013). Sutton and Arnold, 2018 evoked Braverman’s (1974) work arguing that the implementation of scientific management and consolidation of labor in large, production line-based facilities results in deconstructing of high skill work into smaller pieces that can be easily performed by machines or low-skilled workers.…”

Section: Expertise and Expertise Developmentmentioning

confidence: 99%

“…Thus, the need for high-skilled (and more expensive) workers is decreasing; workers lack pride of artisanship, work meaning, and are forced to accept lower-paid and more precarious jobs. While Braverman was mostly concerned with manual and crafts-based labor, Arnold, Sutton, and their colleagues focused on the impact of automation on the skilled knowledge work of accountants and auditors (e.g., Arnold et al, 2006; Arnold et al, 2013). They argued that, while on the surface it may seem that with the assistance of machines knowledge workers can solve problems that are more complex and operate at higher levels of skill, in reality, they lack opportunities to learn and develop their expertise since machines take over large chunks of work.…”

Section: Expertise and Expertise Developmentmentioning

confidence: 99%

The Impact of Artificial Intelligence on Expertise Development: Implications for HRD

Ardichvili

2022

Advances in Developing Human Resources

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Problem The implementation of artificial intelligence (AI) is assumed to lead to increased productivity of knowledge workers. However, AI could also have negative effects on the development of professional expertise. Solution A review of the literature on expertise development is provided, followed by examples of AI implementation in a knowledge-intensive profession, accounting. The analysis of these examples suggests that automation can result in the loss of expertise due to reduced opportunities for learning from deliberate practice and experienced colleagues, and from working on progressively more complex tasks. Implications for human resource development (HRD) include creating alternative individual development opportunities and promoting organizational cultures conducive to expertise development in human-machine interaction modes. Stakeholders The results of this study will be of interest to scholars of HRD, accounting education, and human-machine interaction. Practical implications will be of relevance to HRD professionals and managers responsible for the implementation of artificial intelligence solutions.

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“…Patterson et al (2013) demonstrated that in using CTA based curriculum, it is possible to accelerate on-the-job performance. Some researchers have used scenario-based learning with real-world cases to train complex skills (Arnold, Collier, & Vincent, 2013). Doane, Alderton, Sohn, & Pellegrino (1996)demonstrated that difficult or tough cases could accelerate the proficiency of individuals.…”

Section: Page4mentioning

confidence: 99%

Model of Accelerated Proficiency in the Workplace: Six Core Concepts to Shorten Time-to-Proficiency of Employees

2018

APJABSS

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The high pace business environment poses great competition among firms. The key to an organisation's survival is its workforce. Time taken by the workforce to reach to full proficiency in their job role takes very long in certain job roles. Thus, shortening time-to-proficiency of employees is a critical business problem for today's organisations. This qualitative research study explored the proven practices and strategies that have successfully reduced time-toproficiency of the workforce in various settings. A total of 93 participants from seven countries participated in the research study. Bounded project case (with a defined start and defined end) was used as a sampling unit and unit of analysis in this study. This study collected 67 successful project cases with the evidence of significant reduction in time-to-proficiency of the workforce in their settings. These project cases are spanned across nine economic sectors, 20 business sectors and 28 industrial groups. This study revealed that project leaders across the board used six practices to successfully reduce the time-to-proficiency. The purpose of this paper is to present the model of accelerated proficiency in the work place developed in this study.

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Incase: Simulating Experience to Accelerate Expertise Development by Knowledge Workers

Cited by 11 publications

References 44 publications

The changing technological environment and the future of behavioural research in accounting

The changing technological environment and the future of behavioural research in accounting

The Impact of Artificial Intelligence on Expertise Development: Implications for HRD

Model of Accelerated Proficiency in the Workplace: Six Core Concepts to Shorten Time-to-Proficiency of Employees

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