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Competencies, activity analysis and occupational training: An innovative approach with full-scale simulators in high risk industries

Fauquet-Alekhine, Philippe (2017) Competencies, activity analysis and occupational training: An innovative approach with full-scale simulators in high risk industries. PhD thesis, London School of Economics and Political Science.

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Identification Number: 10.21953/lse.7alr8lf9l1uj


Dealing with the social phenomenon of the “skills drain”, retired workers leaving companies en masse sometimes even before the recruitment of newcomers and consequently impeding classic training through mentoring, managers are seeking innovative solutions to train new employees and ensure a satisfactory level of competencies, especially in high risk industries. This led to questions to which the present research offers solutions: How are competencies of experienced workers mobilized? How can they be accessed? How are they developed through training? And more especially in full-scale simulation, which is key to occupational training in high risk industries. The literature shows that the relationship between knowledge, know-how, skills and competencies remains unclear. A model is suggested, adapted to the present issue. It shows that competencies must be investigated in action through work activity analysis and leads to an approach to describe competencies in action, as in Le Boterf’s model (1998), which presents a relevant link between competencies and action and was tested in the field. However, its application revealed a dearth of the expected description; pre-tests led to adapt it into a new model and protocol: the Square of PErceived ACtion (SPEAC model). The protocol was used, in the line of Subjective Evidence-Based Ethnography (SEBE) methods, to structure the replay interview following the recording of the workers’ activity by subcams, miniaturized cameras mounted on spectacles (first person perspective). The resulting analysis was applied to full-scale simulation and in real operating situations for which a risk assessment protocol whilst using SEBE equipment was developed, tested and applied. It provided more relevant input data for occupational training, and showed higher performance in training than other methods (more exhaustive and less costly). In order to evaluate the impact of SPEAC-improved training on actual performance at work, the SPEAC improvement in a standard training curriculum was tested in two contexts of high risk industries (medicine and nuclear). In doing so, we tackled also the issue of resistance to innovation in training. The application of the SPEAC method to provide input data and to structure the training sessions improved significantly the work performance both at the end of the training sessions and in real operating situations. When combined with improved pedagogical methods in simulation training, the SPEAC protocol has been shown to provide substantial gains for following real operating situations, both in terms of safety (fewer subsequent complications and less pain for patients in hospital, higher levels of reliability for activities in nuclear industries) and in terms of cost (per year, potentially tens of thousands of euros could be saved in hospitals when considering one operation and several millions of euros for a nuclear power plant when all activities are taken into account). Top management now wishes to roll out the method within their professionalization program in the two institutions where the field experiments and applications were carried out. In parallel, as a theoretical perspective, developments and applications in the framework of the present research have suggested the relevance of a systemic approach of the professionalization cycle in complex socio-technical systems: the Experiential Learning Theory-based excursive cycle of the professional training process developed in this study might contribute towards modelling a systemic approach of simulation training in high risk industries providing areas for improvement and consequently higher performance.

Item Type: Thesis (PhD)
Additional Information: © 2017 Philippe Fauquet-Alekhine
Library of Congress subject classification: H Social Sciences > HV Social pathology. Social and public welfare. Criminology
Sets: Departments > Psychological and Behavioural Science
Supervisor: Lahlou, Saadi

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