an article by Stan Lester (Stan Lester Developments, Taunton, UK), Anna Koniotaki (Elliniki Etairia Topikis Anaptiksis kai Aftodioikisis, Athens, Greece; VFA, Athens, Greece) and Jolanta Religa (National Research Institute, Radom, Poland) published in Education + Training Volume 60 Issue 4 (2018)
Abstract
Purpose
The purpose of this paper is to describe a revised approach describing occupational competence, with particular reference to its application in two European countries at the level of specific occupational fields and in relation to the models used in national vocational education and training (VET) systems.
Design/methodology/approach
An Erasmus+ project involved partners in five countries developing and trialling competence standards, following principles developed from approaches that have recently emerged in some British self-governing professions.
Findings
The model used in the project avoids the narrowness that was characteristic of earlier British approaches to occupational competence. It provides a template that can be used for articulating the essentials of practice, including in emerging fields and those that cut across professions and occupations. It is also flexible enough to provide underpinnings for different types of VET system without making assumptions about the way that economies, labour markets and education systems are organised.
Practical implications
A number of factors are outlined that improve the applicability of practice-based competence descriptions, including starting from occupational fields rather than job roles, focussing on the ethos and core activities of the field, and using concise and precise descriptions that are not limited to specific roles and contexts.
Originality/value
A tested, practice-based model of competence is put forward that can be applied at the level of broad professional or occupational fields, is neutral in respect of national labour markets and educational systems, and offers a means of developing a common “language” of competence at a European level.
Tuesday, 24 July 2018
Brexit, Twitter, public_opinion, machine_learning, nationalism, populism, referendum,
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