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Apprentices’ Adaption and Innovation Styles in Relation to Dimensions of Workplaces as Learning Environments

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Details

Original languageEnglish
Title of host publicationEmerging Issues in Vocational Education & Training
Subtitle of host publicationVoices from Cross-national Research
EditorsLázaro Moreno Herrera, Marianne Teräs, Petros Gougoulakis
PublisherStockholm University Press
Pages370-388
Number of pages19
ISBN (Print)978-91-86743-74-1
Publication statusPublished - 8 May 2018
Publication typeA3 Part of a book or another research book

Abstract

Previous research has shown that workplaces vary as learning environments, some providing opportunities for developing expertise, while others restrict the possibilities of learning. Workplace as learning environment (WLE) survey was designed to identify the aspects of the workplace that contribute to offering more expansive working environments. In order to examine learner factors, we use the Adaption-Innovation theory, which is premised on the idea that individuals can be placed on a continuum ranging from an extremely adaptive to an extremely innovative style. Cognitive style is distinguished from cognitive level (ability to successfully solve problems) and both styles are creative but in different ways. For the purpose of this study, a self-report version of Kirton Adaption-Innovation (KAI) survey was created. In order to survey the person-environment fit, participants responded to each item on two scales, first one measuring their own cognitive style, and the second one the style of their workplace. Based on a survey addressed to vocational students and a sub-sample of apprentices (N=305), this study aims at answering following research questions: 1) How do apprentices locate on a continuum of cognitive style ranging from adaption to innovation?, 2) How the dimensions of WLE are related to KAI score and dimensions?, 3) How the person-environment fit is related to WLE dimensions? The survey data is analysed with non-parametric frequentistic and non-frequentistic methods due to discrete measurement level of variables.

Publication forum classification

Field of science, Statistics Finland