Comparing crowdworkers’ and conventional knowledge workers’ self-regulated learning strategies in the workplace

Margaryan, Anoush ORCID: https://orcid.org/0000-0002-1740-8104 (2019) Comparing crowdworkers’ and conventional knowledge workers’ self-regulated learning strategies in the workplace. Human Computation: A Transdisciplinary Journal, 6 (1). pp. 83-97. ISSN 2330-8001

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Abstract

This paper compares the strategies used by crowdworkers and conventional knowledge workers to self-regulate their learning in the workplace. Crowdworkers are a self-employed, radically distributed workforce operating outside conventional organisational settings; they have no access to the sorts of training, professional development and incidental learning opportunities that workers in conventional workplaces typically do. The paper explores what differences there are between crowdworkers and conventional knowledge workers in terms of self-regulated learning (SRL) strategies they undertake. Data were drawn from four datasets using the same survey instrument. Respondents included crowdworkers from FigureEight (previously CrowdFlower) and Upwork platforms and conventional knowledge workers in the finance, education and healthcare sectors. The results show that the majority of crowdworkers and conventional knowledge workers used a wide range of SRL strategies. Among 20 strategies explored, a statistically significant difference was uncovered in the use of only one strategy. Specifically, crowdworkers were significantly less likely than the conventional workers to articulate plans of how to achieve their learning goals. The results suggest that, despite working outside organisational structures, crowdworkers are similar to conventional workers in terms of how they self-regulate their workplace learning. The paper concludes by discussing the implications of these findings and proposing directions for future research.

Item Type: Article
Additional Information: © 2019, Margaryan. CC-BY-3.0 This is an Accepted Manuscript of an article published in Human Computation: A Transdisciplinary Journal.
Subjects: Education
Social sciences
Related URLs:
Depositing User: Anoush Margaryan
Date Deposited: 17 Oct 2018 10:13
Last Modified: 15 Aug 2019 07:28
URI: http://repository.uwl.ac.uk/id/eprint/5539

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