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Workplace learning in crowdwork


Purpose
This paper aims to explore workplace learning practices within two types of crowdwork – microwork and online freelancing. Specifically, the paper scopes and compares the use of workplace learning activities (WLAs) and self-regulatory learning (SRL) strategies undertaken by microworkers (MWs) and online freelancers (OFs). We hypothesised that there may be quantitative differences in the use of WLAs and SRL strategies within these two types of crowdwork, because of the underpinning differences in the complexity of tasks and skill requirements.


Design/methodology/approach
To test this hypothesis, a questionnaire survey was carried out among crowdworkers from two crowdwork platforms – Figure Eight (microwork) and Upwork (online freelancing). Chi-square test was used to compare WLAs and SRL strategies among OFs and MWs.


Findings
Both groups use many WLAs and SRL strategies. Several significant differences were identified between the groups. In particular, moderate and moderately strong associations were uncovered, whereby OFs were more likely to report (i) undertaking free online courses/tutorials and (ii) learning by receiving feedback. In addition, significant but weak or very weak associations were identified, namely, OFs were more likely to learn by (i) collaborating with others, (ii) self-study of literature and (iii) making notes when learning. In contrast, MWs were more likely to write reflective notes on learning after the completion of work tasks, although this association was very weak.


Originality/value
The paper contributes empirical evidence in an under-researched area – workplace learning practices in crowdwork. Crowdwork is increasingly taken up across developed and developing countries. Therefore, it is important to understand the learning potential of this form of work and where the gaps and issues might be. Better understanding of crowdworkers’ learning practices could help platform providers and policymakers to shape the design of crowdwork in ways that could be beneficial to all stakeholders.
