crowdwork

Using life course perspective to understand learning practices within crowdwork

I am pleased to have an abstract accepted for the ‘Research Methods for Digital Work: Innovative Methods for Studying Distribute and Multi-modal Working Practices’ conference organised by the Institute of Advanced Studies at the University of Surrey.

In the abstract, Heather Hofmeister and I outline how the Life Course perspective could help advance research into digital work and particularly the study of learning practices within crowdwork.  To my knowledge, this is the first attempt to apply the Life Course perspective in crowdwork research. If you know of other research where the Life Course perspective has been used to study crowdwork or other gig-economy practices please get in touch.

Abstract: Using life course perspective to understand learning practices within crowdwork

Anoush Margaryan and Heather Hofmeister, Department of Sociology, Goethe University Frankfurt 

Background

The unfolding digitalisation of our society has stimulated the development of new types of work practices termed ‘virtual work’ (Huws, 2014). These emerging digitally-mediated work practices challenge traditional patterns of individual agency, organisation, power, responsibility and learning (Littlejohn and Margaryan, 2014). Working under conditions of precarity, digital transformation and changing patterns of agency, workers increasingly have to initiate and regulate their own learning. As the nature of work evolves, understanding how workers learn within these new work practices becomes increasingly important.

One type of virtual work is crowdwork – a form of labour in which a large group of people are brought together within Internet-based platforms for the purpose of performing a task. These platforms act as intermediaries between clients/task requesters and workers, helping oversee the definition, submission, acceptance and payment for the work done (Kuek et al, 2015). Examples are Amazon Mechanical Turk, Upwork and CrowdFlower.  In this highly distributed and fragmented type of work, where workers may not have access to the learning opportunities available within traditional employment (eg training or access to experienced colleagues), how do crowdworkers go about managing their learning? What strategies do crowdworkers use to identify their learning needs, source knowledge, and find others to learn with and from?

In crowdwork research, three key methods have been used – questionnaire survey, interview, and ethnography- all focusing on crowdworkers (Gray et al, 2016; Ipeirotis, 2010; Martin et al, 2016). The perspectives of other key stakeholders e.g. platform providers and task requesters/clients have been overlooked. Also, workers’ experiences have been examined as snapshots rather than being contextualised historically and developmentally.

This paper argues that essential to understanding the learning practices within crowdwork is to analyse both the individual and the historical-environmental factors impacting crowdworkers’ learning. Crowdwork occurs largely online, although it is plausible that crowdworkers’ learning activities span the online and offline realm. Methodological approaches that bridge sociological, psychological, individual, collective, online, offline, and temporal processes and practices of learning within crowdwork are needed.

Life course perspective

We propose the life course perspective as an analytical framework to facilitate a nuanced, contextualised analysis of crowdworkers’ learning (Elder and Giele, 2009; Hofmeister, 2015; Levy, 2013). The life course is an interdisciplinary perspective drawing on sociology, psychology, anthropology, history and biology to help understand human development across the life span (Mortimer and Shanahan, 2004). The life course perspective stresses the importance of the socio-cultural environment in explaining individual behaviour and life history. It focuses on the interplay of the individual, their setting, and the dynamic processes of change individuals undergo within these settings.

Four key elements of the life course perspective would help analyse crowdworkers’ learning: agency, context, linked lives, and timing. Agency refers to an individual’s motives and goals, and the self-regulated activities undertaken to fulfil them (Elder, 1994). Context refers to the setting in which each individual acts, comprising psychological, social, cultural, organisational, technological and physical dimensions, as well as the temporally-constituted patterns that emerge from the interplay between these diverse contexts (Blossfeld, 2009; O’Rand, 2009). Linked lives denotes the interrelations between individuals in their contexts (Moen and Hernandez, 2009). Timing refers to the sequencing of events and pathways of personal activities individuals engage in to reach their goals (Viry et al, 2013).

Quantitative and qualitative methods have been applied in Life Course research (Elder and Giele, 2009). For example, Laub and Sampson (1998) discuss a longitudinal study of juvenile delinquency where data on social, psychological and biological characteristics, family life, school performance, work experience were collected from multiple sources, several points of view and at separate times. They show how the merging of quantitative and qualitative data provides important cues for explaining continuity and change in human behaviour.

Applying life course perspective to crowdworkers’ learning    

The project this paper is based on examines learning strategies and activities, personal motivations, goals, agency beliefs and pathways underpinning crowdworkers’ learning, and the individual and environmental factors impacting upon their learning. Data are collected from two platforms: CrowdFlower and Upwork.

 Several methods are combined to help generate rich descriptions of crowdworkers’ learning practices (Johnson et al., 2004). Crowdworkers’ self-regulatory learning strategies and learning activities are scoped using the Self-Regulated Learning at Work Questionnaire, SRLWQ (Fontana et al., 2015). The survey is supplemented by biographical interviews to ascertain crowdworkers’ professional trajectories and learning pathways, educational and work experiences, current and desired skills, learning goals and motivations to engage in crowdwork and learning.  The interviews are combined with field visits to conduct observations of crowdworkers’ local contexts and to collect data on specific SRL strategies in situ using SRL microanalysis protocols (Cleary, 2011).  Online ethnography is carried out within discussion fora and social networks used by crowdworkers and clients/task requesters to identify learning activities. To contextualise crowdworkers’ perspectives, representatives of crowdwork platforms and selected task requesters are interviewed and training and development provisions offered by the platforms are scoped. Table 1 illustrates how these methods help elucidate the key components of the life course applied to crowdworkers’ learning.

Table 1.  Mapping of methods and the life course framework

Life course components Methods
Human agency

·       Motives to engage in crowdwork

·       Learning and performance goals

·       Career aspirations

·       SRL strategies

·       Learning activities

·       Existing knowledge and skills

 

·       Biographical interviews with crowdworkers

·       Analysis of online fora

·       SRLWQ

·       SRL microanalysis

·       Experience sampling methods (eg diary or tracking devices)

Context

·       Design of crowdwork platforms

·       Task design

·       Physical environment

·       Local infrastructure

·       Local culture

·       Other work/professional commitments

·       Education and training

·       Previous work experiences

·       Local economic conditions, employment and regulatory regimes

·       Training and development provision by the platforms

·       Review of platforms

·       Scoping of sample work tasks

·       Interviews with platform providers and clients

·       Interviews with crowdworkers

·       Interviews with policymakers (trade unions, labour organisations, politicians)

·       Ethnographic observation

·       Document review

·       Analysis of artefacts

Linked lives

·       Family, friends, neighbours

·       Professional networks in and outside crowdwork

·       Clients and employers

·       Online communities

·       Client networks

 ·       Biographical interviews

·       Interviews with platforms and clients

·       Opportunistic interviews with family members/friends

·       Social network analysis

Timing

·       Education

·       Workplace

·       Retirement

·       Disability

·       Immigration

·       Loss of job

·       Decision to freelance

·       Family events

·       Significant other prior events/experiences

·       Biographical interviews

The data collection is in early stages and specific examples of data capture and analytic techniques will be demonstrated at the conference. Opportunities and challenges in mixing methods to study crowdworkers’ learning will be discussed.

The paper contributes an interdisciplinary methodological perspective drawing on Sociology, Learning Sciences, Psychology, Internet Studies and HCI offering insight into how people work and learn within crowdwork and how crowdwork may be shaped to foster learning. 

References

Blossfeld, H. P. (2009). Comparative Life Course research. In G. H. Elder, & J. Z. Giele (Eds.), The craft of Life Course research (pp. 280-306). New York: Guilford Press.

Cleary, T. (2011). Emergence of self-regulated learning microanalysis. In Zimmerman, B., & Schunk, D. (Eds.), Handbook of self-regulation of learning and performance. London: Routledge.

Elder, G. H. (1994). Time, human agency, and social change. Social Psychology Quarterly, 57(1), 4-15.

Elder, G. H., & Giele, J. Z. (Eds.). (2009). The craft of Life Course research. New York: Guilford Press.

Fontana, P. et al (2015). Measuring self-regulated learning in the workplace. International Journal of Training and Development, 19(1), 32-52.

Gray, M. et al (2016). The crowd is a collaborative network. In Proceedings of CSCW 2016 Conference (pp. 134-147). San Francisco: ACM.

Hofmeister, H. (2010). Life Course. In S. Immerfall, & G. Therborn (Eds.), Handbook of European societies (pp. 385-411). New York: Springer.

Hofmeister, H. (2015). Individualisation of the life course. International Social Science Journal, 64(213), 279-290.

Huws, U. (2014). Labour in the global digital economy. New York: Monthly Review Press.

Ipeirotis, P. (2010). Demographics of Mechanical Turk. http://www.ipeirotis.com/wp-content/uploads/2012/02/CeDER-10-01.pdf

Johnson, R., & Onwuegbuzie, A. (2004). Mixed methods research. Educational Researcher, 33(7), 14-26.

Kuek, S. C., et al. (2015). The global opportunity in online outsourcing. Washington, DC: World Bank.

Laub, J. H., & Sampson, R. J. (1998). Integrating quantitative and qualitative data. In J. Z. Giele, & G. H. Elder, Jr. (Eds.), Methods of Life Course research (pp. 213-230). Thousand Oaks, CA: Sage.

Laub, J. H. et al (1998). Trajectories of change in criminal offending. American Sociological Review, 63(2), 225-238.

Levy, R. (2013). Life Course analysis. In R. Levy, & E. D. Widmer (Eds.), Gendered life courses between standardization and individualization (pp. 315-338). Zürich: LIT.

Littlejohn, A., & Margaryan, A. (2014). Technology-enhanced professional learning. London: Routledge.

Martin, D., et al. (2016). Turking in a global labour market. Computer-Supported Cooperative Work, 25(1), 39-77.

Moen, P., & Hernandez, E. (2009). Social convoys. In Elder, G. H., & Giele, J. Z. (Eds.), The craft of Life Course research (pp. 258-79). New York: Guilford Press.

Mortimer, J.T., & Shanahan, M.J. (2004) (Eds.). Handbook of the life course. New York: Springer.

O’Rand, A. M. (2009). Cumulative processes in the Life Course. In G. H. Elder, & J. Z. Giele (Eds.), The craft of Life Course research (pp. 121-140). New York: Guilford Press.

Viry, G. et al (2013). Residential trajectories in the early life course and their effects. In Levy, R., & Widmer, E. D. (Eds.), Gendered life courses between standardization and Individualization (pp. 141-160). Zürich: LIT.

 

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Learning within crowdwork platforms

My paper on crowdworkers’ learning within microwork and online freelancing platforms has been accepted at Internet, Policy and Politics 2016 Conference organised by Oxford Internet Institute. I’m very much looking forward to the conference.

Abstract: 

This paper reports findings of a survey exploring how crowdworkers develop their knowledge and skills in the course of their work on digital platforms. The focus is on informal learning initiated and self-regulated by crowdworkers: engaging in challenging tasks; studying professional literature/online resources; sharing knowledge and collaborating with others. The survey was run within two platforms representing two types of crowdwork – microwork (CrowdFlower) and online freelancing (Upwork). The survey uncovered evidence for considerable individual and social learning activity within both types of crowdwork. Findings suggest that both microwork and online freelancing are learning-intensive and both groups of workers are learning-oriented and self-regulated. Crowdwork is a growing form of employment in developed and developing countries. Improved understanding of learning practices within crowdwork would inform the design of crowdwork platforms; empower crowdworkers to direct their own learning and work; and help platforms, employers, and policymakers enhance the learning potential of crowdwork.

 

Reference: Margaryan, A. (22 September, 2016). Understanding crowdworkers’ learning practices. Paper presented at Internet, Policy and Politics 2016 Conference, Oxford Internet Institute, University of Oxford, UK.  [Online] http://ipp.oii.ox.ac.uk/sites/ipp/files/documents/FullPaper-CrowdworkerLearning-MargaryanForIPP-100816%281%29.pdf