gigeconomy

How do crowdworkers learn? Workplace learning activities

This is the first blogpost in the series about learning practices of crowdworkers.

One of the foci of the study is how crowdworkers learn on-the-job: what  types of workplace learning activities they undertake and what learning strategies they use to self-regulate their learning.   The range and frequency of use of learning activities and learning strategies that people undertake in the workplace give us an indication of learning-intensity of a job (that is, the extent to which people need to regularly acquire new skills and knowledge to be able to maintain their job).   Crowdwork is often presumed to be low learning-intensity, low-skill, lacking in professional development opportunities and preventing workers for applying and developing their skills and know-how.  So it’s useful to scope the range and frequency of use of workplace learning activities and strategies among crowdworkers to see what, if any, empirical base there is to these assumptions about crowdwork.

This blogpost is focused on workplace learning activities. The resuts reported here are based on 182 survey responses (167 microworkers and 15 online freelancers). I’m currently collecting more survey responses from online freelancers in order to balance out the sample.

In the survey, I asked the participants to indicate how frequently they used the following 14 workplace learning activities within the last 3 months as part of their work on the crowdwork platforms (never, rarely, frequently or very frequently):

  1. Acquiring new information to complete their crowdwork tasks
  2. Working alone to complete their crowdwork tasks
  3. Collaborating with others to complete their crowdwork tasks
  4. Following new developments in their field
  5. Performing tasks that are new to them
  6. Asking others for advice
  7. Attending a training course/workshop to acquire knowledge/skills for their crowdwork
  8. Taking free online courses or webinars (e.g. Coursera) to acquire knowledge/skills for crowdwork
  9. Using paid online tutorials (e.g. Lynda) to acquire knowledge/skills for crowdwork
  10. Reading articles/books to acquire knowledge/skills for crowdwork
  11. Observing/replicating other people’s strategies
  12. Finding a better way to do a task by trial-and-error
  13. Thinking deeply about their work (e.g. what they could do better next time)
  14. Receiving feedback on their crowdwork tasks (e.g. from a client or peers)

Below are the survey results showing the percentage of the crowdworkers who reported using each learning activity ‘frequently’ or ‘very frequently’.

WLAOverallFigure 1. Percentage of crowdworkers who reported using these workplace learning activities frequently or very frequently

From this chart, crowdworkers most frequently learn by working alone on novel tasks, acquiring new information, following new developments in their fields, seeking better ways to do the tasks by trial-and-error and reflecting deeply on their work.

Crowdworkers reported some other learning activities not included in the list above, such as:

  • Watching YouTube videos
  • Participating in project groups on specific tasks
  • Participating in platform-specific online fora
  • Discussing ideas with others
  • Reading platform-specific blogs
  • Watching news in foreign languages to improve language skills
  • Taking private lessons to improve skills in a particular area
  • Scoping and learning highly-demanded technologies trending on specific crowdwork platforms

It is  interesting that just over a third of the respondents reported observing and replicating other people’s strategies as a key way in which they learn.  Also, some undertake social learning activities such as asking others for advice, collaborating with others, receiving feedback. How does this sort of mimetic and cooperative learning take place in a distributed, digital online workplace? What are the underpinning mechanisms and processes and what is the nature of the connections? These questions will be further explored in the interviews with crowdworkers.

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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.