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1
Insights from the CrowdLearn study
Vili Lehdonvirta (Oxford University),
Anoush Margaryan (Copenhagen Business School)
2
CrowdLearn: Major study on skills and learning in the platform economy
• Interviews with 77 crowdworkers and survey of 1,001 crowdworkers
• Across six European countries and working on four major platforms
• Interviews with 25 representatives of stakeholder organizations
3
Skills typology for platform work
Skill categories Examples
Technical/core skills
Language skills
Obtaining work on platform
Learning to learn
Setting up as a freelancer
Communication skills
Personal dispositions/attributes
Organizational skills
Analytical skills
Computer literacy
Programming languages, social media marketing practices
English, French, Spanish
Independence, confidence, creativity
Pricing, bidding for projects
Project management, time management
Taxes, registering as a business
Business email writing, handling customers
SOURCE: CrowdLearn (Interview data)
4
66
50
47
59
58
47
37
30
37
35
Skills typology % of respondents
Obtaining work on platform
Technical/core skills
Language skills
Learning to learn
Setting up as a freelancer
Communication skills
Personal dispositions
Organizational skills
Analytical skills
Computer literacy
I have developed these
skill categories before
joining the platform but
found them useful during
crowdwork over the past
3 months
Crowdworkers apply skills developed in previous education and employment
SOURCE: CrowdLearn (Survey data)
5
66
50
47
59
58
47
37
30
37
35
56
36
36
74
70
71
55
45
59
65
Skills typology
Obtaining work on platform
Technical/core skills
Language skills
Learning to learn
Setting up as a freelancer
Communication skills
Personal dispositions
Organizational skills
Analytical skills
Computer literacy
I have developed these
skill categories before
joining the platform but
found them useful during
crowdwork over the past
3 months
I have developed these
skill categories at least
weekly during
crowdwork over the
past 3 months
Crowdworkers also continue to develop their skills during crowdwork
SOURCE: CrowdLearn (Survey data)
% of respondents
6
Educational
background
Primary income
Hourly wage,
in USD/h
1.6
Bachelors or Masters
1.7
1.7
Female
1.1
1.6
1.4 Vocational degrees
Secondary
1.5 Below secondary
1.9 [Platform] as primary income
[Platform] not primary income
1.6 5
1.7 10.5
1.5
Medium
75.5
Low
1.5
100
1.6
High
1.4
1.7
40.5
1.2
1.5
Male
Other
23
2.0 Level of
self-regulated
learning
Gender
Fewer than 50 observations
Frequency of skill development varies by worker background
Average frequency of skill development during crowdwork
As averages across entire skill typology (10 skill types, 0 – 3 scale)
1 = Occasionally 2 = Weekly
Worker
characteristics
7
17
62
5
14
10
4
6
12
6
14
29
30
11
43
25
12
30
33
15
11
16
9
31
27
38
44
41
21
29
9
24
34
43
41
23
27
15
30
40
34
21
22
29
Acquiring new information to complete my [platform] projects
2
Collaborating with others to complete my [platform] projects
Thinking deeply about my work (e.g., what I could do better next time)
Working alone to complete my [platform] projects
Following new developments in my field
Asking others for advice
Performing tasks that are new to me
78
Taking free online courses or webinars to acquire knowledge/skills
73
3 Using paid online tutorials to acquire knowledge/ skills for [platform]
Reading articles/ books to acquire knowledge/ skills for [platform]
Observing/ replicating other people’s strategies
Attending a training course/workshop to acquire knowledge/skills for [platform]
Receiving feedback on my [platform] projects (e.g., from my client)
Learning from online community forums (e.g., StackOverflow)
74
60
89
95
96
41
86
36
48
26
86
92
60
Finding a better way to do a task by trial and error
Occasionally Weekly Daily
Learning activities are largely informal and individual
– client feedback is an exception % of respondents
Frequency of use of workplace learning activities over the past 3 months
8
Platforms provide some support for workers‘ learning activities
Providing information on in-demand skills
Facilitating peer-to-peer learning
Recommending training courses
Providing a training marketplace
SOURCE: Screenshots Upwork (2x), Fiverr and PeoplePerHour
9 SOURCE: Fiverr
10
Crowdwork and skills matching
SOURCE: Screenshot Upwork
11
28
21
25
17
9 7 or more tests
Not applicable
None
1 - 2 tests
3 - 6 tests
64
36
No
Yes
Since joining the platform, how many free [platform]
skills tests have you taken? Have these [platform]-specific skill tests been required
or helpful when getting projects on the [platform]?
Have other, non-platform specific digital/online skill tests
and certificates been required or helpful when getting
projects on [platform]?
74
26
No
Yes
Entire sample
Sample size: N=1,001 Sub-sample
Sample size: N=516
26.11.2019 But micro-certificates not very useful?
% of respondents
12
13
33
38
16
9
2
2
0
0
0
3
0
2
1
4
5
10
6
7
Number of other platforms respon-
dents have earned income from
Most common platforms respondents have
earned additional income from
30
27
20
11
7
5
4
4
3
2
1
Gumtree
Other1
Ebay
Other target platform(s)
[Fiverr, PPH, Upwork, Twago]
Youtube
AirBnB
Mturk
Craigslist
BlaBlaCar
1 'Other' is defined as categories not mentioned in the survey!
Most common
combinations:
Fiverr and Upwork: 9
PPH and Upwork: 8
Fiverr, PPH and Upwork: 5
Fiverr and PPH: 3
Many crowdworkers are active on several platforms % of respondents
14
Over half of respondents feel locked into their main crowdwork platform % of respondents
Strongly Agree
Agree
Neither Agree nor Disagree
Disagree
Strongly Disagree
5%
12%
25%
41%
16%
I could easily switch to another platform without negatively impacting my income.
N = 530
15
Cross-platform portability of skills/reputation data
Potential benefits
▪ Skills portability
empowers workers
▪ Freelancers less
dependent on any single
platform
Evidence
▪ Existing initiatives
working towards skills
portability solutions, eg.:
– My Data
– Job Tech
Experimental research
suggests portability can
help when there is a good
source-target fit between
platforms (Teubner et al.)
Challenges
▪ Leading platforms have little
incentive to participate
▪ Fluid nature of skills
ontologies and reputation
systems makes
standardization problematic
▪ Underlying infrastructure &
interoperability principles
(e.g., data formats, data
security)
▪ Data protection regulation,
especially interpretation of
EU's GDPR on data portability
(De Hert et al, 2018)
16
Proposals for VET and skills policies targeting crowdworkers
Vili Lehdonvirta (Oxford University), Anoush Margaryan (CBS)
17
Fewer than 10% of respondents feel supported by government
7%
Strongly Agree 1%
Disagree
Agree
30%
Strongly Disagree
Neither Agree nor Disagree
30%
32%
I feel that the national government supports freelancers
N = 536
18
11 recommendations structured around platform work and…
Labour
market
integration
Continuing
professional
development
Education &
vocational
training
Skills matching
19
Subsidized “micro-internships” Labour market
integration
Status quo Recommendation
▪ Platform work is frequently seen as a tool
for labour market integration
▪ But: Newcomers face barriers to entry
due to lacking client feedback
▪ >70% of crowdworkers survey have
previously been hired for a small test
project by clients to evaluate their
performance (cf. internships)
▪ Policy makers should collaborate with
platfroms to experiment with subsidized
"micro-internships" in platform work
▪ Clients are offered a subsidized rate on
workers lacking platform-based experience
▪ In exchange, clients must provide workers
with formative and evaluative feedback
20
Professional
development
“Just-in-time” formal learning provision
Status quo Recommendation
▪ ~60% of crowdworkers surveyed develop
their skill set at least weekly
▪ Resources like MOOCs often considered to
be too long, too broad and too
introductory
▪ Consider offering short online courses and
workshop to meet crowdworkers' "just-
in-time" learning needs
▪ At the same time, reconsider fee
structure with ad-supported free content
becoming normalized across the internet
21
Skills
matching
Policy task force on cross-platform portability
Status quo Recommendation
▪ Limited worker mobility between platforms
results in skills underutilization
▪ Portable portfolios to transfer
crowdworkers’ skills and reputation data
could improve worker mobility
▪ However, achieving cross-platform
portability poses significant challenges
▪ Policymakers and platforms could create
a policy task force to address
challenges:
– Lack of a business case for leading
platforms
– Constantly evolving nature of skills
and reputation systems across
platforms, hampering standardization
– Data protection regulation