1. Crowdsourcing: language learning and commercial
imperatives in web 2.0 language learning
communities
Katerina Zourou, Ph.D., Web2Learn, Greece
EnetCollect workshop, Iasi, Romania, March 14, 2018
Funded by the Horizon 2020 Framework
Programme of the European Union
EnetCollect: European
Network for Combining
Language Learning with
Crowdsourcing Techniques

2. Workshop’s topic: how crowdsourcing techniques are used for
generating language learning materials?
This presentation: What kind of mechanisms sustain
crowdsourced language learning?
• mechanics sustaining language learning and language tutoring.
• Language tutoring: creation of language learning materials in one’s
L1 as part of “duties” of an L2 learner
• Emphasis on crowdsourcing dynamics enabled by social
networking and gamification elements.
• Crowdsourcing happening without remuneration (e.g. Mechanical
Turk), on a “voluntary” basis.
Scope
Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

3. An attempt to connect recent studies on gamification, social
networks, crowdsourcing and computer assisted language learning
(CALL).
Contribute to an understanding of the nuances between implicit and
explicit crowdsourcing, by looking at the game and social network
dynamics and the way they are instrumentalized to serve
crowdsourcing purposes, often for a value making process.
Background
Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

4. « Explicit » crowdsourced production of
language learning materials
Example: Duolingo’s Incubator
Note: just an indicative example. Developments are in progress.
Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

5. Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

6. Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

7. « Implicit » crowdsourced production of
language learning materials
• Field analysis: web 2.0 language learning communities (2012 typology
by Loiseau, Potolia & Zourou)
A. Structured web 2.0 language learning communities
B. Language exchange sites
C. Market places
D. Language correction sites
• Language tutoring: creation of language learning materials in one’s
L1 as part of “duties” of an L2 learner
• An incentivized process (gamification; incentivized learning)
enhanced by social networking and gamification elements.
Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

8. Social networking and gamification elements
From Zourou, K., & Lamy, M. (2013). Social networked game dynamics in web 2.0 language learning
communities. Alsic, 16. Retrieved from http://alsic.revues.org/2642
Reminder:
GM: Game mechanics
Type of community:
A.Structured web 2.0 lang.
learning communities
B.Language exchange sites
C.Market places
D.Language correction sites

9. Social networking and gamification elements
In red box: tutor specific incentives
In blue box: learner specific incentives

10. Gamification elements enabling crowdsourced
language tutoring (and some content generation)
Game mechanism 1 : teacher score (in points)
1. Through correction of learner input
2. By being the first person to correct a learner’s production
3. Through translation of materials into one’s native language
4. By creating flashcards
5. By contributing to ”Featured tips”
6. By giving quality feedback (by earning positive ratings)
Game mechanism 2: badges
1. By commenting on learners’ posts
2. By creating and/or being leader in groups (Busuu only)
3. For being the top 10 Teacher or the top 100 teacher of the week/the month
4. By Translating content
5. By being rated as a (very) helpful corrector
Game mechanism 4 rating systems
1. 1.Rating of learner input stars)
2. Rating of learner input followed by feedback stars)
3. Rating of tutor feedback (stars)
4. Intra-native speaker feedback (points or “nods”)
Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018

11. Conclusion
Katerina Zourou, EnetCollect workshop, Iasi, March 14, 2018
• Gaming rewards and reputation management as triggers to more user activity
• "crowdsourcing" : Engagement of individuals who voluntarily offer their knowledge
to a knowledge seeker (an organisation, a company, etc.) Howe (2006). Depending
on the context
• it can be seen not only as a movement towards massive user engagement in an
unrestricted and collaborative manner, but also as a means by which companies
exploit users' collective efforts of knowledge building, without a corresponding
remuneration, "[by] tap[ping] the latent talent of the crowd"
• Game mechanics are instrumental in triggering engagement and in increasing
motivation in non-game environments.
• The risk of crowdsourcing is often the exploitation of the results of users' efforts
and a profit-making mechanism in favour of the knowledge seeker.
Full paper: Zourou, K., & Lamy, M. (2013). Social networked game dynamics in web 2.0 language
learning communities. Alsic, 16. Retrieved from http://alsic.revues.org/2642

12. Thankyou!
#enetcollect
@web2learn_eu
Slides available at
https://www.slideshare.net/Web2Learn_eu