Team Dating: A Self-Organized Team Formation Strategy for Collaborative
Crowdsourcing
Late-Breaking Works: Collaborative Technologies
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Lykourentzou, Ioanna
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Wang, Shannon
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Kraut, Robert E.
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Dow, Steven P.
Extended Abstracts of the ACM CHI'16 Conference on Human Factors in
Computing Systems
2016-05-07
v.2
p.1243-1249
© Copyright 2016 ACM
Summary: Online crowds have the potential to do more complex work in teams, rather
than as individuals. However, at such a large scale, team formation can be
difficult to coordinate. (How) can we rely on the crowd itself to organize into
effective teams? Our research explores a strategy for "team dating", a
self-organized crowd team formation approach where workers try out and rate
different candidate partners. In two online experiments, we find that team
dating affects the way that people select partners and how they evaluate them.
We use these results to draw useful conclusions for the future of team dating
and its implications for collaborative crowdsourcing.
Personality Matters: Balancing for Personality Types Leads to Better
Outcomes for Crowd Teams
Distributed Teams
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Lykourentzou, Ioanna
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Antoniou, Angeliki
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Naudet, Yannick
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Dow, Steven P.
Proceedings of ACM CSCW 2016 Conference on Computer-Supported Cooperative
Work and Social Computing
2016-02-27
v.1
p.260-273
© Copyright 2016 ACM
Summary: When personalities clash, teams operate less effectively. Personality
differences affect face-to-face collaboration and may lower trust in virtual
teams. For relatively short-lived assignments, like those of online
crowdsourcing, personality matching could provide a simple, scalable strategy
for effective team formation. However, it is not clear how (or if) personality
differences affect teamwork in this novel context where the workforce is more
transient and diverse. This study examines how personality compatibility in
crowd teams affects performance and individual perceptions. Using the DISC
personality test, we composed 14 five-person teams (N=70) with either a
harmonious coverage of personalities (balanced) or a surplus of leader-type
personalities (imbalanced). Results show that balancing for personality leads
to significantly better performance on a collaborative task. Balanced teams
exhibited less conflict and their members reported higher levels of
satisfaction and acceptance. This work demonstrates a simple personality
matching strategy for forming more effective teams in crowdsourcing contexts.
Collaborative e-learning environments enhanced by wiki technologies
Workshops
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Giannoukos, Ioannis
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Lykourentzou, Ioanna
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Mpardis, Giorgos
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Nikolopoulos, Vassilis
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Loumos, Vassili
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Kayafas, Eleftherios
Proceedings of the 1st International Conference on PErvasive Technologies
Related to Assistive Environments
2008-07-16
p.59
Keywords: collaborative learning, e-learning, wikis
© Copyright 2008 ACM
Summary: E-learning environments have met rapid technological advancements in the
previous years. Nevertheless, current e-learning techniques do not adequately
support student interaction and collaboration, resulting in decreased student
progress and motivation. In this paper, a blended technique combining
collaborative forums and wiki technologies is proposed. Through collaborative
forums, students discuss course related topics assigned by the tutors to
produce new educational material. This material is then stored in the wiki
platform for further use. The proposed technique was applied on an e-learning
course provided by the National Technical University of Athens and its
effectiveness was evaluated using student activity data and questionnaire
analysis. Results showed that the technique adequately supported teamwork,
increasing student motivation and progress while simultaneously producing
satisfactory level educational material.
