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Title:LIFT: Integrating stakeholder voices into algorithmic team formation
Author(s):Hastings, Emily Marie
Advisor(s):Bailey, Brian P.; Karahalios, Karrie
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Algorithms
CATME
Learnersourcing
Crowdsourcing
Team formation
Team composition
Abstract:Team formation tools assume instructors should configure the criteria for creating teams, precluding students from participating in a process that affects their learning experience. We propose LIFT, a novel learner-centered workflow where students propose, vote for, and weigh team formation criteria, and the collective results serve as inputs to the team formation algorithm. We conducted an experiment (N=289) comparing LIFT to the usual instructor-led process, and interviewed participants to evaluate their perceptions of LIFT and its outcomes. We found learners were capable of proposing novel criteria not part of existing algorithmic tools, like organizational style. Generally, learners avoided criteria frequently selected by instructors, including gender and GPA, and instead preferred those that promoted efficient collaboration. Second, LIFT led to team outcomes comparable to those achieved by the instructor-led approach, despite the differences in the configurations, and teams valued having control of the team formation process. We provide instructors and tool designers with a workflow and evidence supporting giving learners control of the algorithmic process used for grouping them into teams.
Issue Date:2019-04-18
Type:Text
URI:http://hdl.handle.net/2142/104866
Rights Information:Copyright 2019 Emily Marie Hastings
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05


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