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@article{gamage2021peer,

title = {Peer assessment in MOOCs: Systematic literature review},

author = {Dilrukshi Gamage and Thomas Staubitz and Mark Whiting},

url = {https://www.researchgate.net/profile/Dilrukshi-Gamage-2/publication/351344733_Peer_assessment_in_MOOCs_Systematic_literature_review/links/60923fc3a6fdccaebd093ccc/Peer-assessment-in-MOOCs-Systematic-literature-review.pdf},

doi = {10.1080/01587919.2021.1911626},

year  = {2021},

date = {2021-05-03},

journal = {Distance Education},

pages = {1-22},

abstract = {We report on a systematic review of the landscape of peer assessment in massive open online courses (MOOCs) with papers from 2014 to 2020 in 20 leading education technology publication venues across four databases containing education technology–related papers, addressing three research issues: the evolution of peer assessment in MOOCs during the period 2014 to 2020, the methods used in MOOCs to assess peers, and the challenges of and future directions in MOOC peer assessment. We provide summary statistics and a review of methods across the corpus and highlight three directions for improving the use of peer assessment in MOOCs: the need for focusing on scaling learning through peer evaluations, the need for scaling and optimizing team submissions in team peer assessments, and the need for embedding a social process for peer assessment.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{cao2021my,

title = {My Team Will Go On: Differentiating High and Low Viability Teams through Team Interaction},

author = {Hancheng Cao and Vivian Yang and Victor Chen and Yu Jin Lee and Lydia Stone and N'godjigui Junior Diarrassouba and Mark Whiting and Michael Bernstein},

url = {https://arxiv.org/pdf/2010.07292},

doi = {10.1145/nnnnnnn.nnnnnnn},

year  = {2021},

date = {2021-01-05},

journal = {Proceedings of the ACM Human-Computer Interaction},

volume = {4},

number = {CSCW3},

pages = {1-27},

abstract = {Understanding team viability — a team’s capacity for sustained and future success — is essential for building effective teams. In this study, we aggregate features drawn from the organizational behavior literature to train a viability classification model over a dataset of 669 10-minute text conversations of online teams. We train classifiers to identify teams at the top decile (most viable teams), 50th percentile (above a median split), and bottom decile (least viable teams), then characterize the attributes of teams at each of these viability levels. We find that a lasso regression model achieves an accuracy of .74–.92 AUC ROC under different thresholds of classifying viability scores. From these models, we identify the use of exclusive language such as ‘but’ and ‘except’, and the use of second person pronouns, as the most predictive features for detecting the most viable teams, suggesting that active engagement with others’ ideas is a crucial signal of a viable team. Only a small fraction of the 10-minute discussion, as little as 70 seconds, is required for predicting the viability of team interaction. This work suggests opportunities for teams to assess, track, and visualize their own viability in real time as they collaborate.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{almaatouq2021empirica,

title = {Empirica: a virtual lab for high-throughput macro-level experiments},

author = {Abdullah Almaatouq and Joshua Becker and James P Houghton and Nicolas Paton and Duncan J Watts and Mark E Whiting},

url = {https://drive.google.com/file/d/1asyd8onp_2df10W1AbzPOyar6WknEiCU/view},

doi = {10.3758/s13428-020-01535-9},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Behavior Research Methods},

pages = {1--14},

publisher = {Springer},

abstract = {Virtual labs allow researchers to design high-throughput and macro-level experiments that are not feasible in traditional in-person physical lab settings. Despite the increasing popularity of online research, researchers still face many technical and logistical barriers when designing and deploying virtual lab experiments. While several platforms exist to facilitate the development of virtual lab experiments, they typically present researchers with a stark trade-off between usability and functionality. We introduce Empirica: a modular virtual lab that offers a solution to the usability--functionality trade-off by employing a ``flexible defaults'' design strategy. This strategy enables us to maintain complete ``build anything'' flexibility while offering a development platform that is accessible to novice programmers. Empirica's architecture is designed to allow for parameterizable experimental designs, reusable protocols, and rapid development. These features will increase the accessibility of virtual lab experiments, remove barriers to innovation in experiment design, and enable rapid progress in the understanding of human behavior.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{whiting2020can,

title = {Can We Just Start Over Again? Resetting Remote Team Dynamics},

author = {Mark Whiting and Michael Bernstein},

url = {https://www.microsoft.com/en-us/research/uploads/prod/2020/07/NFW-Whiting-et-al.pdf},

year  = {2020},

date = {2020-07-07},

abstract = {Interactions defining teamwork today are heavily influenced by constraints and expectations found in in-person teams, however, remote collaboration provides the opportunity to try new ways to make teams work. One foundation of teamwork is persistent identity—we are who we were last time we worked together. Breaking with the expectation of in-person teams, we present a system that affords discontinuous identity using two-way pseudonym masking—enabling teams with new behaviors to arise from the same group of individuals. With this scaffold, a novel family of experiments, comparing the same group across multiple fresh starts, are possible. Further, interventions that involve choosing between versions of the same team are unlocked. We present an overview of experiments and interventions leveraging this system, and propose methods for its broader use in organizations enacting the future of work.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}