Facilitating Adaptive Team Performance: The Influence Of Membership Fluidity On Learning

Organizations across work domains that utilize teams to achieve organizational outcomes experience change. Resources change. Project deadlines change. Personnel change. Within the scientific community, research has recently surged on the topic of team adaptation to address the issue of change specifically within teams. There have generally been two lines of research regarding team adaptation (task and membership). This effort is focused on membership. Teams are not static— members come and go. The membership adaptation literature has traditionally focused on the performance effects of newcomers to teams. Yet in practice, more and more teams today experience membership loss without replacement. Military units are stretched to capacity. Economic conditions have forced organizations to do more with less. When members leave, they are rarely, if ever, replaced. The very nature of some organizations lends itself to fluid team memberships. Consider an emergency room where a team of nurses and doctors work on Patient A. When a more critical Patient B arrives that requires the expertise of one of those team members, that doctor will leave the Patient A to tend to the Patient B. This practice is common in such work environments. Yet despite the prevalence of this practice, the scientific community knows very little about the impact of losing members on team performance. The current study examines the impact of membership fluidity on team performance. The purpose of this study was twofold. First, there was the need to address an empirical gap in the adaptation literature by focusing on membership changes (loss and loss with replacement) in non-creative tasks. Second was the consideration of the processes underlying adaptation—namely learning, operationalized as the development of effective shared mental models (SMMs). Thus, a primary goal was to determine the magnitude of team performance decrements associated with such changes within a decision-making task as well as the associated changes in team process. Results suggest that three-person intact teams demonstrated greater adaptive performance iv than membership loss with replacement teams. Furthermore, two-person intact teams developed more similar task and team interaction SMMs than membership loss teams when SMMs were indexed as a Euclidean distance score. There were no differences in the level of sharedness regarding task, team interaction or teammate SMMs for three-person intact teams as compared to membership loss with replacement teams. However, when teammate SMMs were operationalized as the personality facets (i.e., the Big 5) in exploratory analyses, three-person intact teams did develop more similar SMMs regarding the agreeableness facet than membership loss with replacement teams. Additionally, when operationalized as Euclidean distance, the agreeableness facet significantly predicted adaptive team performance—specifically, the smaller the distance (i.e., more similar the MMs), the greater the adaptive performance in teams. When operationalized as the similarity index, the neuroticism facet significantly predicted adaptive team performance such that the more similar the SMMs, the greater the adaptive performance in teams. Results suggest that membership fluidity does negatively influence the development of shared mental models among teammates. Furthermore, this study provides additional evidence that teammate and team interaction mental models, which are typically not examined together in team studies, are differentially influenced by membership fluidity and differentially predict outcomes like adaptive team performance. This suggests researchers should include both of these cognitive components of team performance to fully understand the nature of these constructs

You’ve Got Mail: Examination of a Brief Online Email Training

Many companies train employees on writing emails in seminar-style training sessions. However, in-person, seminar-style trainings are costly. This study aims to create a training program, rooted in the science of training to address these needs. We examine the mechanisms of action by which the training influences performance and intent to transfer. To do this, we call upon several models of training effectiveness (see Alliger, Tannenbaum, Bennett, & Traver, 1997; Baldwin & Ford, 1988; and Kirkpatrick, 1959). Taken together, these models suggest that individual differences will predict affective reactions, which will lead to utility reactions, ultimately leading to learning. We aim to test this synthesized model. Participants were 164 undergraduate students, informed they were working for a hypothetical customer service department. Email training was provided online through Qualtrics survey software, and provided information, demonstration, and an opportunity for practice. Participants then wrote a final email according to the training. Path analysis, using maximum likelihood estimation, found acceptable model fit (c2(3)= 9.87, p = 0.02; CFI = 0.95, SRMR = 0.045), suggesting that conscientiousness predicts comfort with training (an affective reaction; β = 0.25, p \u3c .001), which influences motivation to transfer (a utility reaction; β = 1.17, p \u3c .001). Motivation to transfer did not predict task performance. Although the model did not significantly account for task performance, it did highlight that individual characteristics can predict affective reactions which then predict utility reactions. Practitioners and researchers should account for individual and both affective and utility reactions when evaluating training programs

The pipeline project:Pre-publication independent replications of a single laboratory's research pipeline

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had "in the pipeline" as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed. (C) 2015 The Authors. Published by Elsevier Inc.</p

Data from a pre-publication independent replication initiative examining ten moral judgement effects

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science

The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline

This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had “in the pipeline” as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed

Data from a pre-publication independent replication initiative examining ten moral judgement effects

We present the data from a crowdsourced project seeking to replicate findings in independent laboratories before (rather than after) they are published. In this Pre-Publication Independent Replication (PPIR) initiative, 25 research groups attempted to replicate 10 moral judgment effects from a single laboratory's research pipeline of unpublished findings. The 10 effects were investigated using online/lab surveys containing psychological manipulations (vignettes) followed by questionnaires. Results revealed a mix of reliable, unreliable, and culturally moderated findings. Unlike any previous replication project, this dataset includes the data from not only the replications but also from the original studies, creating a unique corpus that researchers can use to better understand reproducibility and irreproducibility in science.Link_to_subscribed_fulltex

The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline

© 2015 The Authors This crowdsourced project introduces a collaborative approach to improving the reproducibility of scientific research, in which findings are replicated in qualified independent laboratories before (rather than after) they are published. Our goal is to establish a non-adversarial replication process with highly informative final results. To illustrate the Pre-Publication Independent Replication (PPIR) approach, 25 research groups conducted replications of all ten moral judgment effects which the last author and his collaborators had âin the pipelineâ as of August 2014. Six findings replicated according to all replication criteria, one finding replicated but with a significantly smaller effect size than the original, one finding replicated consistently in the original culture but not outside of it, and two findings failed to find support. In total, 40% of the original findings failed at least one major replication criterion. Potential ways to implement and incentivize pre-publication independent replication on a large scale are discussed.Link_to_subscribed_fulltex

Cognitive Aids In Emergency Medical Services

If there were just one defining characteristic of EMS, it would unequivocally be flawless service as quickly as possible. As Kobusingye et al. (2006, p. 1261) suggest, EMS requires “rapid assessment, timely provision of appropriate interventions, and prompt transportation to the nearest appropriate health facility by the best possible means to enhance survival, control morbidity, and prevent disability” (emphasis added). Within this statement lies an obvious paradox: perform optimally and rapidly. Yet science and practice both suggest a clear speed-accuracy trade-off (Fitts, 1954). So consistent is this finding that it has been named Fitts?s law (MacKenzie, 1992) and, thus, placed on equal footing with other indisputable phenomenon such as gravity and thermodynamics. But the presence of gravity did not stop humans from reaching the moon, nor have the laws of thermodynamics prevented discovery/creation of a variety of superconductors. In short, every law is made to be broken-or at least bent. The question is, how can we bend Fitts?s law to make EMS both 124exceptionally fast and highly accurate? We argue that the answer lies, at least in part, with cognitive aids