Organizations in the United States alone spend billions on training each year. These training and development activities allow organizations to adapt, compete, excel, innovate, produce, be safe, ...improve service, and reach goals. Training has successfully been used to reduce errors in such high-risk settings as emergency rooms, aviation, and the military. However, training is also important in more conventional organizations. These organizations understand that training helps them to remain competitive by continually educating their workforce. They understand that investing in their employees yields greater results. However, training is not as intuitive as it may seem. There is a science of training that shows that there is a right way and a wrong way to design, deliver, and implement a training program. The research on training clearly shows two things: (a) training works, and (b) the way training is designed, delivered, and implemented matters. This article aims to explain why training is important and how to use training appropriately. Using the training literature as a guide, we explain what training is, why it is important, and provide recommendations for implementing a training program in an organization. In particular, we argue that training is a systematic process, and we explain what matters before, during, and after training. Steps to take at each of these three time periods are listed and described and are summarized in a checklist for ease of use. We conclude with a discussion of implications for both leaders and policymakers and an exploration of issues that may come up when deciding to implement a training program. Furthermore, we include key questions that executives and policymakers should ask about the design, delivery, or implementation of a training program. Finally, we consider future research that is important in this area, including some still unanswered questions and room for development in this evolving field.
Team debriefings are structured interventions in which teams reflect on their past performance, adapt, and plan for future events. Results from meta-analyses indicate that team debriefings are ...effective in improving task performance (Keiser & Arthur,
Journal of Applied Psychology
,
106
(7), 1007–1032,
2021
,
Journal of Business and Psychology
,
37
(5), 953–976,
2022
; Tannenbaum & Cerasoli
, Human Factors: The Journal of the Human Factors and Ergonomics Society, 55
(1), 231–245,
2013
). Although far less often studied, there is also some evidence to suggest that team debriefings (compared to no debriefings) can be used to develop norms for open communication (Jarrett et al.,
Human Performance, 29
(5), 408-427,
2016
; Villado & Arthur,
Journal of Applied Psychology, 98
(3), 514-528,
2013
). However, there is currently a dearth of quantitative evidence to guide practitioners in selecting from the myriad methods available to achieve this purpose. Grounded in theory and research on episodic models of team performance (Marks et al.,
Academy of Management Review, 26
(3), 356-376,
2001
) and the Motivated Information Processing in Groups model (MIP-G) (De Dreu et al.,
Personality and Social Psychology Review, 12
(1), 22–49,
2008
), we conducted a quasi-experiment which compared two debriefing methods. The first, a chronological debriefing, emphasizes outcome accountability and makes competitive interdependence salient, whereas the second method, Team Dimensional Training (TDT), emphasizes process accountability and makes cooperative interdependence salient. Data from 76 flight controllers at Johnson Space Center indicated that the communication climate in TDT debriefings was perceived to be more open than was the climate in chronological debriefings. Analyses of coded transcripts from 69 debriefings revealed that teams engaged in deeper reflexivity when the TDT method was used than they did when the chronological method was used.
Objective: This article presents a model for predicting complex collaborative processes as they arise in one-of-a-kind problem-solving situations to predict performance outcomes. The goal is to ...outline a set of key processes and their interrelationship and to describe how these can be used to predict collaboration processes embedded within problem-solving contexts. Background: Teams are increasingly called upon to address complex problem-solving tasks in novel situations. This represents a domain of performance that to date has been underrepresented in the research literature. Method: Multidisciplinary theoretical and empirical literature relating to knowledge work in teams is synthesized. Results: A set of propositions developed to guide research into how teams externalize cognition and build knowledge in service of problem solving is presented. First, a brief overview of macrocognition in teams is provided to distinguish the present work from other views of team cognition. Second, a description of the foundational theoretical concepts driving the theory of macrocognition in teams presented here is provided. Third, a set of propositions described within the context of a model of macrocognition in teams is forwarded. Conclusion: The theoretical framework described in this article provides a set of empirically testable propositions that can ultimately guide practitioners in efforts to support macrocognition in teams. Application: A theory of macrocognition in teams can provide guidance for the development of training interventions and the design of collaborative tools to facilitate knowledge-based performance in teams.
The CEO begins their team self-evaluation session by offering his take on the team's coordination processes, followed by the new VP. Some members look like deer caught in headlights. Others shoot ...knowing looks at one another but remain silent. Finally, a senior member hesitantly points out that the extra steps involved in getting approval (introduced by the new VP) have slowed down his work. The VP snaps back defensively and the room falls silent again. Visibly uncomfortable, the well-meaning CEO shifts gears and begins walking through a timeline of milestones from their most recent project, noting which were completed on time and which were missed. He asks each functional group one at a time to provide their perspectives on why. The discussion quickly turns heated as sales, accounting, and product development groups complain about one another. An hour later, team members shuffle out of the conference room looking either confused, embarrassed, angry, or frustrated, asked for their inputs.
Linkages between 2 types of shared mental models (SMMs)-that is, positional-goal interdependencies and cue-strategy associations-and effectiveness in an air traffic control environment were ...investigated. Two types of SMMs were expected to contribute uniquely, as well as interact, to predict tower safety and efficiency. Using SMM data from 306 air traffic controllers, and corresponding archival efficiency and safety measures for 47 airports, the authors found no significant linear relationships between SMMs and either outcome measure. However, the 2 SMMs interacted with one another to predict both outcomes. Results are discussed in terms of the importance of measuring multiple types of SMMs, the examination of complex relationships, and the importance of indexing decisions.
Objective: The present study investigated factors that explain when and why different groups of teammates are more likely to request and accept backup from one another when needed in an environment ...characterized by extreme time pressure and severe consequences of error: commercial air traffic control (ATC). Background: Transactive memory theory states that teammates develop consensus regarding the distribution of their relative expertise as well as confidence in that expertise over time and that this facilitates coordination processes. The present study investigated whether this theory could help to explain between-team differences in requesting and accepting backup when needed. Method: The present study used cross-sectional data collected from 51 commercial ATC teams. Hypotheses were tested using multiple regression analysis. Results: Teammates with greater experience working together requested and accepted backup from one another more than those with lesser experience working together. Teammate knowledge consensus and perceived team efficacy appear to have mediated this relationship. Conclusion: Transactive memory theory extends to high-stress environments in which members' expertise is highly overlapping. Teammates' shared mental models about one another increase the likelihood that they will request and accept backup. Application: Teammate familiarity should be considered when choosing among potential replacement team members. Training strategies that accelerate the development of teammate knowledge consensus and team efficacy are warranted.
Guided Team Self-Correction Smith-Jentsch, Kimberly A.; Cannon-Bowers, Janis A.; Tannenbaum, Scott I. ...
Small group research,
06/2008, Letnik:
39, Številka:
3
Journal Article
Recenzirano
This research investigated the effects of guided team self-correction using an empirically derived expert model of teamwork as the organizing framework. First, the authors describe the process used ...to define this model. Second, they report findings from two studies in which the expert model was used to structure the process of guided team self-correction. Participants were U.S. Navy command and control teams (25 in Study 1, 13 in Study 2). Results indicated that teams debriefed using the expert model-driven guided team self-correction approach developed more accurate mental models of teamwork (Study 1) and demonstrated greater teamwork processes and more effective outcomes (Study 2) than did teams debriefed using a less participative and chronologically organized approach that is more typical for these teams.
The present paper reports data from two studies that utilized a card sorting approach to measuring mental model similarity in naturalistic training environments. Results from the first study ...indicated that higher ranking navy personnel held mental models of teamwork that were more similar to an empirically derived model of expert team performance than lower ranking personnel. Furthermore, comparisons of mental model similarity within groups of high and low ranking trainees and within groups of high and low experience trainees indicated greater similarity between those of higher rank and between those with greater experience. The second study tested the effects of a computer-based training (CBT) strategy that was designed to develop teamwork mental models that were more similar to the 'expert model' described in Study 1. Using the same card sorting approach, positive training effects were demonstrated on similarity to the expert model, similarity to other trainees, and consistency.
Making smart investments in training Smith-Jentsch, Kimberly A.
Organizational dynamics,
April-June 2020, 2020-04-00, Letnik:
49, Številka:
2
Journal Article
One of the significant challenges for the burgeoning field of macrocognition is the development of more sophisticated models that are able to adequately explain and predict complex cognitive ...processes. This is even more critical when specifying research questions involving cognition unfolding across interacting individuals, that is, macrocognition in teams. In this article, we provide a foundation for developing a model of macrocognition focusing on collaborating problem-solving teams with a measurement framework for studying macrocognitive processes in this context. We first discuss an important set of key assumptions from team measurement theory that form a critical foundation for this model. We then describe the core definitions we suggest are foundational to the conceptualisation of macrocognition in teams. We conclude with a description of the key dimensions and subcomponents of our model in order to lay the foundation for a principled approach to measuring and understanding macrocognition in teams.
