Adaptive Perspectives on Human-Technology Interaction: Methods and Models for Cognitive Engineering and Human-Computer Interaction

Leonard Adelman, Cedric Yeo, and Sheryl L. Miller

Some studies (e.g., Urban et al., 1996) have shown that time pressure degrades team decision-making performance. In contrast, other studies have shown process changes but no effect on performance (e.g., Hollenbeck et al., 1997b). Using a longitudinal design, Adelman and colleagues (2003) found that teams adapted their processes in different ways, all of which were effective in maintaining high and constant performance until almost twice the initial time pressure level. Then different teams lost performance constancy as time pressure increased, depending on their process adaptations. The findings suggest that one should not necessarily expect to find a process–performance relationship with increasing time pressure; team processes change early and in different ways, but performance can be maintained under high time pressure levels depending on the effectiveness of the team's process adaptations. These findings are consistent with Entin and Serfaty's (1999) team adaptation model and, as discussed in Adelman, Henderson, and Miller (2001), Brunswik's (1952) concepts of vicarious functioning (process intersubstitutability) and performance constancy.

Also consistent with Brunswikian theory (Hammond & Stewart, 2001), one can argue that one's results depend on the task, and in the case of Adelman et al. (2003), the features of the human–computer interface. In a follow-up study, Miller and colleagues (2000) demonstrated this point, but only to a limited extent. They found that a “perceptual” interface designed to make it easier for team members to see what decisions they had made permitted teams to maintain the percentage of decisions they made as time pressure increased. However, contrary to prediction based on previous research (e.g., Balzer, Doherty, & O'Connor, 1989), a “cognitive” interface designed to provide feedback on team members' decision processes had no effect on decision accuracy. As time pressure increased, team decision accuracy declined regardless of the type of human-computer interface.

We were unable to explain this finding fully at the time of the study. We can now do so using a Brunswikian theory of team decision making and the lens model equation. The next section presents the relevant theoretical concepts; then we describe the experiment and new analyses. The final section discusses the strength and limitations of the research.

-43-