Why We Can’t Text and Drive: An Experimental Study of the Tradeoff of Learning Efficiency and Multitasking Capacity in Human Cognition

Abstract

People cannot conduct more than a few, and usually only one, control-demanding tasks at a time. Although this limitation is a well-recognized feature of goal-directed behavior, the reason for this limitation has yet to be fully understood. At present, one of the more promising explanations of this phenomenon is that the execution of multiple tasks is limited by cross-talk between overlapping task processing pathways (Allport, 1980; Feng, Schwemmer, Gershman, & Cohen, 2014; Meyer & Kieras, 1997; Navon & Gopher, 1979; Salvucci & Taatgen, 2011). The current work seeks to test the hypothesis that the emergence of overlapping task representations between tasks based on task similarities in the environment promotes learning efficiency, but impairs multitasking performance (Musslick et al., In Press, 2016b). I will present an experiment in which subjects learned multiple tasks that relied to different degrees on similar task-features. After learning all tasks, multitasking performance was assessed. The results of the experiment suggest that new tasks can be learned at a faster rate if they share features with previously acquired tasks, although early learning may be impaired. Our results yield higher interference for multitasking conditions in which the tasks relied on features shared with other tasks as opposed to independent tasks, although this did not significantly change multitasking accuracy. These antagonistic performance effects of learning rate and multitasking interference may indicate a computational tradeoff between learning efficiency through the use of shared representations and multitasking performance.