Evading a Multitasking Bottleneck: Presenting Intermediate Representations in the Environment

Evading a Multitasking Bottleneck: Presenting Intermediate Representations in the Environment Trudy A. Buwalda (t.a.buwalda@rug.nl) Jelmer P. Borst (j.p.borst@rug.nl) Niels A. Taatgen (n.a.taatgen@rug.nl) Department of Artificial Intelligence, University of Groningen Nijenborgh 9, 9747 AG Groningen, the Netherlands Hedderik van Rijn (d.h.van.rijn@rug.nl) Department of Psychology, University of Groningen Grote Kruisstraat 2/1, 9712 TS Groningen, the Netherlands Abstract When people have to store intermediate results for multiple tasks concurrently, performance decreases considerably as opposed to when at most one intermediate result has to be stored. Borst, Taatgen and Van Rijn (2010) have shown that a multitasking bottleneck associated with intermediate problem representations can account for this effect. This study investigates whether representing problem representations externally reduces the interference. To this end we extended the experiment in Borst et al. (2010) with a version that required no problem representation. The results show that there is an over-additive increase in response times when both tasks need to store an intermediate representation, as compared to a situation in which at most one task requires an intermediate representation, either because no intermediate representation is needed, or because the intermediate representation is available on the screen. These results suggest that multitasking performance can be improved by presenting intermediate representations in the environment. Keywords: multitasking; interference; problem state; external representation; threaded cognition. Introduction When you walk through the city on a Saturday afternoon you come across many examples of multitasking: Business men who are trying to talk on the phone while driving, tourists reading a map while walking, and boys watching girls while riding their bikes. These are examples of the ability of human beings to do several tasks at once. While this capability works effortless in certain situations, like walking and talking, other examples suggest it is nearly impossible to execute two tasks at once (e.g., writing a paper and watching television). Here we discuss multitasking interference in the problem state resource, which can be considered part of working memory, and how to avoid it. There are several theories that discuss multitasking interference (e.g., Pashler, 1984; Meyer & Kieras, 1997; Salvucci & Taatgen, 2008). These theories differ in their explanation of what causes interference during multitasking: ranging from one central processing bottleneck (e.g., Pashler, 1984) to a purely cognitive control account (e.g., Meyer & Kieras, 1997) The theory of threaded cognition (Salvucci & Taatgen, 2008; Salvucci, Taatgen, & Borst, 2009) takes the middle ground by assuming multiple processing bottlenecks, both cognitive and perceptual. According to threaded cognition human multitasking is not limited by the number of tasks that are carried out, but by capacity limitations of cognitive and peripheral resources. As soon as a resource is required by more than one task, this leads to interference. Previously Salvucci and Taatgen (2008) discussed two peripheral bottlenecks (the visual and motor systems) and two central cognitive bottlenecks (declarative and procedural memory; cf. “attentional limitations” Pashler & Johnston, 1998). A third central cognitive resource that can act as a bottleneck, the problem state resource, was identified by Borst, Taatgen and Van Rijn (2010). The problem state is the cognitive resource that holds intermediate results of processing. While solving an equation like 3x – 4 = 8, a likely intermediate representation that is stored in the problem state is 3x = 12. According to threaded cognition, a resource can only be used for one task at a time, which means that the problem state resource can only store a single intermediate representation. Intermediate representations that are removed from the problem state resource are automatically stored in declarative memory. The distinction between the problem state resource on the one hand, and declarative memory on the other hand is an important one: Information that is represented in the problem state resource is directly accessible, while retrieving facts from declarative memory costs time. The idea of a problem state is similar to the focus of attention in working memory (e.g., Cowan, 1995; Garavan, 1998; Oberauer, 2002) in the sense that it has a size of only one element and can be accessed without time costs. Changing from one problem state to another takes a small amount of time (previously estimated to be around 200 ms, Anderson, 2007). Moreover, when a previous problem state has to be retrieved from declarative memory this increases the time it takes to change the problem state.