Information-Requirements Grammar: A Theory of the Structure of Competence for Interaction

Information-Requirements Grammar: A Theory of the Structure of Competence for Interaction Andrew Howes (HowesA@Cardiff.ac.uk) School of Psychology, Cardiff University, Cardiff, Wales, CF10 3AT, UK Richard L. Lewis (rickl@umich.edu) Department of Psychology, University of Michigan, Ann Arbor, MI 48109-1109 Alonso Vera (avera@mail.arc.nasa.gov) Carnegie Mellon University and NASA Ames Research Center, MS 262-3 Moffet Field, CA 9403 Juliet Richardson (Juliet.Richardson@convergys.com) Convergys, Westbrook Centre, Milton Road, Cambridge, UK ABSTRACT on the basis of how they determine temporal ordering: (1) extensions and uses of techniques such as GOMS (Card, et al., 1983) that use the serial position of operators in the task description to determine temporal order; and (2) techniques such as PDL and UAN that specify temporal dependencies between operators. In this paper, we argue that existing languages for representing routine cognitive tasks (such as GOMS, UAN, and PDL) can fail either because they demand that task competence is described using serial position to determine temporal order (and they are therefore overly restrictive) or because they demand that partial orderings are specified with temporal dependencies and other logical relationships (and they are therefore under-constrained). We propose a novel task description language, called Information-Requirements Grammar (IRG), which is motivated by a theory of how higher-level task performance is constrained by the information requirements and resource demands of lower- level tasks. We demonstrate the use of IRG and show how it replaces serial ordering and temporal dependencies with resource-bound information cascades between architectural information processes. To illustrate these techniques we use a payment inquiry (PI) task. The task involves a customer contacting a call center to check whether his/her previous payment has been credited to an account (the task is similar to that studied in the seminal work by Gray, et al., 1993). To answer the inquiry the call center agent must find the customer’s record in the system and then view the key details of the most recent payment. For this type of task, both categories of cognitive modeling approach have problems. First, let us examine an example GOMS method rule for part of the PI task, namely entering the customer’s postcode as part of the search criteria to find the customer’s account: Introduction We propose a theory of competence for tasks that is called Information-Requirements Grammar (IRG). It is motivated by the assumption that constraints on tasks derive from their need for information. The assumption is not novel. In particular, Gray, John and Atwood (1993) emphasized the importance of information flow between processes in describing complex behaviors. What are novel are the implications that we draw from it. We argue that application of the theory to the modeling of task knowledge can solve two serious problems with established approaches, particularly GOMS (Card, Moran & Newell, 1983), but also UAN (Hartson & Gray, 1992), PDL (Freed, Matessa, Remington &, Vera, 2003) and similar scheduling-based languages. Enter postcode  Step 1: request postcode, Step 2: listen for postcode, Step 3: select postcode field, Step 4: type postcode. This method specifies that to achieve the ‘enter postcode’ goal, steps 1 to 4 must be conducted in order. The serial position of step 3 (between step 2 and 4) in the method description determines its temporal ordering in a behavior prediction. However, often the environment does not impose strict ordering constraints between components of the method. For example, with most devices step 3, select field, could in fact be the very first step in the “enter” method, it could also be executed in parallel with steps 1 and 2. The problem, as observed by Gray, et al. (1993), is that a GOMS method does not specify which components can be reordered; rather there is a universal assumption that temporal ordering will reflect serial position in the method. Cognitive Modeling Approaches Since Card, et al. (1983) there have been numerous advances in task knowledge modeling techniques. For our purposes, we broadly categorize these into two approaches