Abstract not found

This article provides an overview of the EPIC architecture being developed by Kieras and Meyer for modeling human cognition and performance (Kieras, Wood, & Meyer, 1997; Meyer & Kieras, 1997a, 1997b). EPIC is similar in spirit to the Model Human Processor (MHP; Card, Moran, & Newell, 1983), but EPIC incorporates many recent theoretical and empiri- cal results about human performance in the form of a software framework for computer simulation modeling. Using EPIC, a model can be con- structed that represents the general procedures required to perform a complex multimodal task a a set of production rules. When the model is supplied with the external stimuli for a specffic task, it will then execute the procedures in whatever way the task requires, thus simulating a human 's performing the task and generating the predicted actions in simulated real time. EPIC is an architecture for constructing models of 394 performance. It is notet a learning system and so has no mechanisms for learning how to perform a task. Rather, the purpose of EPIC is to repre- sent in detail the perceptual, motor, and cognitive constraints on the human ability to perform tasks

ing with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. GOMS Family Comparison p. 2 2 Keywords: GOMS, cognitive modeling, usability engineering ABSTRACT Since the publication of The psychology of human-computer interaction (Card, Moran & Newell, 1983), the GOMS model has been one of the most widely known theoretical concepts in HCI. This concept has produced several GOMS analysis techniques that differ in appearance and form, underlying architectural assumptions, and predictive power. This paper compares and contrasts four popular variants of the GOMS family (the Keystroke-Level Model, the original GOMS formulation, NGOMSL, and CPM-GOMS) by applying them to a single task example. 1. INTRODUCTION Since the publication of The psychology of human-computer interaction (Card, Mora...

Distinctions have been proposed between systems of reasoning for centuries. This article distills properties shared by many of these distinctions and characterizes the resulting systems in light of recent findings and theoretical developments. One system is associative because its computations reflect similarity structure and relations of temporal contiguity. The other is "rule based " because it operates on symbolic structures that have logical content and variables and because its computations have the properties that are normally assigned to rules. The systems serve complementary functions and can simultaneously generate different solutions to a reasoning problem. The rule-based system can suppress the associative system but not completely inhibit it. The article reviews evidence in favor of the distinction and its characterization. One of the oldest conundrums in psychology is whether people are best conceived as parallel processors of information who operate along diffuse associative links or as analysts who operate by deliberate and sequential manipulation of internal representations. Are inferences drawn through a network of learned associative pathways or through application of a kind of "psychologic"

The question is not whether intelligent machines can have any emotions, but whether machines can be intelligent without any emotions. – Marvin Minsky, (Minsky, 1986) p. 163 In every art form it is the emotional content that makes the difference between mere technical skill and true art.

Usability evaluation is an increasingly important part of the user interface design process. However, usability evaluation can be expensive in terms of time and human resources, and automation is therefore a promising way to augment existing approaches. This article presents an extensive survey of usability evaluation methods, organized according to a new taxonomy that emphasizes the role of automation. The survey analyzes existing techniques, identifies which aspects of usability evaluation automation are likely to be of use in future research, and suggests new ways to expand existing approaches to better support usability evaluation. Categories and Subject Descriptors: H.1.2 [Information Systems]: User/Machine Systems—human factors; human information processing; H.5.2 [Information Systems]: User Interfaces—benchmarking; evaluation/methodology; graphical user

Goal-directed cognition is often discussed in terms of specialized memory structures like the "goal stack." The goal-activation model presented here analyzes goal-directed cognition in terms of the general memory constructs of activation and associative priming. The model embodies three predictive constraints: (1) the interference level, which arises from residual memory for old goals; (1) the strengthening constraint, which makes predictions about time to encode a new goal; and (3) the priming constraint, which makes predictions about the role of cues in retrieving pending goals. These constraints are formulated algebraically and tested through simulation of latency and error data from the Tower of Hanoi, a means-ends puzzle that depends heavily on suspension and resumption of goals. Implications of the model for understanding intention superiority, postcompletion error, and effects of task interruption are discussed.

Abstract not found

. Most learning systems and electronic textbooks accessible via the WWW up to now lack the capabilities of individualized help and adapted learning support that are the emergent features of on-site intelligent tutoring systems. This paper discusses the problems of developing interactive and adaptive learning systems on the WWW. We introduce ELM-ART II, an intelligent interactive textbook to support learning programming in LISP. ELM-ART II demonstrates how interactivity and adaptivity can be implemented in WWW-based tutoring systems. The knowledge-based component of the system uses a combination of an overlay model and an episodic user model. It also supports adaptive navigation as individualized diagnosis and help on problem solving tasks. Adaptive navigation support is achieved by annotating links. Additionally, the system selects the next best step in the curriculum on demand. Results of an empirical study show different effects of these techniques on different types of users during ...

Information foraging theory is an approach to understanding how strategies and technologies for information seeking, gathering, and consumption are adapted to the flux of information in the environment. The theory assumes that people, when possible, will modify their strategies or the structure of the environment to maximize their rate of gaining valuable information. The theory is developed by (a) adaptation (rational) analysis of information foraging problems and (b) a detailed process model (adaptive control of thought in information foraging [ACT-IF]). The adaptation analysis develops (a) information patch models, which deal with time allocation and information filtering and enrichment activities in environments in which information is encountered in clusters; (b) information scent models, which address the identification of information value from proximal cues; and (c) information diet models, which address decisions about the selection and pursuit of information items. ACT-IF is instantiated as a production system model of people interacting with complex information technology. Humans actively seek, gather, share, and consume information to a degree unapproached by other organisms. Ours might properly be characterized as a species of informavores (Dennett, 1991). Our adaptive success depends to a large extent on a vast and complex