| ADAPT: A Predictive Cognitive Model of User Visual Attention and Action Planning | | BIBAK | Full-Text | 1-45 | |
| Stephanie M. Doane; Young Woo Sohn | |||
| We present a computational cognitive model of novice and expert aviation
pilot action planning called ADAPT that models performance in a dynamically
changing simulated flight environment. We perform rigorous tests of ADAPT's
predictive validity by comparing the performance of individual human pilots to
that of their respective models. Individual pilots were asked to execute a
series of flight maneuvers using a flight simulator, and their eye fixations
and control movements were recorded in a time-synched database. Computational
models of each of the 25 individual pilots were constructed, and the individual
models simulated execution of the same flight maneuvers performed by the human
pilots. The time-synched eye fixations and control movements of individual
pilots and their respective models were compared, and rigorous tests of ADAPT's
predictive validity were performed. The model explains and predicts a
significant portion of pilot visual attention and control movements during
flight as a function of piloting expertise. Implications for adaptive training
systems are discussed. Keywords: cognitive models; action planning; modeling expertise; hybrid models | |||
| The Evaluation of a Personalised Health Information System for Patients with Cancer | | BIBAK | Full-Text | 47-72 | |
| Alison J. Cawsey; Ray B. Jones; Janne Pearson | |||
| In this paper we describe the evaluation of a personalised information
system for patients with cancer. Our system dynamically generates hypertext
pages that explain treatments, diseases, measurements etc related to the
patient's condition, using information in the patient's medical record as the
basis for the tailoring. We describe results of a controlled trial comparing
this system with a nonpersonalised one. The results of the trial slow
significant results concerning the patients' preferences for personalised
information. We discuss the implications of our evaluation and results for the
development and evaluation of future personalised systems, and adaptive
hypertext systems in particular. Keywords: empirical evaluation; tailored explanations; healthcare; dynamic hypertext;
information systems; language generation | |||
| Mark Maybury (Author), Intelligent Multimedia Information Retrieval | | BIB | Full-Text | 73-75 | |
| Fiorella de Rosis | |||
| Preface | | BIB | Full-Text | 77-80 | |
| Sandra Carberry | |||
| Modeling Student Knowledge: Cognitive Tutors in High School and College | | BIBAK | Full-Text | 81-108 | |
| Albert Corbett; Megan McLaughlin | |||
| This paper examines the role of adaptive student modeling in cognitive tutor
research and dissemination. Cognitive tutorsTM are problem solving environments
constructed around cognitive models of the knowledge students are acquiring.
Over the past decade we in the Pittsburgh Advanced Cognitive Tutor (PACT)
Center at Carnegie Mellon have been employing a cognitive programming tutor in
university-based teaching and research, while simultaneously developing
cognitive mathematics tutors that are currently in use in about 150 schools in
14 states. This paper examines adaptive student modeling issues in these two
contexts. We examine the role of student modeling in making the transition from
the research lab to widespread classroom use, describe our university-based
efforts to empirically validate student modeling in the ACT Programming Tutor,
and conclude with a description of the key role that student modeling plays in
formative evaluations of the Cognitive Algebra II Tutor. Keywords: student modeling; adaptivity; intelligent tutoring systems; mastery
learning; empirical validation | |||
| Minimalist User Modelling in a Complex Commercial Software System | | BIBAK | Full-Text | 109-146 | |
| Linda Strachan; John Anderson; Murray Sneesby | |||
| While user modelling has produced many research-based systems, comparatively
little progress has been made in the development of user modelling components
for commercial software systems. The development of minimalist user modelling
components which are simplified to provide "just enough" assistance to a user
through a pragmatic adaptive user interface is seen by many as an important
step toward this goal. This paper describes the development, implementation,
and evaluation of a minimalist user modelling component for the Tax and
Investment Management Strategizer (TIMS), a complex commercial software system
for financial management. This user modelling component manages several levels
of adaptations designed to assist novice users in dealing with the complexity
of this software package. Important issues and considerations for the
development of user modelling components for commercial software systems and
the evaluation of such systems in commercial settings are also discussed. Keywords: pragmatic user modeling; knowledge-based systems; empirical evaluation;
commercial software systems; financial planning | |||
| User Modeling for Adaptive News Access | | BIBAK | Full-Text | 147-180 | |
| Daniel Billsus; Michael J. Pazzani | |||
| We present a framework for adaptive news access, based on machine learning
techniques specifically designed for this task. First, we focus on the system's
general functionality and system architecture. We then describe the interface
and design of two deployed news agents that are part of the described
architecture. While the first agent provides personalized news through a
web-based interface, the second system is geared towards wireless information
devices such as PDAs (personal digital assistants) and cell phones. Based on
implicit and explicit user feedback, our agents use a machine learning
algorithm to induce individual user models. Motivated by general shortcomings
of other user modeling systems for Information Retrieval applications, as well
as the specific requirements of news classification, we propose the induction
of hybrid user models that consist of separate models for short-term and
long-term interests. Furthermore, we illustrate how the described algorithm can
be used to address an important issue that has thus far received little
attention in the Information Retrieval community: a user's information need
changes as a direct result of interaction with information. We empirically
evaluate the system's performance based on data collected from regular system
users. The goal of the evaluation is not only to understand the performance
contributions of the algorithm's individual components, but also to assess the
overall utility of the proposed user modeling techniques from a user
perspective. Our results provide empirical evidence for the utility of the
hybrid user model, and suggest that effective personalization can be achieved
without requiring any extra effort from the user. Keywords: user modeling; machine learning; information retrieval; intelligent agents;
recommender systems | |||
| Recommender Systems for Learning: Building User and Expert Models through Long-Term Observation of Application Use | | BIBAK | Full-Text | 181-208 | |
| Frank Linton; Hans-Peter Schaefer | |||
| Information technology has recently become the medium in which much
professional office work is performed. This change offers an unprecedented
opportunity to observe and record exactly how that work is performed. We
describe our observation and logging processes and present an overview of the
results of our long-term observations of a number of users of one desktop
application. We then present our method of providing individualized instruction
to each user by employing a new kind of user model and a new kind of expert
model. The user model is based on observing the individual's behavior in a
natural environment, while the expert model is based on pooling the knowledge
of numerous individuals. Individualized instructional topics are selected by
comparing an individual's knowledge to the pooled knowledge of her peers. Keywords: agent; cluster analysis; data mining; instructional technology;
instrumentation; knowledge acquisition; learning; logging; long-term
observation; organizational learning; OWL; recommender system; sequence
analysis; student modeling | |||
| A Review and Analysis of Commercial User Modeling Servers for Personalization on the World Wide Web | | BIBAK | Full-Text | 209-249 | |
| Josef Fink; Alfred Kobsa | |||
| The aim of this article is to present and discuss selected commercial user
modeling systems against the background of deployment requirements in
real-world environments. Following the recent trend towards personalization on
the World Wide Web, these systems are mainly aimed at supporting e-commerce
including customer relationship management. In order to guide and structure our
review, we define a requirements catalogue that comprises the main dimensions
of functionality, data acquisition, representation, extensibility and
flexibility, integration of external user-related information, compliance with
standards, concern for privacy, and system architecture. Apart from the novelty
of such a comparison both inside and outside the classical user modeling
literature, a presentation of the core features of these commercial systems may
provide a source of information and inspiration for the design, implementation,
and deployment of future user modeling systems in research and commercial
environments. Keywords: personalization; one-to-one marketing; customer relationship management;
electronic commerce; deployment requirements; commercial user modeling; company
profiles; product reviews; user modeling servers | |||
| Tailoring the Interaction with Users in Web Stores | | BIBAK | Full-Text | 251-303 | |
| Liliana Ardissono; Anna Goy | |||
| We describe the user modeling and personalization techniques adopted in
SETA, a prototype toolkit for the construction of adaptive Web stores which
customize the interaction with users. The Web stores created using SETA suggest
the items best fitting the customers' needs and adapt the layout and the
description of the store catalog to their preferences and expertise. SETA uses
stereotypical information to handle the user models and applies personalization
rules to dynamically generate the hypertextual pages presenting products. The
system adapts the graphical aspect, length and terminology used in the
descriptions to parameters like the user's receptivity, expertise and
interests. Moreover, it maintains a model associated with each person the goods
are selected for; in this way, multiple criteria can be applied for tailoring
the selection of items to the preferences of their beneficiaries. Keywords: adaptive hypermedia; customization of Web stores; electronic shopping;
knowledge-based approaches to the personalization of the interaction;
personalized information presentation; user modeling | |||
| Herbert Clarck, Using Language | | BIB | Full-Text | 305-308 | |
| Sandra Carberry; Leah Schroeder | |||
| Gillian Brown, Speakers, Listeners, and Communication: Explorations in Discourse Analysis | | BIB | Full-Text | 309-313 | |
| Susan McRoy | |||