A Distributed Adaptive Learning Environment
Qiangguo Pu2, Harris Wang1, Oscar Lin1, Nikos Mastorakis3
CCIS, Athabasca University, 1 University Drive, Athabasca AB T9S 3A3, Canada
2
Computer Center, University of Science and Technology of Suzhou
298 Binhe Road, Suzhou, Jiangsu 215011, China
3
Hellenic Naval Academy, Terma Hatzikyriakou, 18539 Piraeus, Greece
Also: WSEAS, Ag.I.Theologou 17-23, 15773, Zografou, Athens, Greece
mastor@wseas.com
1
Abstract: - The World Wide Web is evolving into a virtual environment where people work, shop, play, and learn.
The early WWW learning systems were generic and aimed at a general class of student. DALE (Distributed Adaptive
Learning Environment) is an evolving learner-centered system for learning and teaching computer science at a distance.
Older generations of electronic learning systems have a central server with thin clients for computer-mediated
communications. DALE adds much more functionality. DALE is a large-scale Internet-based distributed information
management system with the many merits of distributed systems. DALE includes not only a central server for
cooperative systems but also peer-to-peer server components and local modules similar to the emerging 3 D gaming
environments for processing simulations/multimedia. Furthermore, DALE integrates agents and learning objects in the
context of a distributed system. This paper covers the design and implementation of many aspects of DALE.
Keywords: - Distance Education, Computer Science Education, Distributed Adaptive Learning Environments, Learner
Centred
1. Introduction
The opportunity for life long learning is a prerequisite
for modern society. Information technology supports the
creation of
stimulating and complete learning
experiences occurring at the time and place of the
learner’s convenience. Athabasca University
(AU)
believes that due to the World Wide accessibility,
storage capabilities, and its relatively easy to use
standard ways of
multimedia publishing one of its
potential greatest uses is as an interactive learning
environment (Holt, Gismondi, Fontaine, and Ramsden,
1995). The goal of AU (http://www.athabascau.ca) is to
provide lifelong open learning (Race, 19942) by reducing
barriers to education. Generally, students can take the
courses at the time and place of their convenience. AU
serves about 25,000 students a year. Most of the students
are part-time. AU offers about 420 undergraduate
courses and 25 undergraduate degrees. The University
also has five graduate degrees and serves about 1,500
graduate students annually. Most of the Masters courses
are paced with fixed start-dates, but most undergraduate
courses can be entered at any time in the year, and
students have six months at their own pace to complete
all the assignments and the final examination.
The Centre for Computing and Information Systems
(CCIS) (http://ccism.pc.athabascau.ca) at AU offers four
undergraduate credentials and an MSc IS shaped
primarily by ACM curricula, professional requirements,
and student needs.. Most of the 1600 undergraduate
students are part-time, generating about 2400 course
registrations per year. It is anticipated that in two years
the Masters in IS will have about 150 students per year
generating about 450 course registrations per year. CCIS
has been leading AU in developing an online learning
system. In the past, the separation by space and time of
the AU students diminished the effectiveness of distance
education approaches. Informal peer support and group
work efforts were particularly restricted, with students
often feeling lost in their attempts to deal with new
endeavors in isolation. Now computer technology
provides a new and innovative approach to open
learning. E-mail, computer based conferencing,
structured hypertext and the virtual reality technologies
change the nature and enhance the quality of distance
education (Pea, 19933). Starting in 1995 (Holt et al,
19954), CCIS has implemented 24 undergraduate and a
number of graduate courses for World Wide Web
(WWW) delivery. Students at home and work are
supported with e-mail, chat, and computer conferencing.
Led by CCIS other centers of AU have become
increasingly reliant on electronic delivery. Our goal is to
develop an integrated system for course development
and delivery. Before describing that endeavor how we
will describe some underlying concepts and technologies
of our endeavor.
Experiential thought is easily integrated into computer
based learning systems. Students are continually
interacting with the computer and with one another
through the computer. But reflective thought is more
2. Technologies and Concepts Underlying
difficult concept to tie directly to the computer based
Design, Delivery, and Evaluation
learning system. Reflective thought in our curriculum
occurs in analysis and design and generating of
algorithms. It is nurtured by interaction with students and
Learner-Centred Design
tutors and by access to appropriate computer based tools.
Students who grew up with Internet gaming expect
In our system design we define coordinator
sophisticated use of graphics and multimedia to
requirements,
tutor
requirements
and
learner
supplement their courses. We have begun adding Java
requirements. In this paper we focus on the learner.
applet and animated simulations for explication of
Curriculum and course design in CCIS is learnerdifficult material --particularly data communications,
5
centered (Norman and Spohrer, 1996 ). Thus a key
computer networks, and distributed systems. A balance
feature of the requirements definition are the needs of the
between multimedia and electronic text is required.
learner (Holt et al 20017) which we abstract from our
Multimedia material places a burden on resources must
experience with focus groups, case studies from fieldbe limited within current Internet bandwidth and
testing, some questionnaire evaluations, anecdotal
personal computers owned by average students.
reports, and
the literature. The systems should be
designed to optimize the use of the learner’s time not the
Learning Objects
convenience of the institution or instructor. Learners
must be involved in the conceptualization, design,
Our long-term goal is to create a body of electronic
development, implementation and evaluation of the
instructional support tools, curriculum content, and
environment. In the design of our system we begin with
design strategies from which, on the basis of learner
the assumption that the learning environment should
needs, we can select materials for a particular course or
belong to the learner and as much as possible be under
module (Holt, 199814). According to the Sharable
the learner's control. Users learn quickly and gain a fast
sense of mastery when they are placed ‘in charge.’ The
Content Object Reference Model (SCORM, 200015) a
learning environment should be open to exploration but
learning object is modeled as the smallest stand-alone
must have some constraints or it is likely the learner will
and meaningful component of a course that is
not feel comfortable. It is important to optimize the
interoperable, modular, and discoverable. We have
learner’s privacy and security. If users control their own
modified that description slightly to allow a hierarchy of
information, privacy will be enhanced. As much as
learning objects with any dependencies amongst objects
possible, learners’ data should reside on their own
specified. The highest-level learning object is the course
machine. In other cases it should be behind proper
itself. Our design uses the eXtensibe Markup Language
firewall and guarded with other security features. All
(XML) to define our learning. The IMS project is
materials originating on the institutional server must be
developing standards for content packaging so that
virus free. Institutions should provide consultation on
learning objects can be easily shared. The metadata
privacy and security issues. An assumption of our
describes and specifies the use of learning objects.
approach is that learning environments can be
Different XML schema may define what is a valid
challenging but still provide a relatively low stress
learning object structure at different levels of our course
psychological experience for the user. Psychological and
hierarchy. Much research on defining, constructing, and
social concerns generated by a stressful technological
building and displaying learning objects has been
environment can be inimical to the learning process.
conducted over the past few years. The CAREO project
defines learning objects to include "simulations, tutorials,
The learning environment should optimize the various
drill and practice modules, content databases, multiapproaches to learning available to the learner such as
media exercises" (Downes, 200016). There remains
apprenticeship learning (Collins, Brown, and Newman
much work on development of an ontology for subject
19898), guided discovery (Holt et al, 19959), peer
domains, an ontology for instructional design, definitions
10
of the granularity of learning objects, methods for
tutoring (Greer et al, 1998 ), situated learning (Brown,
11
combining learning objects into courses, and several
Collins, and Duguid, 1990 ), case-based learning and
other issues.
12
collaborative learning (Harasim, 1993 ). These can
often be accommodated by instructional design although
Distributed Adaptive Learning Environments
particular approaches can be facilitated by software (e.g.
peer tutoring Greer et al, 199813) and some require some
We define the learning environment as consisting of all
special capabilities (e.g. computer conferencing).
the interaction with materials, the tools, the interactions
with peers, and the interaction with tutors, access to
other materials, and even the approaches to learning
available. In a distributed learning environment the
various resources are geographically distributed but
connected by information technology. The World Wide
Web offers the most successful model of a distributed
learning environment. Originally web based learning
was restricted to basic to text and images presented
through HTML. With the rapid increment of bandwidth
available on the web these have been supplemented with
audio, video, animations, and simulation. The web has
become a virtual environment – a place where people
work, play, shop, and learn
A basic premise of the CCIS distributed learning
environment is that our learners are best served by an
underlying distributed architecture with much of the
processing occurring on the learner’s computer.
Advanced Internet gaming activities are based on such a
distributed model. There are services that must be
offered centrally but many functions are best performed
locally (URL re desktop). A local component best
provides an environment supporting learner autonomy,
empowerment, and privacy. Learners can provide
services to other learners in a peer-to-peer network ala
Napster (www.napster.com).
A distributed learning
environment facilitates a learner-centered educational
paradigm and promotes active learning. Our model of
web-based distributed learning focuses on a model of
guided self-discovery in which learners engage in
learning activities at the time and place of their
convenience. However, where it best fits the learners’
needs we also use the technology a more traditional
“paced” approach where the learners are part of a cohort
group with a fixed schedule for all assignments etcetera.
We also used hybrid models that fall between these two
models.
The term adaptive learning environment refers to
technology that will adapt the environment in various
ways.
First, CCIS wants its content to be reusable
across various modules and courses. XML combined
with international standards such as IMS (see
www.imsproject.org) provides a standard way of storing
learning objects making them available for use in a
variety of ways. Second, content must be able to be
delivered across different platforms. XML, XSLT, and
related Java technologies provide the means
for
transforming material for presentation on various devices
such as desktop computers and wireless handheld
devices.
Third, CCIS wants the content to be
dynamically adaptable to the needs of particular learners.
Intelligent software agents (Lin and Holt, 200117)
provide the key intelligence for a wide range of
adaptations. Finally, standards such as IMS and a variety
of tools help make material adaptable to the needs of the
authors, instructors, and the educational institutions.
Agent Based Systems
The agent-based computing paradigm is particularly
suitable for developing the web-based distributed
adaptive learning environments (Lin and Holt, 200118).
A software agent is a higher-level system component,
defined around a particular function, or utility, or role in
the overall system and it is more autonomous than a
simple object. The autonomous nature of software agents
makes them ideal for implementing a distributed learning
environment. Intelligent agents make the environment
adaptable. There has been considerable exploration of
agent technology applications for education
for
example: multi-agent approach to the design of peer-help
environment (Vasileva et al, 199919); agents for
information retrieval (Hiltz and Wellman, 199720);
agents for student information processing, distribution,
and feedback collection (Huhns and Mohamed, 199921);
pedagogical agents (Johnson and Shaw, 199722);
teaching agents (Selker, 199423); tutoring agents
(Solomos and Avouris, 199724); agents for assignment
checking (McCollum, 199725); agents for student group
online support (Whatley et al, 199926). An empirical
study evaluating the effectiveness of intelligent agents in
online instruction has suggested that the application of
agent technology to online learning hold promise for
improving completion rates, learner satisfaction, and
motivation (Thaiupathump, 199927)
From the Web-based educational experience, we know that
the students need to
 download course materials
 get dynamic updates to downloaded materials
 connect to obtain and interact with central dynamic
materials
 serve materials to other students/tutors
 submit assignment to tutors
 ask tutors for course-related questions
 interact with other students
 have optimal control over their own
information/tools etc
Tutors’ tasks are
 answering questions from their students;
 knowing student profiles, especially those that need
contacting;
 checking students’ assignment;
 contacting other course tutors to answer students’
questions sometimes.
The primary teaching tasks of professors are to
 develop and update course materials
 serve as course coordinators
 contact to know students’ performance and
feedback about the courses

understand student’s profiles taking their courses
some course-related agents. The system includes four
course-related agent classes: content agent class,
collaboration agent class, tutoring agent class, and
evaluation agent class. For instance, a content agent has a
goal that is to keep the course content updated and fit best to
the students. It realizes its goal by continuously monitoring
the links for the course and notifying the students taking this
course when the links have updated or changed. More
importantly, the content agent is able to proactively and
adaptively generate the content structure for the student
according to the knowledge structure of the course and
students' performance. It accomplishes this task by
collaborating with a curriculum management agent that is a
server agent and is responsible for determining the
knowledge structure of a course.
Tutor agents: Tutor agents are responsible for helping
tutors to provide on-line tutoring to students. Their role is to
interact with student agents to receive and answer students’
questions, to do some marking work, and to contact
professor agents and other tutor agents within the
collaborative learning environments. The tutor agents can
further monitor student’s interactions6.
Professor agents: Professor agents’ role is helping
human professors do course coordination, offer course
materials by creating and maintaining course material
databases, make examination papers, and offer solutions to
exercises of courses. A professor agent may need to inquire
into students’ learning performance from tutor agents and
profiles from students profile database to design adaptive
learning materials.
From system point of view, the requirements for the
architecture are:
 Distributed: In fact, the Internet is the largest
distributed systems. Distributed systems use
multiple computers to solve a problem and provide
a common, consistent global view of the database
system, name space, time, and security, and access
to resource. This can be done to increase
performance, improve reliability and scalability, or
support multiple geographical locations. For
instance, to ensure system scalability, in our
Figure 1: User case diagrams for distributed learning
infrastructure we deploy a set of special agent
environment
servers rather than a single one. These servers
identify agents that provide services that are the
Therefore, we have three types of agents: student agents,
same as or similar to a requested service.
tutor agents, and professor agents. These agents’ roles are
 Mobile agents-based: Multi-agent systems are
described as follows:
subject to performance bottleneck in cases where
agents cannot perform tasks by themselves due to
Student agents: Student agents can be hosted by central
insufficient resources. A mobile agent approach is
site for more complex updates. Each student taking an
much less susceptible to nagging client/server
online course will have an interface agent that actually is a
network bandwidth problem, network traffic,
collection of more or less independent smaller agents, each
transaction volume, number of clients and servers,
having an associated visual presence, downloading initially
and many other factors. Furthermore, the
from the server, operating in the background, watching
downloading of aspects of our course materials
progress, measuring it against the plan, and taking remedial
gives us a great environment for testing distributed
actions when necessary. These smaller agents are typically

agents and mobile agents. We enhance the existing
course materials download system with mobile
agent-based course material disseminators. These
mobile agents embody the so-called "Internet push
model". They can disseminate information such as
news and automatic course material updates for
course instructors. The agents can carry the new
materials as well as installation procedures directly
to the students’ personal computers. These agents
can manage material on the computer creating
personalized learning materials.
Incorporation of Legacy-Systems: For those
components in use, our strategy is to incorporate
them as far as possible by giving them wrappers.
Incorporating these components into different
agents’ structures and integrating them with new
developed components would make our system
more cost-effective. Each student agent has
currently incorporated a course material manager, a
VHD, a WWW Conferencing system, an E-mail
system, and a white board. Each tutor agent has
been equipped with a VHD, a WWW conferencing
system, a white board, and a TRIX, and Course
material manager. Each professor agent uses a
WWW conferencing, an E-mail, a white board, a
TRIX, and a course material manager.
3. An Integrated Architecture for a
Distributed
Adaptive
Learning
Environment
CCIS academics have focused much of their research our
Distributed Adaptive Learning Environment (DALE)
project. The DALE project explores the issues in
creating a learner-centered platform for electronic
distance learning, particular for a computer and
information systems programme. The DALE project is
based on a distributed processing architecture to take full
advantage of the powerful student client computer
(Gelernter, 200028) and investigate the potential of peer
to
peer
computing
(Oram,
200129).
Course development system
Course
Server
Course delivery system
Figure 2: The whole picture - course authoring, course delivery and course server
It is important that there be an overall
integrating
architecture for organizing the various functions and the
associated technology (see Figure 2). It must be capable
providing a stimulating, interactive informative
environment for situated learning, peer-to-peer
collaboration, and communicating with tutors (DALE
Research Team, 200231). It should support tutors
facilitating student learning and support professors in
designing, creating, and delivering their course materials.
The development and delivery systems are both critical
and enhances the functionality of both systems. For
example, feedback from the delivery informs timely
revision of course materials. However, this paper focuses
on the delivery system and the student-learning
environment.
Course Server
As can be seen from Figure 1, the course server plays
some important roles in the whole integrated system. On
the development side we anticipate agent technology will
be use to implement courses comprised of learning
objects (Lin, Holt, Korba, and Shih, 200132). To enable
computer agents to automatically and dynamically
compose personalized course materials for an individual
learner, we need some effective knowledge management
mechanisms and to include instructional design
information in the metadata. Presumably learning objects
may include their own agents and our system agents
would have to negotiate with these “foreign agents. For
delivery it must be able to store a variety of learning
objects consisting of text, image, graphs, audio and video
clips, and use them for composing courses. The course
server serves both general web browsing clients such as
Netscape and Internet Explorer, and our specialized
system. The server has a JASIG u-portal (http://www.jasig.org/), which will include standard channels for online
testing, external links, agent enhanced conferencing,
agent dispatch, and student white pages (and yellow
pages) for peer-to-peer networking. An agent maintains
the link database removing broken links and notifying
students’ agents of links of particular interest to their
owner. Some of these services will be presented in the
browser; some may interact directly with agents on the
student’s computer. Some special attention must be paid
to course server support for data encryption, user
authentication and some more complex security
operations, as well as support for the implementation and
deployment of intelligent mobile agents within the
system.
A course delivery module on the server is designed to
link course servers to course clients running on student’s
computers. This module plays four important roles. The
first role is to generate individualized course contents for
each individual student based on the course material and
students' information in the student database. Some
course materials such as assignments, external links and
other dynamic course material may be kept on the central
course server. The second role is to serve the centrally
delivered materials. Other materials are downloaded to
ICSSL. The third role is to deliver the individualized
course materials to the students. The fourth role is to
manage the updating of downloaded materials). To
reduce dependence on a live connection and enhance
mobility the bulk of the course materials are distributed
to the student’s machine along with a student-learning
module (SLM). A special mobile agent initially resides
at the educational institution free the institution. It
watches for connections from students. When there has
been an update of the course materials since that last
connection from a student it then makes a copy of itself,
and travels to the student's computer with updating files
specific for the identified student. It frees the learner
from paying attention to and spending time on updating
and maintaining course materials.
Distributed Sub-systems
There are three distributed sub-systems: the sub-system
for course coordinators (SCC), the sub-system for course
tutors (SCT), and the sub-system for student learning
(SSL). These systems share some modules such as the
course messaging module, the course conferencing
module, and the shared workspace module. Then the
SCC has a module to help coordinators make decisions
on student’s evaluation and other academic-related
matters involved in student management. The SCT has a
module to help manage the duties of answering student
questions in a timely fashion and demonstrating course
contents to students. It includes a scheduler built in to
help tutors to schedule their work. Much of the rest of
this paper will deal with exploring the SSL as it is a
relatively new and original concept for web-based
learning environments.
The SSL (see Figure 3) consists of the learning
management module, the course-messaging module, the
course conferencing module, and the shared workspace
module. The learning management module is designed to
help students download and digest course materials, and
access external documents. Standards-based educational
material can be processed in a variety of ways according
to educational features and passed to an appropriate
viewer (for instance the XML enabled mozzilla
embeddable browser, a multimedia viewer, or a
simulations player). The browser will support shared
browsing of course materials between two or more
students (or a tutor and one or more students). There are
many multimedia-viewing programs but they do not
include many of the functions useful for learning such as
tools for testing the recognition of specific situations in a
video clip. This module includes an interface to the many
tools a learner might use for his course. Finally, since it
supports many functions at a local level, ISSL allows
mobile users to accomplish their learning on the move.
With the course messaging module students can
communicate with course coordinators and tutors and
submit their assignments directly without having to
switch to other mail readers. Instant messaging, chat,
audiochat, and video chat will be optional sub-modules
of this module. The course conferencing module
provides a
posting management system for course
conferencing. Finally the workspace-sharing module
allows students to share files during collaborative work.
Overall the SSL will be an ideal learning environment
for collaborative work and will support professional
practices such as extreme programming.
Student
Data
Course
Database
Tutor
Data
Central
Conference
Data
Course
Server
Course
Messaging
Module
Email
Data
Shared
Files
Workspace
Module
Learning
Management
Module
Downloaded
Course Data
Learning
activity data
Course
Conference
Module
Cached
Conference
Data
Course
Presentation
Module
Figure 3: Sub-System for Student Learning (SSL)
appropriate research focus for a computer science
Lin and Holt, 200133, have outlined how distributed
program at a distance education university. However, it
intelligent agents can be incorporated to enhance the
is clear that neither a single department nor even a single
functionality of DALE
student profiles (for student
university will be able to develop, implement, and
modeling) and access to course materials. Student agents
support a complete open learning environment. The other
reside primarily on the student client after being
options are commercial proprietary closed systems,
dispatched from an agent archive on the server.
proprietary open source systems, or open source systems
Functions supported by agents include collaborating with
developed by formal and informal collaborations of
other students, generating self-tests of random items,
educational institutions and government. Hence, CCIS is
tailoring course material to student profile, managing
involved in or is tracking a number of open source and
course material presentation, managing external links
related collaborative endeavors: JA-SIG (http://www.ja(reporting new links to of interest to the students). There
sig.org/) is an independent organization whose mission is
is no reason to restrict connections to a single institution.
to enhance the flow of information among educational
Learner’s agents could reside on the learner platform
institutions and companies involved in the development
interacting with a variety of institutions and peers from
of administrative applications using Java technology.
those institutions. Some agents may be mobile and visit
The JA-SIG uPortal is a free, sharable portal for posta variety of hosting institutions looking for particular
secondary institutions. It is an open-standard effort
courses, information, or peer support.
using Java, XML, JSP and J2EE and a collaborative
development project. The Open Knowledge Initiative
4. Implementation Strategies
(http://web.mit.edu/oki/) led by the Massachusetts
Institute of Technology and Stanford University is
CCIS uses open source and free software following open
developing open source software for e-learning. The
systems standards so we are not locked into a particular
software is an alternative for institutions that want to
vendor's solution. This approach providea e-learning
provide online courses but do not want to invest in
environments that are not under the control of
commercial course management systems. The mozilla
commercial interests. Also it provides CCIS with an
project (http://www.mozilla.org/) is developing an
embeddable xml-enable browser that can be embedded
with
a
Java
application
(http://www.mozilla.org/projects/blackwood/webclient/)
as part the learner’s platform in a distributed learning
environment.
SUN supported Project JXTA
(http://www.jxta.org/) is an open source effort aimed at
providing “an open, generalized protocol that
interoperates with any peer on the network including
PCs, servers and other connected devices” to facilitate
the development of distributed applications. GNOME
(http://www.gnome.org/) is an open source desktop
environment for Linux..
With the emergence of XML with DTD's and schemas,
X-Path, X-link, XML objects (DOM) and XSL, tools are
emerging for building inheritance hierarchies for all
curriculum objects that can be easily manipulated by
Java. JMF allows us to easily integrate and manipulate
multimedia. For foreseeable future we will continue to
build on XML, Java, and Java related tools For example
for agent communications we will use the
Java
Reflection
Broker
(JRB:
http://andromeda.cselt.it/users/g/grasso/free.htm) which
deploys a dynamic invocation model similar to the
dynamic invocation interface in the Common Object
Request Broker Architecture ( CORBA). We use a
KQML-like message protocol and the Java Bean event
model to provide the communication mechanism
between agents and the facilitator and define our own
event objects to handle the message content. We are
considering
using
SOAP
(http://www.w3.org/TR/SOAP/) for XML document
exchange. We add security using the Java Security API,
including user authentication and data encryption. Our
peer-to-peer technology will be based on JXTA
(http://www.jxta.org).
5. Evaluation
"Situated research" is a very important concept for us.
The WEB provides a means for other researchers to
immediately experience students’ educational experience
as the student does. Further, the students become a direct
part of the research and development. We want to
understand the experience of learners and the context in
which learning occurs. Thus along with traditional
quantitative methods for informative evaluation we use
"illuminative evaluation" (Partlett and Hamilton, 1972).
References

Holt, P., Fontaine, C., Gismondi, J. and Ramsden, D.
(1995) Collaborative Learning Using Guided Discovery
on the INTERNET. ICCE95. Singapore.
2
Race, Phil. (1994) The Open Learning Handbook. NJ:
Nichols Publishing Company Review of Design,
Teaching, and Institutional Issues. PA: ACSDE.
3
Pea, R. (1993) Seeing what we build together:
Distributed multimedia learning environments for
transformative communications. The Journal of the
Learning Sciences, 3 , 3, 285-299.
4
Holt, P., Fontaine, C., Gismondi, J. and Ramsden, D.
(1995) Collaborative Learning Using Guided Discovery
on the INTERNET. ICCE95. Singapore.
5
Norman, Donald A. & Spohrer (1996). LearnerCentered Education. Communications of the ACM, 39, 4,
24-27. Oram, A. (Ed.) ( 2001) Peer-to-Peer Harnessing
the Power of Disruptive Technologies, O’Reilly
Sebastapol CA
6
Shih, T. K., Chang, S. K., Wang, C. S., Ma, J., Huang,
R. An Adaptive Tutoring Machine Based on Web
Learning Assessment. In: Proceedings of the IEEE Inter.
Conf. on Multimedia and Expo 2000, New York City,
USA, July 31 – August 2, 2000.
7
Holt, O. Lin, F., Stauffer, K., Jelica, G., Shih, T.
(2001). An Infrastructure for Developing Agents for
Distance Education on the Internet, Journal of
Computers, special issue on Distance Learning, May
2001 (in press)
8
Collins, A., Brown, J.S. and Newman, S. (1990).
Cognitive apprenticeship: Teaching the craft of reading,
writing, and mathematics, in L. B. Resnick (Ed.),
Knowing, Learning, and Instruction: Essays in the
Honour of Robert Glaser. Hillsdale, N.J.: Erlbaum.
9
Holt, P., Fontaine, C., Gismondi, J. and Ramsden, D.
(1995) Collaborative Learning Using Guided Discovery
on the INTERNET. ICCE95. Singapore.
10
Vassileva, J.I., Greer, J.E., McCalla, G.I., Cooke, J.E.,
Collins, J., Kumar, V.S., and Bishop, A. (1998) The
Intelligent Helpdesk: Supporting Peer-Help in a
University Course, International Intelligent Tutoring
Systems Conference (ITS'98), San Antonio, August 1998
(pp. 494-505).
11
Brown, J. & Collins, A. & Duguid, P. (1989)
Situated Cognition and the Culture of Learning.
Educational Researcher, 18, 4, 10-12.
12
Harasim, L. (1993) Collaborating in cyberspace:
Using computer conferences as a group learning
environment. Interactive Learning Environments, 3, 2,
119-130.
13
Vassileva, J.I., Greer, J.E., McCalla, G.I., Cooke, J.E.,
Collins, J., Kumar, V.S., and Bishop, A. (1998) The
Intelligent Helpdesk: Supporting Peer-Help in a
University Course, International Intelligent Tutoring
Systems Conference (ITS'98), San Antonio, August 1998
(pp. 494-505).
14
Holt, P. (1998) Waiting for Godot. Principles
Underlying an Interim Distance Education System
for World Wide Web Delivery. ICCE 98, Beijing,
China.
15
SCORM “Advanced Distributed Learning Initiative.
Sharable Courseware Object Reference Model
(SCORM)” Version 1.0. January 31, 2000.
16
Downes, S. (2000) Exploring New Directions
in Online Learning,
17
Lin, F., Holt, P. (2001a) Towards Agent-based
Online Learning, CATE'2001, Banff, Canada.
18
Lin, F., Holt, P. (2001a) Towards Agent-based
Online Learning, CATE'2001, Banff, Canada.
19
Vassileva, J.I., Greer, J.E., McCalla, G.I., Cooke, J.E.,
Collins, J., Kumar, V.S., and Bishop, A. (1998) The
Intelligent Helpdesk: Supporting Peer-Help in a
University Course, International Intelligent Tutoring
Systems Conference (ITS'98), San Antonio, August 1998
(pp. 494-505).
20
Hiltz, S. R. and Wellman, B. (1997). Asynchronous
learning networks as a virtual classroom.
Communications of the ACM, Vol. 40, N. 9, pp. 44-49.
21
Huhns, M., A. Mohamed. (1999). "Benevolent
Agents", IEEE Internet Computing, Vol.3, No.2, pp.9698
22
Johnson., W. L. and Shaw, E. (1997). Using Agents
to Overcome Deficiencies in Web-Based Courseware,
AI-ED'97.
23
Selker, T., Coach: A Teaching Agent that Learns,
Communications of ACM, 37(7), 1994.
24
Solomos, K. and Avouris, N. (1999). Learning from
Multiple Collaborating Intelligent Tutors: An Agentbased Approach, J. of Interactive Learning Research,
10(3/4), 243-262
25
McCollum, K. (1998). How a Computer
Program Learns to Grade Essays, The Chronicle
of Higher Education, September 4, 1998.
26
Whatley, J.G, Staniford, Beer, G. M. and Scown,
P. (1999). Intelligent Agents to Support Students
Working in Group Online, Journal . of Interactive
Learning Research, 10(3/4), 361-373
27
Thaiupathump, C., J. Bourne, J. and Campbell, J.
(1999) Intelligent Agents for Online Learning, JALN
Volume 3, Issue 2 - November 1999.
http://www.aln.org/alnweb/journal/Vol3_issue2/Choon2.
htm
28
Gelernter, D. (2000) The second coming a
manifesto. Edge, 70, June 15. URL
http://www.edge.org/documents/archive/edge70.ht
ml
29
Oram, A. (Ed.) ( 2001) Peer-to-Peer
Harnessing the Power of Disruptive Technologies,
O’Reilly Sebastapol CA
30
Partlett and Hamilton (1972). Evaluation as
Illumination: a new approach to the study of Innovatory
Programs, Centre for Research in the Educational
Sciences, University of Edinburgh, Occasional Paper - 9,
Edinburgh 1972
31
DALE Research Team. (2002) The Design of an
Integrated System for Web-based Distance Education,
CCIS Report in preparation.
32
Lin, F., Holt, P., Korba, L. and Shih, T.
(2001). A Framework for Developing Online
Learning Systems, DMS'2001, Taipei, Tiawan.
33
Lin, F., Holt, P. (2001a) Towards Agent-based Online
Learning, CATE'2001, Banff, Canada.