AN INTELLIGENT AGENT BASED APPROACH TO MOSAICA’S

PEDAGOGICAL FRAMEWORK

Nazaraf Shah, Jawed Siddiqi and Babak Akhgar

Informatics Research Group, Sheffield Hallam University, Sheffield, UK

Keywords: Intelligent Pedagogical Agent, Artificial Intelligence, Virtual Learning, Virtual Expeditions.

Abstract: There has been a significant amount of research in application of intelligent agent technology in virtual

training and pedagogical environments. The characteristics of intelligent agents, such as flexible behaviour,

autonomy and socialablity make them highly suitable candidates to overcome the shortcomings of the

traditional course management systems, online learning and Web resources available to learners. In this

paper we propose an agent based approach to manage virtual expeditions and learning activities in

Semantically Enhanced, Multifaceted, Collaborative Access to Cultural Heritage (MOSAICA) project. We

believe that Belief, Desire, Intention (BDI) model of intelligent agent better serve the pedagogical

requirements identified in MOSAICA project. The cognitive characteristics of MOSAICA pedagogical

framework are easy to map to mental model of BDI intelligent agents.

1 INTRODUCTION

MOSAICA (MOSAICA) is an EU-IST funded

collaborative project being carried out by a

consortium consisting of seven EU countries and

Israel. MOSAICA is envisioned as an advanced web

portal, featuring multifaceted interfaces for

knowledge based exploration and online utilities

empowering users to collaboratively author and

manage cultural resources in a globally distributed

environment.

The purpose of MOSAICA is to design a toolbox

for intelligent presentation, knowledge-based

discovery and interactive and creative educational

experience covering a broad variety of cultural

heritage resources. The initial focus of MOSAICA is

Jewish cultural heritage but the project is potentially

applicable to other cultural heritages.

MOSAICA’s proposed inovations and technical

challenges include Semantic Web technologies,

distributed content management, Geographical

Information Systems (GIS), and pedagogical

framework.

In this paper our focus will be on the

management of technical issues related to

MOSAICA’s pedagogical framework. We propose

an intelligent agent based approach for realisation of

MOSAICA’s pedagogical framework. We believe

that the objectives of pedagogical framework of

MOSAICA can be best achieved by application of

intelligent pedagogical agents.

2 MOSAICA’S PEDAGOGICAL

FRAMEWORK

MOSAICA’s pedagogical framework is based on

well know theory of knowledge known as

constructivism. The constructivist theory applied to

teaching assumes that knowledge cannot simply be

transmitted from teachers to learners: learners must

be engaged in constructing their own knowledge

(Von Glaserfeld, 1987). The focus of constructivism

is on promotion of active and inquiry-based learning

(Bruner, 1990). In constructivist environments the

learners are encouraged to create their own mental

framework and formulate their own conceptual

models to understand the learning material.

Technologies to support constructivist learning

environments require the designing of new platforms

and curricula. Effective integration of technology in

a coherent and authentic way into the curriculum is

not a trivial problem. However, judicious

implementation of educational technology may offer

means to support teaching and learning

[4],[5]

. One

way of doing this is to integrate visualizations and

virtual environments (Dori and Belcher, 2005).

Computerized visualizations and virtual worlds

are used simplify and clarify abstract concepts. The

use of textbooks presents students with two-

dimensional drawings; however, they do not

represent the true spatial nature of things. With the

development of computer graphics technology,

three-dimensional imaging has become a prominent

219

Shah N., Siddiqi J. and Akhgar B. (2007).

AN INTELLIGENT AGENT BASED APPROACH TO MOSAICA’S PEDAGOGICAL FRAMEWORK.

In Proceedings of the Ninth International Conference on Enterprise Information Systems - SAIC, pages 219-224

DOI: 10.5220/0002400902190224

 SciTePress

tool for representing complex structures and real-

world phenomena. Incorporating visualization as

part of the educational process has been found to

foster students' understanding of three-dimensional

structures, spatial ability, and meaningful learning

(Barnea and Bori, 1999), (Bori et al., 2003),

(Donovan and Nakhleh, 2001). In spite of the

prevalent use of visualization and virtual worlds in

the cooperative world, and the recognition of its

educational value, the integration of virtual

environments in school courses is still limited,

mostly because of lack of appropriate technology.

Mental operations elicited by virtual

environments differ from those occurring in

traditional instructional settings that allow learners

to experience physical properties of objects and

events, such as shape, size, distance and time, and

realize the actual implications of such properties.

The virtual pedagogical environments have limited

benefits of cooperation and coordination as

compared to physical learning environments.

The learning experience in both worlds is

essentially different. Real world learning

environments offer myriad opportunities for

observations and interactions. Real world learning

incorporates body and mind experience, including

all five senses. Learners physically walk amongst

the observed objects, touch them (in most cases),

listen to surrounding sounds, sense odours, and

communicate with a guide or fellow learners to

enhance the learning experience.

Transfer of the real world into a virtual

environment is certainly not merely a one-to-one

mapping, but must follow a complex logic of

transformation. Learning in virtual worlds must be

specifically designed for virtual environments. Our

research will address problems of accessibility and

complexity, aiming at developing an educational

framework, and a platform for interactive inquiry

and exploration. We intend to research how to do it

efficiently, but through entertaining exploration.

Within this general research direction, a special

track will be directed toward development of the

methodology and the technology for Virtual

Expeditions. Virtual Expeditions are a specific

educational instrument based on conceptual

modelling, and designed specifically for learning

through exploration of virtual worlds. The Virtual

Expedition methodology must devise a step-by-step

procedural approach to the thematically driven

conceptualisation of cultural resources aiming at

long-term educational impact. Such a methodology

will include:

1. Selection and design of pedagogical themes,

2. Development of educational content,

including: (a) the general site in which the

virtual expedition takes place, (b) the three-

dimensional images learners will encounter,

description, (d) the conceptual relationships

between the images and potential exploration

paths,

3. Implementation of the virtual expeditions,

including short assignments and/or extensive

projects, as well as individual and/or

collaborative learning, and

4. Documentation, including “tutorial” and

“help” buttons, and the instructions for their

use to various purposes and age groups.

Each virtual expedition will be triggered by a

driving question, riddle or problem that needs

solving. The students will be asked to make

assumptions, hypothesize, or problem-solve an

authentic issue that confronts the real world. One of

the objectives is that students respond to problems

that prompt higher-order thinking. Built into the

virtual expedition process are the strategies of

cognitive psychology and constructivism. The

problems posed to students cannot be answered

simply by collecting and retrieving information. In

order to engage students in higher-order thinking,

virtual expedition methodology will use scaffolding

or prompting, that is, breaking tasks into meaningful

“chunks” and steer students through a thinking

process that is used by expert learners.

The Virtual Expedition methodology will offer

two ways for implementing collaborative learning:

(1) by assigning group assignments, and (2) by

utilizing an online forum for informal text-based

discourse. As part of the group assignments, students

take on roles. Each student will focus on a certain

aspects of the large and complex problem and

become an expert in it. By running several Virtual

Expedition groups in the same class, students will

also see different solutions chosen by different

teams.

Thus, Virtual Expedition is an innovative

approach to learning in virtual environments. It

offers a structured way to guide users through

virtuality. Therefore, our methodology will be

designed, developed and researched, so that it could

be followed by other, less expert users to construct

their own Virtual Expeditions.

In addition to the pedagogical research,

technological research is also required, in order to

develop a framework enabling design, recording and

automatic execution of Virtual Expeditions. This

effort must provide an online editing tool

empowering end users with the ability to create and

record their own Virtual Expeditions.

For demonstration purposes, research will develop

few exemplifying Virtual Expeditions. These

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demonstrators will be also used as tutorials and

instructional material to guide end users in designing

their own Virtual Expeditions. MOSAICA's

repository will contain ready-to-use educational

material designed for the educational personnel to

use them in instruction and

teaching, but also for

students and other visitors to use them for individual

studies. A mock up screen shot of a 1

MOSAICA’s virtual expedition is shown in

Figure 1 All navigational interfaces will be tightly

interconnected enabling users to seamlessly move

between them. For example, by selecting a certain

item from the search results, users will be able to

move to the GIS empowered map with related

locations automatically marked on it, or to the

MOSAICA directory displaying the relevant

concepts and their semantic relations, etc.

3 INTELLIGENT AGENT

The definition of an intelligent agent is still subject

of controversy. However, it is generally accepted

that an agent can be viewed as “an encapsulated

computer system that is situated in some

environment and is capable of flexible and

autonomous actions in that environment in order to

meet its design objectives” (Wooldridge, 2000).

Wooldridge and Jennings (Wooldridge and

Jennings, 1995) argue that the term agent can be

used to denote a hardware or (more usually)

software-based computer system that has following

properties:

Autonomy: Agents can operate without the

direct intervention of humans or other agents, and

have control over their individual actions and

internal state.

Social Ability: Agents are able to interact with

other agents (and possibly humans) via an agent

communication language.

Reactivity: Agents perceive their environment,

and should respond in a timely fashion to changes

that occur in it.

Pro-activeness: Agents do not simply act in

response to their environment; rather they are able to

exhibit goal-directed behaviour by taking the

initiative.

Franklin et al. provide a useful taxonomy of the

agents based on agent definitions arising from their

functional characteristics and attributes (Stan and

Graesser, 1996).

Multi-agent systems can be viewed as a

collection of autonomous problem solving entities,

capable of achieving their goals through interaction,

coordination, cooperation and collective intelligence

(Jennings et al., 1998).

An MAS is a system composed of a population

of autonomous agents, which cooperate with each

other to reach common objectives, while

simultaneously each agent pursues individual

objectives " (Jacques, 1999), (Wooldridge, 2000).

Figure 1: A Mock-up Screen Shot of MOSAICA’s Virtual Expedition.

AN INTELLIGENT AGENT BASED APPROACH TO MOSAICA’S PEDAGOGICAL FRAMEWORK

221

4 PROPOSED APPROACH

The original proposal of MOSAICA’s pedagogical

framework does not propose the use of intelligent

agent technology in realisation of the framework. It

leaves the technological issues involved in

realisation of framework for further investigation.

Our past experience of working in intelligent agent

area and a growing number of research efforts

related to application of pedagogical agent in online

learning environment (Blanchard et al., 2006),

(Conati, 2004), (Baylor, 2001) motivate us to

investigate the suitability of agent technology in

realisation of MOSAICA’s pedagogical framework.

Intelligent agent technology provides promising

approaches for modelling high level abstractions and

high level reasoning. We propose the use of BDI

agents in as enabling technology for MOSICA’s

pedagogical framework.

BDI agent model (Rao and Georgeff, 1995) is

one of the most popular approaches towards the

design and development of intelligent agents. The

defining characteristic of this model is that the

generation of agent behaviour is driven by mental

attitudes such as belief desire and intentions. It aims

to be a model that is a functional abstraction of high

level reasoning carried out by human mind.

Our proposed approach makes use of two types

of intelligent agent know as Virtual Expedition

Agent and User Agents are shown in figure 2. These

agents use various software components attachments

in order to support their low level system

functionality.

Abstract descriptions of these agents are given

below.

4.1 User Agent

A User Agent sits between a user and Virtual

Expedition Agent (VEA). It is responsible for

managing user interaction with VEA during a virtual

expedition. It obtains user input and, formulates and

sends an expedition request to VEA. This agent acts

as a tutor/coach for its user and provides proactive

help whenever necessary.

User agent uses two different set of rules for

managing its learning and coaching functionality.

These rules will be realised in the belief component

of user agents. The implementation of rules set as

agent beliefs enables context sensitive reasoning

during presentation of an expedition to user and

coaching service whenever a user needs it.

User Agent has a set plans for carrying out

expeditions and coaching tasks. Each plan in agent’s

plan library is a recipe of actions that it executes in

response to achievement of a specific goal.

Figure 2 depicts User Agent and collaborative

user agent group. These all agents are essentially the

same, but they operate in different mode.

a) A single user mode, where a User Agent is

serving a single user during a virtual

expedition without any regard to other agents

interacting with VEA. In this mode user

agent uses the request-response interaction

protocol to manage interaction with VEA.

Figure 2: Agent Based Framework for MOSAICA Pedagogical Framework.

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Collaborative mode, where user agents interact with

VEA and with each other for the purpose of

collaborative learning. Each User Agent in a group

of users agents involved in collaborative learning

will focus on certain aspects of a complex problem.

The group needs to be aware of contribution of each

remember in order to progress toward overall

solution. The agents in this mode use teamwork

interaction protocol for managing interaction among

group members in addition to request-response

interaction protocol.

4.2 Virtual Expedition Agent

Virtual Expedition Agent is at the heart of our

proposed approach. It manages interactions with

user agents and Web resources. MOSAICA proposes

the use of Service Oriented Architecture (E. Ort) for

the integration of different systems components. An

Agent-WS gateway is proposed to manage seamless

interaction between intelligent agents and Web

Services (WS). This gateway will provide a

translation service that will convert message in agent

communication language (FIPA, 2000) to Web

Services Description Language (WSDL)

(Christensen et al., 2001) and vice versa.

VEA respond to User Agent’s requests using an

expedition from its libraries of static or dynamic

expeditions or preparing a new virtual expedition if

not already present in expedition library.

VEA expedition libraries contain two types of

virtual expeditions known as static and dynamic

expedition.

a) Static Expeditions are few exemplifying those

that will be used as tutorials and instructional

material to guide end users in designing their

own Virtual Expeditions. These also contains

ready-to-use educational material designed for

the educational personnel to use in instruction

and teaching, but also for students and other

visitors to use them for individual studies.

b) Dynamic Expeditions are expeditions that a

VEA agent complies in response to requests

received from User Agent. VEA compiles

these expeditions by interacting with resources

via an Agent-WS gateway. It also maintains a

record of dynamic expeditions and uses them

in order to serve identical request coming from

different User Agents.

VEA uses different kind of interaction protocols in

order to maintain interactions between various User

Agents and resources. It also supports User Agents in

their collaborative expeditions.

5 RELATED WORK

In this section we present literature review in

relation to the use of intelligent agents as

pedagogical agents in order to make the case for

suitability of agent technology in realisation of

MOSAICA’s pedagogical framework.

Johnson (Johnson, 1998) purpose the definition

of pedagogical agent as special purpose

agent:“Pedagogical agents are autonomous agents

that support human learning, by interacting with

students in the context of interactive learning

environments. They extend and improve upon

previous work on intelligent tutoring systems in a

number of ways. They adapt their behaviour to the

dynamic state of the learning environment, taking

advantage of learning opportunities as they arise”.

Blanchard (Blanchard et al., 2006) propose an

intelligent tutoring system in which pedagogical

agents have ability to evolve. This evolution process

allows producing agents whose behaviours are

fitting the learner motivational and cultural needs.

They have used rule based methodology for

evolution process.

Conati (Conati et al., 2006) propose intelligent

pedagogical agents that can provide individualised

instructions integrated with the entertaining nature

of the games. They describe different ways of

improving learning using intelligent agents in

educational games.

Baylor (Baylor, 2001) proposes the cognitive

requirements for agent based learning environments

and identifies four dimension of control that must be

considered in designing agent based learning

environments.

Rickel (Rickle, 1998) introduce a pedagogical

agent STEVE for virtual reality learning

environment. STEVE handles high level cognition

processing and sensor motor processing as two

separate but related processes.

The cognitive process interprets the state of the

world and executes plans to achieve its goals. The

sensory motor process deals with its interface with

virtual world.

Hamburger (Hamburger and Tecui, 1998)

propose architecture for pedagogical agents that can

learn from human tutor and then teach to human

learners. They used machine learning and

knowledge acquisition approaches in their proposed

architecture.

Johnson (Johnson et al.) propose the integration

of pedagogical agents into virtual environment.

These pedagogical agents monitor the trainees’

behaviour in virtual environment and provide them

instructions by interaction with them. This

integration enables trainees to get guidance and

coaching in virtual environment.

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Although none of these approaches deal directly

with the issues related to virtual expedition

discussed in MOSAICA’s pedagogical framework.

But these approaches do make a case for the use of

intelligent agent as enabling technology in

pedagogical applications. We believe that these

approaches provide foundational building blocks for

realisation of MOSAICA’s pedagogical framework.

6 CONCLUSION

In this paper we have presented MOSAICA’s

pedagogical framework and proposed an intelligent

agent based approach for the realisation of this

framework. Intelligent agents provide an intelligent

virtual learning environment, where user will engage

in learning individually and collaboratively with the

help of their agents. Our future work will focus on

design and implementation of User Agent and VEA.

We have also provided discussion of related

literature in order to justify the use of intelligent

agent technology in realisation of MOSAICA’s

pedagogical framework.

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