SOFTWARE AGENTS FOR SUPPORTING STUDENT TEAM

PROJECT WORK

Janice E. Whatley

Information Systems Institute, University of Salford, Manchester, M5 4WT,

eywords: Software Agents, Teamwork, E-Learning,

Abstract: In this paper an agent system is described, which has been designed to support students undertaking team projects

as part of their studies on campus or online. Team projects form an important part of the learning process

for campus based students, but are not easily incorporated into the learning activities for online students.

The particular problems of working on projects in teams are explored, and an agent system was designed to

support some of the maintenance tasks of team working. Agent technology is suggested because of the ease

of communication between software agents and their autonomy in operation. The agent system has been

tested on student teams working on campus, and the results indicate that this type of support agent may be

helpful to students. The modified version of the agent system was successfully implemented, and the trial

suggests that it may be scaled up to use over the Internet to support online student teams.

1 INTRODUCTION

Online learners rely on Internet connections to

communicate with institutions, tutors and other

learners, and there is often a sense of isolation from

the support of others (Hill and Raven, 2000).

Campus based learners are beginning to rely more

on the Internet to support their studies, such as to

enable them to access material outside of lecture

times, to work at more convenient times and

wherever they choose and to supplement their face

to face contact with other students.

Working in teams is particularly problematical,

both for campus based students and for online

students, but team working, and virtual team

working, especially, is becoming an essential skill

for our graduates. Groupware and virtual learning

environments help team members to communicate

and share files, but do not support the maintenance

needs of team working, which are necessary for

successful team operation.

Artificial intelligence has been used to develop

tutoring systems for individualised learning, and

agent technology is being harnessed for Internet

based communicating systems. The analogy between

multi-agent systems and student teams has pointed

to the possibility of agent technology as a solution to

some of the difficulties of working in teams, by

combining the benefits of intelligent tutoring, advice

from an agent and communication.

2 STUDENTS WORKING ON

TEAM PROJECTS

Traditional undergraduate campus-based courses

incorporate a team project element, as an essential

means of “learning by doing”. The learning cycle by

Kolb (Kolb, 1984) summarises the stages of

experiential learning as:

• concrete experience;

• reflective observation;

• conceptualisation;

• active experimentation.

These stages give a starting point for thinking about

how we approach the design of learning activities to

achieve the learning outcomes. The main feature is

that students do not learn by simply being told facts.

They need to be able to practice using the facts, and

reflect on the way they are used in order to form

connections in the brain, which can be regarded as

knowledge. Further experimentation, experience and

reflection leads to intelligence or expertise in a

subject. If the students are able to talk about this

information, then they can be said to have

knowledge of the subject, and intelligence shows in

190

E. Whatley J. (2004).

SOFTWARE AGENTS FOR SUPPORTING STUDENT TEAM PROJECT WORK.

In Proceedings of the Sixth International Conference on Enterprise Information Systems, pages 190-196

DOI: 10.5220/0002633201900196

 SciTePress

their ability to apply the knowledge in a variety of

situations. Collaborative learning may range from a

pair of students working together to a large class of

students learning together, but as Dillenbourg says,

ther is no agreed definition of collaborative learning

(Dillenbourg 1999). Team projects give students an

opportunity to discuss their understanding of the

subject with their peers, as they apply the theory to

practice (Sharan, 1990). Students may be working at

times collaboratively and at times cooperatively,

coordinating their efforts to achieve a project

outcome, and learning about themsolves and about

the subject in the process (Dillenbourg, Baker et al.

1996). When campus based students work on team

projects they experience difficulties in organising

their work together, such as arranging meetings,

deciding who should carry out which part of the

work, and coping with non participation from

members. If we are to provide students undertaking

online courses with a similar opportunity to

experience team working, we need to provide some

means of helping them to organise their work

together. Where face to face contact is not possible,

technologies may be able to provide some additional

resources to help make the online team experience

comparible to the campus based team experience.

Computer mediated communication (CMC)

tools, such as conferencing, email and discussion

forums support the communication needs for the

task roles of team projects, examples of their use are

given in (English and Yazdani, 1998) and (Hendson,

1997). The facilities included in Virtual Learning

Environments (VLE) give students the capability to

communicate with each other and the tutors, and are

based to a large extent on the facilities incorporated

in Groupware products, which in turn have been

developed as a result of research into Computer

Supported Cooperative Working (CSCW)

(Connolly, 1994). The VLE’s provide a structure to

enable communication, but little help in the process

of communication to help the students form

workable learning networks (Lawther and Walker,

2001). Opie used the term “knowledge-based

teamwork” to describe the sort of interaction

between team members who are all bringing to the

case in hand their own interpretation of the situation,

through their own knowledge or expertise. Her work

is specifically related to health care, but this is a

typical domain in which teamwork is essential for

achieving outcomes (Opie, 2000).

Successful team working requires that the

maintenance roles as well as the task roles of the

team are given attention (Hartley, 1997). Group

dynamics play an important role in determining how

successful the outcome of the project is, i.e. the

ways in which the members interact with each other

and how this changes with time as the team develops

(Bion, 1961), (Gibbs, 1994), (Jaques, 1984). Gilly

Salmon (Salmon, 2000) suggested ways in which

tutors can help students to interact socially online, in

order to develop team cohesion. Student support

using commercial groupware products enables

communication between team members and

instructors (Tiwari and Holtham, 1998), also BSCW

(Basic Support for Cooperative Working) is an

example of a tool that has been used as support for

team projects and was found useful for information

sharing, offering greater flexibility in students’ face

to face communication, but it offers limited support

for the maintenance roles of teamwork (Vliem,

1998). In previous work, students’ perceptions of the

manner in which their team worked together

confirmed that teams were more likely to be

successful in their projects if they pay attention to

some of the maintenance factors (Whatley et al.,

1999a).

The essence of learning how to work in a team is an

important aspect of team projects, because

organisations make much use of team working,

whether face to face, or, increasingly, in a virtual

team. The experience provided in Higher Education

is important, but concentrates on face to face teams,

whereas there is an increasing need to offer the

opportunity to learn to work virtually as well.

3 ONLINE TUTORING WITH

AGENTS

The Internet is providing possibilities for learners to

access their course materials in a variety of ways.

Some may prefer to use traditional face to face

means of learning, whereas others may prefer to

learn from home or the workplace, taking advantage

of online access. The new breed of “blended

learners” expect to be able to choose when and

where to access their lecarning, and require support

to enable them to learn effectively.

Intelligent tutoring using artificial intelligence

(AI) concepts has been associated with distance

learning, providing interfaces that respond to an

individual user’s needs (Farr and Psotka, 1992),

though very much aimed at individuals using

programmed learning packages. Agent technology is

a relatively new field of applying AI to practical

areas, e.g. knowledge management (Ferneley and

Berney, 1999) and Internet searchbots (Lieberman,

1997). Knowledge management aims to enable

SOFTWARE AGENTS FOR SUPPORTING STUDENT TEAM PROJECT WORK

191

collaboration between individuals online, notably for

problem solving (Corkill, 2003). Virtual

communities in the workplace are becoming more

common, but collaborating globally requires

different skills from those used for face to face

collaboration (Lipnack and Stamps, 2000).

The concept of an agent originates from human

agents that provide services, such as estate agents

and travel agents. These agents have specialist skills,

access to relevant information, contacts for obtaining

information and are focused on a particular task. In

the same way software agents are autonomous

systems that work on behalf of a user (Bradshaw,

1997). They exhibit the ability to recognise what the

user needs to accomplish and reacts to the user’s

input. A more formal definition is:

An agent is a self-contained, concurrently executing

software process, which encapsulates the current

state in terms of knowledge, and is able to

communicate with other agents through message

passing (Wooldridge, 1995).

In the field of e-learning software agents have

the potential to help online learners in several ways.

One such way is improving the effectiveness of

searching or enable the sharing of resources between

students who have similar interests (Ferneley and

Berney, 1999). Another aims to bring together

students with similar interests or needs into a

discussion area where they can receive help on

particular problems (Vassileva and Deters, 2001).

There are agents for guiding students in completing

work, by offering tutorial help using a character

(Nijholt, 2001). Finally, software agents may be

used to help teach learners, for example using virtual

environments to portray an example scenario

(Aylett, 2001). Soller suggests an architecture for

multi-agents to support online group learning,

concentrating on knowledge sharing between

students (Soller and Busetta). Software agents can

be made to work actively and adapt to users, which

means they can simulate some of the roles of tutors.

Pedagogical agents can monitor progress, give

instruction when needed, help organise students’

work and provide feedback for tutors (Baggetun et

al., 2002). These agent systems continuously operate

in the background on a student’s workstation and act

autonomously to suggest ways in which the learner

might improve performance.

A software agent may operate in isolation,

working on behalf of an individual, similar to

personalised intelligent tutors, but their power

derives from an ability to communicate with other

agents to fulfil tasks they would be unable to

complete alone. Typically a multi-agent system may

consist of several agents, each capable of performing

a different task autonomously. A network of agent

systems, communicating over a wide area network

(WAN) or a local area network (LAN), will make

use of Internet connectivity to pass messages

between each other. These multi-agent systems are

the main thrust of current research, and have arisen

as a result of the massive global infrastructure of

networks now available.

We now turn to the notion that multi-agents may

be applied to supporting collaborating members of a

team, and in particular teams of learners. In the next

section an application of a software agent for

supporting students working on team projects is

described.

4 DESIGNING A SOFTWARE

AGENT SYSTEM FOR TEAM

WORKING

The support needed by students for teamwork differs

from that which might be appropriate for an

individual working alone, as the dynamics of team

working also need to be considered. The advantage

of using software agents for supporting online

students is that agents can bridge the divide between

time and place. Students may be dispersed and

working at times to suit themselves, so the agents

can keep track of the students’ progress on the work,

and enable all the students to be aware of the status

of the project. Similarly, campus based students may

benefit from such a software agent system, as these

students demand the flexibility to work at different

times and places.

A preliminary version of an agent system

prototype has been developed, performing a limited

set of functions to help students to get started on

their teamwork, and the results of a trial carried out

using teams working on projects on campus are

discussed. These results have informed our further

design, leading to a second version of the agent

system, which has similarly been tried on student

teams working on campus.

An action research approach was adopted for this

study, because a more user-centred design may be

achieved by active user involvement in the

development process. Over several iterations of a

prototyping method, further functions may be added

and refined, by considering feedback from students

in the form of questionnaires, interviews and focus

groups. Although each successive cycle will not

involve the same individuals, a broadly similar range

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of students have participated in the design process,

and the final product should be acceptable to a

generic type of students.

5 FUNCTIONS OF THE AGENT

SYSTEM

There are limited examples of teamwork being used

for learning activities with online learners, because

there is a belief that face to face contact is essential

for successful teamwork (Lewis, 2002). Previous

surveys have been carried out to determine the

nature and extent of the difficulties experienced by

students working face to face, the intention being to

design an agent system to alleviate these problems

initially (Whatley et al., 1999b). Three main stages

of a team project have been identified, each with its

own associated problems, and these are summarised

in Table 1.

These stages of a team project do not correlate

directly with the stages of team development

originally defined by Bruce Tuckman (Tuckman,

1965), but represent stages of the tasks with which

students will identify (O'Sullivan et al., 1996). The

identified factors “introductions” and “setting the

ground rules” are processes that contribute towards

the maintenance roles of team projects. It was

decided that the initial work on developing a

software agent to support students should be targeted

at these functions, forming part of the planning stage

of a project.

6 DESIGN OF THE FIRST

PROTOTYPE AGENT SYSTEM

The initial prototype for the agent system was

developed in LPA Prolog, using their Agent

Development Kit (Logic Programming Associates,

2000). This tool enabled the developer to code the

interfacing aspects of the agent without worrying

about the technicalities of the agent communication,

which is dealt with by the tool. The declarative

features of Prolog were used for handling facts and

rules, which can be passed between each student’s

agent and the server agent. The first prototype

considered the allocation of tasks to the team

members.

In designing the prototype agent system, we were

interested in these main features:

• whether such an agent system would be

acceptable to students;

• whether the agent system would be of any

help to the students;

• whether communicating agents could be

implemented successfully within a typical

intranet environment.

Figure 1: Structure of Guardian Agent System

In the chosen system structure, each individual

student communicates with the agent system by

means of their individual agent (Figure 1). Each

agent will have a similar structure when the team

project begins, with interfacing capabilities for

communicating with its student, reasoning

capabilities for monitoring and analysing the current

situation, a knowledge base personal to its student

and communication capabilities for communicating

with other students’ agents. All communications

between agents is through a server agent, allowing

for a knowledge base to be built up for the particular

project the students are working on.

Table 1: Stages of the team project

Project stage Factors identified as

problematical

Planning Introductions

Setting ground rules

Produce a project plan

Allocate tasks

Doing the

project

Check the time schedule

Ensure all members

contribute

Identify lack of skills

Discuss each others’

contributions

Completing Collating the individual parts

Preparing a report

Appraising the team’s

performance

Student

Agent

Server

Agent

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Online students may be working on the

team project at different times of the day, so there is

limited possibility of discussing the allocation of the

tasks for the project. Even campus based students

may not all be present at the same time for formal

meetings. Comparing individual abilities would take

a considerable length of time using a discussion

forum, or other CMC means. Thus the agent system

aims to reduce the time spent on a mundane task,

and inform the students of the status of this task.

The process of allocating tasks begins with the

agent asking its student to enter details of their

abilities and preferences. The agent system will

obtain its own student’s abilities and preferences and

post these to the server agent so that all of the

students’ agents can access them. Once all of the

students in the team have posted their abilities and

preferences the agent system can apply a set of rules

to the facts, in order to determine which tasks of the

project could be allocated to each student. The agent

system will maintain a record of the suggested

allocations on the server agent, necessary later when

the agent system will be able to monitor student

activity against the work plan. As each student

returns to the team project, the agent will present the

allocations, so that all of the students can consider

and discuss them with the other students on the

project. Any allocations proposed by the agent

system may be subject to negotiation between the

students, the allocations are simply suggestions.

The agent system has been programmed to work

with three levels of allocation, using the following

rules:

Allocation1 -

• If studentA likes X and is able at X

• Then studentA should do X.

Allocation2 –

• If studentB is good at X and has not expressed a

dislike of X

• Then studentB could do X

Allocation of tutoring -

• If studentC likes X, but is unable at X

• Then studentC could be offered tutoring in X

7 RESULTS FROM THE FIRST

TRIAL OF THE AGENT

SYSTEM

The agent system was tested with seven teams

working on projects in systems development as part

of their undergraduate programme. The teams

consisted of between 6 and 10 second and final year

members, working on campus, and they were asked

to use the allocation of tasks function as they began

their projects. Each team project is slightly different,

so the tasks were specific to each team. After some

brief instructions for using the agent system, each

student in the teams used the agent to input their

details over a period of four weeks. As not all

students were present for each session, they did not

all use the system on the same occasion, which

matched the way in which the agent might be used

online.

Afterwards the students were asked to complete

questionnaires and were invited to a focus group so

that we could obtain feedback on the usefulness of

the system.

The interface was generally acceptable, but some

students suggested improvements, which we have

incorporated into the second prototype. About half

of the students said that the output from the

allocation of tasks function was useful, these were

mainly team leaders, who compared the output with

the ways in which they would have normally made

task allocations. A majority of the students thought

that such an agent system would be useful to

students working online as well as for campus based

students. Just over half of the students said that they

personally would like to use such an agent.

From our initial results it is clear that

students would find an agent system acceptable,

particularly for online students (though the term

“online” was not defined). It is difficult to establish

how helpful the agent system might be to either

online or campus based students, but comments

made during the focus group session did suggest that

the agent system performed a helpful function.

Table 2 – Questionnaire findings

Questions to students after

completing the Guardian Agent

trial

% of total

responses

Did you find the function useful? 56

Did you find the system easy to

use?

Was it self explanatory? 78

Do you think it would be useful for

students online?

Do you think it would be useful for

students on campus?

Do you like the concept of agent

help for working online?

Do you like the concept of agent

help for working on campus?

Would you personally like to use

this sort of agent?

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Most importantly, we did find that the agent system

implementation, using a server agent, was

successful, though a limited number of students

were involved in the study. However, implementing

the system using Prolog proved difficult, owing to

the reluctance of the code to compile correctly.

8 DESIGN FOR THE SECOND

TRIAL OF THE AGENT

SYSTEM

Taking into consideration the feedback from

students and issues of portability, we built the

second prototype in Java. The programs for the

agents were produced as Java executable files,

incorporated into web pages, and an improved user

interface was designed for the system. The server

agent was replaced by a file server, running a

MySQL database, in which the facts are stored.

Figure 2 shows the screen to obtain a student’s

preferences.

Figure 2: example of the interface to obtain preferences.

The issue of agreeing ground rules for team working

has been little explored, and problems cited included

difficulties getting students to attend meetings,

inform the team leader if they cannot attend and

complete their assigned work on time (Hill and

Raven, 2000). So this additional functionality was

included, to help the students to agree ground rules

for the way they intend to work together. Figure 3

shows the interface for asking about ground rules.

The second prototype was tried on 25 teams of

between 10 and 15 students, working on campus,

and took place over five weeks, when theses teams

were establishing their individual task areas for their

projects.

Once again questionnaires and focus groups were

used to capture the students’ opinions, together with

interviews carried out with the team leaders to

ascertain their views on the differences the agent

system made to their team project.

9 RESULTS FROM THE SECOND

TRIAL OF THE AGENT

SYSTEM

Initial analysis of the findings from the second trial,

indicates some satisfaction with the functions of the

agent system, several team leaders said that the

allocation of tasks was a useful function. Some

limitations with the interface were identified and the

pre-programmed task list did give rise to some

reluctance to use the agent system, as one team

leader said that the tasks included were not relevant

to their particular project.

Technically, the agent system was a

success, as the MySQL database was able to cope

adequately with the number of students using the

system. In spite of the fact that not all of the

computers in the laboratory were equipped to run

Java programs, sufficient machines were available to

satisfy the demand for using the agent system at any

one time. The pattern of usage for the campus based

students probably matched the expected pattern for

online teams.

Further development work will take place to

improve the interface and add more functionality to

the agent system.

10 CONCLUSIONS

In this paper we have described two phases in the

development of an agent system for supporting

Figure 3: interface to ask about ground rules.

SOFTWARE AGENTS FOR SUPPORTING STUDENT TEAM PROJECT WORK

195

students working on team projects. At present the

system has only been tried with campus based

students, but feedback from these students indicates

that the results are likely to be applicable to online

teams.

We have developed an agent system to help

student teams to allocate the tasks between the

members of the team, and to help the team members

to agree to a set of ground rules. Although these are

two relatively simple functions, and only a part of

the planning stage of a project, our findings indicate

that an agent system that can support students

through their team project would be acceptable.

Future investigations will try to establish the

extent to which student teams may be helped by an

agent system to perform more successfully.

The mode of implementation of the second

prototype agent system perhaps deviates from the

true definition of an agent, as each instance of the

agent does not maintain its own knowledge base.

However, as the functionality of the agent system is

enlarged in the future, it is suggested that a self-

contained knowledge base might be an essential part

of each agent for monitoring its student against a

project plan.

Although this trial was carried out on

campus, within a department’s intranet, the results

suggest that the Java agent can be distributed over

the Internet. Issues of security and firewalls may

need addressing, in preparation for it to be

implemented for real online teams.

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