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A TEACHING MODEL FOR ELECTRICAL INSTALLATION DESIGN

INSTRUCTION BASED ON INTELLIGENT TUTORING

Luiz Faria, Antnio Gomes, Antnio Silva, Zita Vale, Carlos Ramos,

Gustavo Santos, Srgio Ramos, Fernando FerreiraGECAD Knowledge Engineering and Decision Support Group

Institute of Engineering Polytechnic of Porto

R. Dr. Antnio Bernardino de Almeida

4200-072 Porto Portugal

[email protected]

Abstract Projects of electrical installations for private

use require not only academic knowledge but also other

types of more empirical knowledge. This paper presents a

project consisting on the development of an Intelligent

Tutoring System (ITS), for training and support concern-

ing the development of electrical installation projects to beused by electrical engineers, technicians and students. One

of the major goals of this project is to devise a teaching

model based on Intelligent Tutoring techniques able to

achieve successfully the training of electrical installation

design.

The project includes the development of a user model

required to support the pedagogical decision making of the

Tutoring System. A library of cases/practical projects will

be produced and a mechanism able to perform a matching

between major features of cases and the related domain

concepts will be implemented. A Cased-Based Reasoning

framework will be devised for select, adapt and store

cases/practical projects in order to offer personalized

courses, improving adaptation to current trainees needs

and preferences. Producing learner stereotypes using

clustering techniques and comparing the stereotypes with

individual learner models can accomplish the selection of

the cases that allowed best past performances.

Keywords: Electric installation design, intelligent

tutoring systems, knowledge based system, adaptive

hypermedia, interactive problem solving.

I. ELECTRICAL INSTALLATION PROJECTS`

TRAINING

Projects of electrical installations for private use re-

quire not only academic knowledge but also other typesof knowledge not easily acquired through traditional

instructional methodologies.

A lot of additional empirical knowledge is missing

and so the academic instruction must be completed with

different kinds of knowledge, such as real-life practical

examples and simulations. On the other hand, the prac-

tical knowledge detained by the most experienced de-

signers is not formalized in such a way that is not easily

transmitted.

In order to overcome these difficulties present in the

designers formation, we are developing an ITS, for

training and support concerning the development of

electrical installation projects to be used by electrical

engineers, technicians and students. This work is inte-

grated in the research project TINSEL, standing for

Intelligent Tutors for Electrical Installation Design,

which is currently financed by FCT Fundao para a

Cincia e Tecnologia, a Portuguese governmental

department, with the reference POSI/EIA/61843/2004.

The TINSEL team was involved in previous projects inthe area of ITS [1][2][3] applied to Power Systems

operation [4][5][6].

The main goal of this work is twofold:

training of students in this domain knowledge;

updating of teachers and technicians on new

technical solutions and legislation.

The goals stated above will be translated into the:

creation of a knowledge base about electric in-

stallations projects;

development of a tutor for electric installation

projects training.

II.

ITSFRAMEWORK AND RELATED WORK

The Intelligent Tutoring System will be based on a

client-server architecture where a part of its functional-

ity will be implemented in Java and will work on the

client side, and another part will work on the server

side. The parts will communicate over the Internet. In

the client side a Java applet, running in a Web browser,

will implement a graphical interface which will be re-

sponsible to send to the server all the trainee actions and

to show the feedback generated by the server.

We found relevant for our project the previous work

by Okamoto [7] and Chan on Cooperative Learning

systems, based on the assumption that learning is

strongly influenced by the interaction between the stu-

dents involved and between them and the environment.

Also the work from Lelouche [8] about Pedagogical

Agents in intelligent training systems and from Miller

and al [9] on the training of teams with cooperative

agents was considered. We also value the insights of

Jacobson [10]on specific constraints of the use of co-

operative learning in engineering education.

One of the goals of the project is to endow the ITS

with capabilities to support collaboration between all

learning entities, including different trainees and virtual

agents. In order to support collaboration between alllearning entities, the tutor will include a suitable envi-

ronment to support cooperative work between several


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students and between students and the tutorial system.

While permitting different types of interaction between

the different agents, this framework shall be allow the

tutor to apply different learning strategies, in order to

tailor the tutoring process to the trainees characteris-

tics. The framework must not only address the issues

related to information flow but also be able to motivateand facilitate the discussion as well as organizing the

distributed decision process.

The tutor will be divided in two modules. The first

one is a tutoring module intended to teach the legisla-

tion and its practical application in the context of an

electrical project. This module will also be in charge of

the transfer of the knowledge needed to accomplish

each phase of an electrical project. We plan to apply to

this module the adaptive hypermedia technologies.

Adaptive hypermedia systems apply different forms

of user models to adapt the content and the links of

hypermedia pages to the user [11]. We distinguish two

major technologies in adaptive hypermedia: presenta-tion and navigation support. Education always was one

of the main application areas for adaptive hypermedia.

First Web-based Adaptive and Intelligent Educational

Systems (AIES) using adaptive hypermedia technolo-

gies were reported in 1996 [12][13]. Adaptive naviga-

tion support (ANS) can be considered as a generaliza-

tion of curriculum sequencing technology in a hyper-

media context. It shares the same goal (to help students

to find an "optimal path" through the learning material)

but has more options than traditional sequencing. In a

WWW context where hypermedia is a basic organiza-

tional paradigm, adaptive navigation support can be

used very naturally and efficiently. There are several

known ways to adapt the links [11]. Two examples of

ANS-based standalone systems are ISIS-Tutor [14]with

adaptive hiding and adaptive annotation and Hy-

padapter [15]with adaptive hiding and adaptive sorting.

The three most popular Web-based AIES are direct

guidance, adaptive link annotation, and adaptive link

hiding.

The most popular form of ANS on the Web is anno-

tation. It was used first in ELM-ART [12]and since that

applied in all its descendants. ELM-ART and InterBook

also use adaptive navigation support by sorting. An-

other popular technology is hiding and disabling. Theoptions are either to make the link completely non-

functional as implemented, for example, the Remedial

Multimedia System [16] or to show the user a list of

pages to be read before the goal page as done in Alba-

tros [17].

Adaptive presentation is very important in WWW

context where the same "page" has to suit very different

students. Only two Web-based AES implement com-

plete adaptive presentation: PT [18] and AHA [19].

Medtec [20] is able to generate adaptive summary of

book chapters. MetaLinks can generate a special preface

to a content page depending on where the student came

from to this page. A very interesting example of adap-tive presentation is suggested in WebPersona project

[21] where presentation is performed by a life-like

agent.

The second module of the ITS is a problem solving

module where the learner will have the opportunity to

develop a practical project with tutor support. This

module will be based on the interactive problem solving

technology.Problem solving support has been considered the

main duty of an ITS system and a main value of an ITS

technology. Three problem solving support technolo-

gies can be identified: intelligent analysis of student

solutions, interactive problem solving support, and

example-based problem solving support.

Intelligent analysis of student solutions deals with

students final answers to educational problems no

matter how these answers were obtained. To be consid-

ered as intelligent, a solution analyser has to decide

whether the solution is correct or not, find out what

exactly is wrong or incomplete, and possibly identify

which missing or incorrect knowledge may be responsi-ble for the error.

Interactive problem solving support is a more recent

and powerful technology. Instead of waiting for the

final solution, this technology can provide a student

with intelligent help on each step of problem solving

and it allows to watch the students actions, understand

them, and use this understanding to provide help and to

update the student model as in LISP-TUTOR [22].

Another example of application of interactive problem

solving can be seen in an ITS previously developed by

our team [1][2][3] and aimed to train Control Centre

operators to get diagnosis of incidents in electrical net-

works.

The example-based problem solving technology is

the newest one. This technology is helping students to

solve new problems not by articulating their errors, but

by suggesting them relevant successful problem solving

cases from their earlier experience. An example is

ELM-PE [23]or, in the Web context, in ELM-ART [24]

and ELM-ART-II [25].

The Case-Based Reasoning concept seems particu-

larly well adapted to the curriculas structure of the

particular domain we are dealing with. The idea of case-

based teaching presented by Schank [26]derived from

the field of case-based reasoning [27][28], which is theprocess of solving new problems based on the solutions

of similar past problems. Schank states that students

learn better from cases representing real tasks to be

presented at the precise point of becoming interested in

acquiring the information conveyed by the case. It is

also relevant the research carried out by Van Lehn and

al [29]in ways of adapting tutor behaviour to students

performance, by varying the scaffolding level of the

support given. On the subject of representing, selecting

and planning tutoring strategies the works of Schank

[30] on Goal-Based Scenarios, Murray [31] on Dis-

course Management Networks and Cho and all [32]

seems suitable for our purposes.


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III.

TEACHING MODEL

Different teaching models had been proposed in the

area of Intelligent Tutoring Systems with the purpose of

teaching in different types of domains. Teaching some

of these domains requires exposition like approaches

where the learner must acquire knowledge presented in

a expositive way, sometimes through the application ofadaptive hypermedia techniques. Law and some sub-

domains of medicine are examples of these domains.

However, the learning process in other domains re-

quires the acquisition of skills that can only be achieved

by the learner through the resolution of practical prob-

lems [2].

Furthermore, the design of electrical installations in-

volves the use of different types of knowledge and

expertise which can only be efficiently transmitted

through the application of different teaching techniques.

As stated in the previous session II, the legislation and

its practical application in the context of an electrical

project is one of the major types of knowledge needed

to accomplish the design of electrical installations. Due

to the nature of this type of knowledge, the adaptive

hypermedia technologies become the best approach to

transmit such kind of knowledge. On the other hand, theuse of interactive problem solving technologies reveals

to be an option to the acquisition of competences

needed to perform tasks such as circuit dimensioning.

Since the electrical installation design requires such

different kinds of competences, which demands for

different teaching techniques, the teaching model de-

vised for the TINSEL project includes different tutoring

approaches. Figure 1 presents in detail the tutoring

model proposed and the tutors roles in different learn-

ing situations.

Figure 1 Tutoring Model and Tutors Roles


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The tutoring model presented in Figure 1 contains

three types of learning units, represented by square

boxes. The rounded boxes represent the tutoring roles

during the activity of the trainee while in a learning

unit.

A trainee starts his training by taking some lessons of

theoretical nature. The knowledge acquired during theselessons is essential to enable the trainee to accomplish

tasks of more practical nature involved in the design of

an electrical installation. For this type of lessons the

tutoring model defines the use of learning units from the

type named knowledge exploration (corresponding to

the top most box in Figure 1. The implementation of

instances of this kind of learning unit is based on the

application of adaptive hypermedia techniques. The role

of the tutor here is to select the most adequate hyperme-

dia pages according to the trainee model and to supply

guidance while the learner navigates through the se-

lected hypermedia pages.

After the trainee had consulted some hypermediapages, the tutor recommends the trainee to be submitted

to an assessment process in order to evaluate the

trainees knowledge about the domain topics addressed

in the reviewed pages. These assessments are imple-

mented through multiple choice exams and correspond

to the second type of learning unit present in the tutor-

ing model. In this type of learning units, the tutors role

includes the exam elaboration and the corresponding

trainee performance evaluation. After the assessment, if

the tutor finds misconceptions in the trainee knowledge

then the tutor guides the trainee back to the lessons

related with the misconceptions and orients the trainee

to overcome these. However if the trainee had a positive

performance and shows enough knowledge to solve a

sub-set of practical problems then the tutor suggests the

trainee to accomplish such a problem.

The practical problem solving activity corresponds to

the third type of learning unit and applies the well

known learning technique named learning by doing.

The implementation of the instances of this kind of

learning unit is based on interactive problem solving

techniques. The mechanisms used to detect misconcep-

tions and to infer the reasons behind these misconcep-

tions are based on the model tracing technique [2],

[29].In this stage of the tutoring process, the role of the

tutor is twofold:

To select the problem according to the present

learning needs of trainee, matching the trainees

model;

To assist the trainee during the problem solving

activity.

During problem solving, if the trainee reveals diffi-

culties the tutor will provide hints in order to overcome

these difficulties. The hints provided by the tutor start

from generic and less detailed hints and follow to more

specific and more detailed hints if the trainee still main-

tains his difficulties. However, if all the hints suppliedby the tutor were not enough to overcome the difficul-

ties, then the tutor guides the trainee back to the lessons

containing the knowledge needed.

Finally, if the trainee solved the proposed practical

problem successfully the tutor can conclude that the

trainee is able to follow the next learning unit and

guides him to a new knowledge exploration unit.

IV.

CONCLUSIONS

An Intelligent Tutor in this specific field will fill a

gap in the learning process structure, performing a func-

tion not fulfilled by anyone. It will also complement and

improve the tutoring process offered by other instruc-

tional techniques in the following aspects:

the experts in the field of electrical installation

design tend to be rare and usually they are not

available to assist novice designers;

the training quality suffers from the lack of an

evaluation mechanism and the fact that the same

training program is applied to all the partici-pants;

the trainees do not have to leave their working

place since the tutor can be used through the

internet.

The teaching model proposed is able to ensure ade-

quate support of the trainees in the acquisition of the

different types of knowledge and expertise required to

perform successfully the design of electrical installa-

tions, since it defines different teaching technologies

appropriated to the acquisition of the heterogenic types

of knowledge involved.

The use of these Tutors can therefore improve elec-

trical installation designers' formation, which is criticaldue to the lack of well-trained technicians in this area.

V.

ACKNOWLEDGMENTS

The authors would like to acknowledge FCT,

FEDER, POCTI, POSI, POCI and POSC for their sup-

port to R&D Projects and GECAD Unit.

REFERENCES

[1] Silva, A., Faria, L., Vale, Z., Ramos, C., Marques,

A., "User Modelling Concerning Control Centre

Operators Training", IEEE Porto Power Tech 2001

(IEEE PPT2001)

[2] Faria, L., Treino e Apoio a Operadores de Centros

de Controlo e Conduo Uma Abordagem

Baseada em Conhecimento e Tutores Inteligentes,

Ph.D. dissertation, Dept. Elect. And Computer

Eng., Faculty of Engineering, University of Porto,

Portugal, 2002

[3] Faria, L., Vale, Z., Ramos, C., Marques, A., Intel-

ligent Training of Incident Diagnostic Task:

Adapting Curriculum to Operator Needs, Intelli-

gent Systems Applications to Power Systems

(ISAP2003), Lemnos, Grcia, 1-3 September,

2003[4] Vale, Z., Fernandes, F., Rosado, Marques, A.,

Ramos, C., Faria, L., "Better KBS for Real-time


5/6

Applications in Power System Control Centers: the

Experience of SPARSE Project", Computers in In-

dustry, Elsevier, 37 (1998), 97-111

[5] Vale, Z., Ramos, C., "Reasoning about Time in AI

applications for Power Systems Control Centers",

Int. Journal of Engineering Intelligent Systems for

Electrical Engineering and Communications, 7, 2(1999), 91-96, CRL Publishing Ltd

[6] Vale, Z., Ramos, C., Faria, L., Malheiro, N.,

Marques, A., Rosado, "Real-Time Inference for

Knowledge-Based Applications in Power System

Control Centers", SAMS - Journal Systems Analy-

sis-Modelling-Simulation, Gordon & Breach Sci-

ence Publishers (2001)

[7] Okamoto, T. e Kasai, T., "The Collaborative sys-

tem with Situated Agents for Activating Observa-

tion Learning", Proc. of the 5th Int. Conf. on ITS,

Canada, 2000

[8] Lelouche, R., "A Collection of Pedagogical Agents

for Intelligent Educational Systems", Proc. of the5th Int. Conf. on ITS, Canada, Springer-Verlag,

143-152, 2000

[9] Miller, M. and al., Human-Agent Teamwork for

Distributed Team Training, 15th

Conference on

Tools with AI, Sacramento, November 2003

[10]Jacobson, Doug and al, Ten myths of Cooperative

Learning in engineering education, Proceedings of

IEEE Frontiers in Education, Tempe, AZ, Nov. 4-

7, 1998

[11]Brusilovsky, P.: Methods and techniques of adap-

tive hypermedia. User Modelling and User-

Adapted Interaction 6, 2-3 (1996) 87-129

[12]

Brusilovsky, P., Schwarz, E., and Weber, G.:

ELM-ART: An intelligent tutoring system on

World Wide Web. In: Frasson, C., Gauthier, G.

and Lesgold, A. (eds.) Intelligent Tutoring Sys-

tems. Lecture Notes in Computer Science, Vol.

1086. Springer Verlag, Berlin (1996) 261-269

[13]De Bra, P. M. E.: Teaching Hypertext and Hyper-

media through the Web. Journal of Universal Com-

puter Science 2, 12 (1996) 797-804, available

online at http://www.iicm.edu/jucs_2_12/

teaching_hypertext_and_hypermedia

[14]Brusilovsky, P. and Pesin, L.: An intelligent learn-

ing environment for CDS/ISIS users. In: Levonen,J. J. and Tukianinen, M. T. (eds.) Proc. of The in-

terdisciplinary workshop on complex learning in

computer environments (CLCE94), Joensuu,

Finland, EIC (1994) 29-33, available online at

http://cs.joensuu.fi/~mtuki/www_clce.270296/Brus

ilov.html

[15]Hohl, H., Bcker, H.-D., and Gunzenhuser, R.:

Hypadapter: An adaptive hypertext system for ex-

ploratory learning and programming. User Model-

ling and User-Adapted Interaction 6, 2-3 (1996)

131-156

[16]Alpert, S. R., Singley, M. K., and Fairweather, P.

G.: Deploying Intelligent Tutors on the Web: AnArchitecture and an Example. International Journal

of Artificial Intelligence in Education 10 (1999)

183-197, available online at

http://cbl.leeds.ac.uk/ijaied/abstracts/Vol_10/alpert

.html

[17]Lai, M.-C., Chen, B.-H., and Yuan, S.-M.: Toward

a new educational environment. In: Proc. of 4th In-

ternational World Wide Web Conference (1995),available online at

http://www.w3.org/pub/Conferences/WWW4/Pape

rs/238/

[18]Kay, J. and Kummerfeld, B.: User models for cus-

tomized hypertext. In: Nicholas, C. and Mayfield,

J. (eds.): Intelligent hypertext: Advanced tech-

niques for the World Wide Web. Lecture Notes in

Computer Science, Vol. 1326. Springer-Verlag,

Berlin (1997)

[19]De Bra, P. and Calvi, L.: AHA! An open Adaptive

Hypermedia Architecture. The New Review of

Hypermedia and Multimedia 4 (1998) 115-139

[20]

Eliot, C., Neiman, D., and Lamar, M.: Medtec: AWeb-based intelligent tutor for basic anatomy. In:

Lobodzinski, S. and Tomek, I. (eds.) Proc. of

WebNet'97, World Conference of the WWW,

Internet and Intranet, Toronto, Canada, AACE

(1997) 161-165

[21]Andr, E., Rist, T., and Mller, J.: WebPersona: A

Life-Like Presentation Agent for Educational Ap-

plications on the World-Wide Web. In: Brusi-

lovsky, P., Nakabayashi, K. and Ritter, S. (eds.)

Proc. of Workshop "Intelligent Educational Sys-

tems on the World Wide Web" at AI-ED'97, 8th

World Conference on Artificial Intelligence in

Education, Kobe, Japan, ISIR (1997) 78-85, avail-

able online at

http://www.contrib.andrew.cmu.edu/~plb/AIED97

_workshop/Andre/Andre.html

[22]Anderson, J. R. and Reiser, B.: The LISP tutor.

Byte 10, 4 (1985) 159-175

[23]Weber, G.: Individual selection of examples in an

intelligent learning environment. Journal of Artifi-

cial Intelligence in Education 7, 1 (1996) 3-31

[24]Brusilovsky, P., Schwarz, E., and Weber, G.:

ELM-ART: An intelligent tutoring system on

World Wide Web. In: Frasson, C., Gauthier, G.

and Lesgold, A. (eds.) Intelligent Tutoring Sys-tems. Lecture Notes in Computer Science, Vol.

1086. Springer Verlag, Berlin (1996) 261-269

[25]Weber, G. and Specht, M.: User modelling and

adaptive navigation support in WWW-based tutor-

ing systems. In: Jameson, A., Paris, C. and Tasso,

C. (eds.) User Modelling. Springer-Verlag, Wien

(1997) 289-300

[26]Schank R, Case-Based Teaching: four experiences

in educational software design, Interactive Learn-

ing Environments, 1, 231-254, 199

[27]Kolodner J, Improving human decision making

through case-based decision aiding, AI Magazine,

12, 2, 52-68, 1991


6/6

[28]Kolodner J, Case-Based Reasoning, San Mateo, M

Kaufman, 1993

[29]VanLehn K et al., Fading and Deepening: The

Next Steps for Andes and other Model-Tracing Tu-

tors, ITS'2000 Conf., Springer, 2000

[30]Schank, Roger C. (1996) Goal-Based Scenarios:

Case-Based Reasoning Meets Learning by Doing.In: David Leake (Ed) Case-Based Reasoning: Ex-

periences, Lessons & Future Directions. AAAI

Press/The MIT Press, 295-347

[31]Murray W, Control for ITSs: A Comparation of

Blackboard Architecture and Discourse Manage-

ment Networks. Tech. Rep. R-6267, FMC Corpo-

ration

[32]

Cho B, and al, A Curriculum Planning Model foran ITS, 12th Int. Florida AI Research Soc. Conf.,

FLAIRS'99, USA, 197-201, 1999

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