1 automatic generation of exercises for self-testing in adaptive e-learning systems: exercises on ac...
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Automatic Generation of Exercises for Self-testing in Adaptive E-Learning Systems: Exercises on AC Circuits
Third International Workshop on Authoring of Adaptive and Adaptable Educational HypermediaAmsterdam, The Netherlands, July 19th, 2005
Paul Dan Cristea, Aurora Rodica TuduceUniversity POLITEHNICA of Bucharest
Spl. Independentei 313, 060042 Bucharest, Romania, Phone/Fax : +40 - 21- 316 95 68, 694
e-mail:[email protected]
AIED 2005 12th International Conference on Artificial Intelligence in Education
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1. Introduction Learning Modalities
Need for Intelligent e-Learning Systems
2. System architecture Pilot System Multiagent Structure
Architecture of ILE Pilot
3. Basic Tools Learner Profile Eliciting Tool
Question Apprisal
Learning Item Apprisal & Status
Point and Acceptance Propagation
4. Automatic Generation of AC
Electric Circuit Problems
5. Implementation & Web Accessibility
6. Conclusions
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Combine the traditional style of teaching with the problem-based style:• learning by being told, • problem solving demonstration, • problem solution analysis, • problem solving, • creative learning
Knowledge transfer Skill development
Learning by being
told
Problem solving demo
Solution analysis
Problem solving
Creative learning
Level of learner’s active participation
Learning ModalitiesLearning Modalities
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• Dramatic change of the target public for trainingDramatic change of the target public for training
• Professional qualification is no longer a life-long Professional qualification is no longer a life-long achievementachievement
• Complex knowledge and skills have to beComplex knowledge and skills have to be
transmitted and acquired efficientlytransmitted and acquired efficiently
• Open and Distance Learning play a continuously Open and Distance Learning play a continuously increasing roleincreasing role
e-Learninge-Learning
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• Intelligent educational tools can bring the flexibility and Intelligent educational tools can bring the flexibility and adaptability required to actively support the learner;adaptability required to actively support the learner;
• Increase efficiency of learning and further motivate Increase efficiency of learning and further motivate learners by giving them a set of intelligent tools that will learners by giving them a set of intelligent tools that will actively support them in the learning endeavour;actively support them in the learning endeavour;
• Promote participative and collaborative learningPromote participative and collaborative learning ;;• Offer learners individualised learning according to Offer learners individualised learning according to
elicited learner profiles.elicited learner profiles.
Intelligent e-LearningIntelligent e-Learning
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• Significant research and implementation effort has been dedicated to develop Intelligent Tutoring Systems and Adaptive Hypermedia, able to adapt to learner’s objectives, interests, and preferences, i.e., to a Learner Profile (LP).
• To implement adaptivity, an ILE needs a quite complex structure, with several parallel version of the same learning item (LI), allowing many different learning paths to be selected in accordance with the LPs.
• Considerable additional effort in elaborating teaching materials, might require several authors and might need institutional support, but brings the advantage of real flexibility and adaptability.
• A course is not a flat juxtaposition of learning items, but a multilevel structure with many branches, along which the ILE recommends an optimal path for a user or for a class of users.
Intelligent e-Learning (cont)Intelligent e-Learning (cont)
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• Authoring learning material and building the structure of adaptive systems tends to become too complicated for the average teacher.
• Portability – the ability to deploy the content of a system on any other system,
Reusability – the ability to store, search and retrieve LIs, including lessons, modules, exercises, activities for reusing,
are strictly necessary for an efficient implementation and for a wide scale acceptance of the concept.
Intelligent e-Learning (cont)Intelligent e-Learning (cont)
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The system is learner centred, all human and artificial agents being focused on achieving the learning-training tasks.
Human agents:• students, • authors of teaching materials, • tutors, • course administrators, • system administrator(s).
The pilot web oriented ILE has a server-client distributed multiagent hybrid architecture
Pilot System StructurePilot System Structure
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Architecture of ILE pilotArchitecture of ILE pilotClient
Student admin. data
Server(s)
Client
INTRANET / INTERNETINTRANET / INTERNET
Learner Learner
System Admin.System Admin.
Author Author
WebBrowser
WebBrowser
Client
Tutor Tutor
Client
Course Admin.
Course Admin.
LOAuthoring
Tools
LOAuthoring
Tools
TestsAuthoring
Tools
TestsAuthoring
Tools
Reg. &Pers. Data
Manag.
Reg. &Pers. Data
Manag.
CourseAdmin. Tools
CourseAdmin. Tools
AutomaticTutoring
Tool
AutomaticTutoring
Tool
Student Tracking
Tool
Student Tracking
ToolLearner’s Profile
Eliciting ToolLearner’s Profile
Eliciting Tool
Course DB
Test DB
Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist.
LOAuthoring
Tools
LOAuthoring
Tools
TestsAuthoring
Tools
TestsAuthoring
Tools
LO FilesLO Files
Aux.FilesAux.Files
BufferBuffer
BufferBufferStudent
Evaluation Tool
Student Evaluation
Tool
Evaluationresults
Student profiles
Comm. Tools
Comm. Tools
SystemAdmin. Tools
SystemAdmin. Tools
WebBrowser
WebBrowser
WebBrowser
WebBrowser Web
BrowserWeb
Browser
Client
Student admin. data
Server(s)
Client
INTRANET / INTERNETINTRANET / INTERNET
Learner Learner
System Admin.System Admin.
Author Author
WebBrowser
WebBrowser
Client
Author Author
WebBrowser
WebBrowser
WebBrowser
WebBrowser
Client
Tutor Tutor
Client
Course Admin.
Course Admin.
LOAuthoring
Tools
LOAuthoring
Tools
TestsAuthoring
Tools
TestsAuthoring
Tools
Reg. &Pers. Data
Manag.
Reg. &Pers. Data
Manag.
CourseAdmin. Tools
CourseAdmin. Tools
AutomaticTutoring
Tool
AutomaticTutoring
Tool
Student Tracking
Tool
Student Tracking
ToolLearner’s Profile
Eliciting ToolLearner’s Profile
Eliciting Tool
Course DB
Test DB
Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist. Comm. Tools
Comm. Tools
Pers. Assist. Pers.
Assist.
LOAuthoring
Tools
LOAuthoring
Tools
TestsAuthoring
Tools
TestsAuthoring
Tools
LO FilesLO Files
Aux.FilesAux.Files
BufferBuffer
BufferBufferStudent
Evaluation Tool
Student Evaluation
Tool
Evaluationresults
Student profiles
Comm. Tools
Comm. Tools
SystemAdmin. Tools
SystemAdmin. Tools
WebBrowser
WebBrowser
WebBrowser
WebBrowser
WebBrowser
WebBrowser
WebBrowser
WebBrowser Web
BrowserWeb
BrowserWeb
BrowserWeb
Browser
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Learner Profile Eliciting ToolLearner Profile Eliciting Tool
Student Input
LearningObjectives
LearningModalities
Student Tracking
Tool
KnowledgeWatch
StudentInitial Input
Tutor Input
Engine
CoursePresentation
AdaptiveTesting
LPET
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Learning Objectives
Control Module Communication Module
Learner’s Profile Eliciting Tool
Student input
Registration form
Questionnaires
Learning Modalities
KnowledgeWatch
• Curricular study for a diploma• Complementary study• Executive up-dating• Specialist up-dating• Problem centered• Test oriented
Preferredly / Predominantly:
• Descriptive• Demo• Analytical details• Practical aspects• Examples• Multimedia / Text
Material to study1 First Chapter xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 1.1 Section 1.1 xxxxxxxxxxxxxxxxxxxxxxxxxxx 1.1.1. Paragraph xxxxxxxxxxxxxxxxxxxxxX 1.1.2. Paragraph xxxxxxxxxxxxxxxxxxxxxX 1.1.3. Paragraph xxxxxxxxxxxxxxxxxxxxxX 1.2 Section 1.2 xxxxxxxxxxxxxxxxxxxxxxxxxx 1.2.1. Paragraph xxxxxxxxxxxxxxxxxxxxxx 1.2.2. Paragraph xxxxxxxxxxxxxxxxxxxxxX 1.2.3. Paragraph xxxxxxxxxxxxxxxxxxxxxX 1.3 Section 1.3 xxxxxxxxxxxxxxxxxxxxxxxxxxx 1.3.1. Paragraph xxxxxxxxxxxxxxxxxxxxxx 1.3.2. Paragraph xxxxxxxxxxxxxxxxxxxxxx 1.3.3. Paragraph xxxxxxxxxxxxxxxxxxxxxx 2 Second Chapter xxxxxxxxxxxxxxxxxxxxxxxxxxxx 2.1 Section 2.1 xxxxxxxxxxxxxxxxxxxxxxxxxxx 2.1.1. Paragraph xxxxxxxxxxxxxxxxxxxxxx 2.1.2. Paragraph xxxxxxxxxxxxxxxxxxxxxX 2.1.3. Paragraph xxxxxxxxxxxxxxxxxxxxxx …………………………………
Studied material1 First Chapter xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx 1.1 Section 1.1 xxxxxxxxxxxxxxxxxxxxxxxxxx 1.1.1. Paragraph xxxxxxxxxxxxxxxxxxxxxxxxxxxxx 1.1.2. Paragraph xxxxxxxxxxxxxxxxxxxxx 1.1.3. Paragraph xxxxxxxxxxxxxxxxxxxx 1.2 Section 1.2 xxxxxxxxxxxxxxxxxxxxxxxxxx 1.2.1. Paragraph xxxxxxxxxxxxxxxxxxxx 1.2.2. Paragraph xxxxxxxxxxxxxxxxxxxxx 1.2.3. Paragraph xxxxxxxxxxxxxxxxxxxxx 1.3 Section 1.3 xxxxxxxxxxxxxxxxxxxxxxxxxx 1.3.1. Paragraph xxxxxxxxxxxxxxxxxxxx 1.3.2. Paragraph xxxxxxxxxxxxxxxxxxxxx 1.3.3. Paragraph xxxxxxxxxxxxxxxxxxxx2 Second Chapter xxxxxxxxxxxxxxxxxxxxxxxxxxx 2.1 Section 2.1 xxxxxxxxxxxxxxxxxxxxxxxxxx 2.1.1. Paragraph xxxxxxxxxxxxxxxxxxxxx 2.1.2. Paragraph xxxxxxxxxxxxxxxxxxxxx 2.1.3. Paragraph xxxxxxxxxxxxxxxxxxxxx…………………………………
?
Standard Path
Recommended Path
ContentManagement
Mandatory
Testing
Contribution to Collaborative Learning
Tutor input
On-line students monitoring
Validation of students proposals
Self
Testing
Student Tracking
Tool
Learner Profile Eliciting Tool (details)Learner Profile Eliciting Tool (details)
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Question # 5
Text for question # 5
Figure for question # 5
Test forsection
5.1.
Number ofquestions
10
Time
Submit
Learner's test windowLearner's test window
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Question appraisalQuestion appraisal
Sum of points for a question Q
)(
)()(QSC
CPQSP
- the set of selected options at question Q.
Correct choices positive points, Wrong answers negative points.
Assigning negative points to wrong choices discourages guessing.
)()( QOQS
Points acknowledged for question Q
),()( if),(
),()(0 if,0
,0)( if),(
)(
QTQSPQSP
QTQSP
QSPQSP
QP
T(Q) - the threshold for the acceptance of the reply to Q
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Sum of points for a learning item LI
)(
)()()(LICILLIQ
ILPCPLISP
C (LI) – the children of LI. The points obtained for LI are transferred upwards
Points acknowledged for a learning item LI
).()( if),()(
),()( if),()(
LITLISPLIALISP
LITLISPLISPLIP
T(LI) - thresholdA(LI) - award for the successful completion of the study of LI
Learning item appraisalLearning item appraisal
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Status of the learning item LI
)),(,1)((
or )()( if,1,)(,0)(
and )()( if ,0
)(
ILCLIILS
LITLISPILCLIILS
LITLISP
LIS
0 – pending, 1 – studied,
Down-propagation of the acquired knowledge confirmation
Learning item statusLearning item status
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Points obtained for choices C from the set of options O(Q) pertinent to a certain question Q are recorded at the LI to which the question is attached and transferred upwards.
Point and acceptance propagationPoint and acceptance propagation
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Automatic Generation of AC Electric Circuit Problems
Automatic Generation of AC Electric Circuit Problems
1. Problem set description
2. Tree generation
3. Cotree generation
4. Tree plot
5. Graph plot
6. Circuit parameters and variables generation
7. Converting voltage sources to curent sources
8. Introducing controlled sources
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OBJECTIVESOBJECTIVESOBJECTIVESOBJECTIVES
Design and develop a software able to automatically generate large sets of circuit analysis problems, all with the same general features, but having different topological structures and parameters of the circuits.
Conditions:• The problems are for use both during the tutorials and for examinations, thus -- despite the inherent risk for an engineering perception of reality -- all parameters and variables describing.the circuits should be integers to facilitate the computational task.
• Problems and solutions should be stored automatically on disk in distinct directories.
• Files referring to the same problem (text, graphics, etc) will have related labels.
• The system will be developed for making it accessible on the web.
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Problem Set DescriptionProblem Set DescriptionChoosing the parameters of the set of AC problems to generate.
Problem Set DescriptionProblem Set DescriptionChoosing the parameters of the set of AC problems to generate.
% 1 2 3 4 5 6 7param = query({'311_CA_21.11.2004', '30','1','RO', 'd', 'g', 'no'}, ... { 'SetID - problem set label (Year of Study/Group ID/Date)', ... % 1 'Nproblems - number of problems', ... % 2 'StartID - ID of the first problem', ... % 3 'Language - RO/EN', ... % 4 'Out_medium - s = save on hard, d = display' ... % 5 'Represent - t = tree, g = graph, b = both, other char = none' ... % 6 'Entropy - yes/no = compute and display graph entropy' ... % 7 }, ... 'Set Parameters');
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CChoosing Variables & hoosing Variables & Independent ParametersIndependent ParametersCChoosing Variables & hoosing Variables & Independent ParametersIndependent Parameters
% 1 2 3 4 5 6 7 8 9 10 11 12 13param = query({'4','7','4','4','1', '4', '4', '0', '1', '4', '4', '2', 'Y'}, ... { 'Nnodes - number of nodes', ... % 1 'Nbranches - number of branches', ... % 2 'I_chord_a_max - maximum absolute value of chord current active components [A]', ... % 3 'I_chord_r_max - maximum absolute value of chord current reactive components [A]', ... % 4 'R_twig_min - minimum value of twig resistences [Ohms]', ... % 5 'R_twig_max - maximum value of twig resistences [Ohms]', ... % 6 'X_twig_max - maximum absolute value of twig reactance [Ohms]', ... % 7 'E_twig_max - maximum absolute value of twig Re & Im emf-s [V]', ... % 8 'R_chord_min - minimum value of chord resistences [Ohms]', ... % 9 'R_chord_max - maximum value of chord resistences [Ohms]', ... %10 'X_chord_max - maximum absolute value of chord reactance [Ohms]', ... %11 'nJ - number of branches with current sources', ... %12 'CrossLinks - Y/N - mutual inductances and controlled sources'... %13 }, ... 'Circuit Variables & Independent Parameters');
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MMutual inductive couplings and utual inductive couplings and controlled source parameterscontrolled source parametersMMutual inductive couplings and utual inductive couplings and controlled source parameterscontrolled source parameters
if strcmp(lower(CrossLinks), 'y') % 1 2 3 4 5 6 7 8 9 10 11 12 13 14 param = query({'0', '0', '0', '0', '0', '3', '0', '3', '0', '5', '0', '5', '0', '4'}, ... { 'nEI - number of current controlled voltage sources E = Zt * I',... %1 'nJU - number of voltage controlled current sources J = Yt * U', ... %2 'nEU - number of voltage controlled voltage sources E = A * U', ... %3 'nJI - number of current controlled current sources J = B * I', ... %4 'nM - number of mutual inductive couplings', ... %5 ['Zta_max - maximum absolute value of transfer resistance [Ohms]' char(10) ... ' Ea + j.Er = (Zta + j.Ztr) (Ia + j.Ir)'], ... %6 'Ztr_max - maximum absolute value of transfer reactance [Ohms]', ... %7 ['Yta_max - maximum absolute value of transfer conductance [Siemens]' char(10) ... ' Ja + j.Jr = (Yta + j.Ytr) (Ua + j.Ur)'], ... %8 'Ytr_max - maximum absolute value of transfer susceptance [Siemens]', ... %9 ['Aa_max - maximum absolute value of voltage gain active component' char(10) ... ' Ea + j.Er = (Aa + j.Ar) (Ua + j.Ur)'], ... %10 'Ar_max - maximum absolute value of voltage gain reactive component', ... %11 ['Ba_max - maximum absolute value of current gain active component' char(10) ... ' Ja + j.Jr = (Ba + j.Br) (Ia + j.Ir)'], ... %12 'Br_max - maximum absolute value of current gain reactive component', ... %13 'XM_max - maximum value of mutual inductive reactance [Ohms]' ... %14 }, ... 'Selection of mutual inductive couplings and controlled source parameters');
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Circuit TopologCircuit TopologyyCircuit TopologCircuit Topologyy
C_nodes_twigs = GenerateTree(Ntwigs, mode)
ShowTree(C_nodes_twigs, SetID, k)
ShowGraphNet(C_nodes_twigs, C_nodes_chords, SetID, k)
C_nodes_chords = GenerateCoTree(C_nodes_twigs, Nchords)
C_twigs_chords = EssIncid(C_nodes_twigs, C_nodes_chords)
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Tree GenerationTree GenerationTree GenerationTree Generation
31 20 54
function C_nodes_twigs = GenerateTree(n, mode)C_nodes_twigs = zeros(n, n);rand('state',sum(100*clock));r = rand(2,n);c = 2 * ( r(2, :) >= 0.5 ) - 1;m = 0;for k = 1:n s = ceil( (k-m)* r(1, k) + m-1 ); f = k; if s>0, C_nodes_twigs(s, k) = c(k); end C_nodes_twigs(f, k) = - c(k); if mode == 's', m = s; endend
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C_nodes_twigs =
-1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 -1 -1 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 -1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 -1 1 0 0 0 0 0 0 0 -1
C_nodes_twigs =
1 -1 0 0 0 0 -1 0 0 1 0 0 -1 0 0 0 0 0 1 0 0 -1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 -1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1
C_nodes_twigs =
-1 0 1 0 1 0 0 0 0 -1 0 0 0 0 1 0 0 0 -1 1 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 -1 1 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 -1
ExamplesExamples
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Cotree GenerationCotree GenerationCotree GenerationCotree Generation
1
2 10
3
4 5
6
7
8
9
11
12
Starts from the chosen tree
Chords are introduced between nodes chosen randomly from the class of nodes with the lowest rank (lowest number of connected branches).
This order assures the best connectivity of the circuit for a given number of chords.
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ExamplesExamples
C_nodes_chords =
0 0 0 0 0 0 1 0 0 0 -1 0 0 0 -1 0 0 0 -1 0 0 0 0 1 0 0 1 0 0 0 0 -1 0 0 0 -1 -1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 -1 0 0 0 0 1 0 0 0 1 0 0 0 -1 0 0 0 -1 0 0 0 0 -1 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 -1 0 0
C_nodes_twigs =
-1 0 1 0 1 0 0 0 0 -1 0 0 0 0 1 0 0 0 -1 1 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 -1 1 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 -1
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Tree PlotTree Plot
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Circuit Parameter and Variable GenerationCircuit Parameter and Variable Generation
Chord currents Twig currents Twig voltages Chord voltages Chord emf’s
cI cI
ctct II ctct II
tttt EIZU tttt EIZU
ttcc UU T ttcc UU T
cccc UIZE cccc UIZE
TtctU cU
tI cI tc
1
tE
tZ
1
cY
cJ
Chord currents Twig currents Twig voltages Chord voltages Chord emf’s
TtctU
cU
tIcI
tc
1
tE
tZ 1
cZ
cEcE cJ cY cY
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Global Circuit Variables Global Circuit Variables
c
t
E
EE
c
t
J
JJ
c
t
U
UU
c
t
I
II
Concatenate the matrices for tree & cotree
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Current sources (change of independent voltage source emf’s)
JZEE new
Converting Voltage Sources to Current SourcesConverting Voltage Sources to Current Sources
ZZ
E Enew =E - Z J
J
Convert nJ voltage sources to current sources
[E, J] = ConvertE2J_AC(E, Z, nJ);
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Controlled sources (change of independent voltage source emf’s)
IZEE tnew
UYZEE tnew
UAEE new
IBZEE new
IZE tcontrolled
UYJ tcontrolled
UAE controlled
IBJ controlled
Cross ParametersCross Parameters
Mutual reactances
[E, J, Zt, Yt, A, B, XM] = ControlledSources_AC(E, J, I, U, Z, ... nControl, nEI, nJU, nEU, nJI, nM, ... Zta_max, Ztr_max, Yta_max, Ytr_max, … Aa_max, Ar_max, Ba_max, Br_max, XM_max);
inducednew EEE IXE Minduced j-
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Web AccessibilityWeb AccessibilityWeb AccessibilityWeb Accessibility
The system will be accessible on the INTERNET, to allow remote use, for both professors and students
Partial examination of problems will be done on the computer,In a face-to-face or remote setting.
The web accessibility is currently partially functional and partially under development
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PlatformPlatformPlatformPlatform
Web server:Tomcat 4.1.29 - http://jakarta.apache.org/tomcat
DB server:MySQL 3.2x - http://www.mysql.com/
Scripts tool:Apache ANT - http://ant.apache.org/
Versioning server:
CVS - http://www.cvshome.org/, http://www.wincvs.org/
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ConclusionsConclusionsConclusionsConclusions
• A specialized e-learning system able to automatically generate large sets of circuit analysis problems, all with the same difficulty,but having different topological structures and parameters of the Circuits, has been designed, implemented and experimented.
• The problems are for use both during the tutorials and for examinations, thus -- despite the inherent risk for an engineer understanding of reality -- all parameters and variables describingthe circuits should be integers to facilitate the computational task.
• Problems and solutions should be stored automatically on disk in distinct directories, with files referring to the same problem having related labels
• The system will be developed for making it accessible on the web
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COMMISSION OF THE EUROPEAN COMMUNITIES EDUCATION AND CULTURE DIRECTORATE - GENERAL SOCRATES - Minerva Transnational Projects in the field of Information and Communication Technology and Open and Distance Learning in Education
This work has been partially supported by the Socrates Minerva Project 87574-CP-1-2000-1-RO-MINERVA- ODL
Artificial Intelligence and Neural Network Tools for Innovative ODL
(http://www.dsp.pub.ro/)
This product does not necessarily represent the Commission's official position.
Acknowledgment and disclaimerAcknowledgment and disclaimer
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• Vrije Universiteit Brussels, BE Prof. Jan Cornelis, Vice-Rector
Prof. Edgard Nyssen, Prof. Rudi Deklerck
• Universität Erlangen-Nürenberg Prof. Manfred Kessler, Director Institute für Physiologie und Kardiologie
• Université de la Rochelle , FR Prof. Michel Eboueya, Assistant Director of Information and Industrial Imaging Lab.
• Universidade Nova de Lisboa, PT Prof. Adolfo Steiger Garcao, President of UNINOVA Prof. Jose Manuel Fonseca
• University of Edinburgh, UK Dr. Judy Hardy, Applications Consultant at EPCC Dr. Mario Antonioletti
• Patras University, GR Prof. Nicolas Pallikarakis, Coordinator of BioMedical Engineering Scool Res. Cristian Badea
• Equant Romania, RO Dr. Pavel Budiu, Strategy Manager
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