Prof. Raimo P. Hämäläinen Systems Analysis Laboratory Helsinki University of Technology

eLearning / MCDA

Systems Analysis LaboratoryHelsinki University of Technology

eLearning Decision Making

eLearning sites on:Multiple Criteria Decision Analysis

Decision Making Under UncertaintyNegotiation Analysis

Prof. Raimo P. Hämäläinen

Systems Analysis Laboratory

Helsinki University of Technology

eLearning / MCDASystems Analysis LaboratoryHelsinki University of Technology

The OR-World project

Funded by the European Commission, IST Programme

Partners form industry and university

University of Paderborn (coordinator)

Helsinki University of Technology

Delft University of Technology

Lufthansa Systems Berlin

Regioworld

Dual-Zentrum


ORWorld

WWW based framework for sharing learning material for Operations Research

Interdisciplinary subjectMethods, applications, case studies

Well suited for hypermediaVisualization, simulation, animation

Joint effort to develop a modular study programme

To be used in universities and companies worldwide


SAL e-learning resources in decision making

Value Tree Analysis Group Decisions and Voting

Uncertainty & RiskNegotiation Analysis


Internet standards

Today’s standard HTML is unstructured No clear separation between

Content, Structure, Representation

Reuse of the existing material problematic Multilingual versions

No inherent possibility to add specific metadata Need for XML (extensible markup language)


Split of content, structureand representation in XML

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reotiuoert dfgdf dfg fg fgdeteroituertfg fgdg fgryko

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Complex, confusing decision problems with multiple objectives have been made since the start of the civilisation. The history of the decision analysis is not that long, however. In 1730s Daniel Bernoulli (1738) first used the concept of utility when explaining the evaluation of a particular uncertain gable known as St Petersburg paradox....

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Structure ContentsInstructions

Visual representation

LMMLLOM

XSL

HTMLPDF

XML


Learning objects

Content module 2

Wrapping material on a higher level Reusable components formulated in XML Classification by meta tags

Media Element-Text, animation,simulation, video,

audio

Learning element

Content module 1Them

atic

met

a str

uctu

re

XSL

HypermediaNetwork

Course

TextPDFHTML


XML elementsCASE

STRUCTURING

1…*

PROBLEM1...*

1

MODELLING

METHOD

1…*

Partition elements

Editing elements

1…*

1…*

*

1…*?Content elements

ANALYSISEditing elements

1

SYNTHESIS

Content elements

1…*

1…*

1…*

Editing elements

1…*

Partition elements

Editing elements

1…*

*

1…*

INPUT

Partition elements

Editing elements

1…*

*

Partition elements

Editing elements

1…*

1…*

OUTPUT

Partition elements

Editing elements

1…*

1…*

Editing elements

1…*

Partition elements


System architecture

Client Web browser

Client Web browser

OR-World server

Learning material

Evaluations:Opinions Online

OR-World server

Learning material

Evaluations:Opinions Online

HUT SAL serverSoftware:

Web-HIPREPrime Decisions

Joint GainsOpinions Online

(voting version)

HUT SAL serverSoftware:

Web-HIPREPrime Decisions

Joint GainsOpinions Online

(voting version)

Self Assessment & Grading

Quiz Star

Q&A Tool set

Self Assessment & Grading

Quiz Star

Q&A Tool set

Value Tree Analysis


Learning paths and modules

Learning path: guided route through the learning material Learning module: represents 2-4 h of traditional lectures and exercises

AssignmentsTheory VideosCases QuizzesLearningPaths Evaluation

Introduction to Value Tree AnalysisIntroduction to Value Tree Analysis

Module 3Module 3

Module 2Module 2

Value Tree Analysis


Learning modules

Theory• HTML pages

Theory• HTML pages

• motivation, detailed instructions, 2 to 4 hour sessions

Case• slide shows

• video clips

Case• slide shows

• video clips

Assignments• online quizzes

• software tasks

• report templates

Assignments• online quizzes

• software tasks

• report templates

Evaluation • Opinions Online

Evaluation • Opinions Online

Web software

• Web-HIPRE

• video clips

Web software

• Web-HIPRE

• video clips

AssignmentsTheory VideosCases Quizzes

LearningPaths Evaluation

Introduction to Value Tree Analysis

Module 3

Module 2Module 2

Value Tree Analysis


Theory

XML documents• divided in sections• colourful graphics and animations• pages in HTML format

introduces concepts and theory

Value Tree Analysis


Cases

Slide presentations• summary of theory• case specific material, problem description, methods, analysis,…• in Power Point and HTML formats• tests with XML + XSLT visualisation

Video clips• how to apply and use Web-HIPRE, Prime Decisions• an easy way to learn software use• help in practical issues

illustrates theoretical aspects, complements theory alternative learning route, learning by doing

Value Tree Analysis


Quizzes

Online Quizzes in Quiz Star• multiple choice, true/false, short answer questions • grouped in sections• correct answers or references to MCDA material• results available for the instructor

for revising, self assessment, online exams

Value Tree Analysis


Video clips

Recorded software use with voice explanations (1-4min)

Screen capturing with Camtasia AVI format for video players

e.g. Windows Media Player, RealPlayer

GIF format for common browsers - no sound


Learning material onValue Tree Analysis

• Divided in sections • Theory and cases closely linked, but independent entities

AssignmentsTheory

Intro

Theoreticalfoundations

Preferenceelicitation

Problemstructuring

Videos

Cases

Step 1

Step 2

Step 4

Step 3

Quizzes

Quiz 1

Quiz 2

Quiz 4

Quiz 3


Value Tree Analysis

Value Tree Analysis


Theory

IntroTheoretical foundationsProblem structuringPreference elicitationSensitivity analysisBehavioural issuesCommunicating the resultsGroup decision makingSoftware

Value tree analysis in brief Bullet points to reduce

reading time Simple animations, figures Links to case part

bisektio_anim.gifSystems Analysis LaboratoryHelsinki University of Technology

AssignmentsVideosCases Quizzes

LearningPaths

Theory

Value Tree Analysis


Theory

Case X

AssignmentsVideosQuizzes

LearningPaths

Cases

Evaluation

Cases

AssignmentsTheory

Intro

Theoreticalfoundations

Problemstructuring

Preferenceelicitation

Job selection case• basics of value tree analysis• how to use Web-HIPRE

Car selection case• imprecise preference statements, interval value trees• basics of Prime Decisions software

Family selecting a car• group decision-making with Web-HIPRE• weighted arithmetic mean method

Job selection case• basics of value tree analysis• how to use Web-HIPRE

Car selection case• imprecise preference statements, interval value trees• basics of Prime Decisions software

Family selecting a car• group decision-making with Web-HIPRE• weighted arithmetic mean method


CasesJob selection case

Car selection case

Money versus design

• basics of value tree analysis

• how to use Web-HIPRE

• group decision making with Web-HIPRE

• weighted arithmetic mean method

• imprecise preference statements, interval value trees

• basics of PRIME Decisions

Family selecting a carValue Tree Analysis


AssignmentsTheory VideosCasesLearningPaths

Quizzes

Value Tree Analysis


Theory VideosCases QuizzesLearningPaths

Assignments

Report templates• detailed instructions in a word document• to be returned in printed format

testing the knowledge on the subject, learning by doing, individual and group reports

Software use• value tree analysis and group decisions with Web-HIPRE


Value Tree Analysis


Value Tree Analysis


Learning material

Value Tree Analysis


Working with Web-HIPRE

Value Tree Analysis

Value Tree Analysis


Video clips

VideosWorking with Web-HIPREStructuring a value tree Entering consequences of ...Assessing the form of value...Direct rating SMARTSMARTSWINGAHPViewing the resultsSensitivity analysisGroup decision makingPRIME method

AssignmentsTheory Cases QuizzesLearningPaths

Videos


Student evaluation

Value Tree learning module Helsinki University of Technology

59 students mainly second and third year

The University of Paderborn 95 students mainly first and second year

Assisted and non assisted groups Opinions-Online

Value Tree Analysis


Summary of student evaluation

Students enjoyed the session Only little difficulties They would like to work in similar environments Recommend the session to fellow students No major gender differences

Interactive results available at:http://www.orworld.hut.fi/mcdm/Learning-modules/Short-intro/evaluation-results.htm

Value Tree Analysis


Learning material on Group Decisions and Voting

AssignmentAssignmentTheoryTheory EvaluationEvaluationQuizQuiz

Group Decisions and Voting module

• One learning module• All material included in the module

Group Decisions and Voting


AssignmentAssignment EvaluationEvaluationQuizQuiz


TheoryTheory

Slide show in HTML + GIF format Group characteristics

Brainstorming

Nominal group technique

Delphi technique

Voting procedures

Value aggregation

Group characteristics

Brainstorming

Nominal group technique

Delphi technique

Voting procedures

Value aggregation

Theory


QuizAssignmentAssignment EvaluationEvaluation


TheoryTheory

Group Decisions and Voting quiz

• in Quiz Star server • 10 multiple choice and 3 true/false questions • correct answers or references to MCDA material• results available for the instructor

for revising, self assessment, online exams

QuizQuiz



AssignmentEvaluationEvaluationQuizQuiz


TheoryTheory AssignmentAssignment

Report template• detailed instructions in a word document• analysis of the voting results• to be returned in printed format

testing the knowledge on the subject, learning by doing, distributed decision making team, voting online over the Web

Software use• voting with Opinions-Online.vote• precompleted voting template• two voting rounds




Opinions-Online.vote:

• voting

• surveys

• group decisions

• advanced voting rules

Opinions-Online.vote:

• voting

• surveys

• group decisions

• advanced voting rules


Learning material onRisk and Uncertainty

Theory slides only Used in decision making course at HUT



Slideshow 1

Meanings of uncertainty

Interpretations of probability

Estimation of probabilities

Biases in probability elicitation

Calibration of experts

Updating of probabilities

Slideshow 1

Meanings of uncertainty

Interpretations of probability

Estimation of probabilities

Biases in probability elicitation

Calibration of experts

Updating of probabilities

Theory

Slideshow 2

Decision criteria

On the concept of risk

Risk measures

Utility function

Risk attitudes

Stochastic dominance

Decision trees

Influence diagrams

Slideshow 2

Decision criteria

On the concept of risk

Risk measures

Utility function

Risk attitudes

Stochastic dominance

Decision trees

Influence diagrams


Theory


Learning material onNegotiation Analysis

Mathematical modelling approach

Game and bargaining theory

Cases e-Commerce: Buyer – Seller Negotiations Resource Management: Problem of Commons

Joint Gains web software

Value Tree Analysis


Theory

IntroMultiple criteria decision analysisGame theoryAxiomatic bargainingNegotiation analysisMethod of improving directions

Main concepts in brief Colourful graphics


Assignments

Quizzes

VideosCasesTheory

Negotiation Analysis

Value Tree Analysis


Quizzes

Evaluation

Cases

AssignmentsTheory

Intro

MCDA

Game THeory

Axiomatic Bargaining

Buyer – Seller Negotiations• basics of a negotiation problem• solving a negotiation problem interactively• how to use Joint Gains

Problem of Commons• solving a negotiation problem by value functions

Buyer – Seller Negotiations• basics of a negotiation problem• solving a negotiation problem interactively• how to use Joint Gains

Problem of Commons• solving a negotiation problem by value functions


Assignments

VideosTheory Cases

Value Tree Analysis


QuizzesAssignments

VideosCasesTheory Quizzes


• 4-6 questions per theory section• the student is asked to interpret graphs

• 4-6 questions per theory section• the student is asked to interpret graphs

Value Tree Analysis


CasesTheory Quizzes

Videos Assignments

Report templates• detailed instructions available in MS word and HTML format• to be returned electronically

testing the knowledge on the subject, learning by doing

Theoretical partSoftware use• buyer - seller negotiations with Joint Gains


Assignments



Joint Gains negotiation

user can create his own case

2 to N participants (negotiating parties, DM’s)

2 to M continuous decision variables

linear inequality constraints

participants distributed in the web



Joint Gains negotiation support system

Case Administrator

Participant NParticipant 2Participant 1

World Wide Web

. . .WWW Browser WWW Browser WWW Browser

WWW Browser

Mediator softwareSERVER


Value Tree Analysis


Quizzes

Video clips


Assignments

CasesTheory Videos

Videos illustrating the use of Joint Gains:

• Creating a negotiation case • Negotiating with Joint Gains• Viewing the results


The module



Student evaluation

Introduction to game theory and negotiation learning module

Virtual university of Finland: Advanced web course on mathematical modelling

Students worked unassisted in Espoo, Tampere, Jyväskylä, Lappeenranta, Oulu and Geneve in one or two person groups 9 groups and 13 students



Summary of student evaluation

Enjoyed the session even if this module requires advanced skills

Willing to work in similar environments Found quizzes and the theory section useful Prefer this format to video lectures



Work package status - completed

Learning modules on 1. Value Tree Analysis

2. Group Decisions and Voting

3. Game Theory and Negotiation

Also material on Decision Making under Uncertainty Value tree analysis theory in XML and HTML formats

Description of new XML elements

Video clips modules 1 and 3

Slides in Power Point and GIF + HTML formats Evaluations of the first and third learning module


Dissemination

All modules Permanent use in SAL courses on decision making and

computational assignments in applied mathematics + national web course on mathematical modelling

OR-World partners

Facilitator training in EU Rodos project Other universities in the future Available at www.decisionarium.hut.fi

DSS software used by different universities


Web sites

www.dm.hut.fi Decision making resources at Systems Analysis Laboratory Links to all evaluations

www.mcda.hut.fi eLearning in Multiple Criteria Decision Analysis

www.negotiation.hut.fi eLearning in Negotiation Analysis

www.decisionarium.hut.fi Decision support tools and resources at Systems Analysis

Laboratory OR-World project site: www.or-world.com

Prof. Raimo P. Hämäläinen Systems Analysis Laboratory Helsinki University of Technology

Documents

Transcript of Prof. Raimo P. Hämäläinen Systems Analysis Laboratory Helsinki University of Technology