Creative Environments

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Format: Hardcover
Pub. Date: 2007-06-03
Publisher(s): Springer Verlag
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Summary

"Creative Environments" is a follow-up on the book Creative Space in the same series and by the same authors, serving this time as editors of a broader book on computational intelligence and knowledge engineering tools for supporting knowledge creation. This book contains four parts. The first part presents a further development of models of knowledge creation presented already in Creative Space, in particular the Triple Helix of normal academic knowledge creation and a new, integrated model of normal academic and organizational knowledge creation, called Nanatsudaki (seven waterfalls) Model. The second part presents computational intelligence tools for knowledge acquisition by machine learning and data mining, for debating, brainstorming, for roadmapping and for integrated support of academic creativity. The third part presents the use of statistics for creativity support, virtual laboratories, gaming and role playing for creativity support, methods of knowledge representation and multiple criteria aggregation, distance and electronic learning. The last part addresses knowledge management and philosophical issues and contains chapters: on management of technology and knowledge management for academic R and D; on knowledge management and creative holism or systems thinking in the knowledge age; on technology and change or the role of technology in knowledge civilisation; on the emergence of complex concepts in science; and the final chapter on summary and conclusions, including a proposal of an integrated episteme of constructive evolutionary objectivism, necessary for the knowledge civilization age.

Table of Contents

Basic Models of Creative Processes
Preliminariesp. 3
Introductory Remarksp. 3
Conclusions from Creative Spacep. 3
Descriptive and Prescriptive Models of Knowledge Creationp. 10
Ba and Creative Environmentsp. 11
Philosophical Questionsp. 13
Knowledge Management and Creative Holismp. 13
Technology and Changep. 14
The Processes of Emergence of Basic Concepts and the Problem of a New Episteme in Knowledge Civilisationp. 16
The Contents of this Bookp. 18
Acknowledgementsp. 23
Testing the Triple Helix Modelp. 25
Introductory Remarksp. 25
Knowledge Creation Processesp. 27
A Survey of Scientific Creativity Supportp. 30
Background and Goalsp. 30
Questionnaire Designp. 31
Study Instrumentsp. 32
Analysis of Survey Resultsp. 32
Reference Profiles and Achievement Functionsp. 34
The Application of Reference Profiles in Our Researchp. 37
Survey Findingsp. 40
Discussionp. 42
Conclusionsp. 44
Knowledge Sciences and JAIST Nanatsudaki Modelp. 47
Introductory Remarksp. 47
Knowledge Management versus Technology Managementp. 48
The Emergence of Knowledge Sciencesp. 50
The Need for a Prescriptive Synthesis of Knowledge Creation Processesp. 52
The Nanatsudaki Modelp. 54
Objective Settingp. 56
Hermeneuticsp. 58
Socializationp. 59
Brainstormingp. 60
Debatep. 61
Roadmappingp. 62
Implementation: Experimental Workp. 63
Closure: A Different Cycle of the Entire Processp. 64
Relation to Experimental Resultsp. 65
Conclusionsp. 66
Tools for Supporting Basic Creative Processes
Knowledge Acquisition by Machine Learning and Data Miningp. 69
Introductory Remarksp. 69
Machine Learning, Knowledge Discovery and Data Miningp. 71
Examples of Progress in Machine Learning and Data Miningp. 78
Scientific Data Miningp. 79
Mining Medical Datap. 81
Mining Genomic and Proteomic Datap. 83
Mining Materials Science Datap. 84
Experiences of Data Mining in Telecommunicationsp. 85
An Example of Complex Interaction Processp. 87
Event Miningp. 89
Exchanging Tacit Knowledgep. 91
Conclusionsp. 91
Creativity Support in Brainstormingp. 93
Contents and Introductory Remarksp. 93
The Meaning and the History of Brainstormingp. 93
Models of the Brainstorming Processp. 95
Software for Brainstorming Supportp. 99
The KJ Method and Creative Problem Solving Systemsp. 100
GRAPE Decision Support Groupwarep. 103
Support System for Consensus Making: Group Coordinatorp. 108
Novel Approaches to Brainstorming Supportp. 115
The Use of Brainstorming in Normal Academic Knowledge Creationp. 116
The Enrichment of Brainstorming by Normal Academic Creative Processesp. 119
Concluding Remarksp. 125
Debating and Creativity Supportp. 127
Introductionp. 127
Existing Software for Supporting Debate and Knowledge Creationp. 129
General Groupwarep. 129
Specific Software or Platforms for Debate and Knowledge Creationp. 130
PathMakerp. 130
Group Argumentation Environment (GAE)p. 134
Electronic Common Brain (ECB)p. 146
Rational and A-rational Aspects of Debate and Related Software Requirementsp. 148
Conclusionsp. 153
Creativity Support for Roadmappingp. 155
Introductory Remarks and Contentsp. 155
Science and Technology Roadmapsp. 156
Roadmapping as a Knowledge Creation Processp. 161
I-System and Knowledge Creation Support in Roadmappingp. 163
Interventionp. 165
Intelligencep. 165
Involvementp. 166
Imaginationp. 167
Integrationp. 169
General Features of Information Technology Support for Roadmappingp. 169
Case Studies - Making Academic Research Roadmaps in JAISTp. 170
An Interactive Planning (IP) - Based Roadmapping Approachp. 172
A Web-based Roadmapping Support Systemp. 178
Experience in Applications of Roadmapping at JAISTp. 181
Individual Research Roadmapsp. 181
Case Study: Roadmaps for Development of Fuel-Cell Technologyp. 183
Conclusionsp. 188
Integrated Support for Scientific Creativityp. 191
Introductionp. 191
User Requirements for a CEp. 192
Models of Creative Processesp. 194
Three Models of Knowledge Creationp. 194
Nanatsudaki Modelp. 195
Experiences with Implementation of CE Prototypesp. 195
Creative Environment at JAISTp. 196
SCI-Blog: a Prototype CE at PJIITp. 199
Scenarios of User Interaction with a CEp. 201
Planning a New Research Projectp. 201
Searching for Related Workp. 202
Describing and Sharing Read Literaturep. 203
Review of Other Users' Workp. 203
Seminar Discussionsp. 203
Planning an Experimentp. 204
Modular Architecture of a CEp. 204
Personal Workspace Modulep. 205
Information Retrieval Modulep. 205
Group Communication Modulep. 206
Planning and Roadmapping Modulep. 207
Experiment Modulep. 208
Data Representation and Metadata in a CEp. 209
Database Structure of a CEp. 209
RDF/XML File Repositories for Semantic Web Documentsp. 210
Security of Information in a CEp. 211
Authentication and Privacyp. 211
Access Controlp. 212
Evaluation of Creative Environmentsp. 212
Conclusionsp. 213
Diverse Tools Supporting Creative Processes
Statistics for Creativity Supportp. 217
Introductory Remarksp. 217
The Grammar of Technology Developmentp. 217
Lessons from Applications of Statistical Tools for Quality Controlp. 218
Statistical Experiment Designp. 222
Orthogonal Experiment Design and Its Applicationsp. 222
History of Statistical Experiment Design and the Taguchi Methodp. 227
A Quadratic Response Surface Approximationp. 228
Possibilities of Creativity Support and Conclusionsp. 230
Virtual Laboratoriesp. 233
Introductory Remarksp. 233
Knowledge-based Problem Solvingp. 234
Knowledge Integrationp. 237
Models for Knowledge Integration and Creationp. 237
Knowledge Integration in Modelsp. 239
Collaborative Modellingp. 241
Model Specificationp. 242
Datap. 242
Model Analysisp. 244
Virtual Organisationsp. 244
Laboratory Worldp. 246
Knowledge Creation by Model Analysisp. 247
Model-based Problem Solvingp. 247
Modelling Technologyp. 248
Model Analysisp. 249
Structured Modelling Technology (SMT)p. 251
Conclusions: Virtual Modelling Laboratoriesp. 253
Gaming and Role Playing as Tools for Creativity Trainingp. 255
Introductory Remarksp. 255
Current Directions in Gaming, Negotiation, and Game Theoryp. 256
Gaming in Business Educationp. 258
What is the Aim of Gaming Simulation?p. 258
Gaming Simulation Efforts in a Business Schoolp. 259
Procedure of the Gaming Simulationp. 260
Macro-cycle and Micro-cyclep. 260
Experiences in Gaming Simulationsp. 261
Significance of Gaming Simulation at a Business Schoolp. 262
Development of Business Simulation Exercisesp. 263
Relations in Gaming Simulation: Facilitator and Designerp. 264
Gaming Simulation and Knowledge Creationp. 265
Role Playing and Negotiations for Problem Solving and Idea Formationp. 266
Basic Concepts of Coalition Game Theoryp. 266
Usual Reference Pointsp. 268
Achievement Functions and Reference Point Approachp. 270
Special Reference Pointsp. 272
The Case of Empty and Extended Corep. 274
Example: Negotiating a Merger of High-tech Firmsp. 275
Lessons from the Examples and Simulated Negotiationsp. 278
Conclusionsp. 279
Knowledge Representation and Multiple Criteria Aggregationp. 281
Introduction: the Need for Knowledge Representation and Integrationp. 281
Knowledge Definitionsp. 283
Representing Knowledge in Logical Formp. 285
Production (Decision) Rulesp. 285
Decision Tablesp. 287
Decision Treesp. 289
Representing Knowledge in Structural Formp. 290
Networksp. 290
Framesp. 292
Description Logicsp. 293
The Problem of Integration of Knowledgep. 294
Multiple Criteria Aggregation for Knowledge Integrationp. 295
An Approach to Multiple Criteria Aggregation, Ranking and Classificationp. 297
Compensatory vs. Noncompensatory Criteria, Subjective vs. Objective Rankingp. 302
Hierarchical Aggregation of Criteriap. 306
Example of Six Divisions of a Corporationp. 307
Multiple-Attribute Aggregation under Uncertainty for Decision Makingp. 309
Problem Descriptionp. 310
Evaluation Analysis Modelp. 313
Dempster-Shafer Theory of Evidencep. 314
The ER Approach for Attribute Aggregationp. 315
From Extended Decision Matrix to Evaluation Matrixp. 318
Conclusionsp. 319
Distance and Electronic Learningp. 321
Introductory Remarksp. 321
The Role of Electronic and Distance Learning and Teaching in the Knowledge Civilisation Erap. 322
Current Achievements and Trends of Electronic and Distance Learningp. 325
Types of e-Learningp. 325
The Characteristics of e-Learning in a Narrow Sensep. 326
Searching for a Better Combination of e-Learning Technologiesp. 328
The Importance of Education Strategy in an Organisation: the Concept of a Learning Organisationp. 330
Integrated Evolutionary Learning Model from a Practical Point of Viewp. 331
Establishment of Learning Strategyp. 331
What Should Be Learned?p. 331
Evolutionary Cyclingp. 333
Conceptual Model of Integrated Evolutionary Learningp. 333
Market Driven Development vs. Long Term Trendsp. 334
Current Trends and Problems of Multimedia Technologyp. 336
Ambient Intelligence vs. Electronic Learningp. 338
Features of Intelligent Tutoring Systems and Commercial Standardsp. 340
SLIT: A Conceptual Model of an Intelligent Tutoring Systemp. 342
The Use of Data Mining in Intelligent Tutoring Systemsp. 344
Course Model, Log Files and Decision Tablesp. 345
Virtual Students for Testing the Effectiveness of Data Mining Methodsp. 346
Simulations Conditions and Test Resultsp. 348
Conclusions: Creativity Support vs. Electronic Learningp. 349
Knowledge Management and Philosophical Issues of Creativity Support
Management of Technology in Academic Researchp. 353
Introductionp. 353
What is Management of Technology (MOT)?p. 354
Establishment of MOT Courses at JAISTp. 357
Development of the Foundations of MOTp. 360
Development of MOSTp. 361
The Significance of MOST: from Implicit to Explicit Knowledgep. 363
Experiences and Problems with MOSTp. 365
Conclusionsp. 368
Knowledge Management and Creative Holism in the Knowledge Agep. 369
Introductionp. 369
Creative Holism - Basic Conceptsp. 371
The Implication of Knowledge in Organisationsp. 373
Static Substance Knowledgep. 375
Dynamic Process Knowledgep. 377
Knowledge Management, Creative Holism, and Creative Spacep. 378
Conclusionsp. 383
Technology and Change: The Role of Technology in the Knowledge Civilization Erap. 385
Introductory Remarksp. 385
The Big Change in Last Fifty Yearsp. 386
The Era of Knowledge Civilizationp. 387
Diverse Perceptions of a New Erap. 387
The Conceptual Platform and the Episteme of a Civilisation Erap. 388
What Happened at the End of the Industrial Civilization Erap. 391
The Three Separate Spheres of Technology, Hard Sciences and Social Sciences with Humanitiesp. 393
Why Separate Spheres?p. 393
The Dominant Episteme of a Sphere and Its Limitationsp. 395
The Views of Philosophy of Technologyp. 396
The General Impression of a Technologistp. 396
A Few Acceptable Viewsp. 397
The Dangers of Misunderstandingsp. 398
How Social Sciences and Humanities Present the Episteme of Hard Sciences and of Technologyp. 398
Theories of Instructional Designp. 399
Soft vs. Hard Systems Thinkingp. 402
Post-modern Social Science and Sociology of Sciencep. 404
What Technology Is and What It Is Notp. 406
The Definition of Technology by Heidegger as Understood By a Technologistp. 406
The Warnings of Heidegger as Understood By a Technologistp. 406
The Sovereign though not Autonomous Position of Technologyp. 407
The Reverse Relation of Science and Technologyp. 408
Two Positive Feedback Loopsp. 410
What Will Be the Technology of the Knowledge Erap. 413
Some Examples of Technology of the Knowledge Erap. 414
New Warnings: What We Must Be Careful Aboutp. 415
Conclusionsp. 415
The Emergence of New Concepts in Sciencep. 417
Introductory Remarksp. 417
Conceptual and Scientific Changep. 418
Mathematical Intuition and Platonism in Mathematics. The Idea of the Reconstruction of the Hermeneutical Horizonp. 420
Platonism and Hermeneutical Conditions for Emergence of Conceptsp. 425
An Example of Emergence of Concepts in Mathematicsp. 427
The Ancient Intuitive Model of Euclidean Geometryp. 429
The Emergence of Absolute Spacep. 432
The Intuitive Analysis of Conceptsp. 433
The Schema of the Intuitive Analysis of Conceptsp. 437
Conclusions and Remarksp. 442
Summary and Conclusionsp. 445
Introductory Remarksp. 445
Summary of Contributionsp. 445
The Emergence of an Integrated Episteme of the Knowledge Civilisation Erap. 456
What Technology and Hard Science Can Proposeas an Emerging Episteme of the Knowledge Civilisation Erap. 457
Constructive Evolutionary Objectivismp. 462
The Problem of Truth in the Knowledge Erap. 464
Concluding Remarksp. 466
Referencesp. 469
Indexp. 497
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