Knowledge Management and Virtual Learning machines support learning

Knowledge Management and Virtual Learning machines support learning individuals Prof. dr. Walter R. J. Baets Director Graduate Programs Euromed Marseille – Ecole de Management Professor Information, Innovation and Knowledge Universiteit Nyenrode, The Netherlands Business School

NOTION The Nyenrode Institute for Knowledge Management and Virtual Education Achmea Microsoft Atos/Origin Philips Sara Lee/DE

Wanderer, your footprints are the path, and nothing more; Wanderer, there is no path, it is created as you walk. By walking, you make the path before you, and when you look behind you see the path which after you will not be trod again. Wanderer, there is no path, but the ripples on the waters. Antonio Machado, Chant XXIX Proverbios y cantares, Campos de Castilla, 1917

A very great musician came and stayed in our house, He made one big mistake … He was determined to teach me music and consequently, no learning took place. Nevertheless, I did casually pick up from him a certain amount of stolen knowledge. Rabindranath Tagore

The problem You don’t know what you don’t know You only know what you don’t know when you need it … then, all classical learning comes too late

Hence Just-in-time Just-enough Learning-by-doing Learning-while-doing Learning from past (corporate) experiences

By the way It has to do with the pedagogical metaphor Empty Ship’s metaphor versus Traveler's metaphor

Just like the optimal process does not exist The optimal learning solution does not exist either Strive for a 60 % solution

The advantage of e-learning technologies Communicative tools on a wider (flexible) scale Search engines

Origin of Taylor’s thinking in Management The computer: attempt to automate human thinking Manipulating symbols Modelling the brain Represent the world Simulate interaction of neurones Intelligence = problem solving Intelligence = learning 0 -1 Logic and mathematics Approximations, statistics Rationalist, reductionist Idealised, holistic Became the way of building computers Became the way of looking at minds

Some principles that apply to knowledge 1. Complex Adaptive Systems: unpredictability 2. Irreversibility of time principle (Prigogine) 3. Behavior far away from equilibrium (Prigogine) 4. Autopoiese (Varela) 5. Embodied mind (Varela) 6. Enacted cognition (Varela) 7. Artificial life (Langton) 8. Emergent behavior (agents; Holland) 9. Law of increasing returns (Arthur)

OADI-cycle/Individual learning ASSESS DESIGN Environmental response OBSERVE IMPLEMENT Individual double-loop learning Individual action INDIVIDUAL MENTAL MODEL & FRAMEWORKS Single-loop learning Organizational double-loop learning ORGANIZATIONAL ROUTINES & SHARED MENTAL MODELS ENVIRONMENT Organizational action

Inter-Action EXPERIENCES Contextual Inter-Action CONTEXTUAL KNOWLEDGE INDIVIDUAL MENTAL MODEL & TACIT KNOWLEDGE SHARING AND COMMUNICATION SHARED MENTAL MODEL & KNOWLEDGE REPOSITORY 4 4 4 4 Contextualization Real life Databases Procedures Simulators Executive seminars Concepts Theory The Hybrid Business School .

IT for the Corporate Knowledge Approach t Struc uring Advis CASE BASED REASONING SYSTEM Sharing and Communicating the Emergent ult Ru le ARTIFICIAL NEURAL NETWORKS & OTHER A. I. TECHNIQUES Co ns at io s 4 DATA BASES 4 LEARNING Learning Material Expertise 4 4 COMMUNICATION PLATFORM / NEURAL NETWORKS n ENVIRONMENT SIMULATORS EXPERT SYSTEMS COMPUTER BASED TEACHING VIDEOCONFERENCING IT for the Hybrid Business School

Some interesting technologies Artificial Neural Networks Genetic Algorithms Genetic Programming Fuzzy Logic Artificial life/Agent simulations Negotiating Agents Semantic Search Engines Case Based Reasoning Language technologies Machine learning technologies Conversational technologies

Your knowledge infrastructure Ownership (search/learn principles) Remains with those that use it Those that want to learn decide what to learn Just-in-time, just-enough Culture Learning platform Turn XYZ into a learning culture (via projects) Provide an ICT infrastructure that allows full access and sharing facilities Rewarding Content What knowledge to share: • explicit • implicit • learned

Learning platform and search/learn principles The knowledge net Implicit knowledge (case base) Case based reasoning system Cases stored in an adapted way A methodology for case analysis and storage Corporate knowledge repository Notion Learned knowledge (case base) Explicit knowledge that is enhanced via experience Using the same methodology for implicit knowledge Interviews with key knowledge owners Search engine Explicit knowledge (database) Open learning platform Collaborative tools Dedicated search engines Accessibility for all Open to connect ‘any’ application Solution for e-learning The user with its learning agenda

Some (Best) Practices Xerox Heineken Atos Origin Sara Lee/DE Mc. Kinsey Dutch Police Knowledge Network General practitioners and hospital knowledge

INTERNET INTRANET S A KIL CT L IV S/ IT IE S A TYPICAL MANAGEMENT DIPLOMA COURSE 3 O % SELF-STUDY (learning-by-doing) 2 O % WORKSHOPS 50 % PROJECT WORK C A HYPERTEXT S DATABASE E S CONCEPTS PC CD ROM LEARNING/DATABASE SOFTWARE EXECUTIVE COURSES WWW site + other knowledge applications BOOKS

Executive Programs E-learning solutions Design of corporate virtual universities Modules of the MBI&I E-learning support for classroom activities Workshops on innovation Action research programs

Over a period of 18 months Developing an intrapreneurial project (1) 6 9 courses based on Developing an on-campus virtual (tutor weeks intrapreneurial project (2) supported) individual of and group study workshops E-ntrepreneurships project 700 hours 900 hours 300 hours

Methodology Actions The Hybrid Business School Building Blocks Brainstorm cases A Skil cti ls vi tie s Implicit knowledge Practices content Knowledge platform r pe y H ed k lin Concepts Search engine r pe y H ed Explicit k lin knowledge ICT platform culture Ownership learn/search Learning Agenda (Pers. Development) learner + learning agenda 4 Brainstorms Project team • Notion • MD/HRM • Line mgt • IT • Marketing/R&D IT/Application plan Outcomes (company-specific) White Paper (Board approval) E-learning view 4 Action plans (Board approval) Infrastructure (Plan) Architecture

Knowledge Management and Virtual Learning machines support learning individuals Prof. dr. Walter R. J. Baets Philips Chair in Information and Communication Technology Universiteit Nyenrode, The Netherlands Business School