Proposition of a Systemic and Dynamic Model to Design Lifelong Learning Structure

At this stage we have to clarify what kind of model we would like to build. Then we will give some insights and elements on the conceptual framework and assumptions supporting the construction of the model. Lastly, we will propose a generic model to design a lifelong learning structure.

Clarification on Modeling

Our purpose is not to rewrite all the work and research done on this subject, but to focus on specific aspects useful for our purpose. (For more details see, for example, MIT Sloan School of Management System Dynamics Group, URL: http://web.mit.edu/sdg/www/.) Let us specify the key points.

The Purpose of the Model

"A model must have a clear purpose, and that purpose should be to solve a particular problem…. Beware the analyst who proposes to model an entire social or economic system rather than a problem. Every model is a representation of a system—a group of functionally interrelated elements forming a complex whole. But for the model to be useful, it must address a specific problem and must simplify rather than attempting to mirror in detail an entire system …. The usefulness of models lies in the fact that they simplify reality, putting it into a form that we can comprehend …. The art of model building is knowing what to cut out, and the purpose of the model acts as the logical knife. It provides the criterion about what will be cut, so that only the essential features necessary to fulfill the purpose are left …. The resulting models would be simple enough so that assumptions could be examined" (Sterman 1991).

The specific problem we address is how to design a learning process enabling concurrent development of individual competencies and maturity of organization in a perspective of the creation of value. The assumptions will be explained in the following.

The Type of Model

The distinction between optimization and simulation models is particularly important since these types of models are suited for fundamentally different aspects. 1) Optimization. "The output of an optimization model is a statement of the best way to accomplish some goal. Optimization models do not tell you what will happen in a certain situation. Instead they tell you what to do in order to make the best of the situation; they are normative or prescriptive models" (Sterman 1991). Limitations of Optimization: "Specification of the Objective Function, linearity, lack of feedback, and lack of dynamics" (Sterman 1991). 2) Simulation. "The purpose of a simulation model is to mimic the real system so that its behavior can be studied. The model is a laboratory replica of the real system, a microworld. Simulation models are descriptive. A simulation model does not calculate what should be done to reach a particular goal, but clarifies what would happen in a given situation. The purpose of simulations may be foresight (predicting how systems might behave in the future under assumed conditions) or policy design (designing new decision-making strategies or organizational structures and evaluating their effects on the behavior of the system). In other words, simulation models are ‘what if’ tools. Often such ‘what if’ information is more important than knowledge of the optimal decision. Every simulation model has two main components. First it must include a representation of the physical world relevant to the problem under study. In addition to reflecting the physical structure of the system, a simulation model must portray the behavior of the actors in the system. In this context, behavior means the way in which people respond to different situations, how they make decisions. The behavioral component is put into the model in the form of decision-making rules, which are determined by direct observation of the actual decision-making procedures in the system. Given the physical structure of the system and the decision-making rules, the simulation model then plays the role of the decision-makers, mimicking their decisions. In the model, as in the real world, the nature and quality of the information available to decision-makers will depend on the state of the system. The output of the model will be a description of expected decisions. The validity of the model's assumptions can be checked by comparing the output with the decisions made in the real system" (Sterman 1991). Limitation of Simulation: "Most problems occur in the description of the decision rules, the quantification of soft variables, and the choice of the model boundary" (Sterman 1991).

The model we plan to build is a simulation one with a "design" purpose in an "insight modeler" perspective (we mean using systems thinking diagramming and not, at that time, a complex quantitative model) (Graham and Sharon).

Conceptual Framework and Assumptions Supporting the Construction of the Model

First, we would like to formulate some preliminary remarks, and then, indicate the approaches, models, and assumptions supporting the construction of the model.

Preliminary Remarks

In spite of a different perspective, we wish this to be based on the contributions of the research and work in progress dealing with the three main aspects we mentioned previously. 1) Project management (ISO 10006, PMBOK Guide), 2) standard and guideline to define the work of the project management personnel and a basis for the assessment of their project management competencies (ICB and ANCSPM), 3) project management practices of organizations (current PMI project OPM3 on project management maturity model).

In the same way, we will adopt a viewpoint of assembler, i.e., initially at least, we will seek to put together existing models, but with the concern of giving it a system dynamics perspective.

The fact of relying on existing or under development standards is coherent with the quality seen from the perspective of theory of conventions (Gomez 1994): as socioeconomical constructs standards are the result of negotiation enabling reduction of complexity and uncertainty in the relations between the stakeholders of projects. (Visible demonstration of the socioeconomic adjustments produced by a convention of qualification [relation of customer-provider] on the one hand, and a convention of effort [relation of manager-project team] on the other hand, whose conjunction characterizes social and technical division of work.)

This implies the following issues:

1. The model proposes a theoretical framework to the problem of the training of the "project" teams. It does not pose it as obviousness, but exposes the logic of its development.

2. It is impossible to find measurements of competence that are not "deus ex machina" and invented for a special case, and this generates uncertainty and explains the existence of conventions of quality, i.e., standards that provide the elements of calibration.

3. The whole of the model constitutes a complex system: there is no causal linearity (such competence leads to such result), but permanent adjustments between competencies and their use.

4. We put at the same level of importance, the standard as built in the exchange, and the standard as a result of an effort of production. That means that we will pay detailed attention to the way in which the profession or the field of the management of projects evolves. The standard is thus not seen as a fixed fact.

Models and Approaches Taken into Account

As mentioned above, the construction of the conceptual model will be based on various models and approaches. (We indicate only some of them, but the list is not exhaustive.)

We have previously presented the four fields and basis of the work: knowledge management (Sveiby 1999; Bontis 1999), performance (Sveiby 1999; Bontis 1999), standards (ICB—IPMA, PMBOK Guide–PMI, ANCSPM, Maturity Model [OPM3]; Remy 1997; Saures 1998; Fincher and Levin 1997), and learning aspects (Senge et al. 1990, 1994, 1999; Kim 1993, 1994; Morecroft and Sterman 1994). These fields may be combined together through different ways to give different kind of models. Table 1 shows examples of combinations according to the different dimensions and fields.

Table 1: Models: Some Examples of Combinations According to the Different Dimensions and Fields

Types of Models	Dimensions S = Synchronic D = Diachronic I = Individual O = Organizational	Fields K = Knowledge Management L = Learning Aspects S = Standards P = Performance	References
Simulation-Design	DO	KLP	Widemon 1998
Simulation-Design	SDO	KLP	Declerck & Debourse 1997
Simulation-Design	SDIO	KLP	Romme & Dillen 1997
Simulation-Forecast	DO	SLP	Alarcon & Ashley 1993
Optimization	SO	SP	Griffith & Gibson 1997
Optimization	DO	P	Milosevic 1990
Optimization	DO	SP	Hartman & Ashrafi 1996
Optimization	SIO	SP	Beale 1991
Optimization	DI	L	Thamhain 1991
Optimization	SI	SP	Pettersen 1991
Optimization	SO	L	Globerson & Ellis 1994
Optimization	DIO	L	Communier 1998
Optimization	DIO	KLP	Peters 1997
Optimization	DIO	LP	Belout 1998
Optimization	DO	KLP	Hubbard 1990
Optimization	DI	LP	Turner 1998

Approaches integrate the different models into a coherent whole.

1. A systemic vision of the management of a project (Declerck and Debourse 1997; Wideman 1997, 1998; Leroy 1998).

2. An approach that highlights the links between competencies of the managers of projects and success of the projects (Project Manager Competency Development Framework under development by PMI).

3. An integrated model of development of competencies in management of project (Development Assessment of Project Management Competence–Crawford 1998).

4. The model of education of the leaders proposed by Hawrylyshyn (1977).

5. Design for learning in teams seen as communities of practice (Wenger 1998).

6. Principles of organizational learning according to a systems dynamic perspective (Kim 1993; Romme and Dillen 1997).

Assumptions

Before presenting the general system in which the model is included we need to clarify some assumptions.

Increasing competencies (individual, team, and organizational) leads to improved performance (Crawford 1998). Implementing standards and best practices (PMI, IPMA) leads to increased performance. But without a double-loop learning system, increasing competencies and implementing standards and best practices leads to limited performance if not poor performance (Kim 1997). We consider that general environment, context of the project, and contingencies affect the performance of people, tasks, project, organization, and stakeholders. They also affect the learning aspects (individual, team, and organizational) (Communier 1998; Wideman 1998). The systemic and dynamic model enables us to deal with different time horizons (from short-term to long-term).

The integration of these different elements leads us to propose the general system and the learning subsystem shown in Figure 3 and Figure 4.

Figure 3: Systemic and Dynamic Model to Design Architecture for Lifelong Learning: The General System

Figure 4: Systemic and Dynamic Model to Design Architecture for Lifelong Learning: The Learning Subsystem

Thus, the model suggested will have to allow the design for learning to answer three series of objectives:

The objectives of individual learning (project managers, project "people"): They are dependent on the gap between their present level (performance, experience, and knowledge) and their expected level. For example, if they need to reinforce their project management capacities, they will have to get Project Management Professional (PMP ) certification or prepare for IPMA project management certification according to their responsibilities, their experiences, and the nature of project they manage or are involved in (Hawrylyshyn 1977)—see Table 2.

Table 2: Individual Learning Level: A Design Framework (Hawrylyshyn 1977)

	Performance = f (Competence, Motivation, Occasion) Competence = f (a-Knowledge, b-Attitudes, c-Aptitudes) a, b, c Weightings = Functions of the position in the hierarchy of decision-making, nature of company, dimension, political, economic and social context, particular functional field, …
Individual Needs	Learning Categories	Learning Process	Learning Methods
Competence	Knowledge	Cognitive	Lecture or based on the didactic media, reading, conferences, discussions, films or audio-visual methods, programmed learning, CAL, exercises
	Attitudes	Emotional	Socio-economic, short speeches, speech in public, group dynamics, confrontations
	Aptitudes	Practical	Participating, real studies, exercise of the "basket-entry", method of the incident, method of the cases, exercise of simulation of decision-making, role play, consultancy work

The objectives of team training: The development of team competencies depends on many aspects—participation/reification, designed/emergent, local/global, identification/negotiation, engagement, alignment, and imagination (Wenger 1998)—and has a great influence on both individual performance and organizational performance (maturity levels, lessons learned). The level is the key of the learning process; it makes the link between individual learning and organizational learning. It integrates all the aspects developed in the other levels and represents a kind of mirror between them. This is also the level of the link between project team members and operational team members (Table 3).

Table 3: Team Learning Level: A Design Framework of a Learning Architecture (Wenger 1998)

Components: Three Infrastructures of Learning → Four Dimensions of Design for Learning ↓	Engagement √ Mutuality: interactional facilities, joint tasks, peripherality √ Competence: initiative and knowledgeability, accountability, tools √ Continuity: reification, memory, participative memory	Imagination √ Orientation: location in space, in time, in meaning, in power √ Reflection: models, patterns, comparisons with other practices √ Exploration: play, simulations, prototypes	Alignment √ Convergence: common focus, leadership, persuasion √ Coordination: standards, methods, communication, boundary facilities, feedback facilities √ Jurisdiction: policies, contracts, mediation, conflict, resolution	← Educational Design ↓
Participation/Reification	Combining them meaningfully in actions, interactions, and the creation of shared stories	Stories, playing with forms, recombination, assumptions	Styles and discourses	Learning as negotiation: how much to reify learning, its subject and its object
Designed/Emergent	Situated improvisation within a regime of accountability	Scenarios, possible worlds, simulations, perceiving new broad patterns	Communication, feedback, coordination, renegotiation, realignment	Teaching and learning: the relation between teaching and learning is not one of simple cause and effect
Local/Global	Multi-membership, brokering, peripherality, conversations	Models, maps, representations, visit, tours	Standards, shared infrastructures, centers of authority	From practice to practice: educational experiences must connect to other experiences
Identification/Negotiability	Mutuality through shared action, situated negotiation, marginalization	New trajectories, empathy, stereotypes, explanations	Inspiration, fields of influence, reciprocity of power relations	Identities of participation: there are multiple perspectives on what educational design is about; its effect on learning

The objectives of organizational learning: They are dependent on the disturbances in organizational learning (Kim 1993; Romme and Dillen 1997) and on the degree of maturity reached by the organization (Figure 5).

Figure 5: Organizational Learning Level: A Design Framework

The architecture for lifelong learning proposed has to be coherent between the different learning levels. It integrates both single-loop and double-loop learning. It considers the factors of contingencies, the characteristics of the organization, the context, the environment, and the state of the standards and best practices.

At this stage we will stay on a general pattern because of the nature of learning. With Wenger (1998) we think that learning cannot be designed. Learning happens, by design or not by design. One can design curriculum but not learning, process but not practice. Learning can only be designed for. Which implies a contextualization of the architecture. There is not a "one best way" architecture.