3. SYSTEMS INQUIRY AND ITS APPLICATION IN EDUCATION

Bela H. Banathy
INTERNATIONAL SYSTEMS INSTITUTE

3.1 PART 1: SYSTEMS INQUIRY

The first part of this chapter is a review of the evolution of the systems movement and a discussion of human systems inquiry.

3. 1. 1 A Definition of Systems Inquiry

Systems inquiry incorporates three interrelated domains of disciplined inquiry: systems theory, systems philosophy, and systems methodology. Bertalanffy (1968) notes that in contrast with the analytical, reductionist, and linear-causal paradigm of classical science, systems philosophy brings forth a reorientation of thought and world view, manifested by an expansionist, nonlinear dynamic, and synthetic mode of thinking. The scientific exploration of systems theories and the development of systems theories in the various sciences have brought forth a general theory of systems, a set of interrelated concepts and principles, applying to all systems. Systems methodology provides us with a set of models, strategies, methods, and tools that instrumentalize systems theory and philosophy in analysis, design, development, and management of complex systems.

3.1.1.1. Systems Theory. During the early 1950s, the basic concepts and principles of a general theory of systems were set forth by such pioneers of the systems movement as Ashby, Bertalanffy, Boulding, Fagen, Gerard, Rappoport, and Wienner. They came from a variety of disciplines and fields of study. They shared and articulated a common conviction: the unified nature of reality. They recognized a compelling need for a unified disciplined inquiry in understanding and dealing with increasing complexities that are beyond the competence of any single discipline. As a result, they developed a transdisciplinary perspective that emphasized the intrinsic order and interdependence of the world in all its manifestations. From their work emerged systems theory, the science of complexity. In defining systems theory, I review the key ideas of Bertalatiffy and Boulding, who were two of the founders of the Society for the Advancement of General Systems Theory. Later, the name of the society was changed to the Society for General Systems Research, then the International Society for Systems research, and recently to the International Society for the Systems Sciences.

3.1.1.1.1. Bertalanffy (1956, pp. 1-10). He suggested that "modem science is characterized by its ever-increasing specialization, necessitated by the enormous amount of data, the complexity of techniques, and structures within every field. This, however, led to a breakdown of science as an integrated realm. "Scientists, operating in the various disciplines, are encapsulated in their private universe, and it is difficult to get word from one cocoon to the other." Against this background, he observes a remarkable development, namely, that "similar general viewpoints and conceptions have appeared in very different fields." Reviewing this development in those fields, Bertalatiffy suggests that there exist models, principles, and laws that can be generalized across various systems, their components, and the relationships among them. "It seems legitimate to ask for a theory, not of systems of a more or less special kind, but of universal principles applying to systems in general."

The first consequence of this approach is the recognition of the existence of systems properties that are general and structural similarities or isomorphies in different fields:

There are correspondences in the principles which govern the behavior of entities that are intrinsically widely different. These correspondences are due to the fact that they all can be considered, in certain aspects, "systems," that is, complexes of elements standing in interaction. [It seems] that a general theory of systems would be a useful tool providing, on the one hand, models that can be used in, and transferred to, different fields, and safeguarding, on the other hand, from vague analogies which often have marred the progress in these fields.

The second consequence of the idea of a general theory is to deal with organized complexity, which is a main problem of modem science.

Concepts like those of organization, wholeness, directiveness, teleology, control, self-regulation, differentiation, and the like are alien to conventional science. However, they pop up everywhere in the biological, behavioral, and social sciences and are, in fact, indispensable for dealing with living organisms or social groups. Thus, a basic problem posed to modem science is a general theory of organization. General Systems Theory is, in principle, capable of giving exact definitions for such concepts.

Thirdly, Bertalanffy suggested that it is important to say what a general theory of systems is not. It is not identical with the triviality of mathematics of some sort that can be applied to any sort of problems; instead "it poses special problems that are far from being trivial." It is not

a search for superficial analogies between physical, biological, and social systems. The isomorphy we have mentioned is a consequence of the fact that, in certain aspects, corresponding abstractions and conceptual models can be applied to different phenomena. It is only in view of these aspects that system laws apply.

Bertalanffy summarizes the aims of a general theory of systems as follows:

(a) There is a general tendency towards integration in the various sciences, natural and social. (b) Such integration seems to be centered in a general theory of systems. (c) Such theory may be an important means of aiming at exact theory in the nonphysical fields of science. (d) Developing unifying principles running "vertically" through the universe of the individual sciences, this theory brings us nearer to the goal of the unity of sciences. (e) This can lead to a much needed integration in scientific education.

Commenting later on education, Bertalanffy noted that education treats the various scientific disciplines as separate domains, where increasingly smaller subdomains become separate sciences, unconnected with the rest. In contrast, the educational demands of scientific generalists and developing transdisciplinary basic principles are precisely those that General Systems Theory (GST) tries to fill. In this sense, GST seems to make an important headway toward transdisciplinary synthesis and integrated education.

3.1.1.1.2. Boulding (1956, pp. 11-17). He underscored the need for a general theory as he suggested that in recent years increasing need has been felt for a body of theoretical constructs that will discuss the general relationships of the empirical world.

This is the quest of General Systems Theory (GST). It does not seek, of course, to establish a single, self-contained "general theory of practically everything" which will, replace all the special theories of particular disciplines. Such a theory would be almost without content, and all we can say about practically everything is almost nothing.

Somewhere between the specific that has no meaning and the general that has no content there must be, for each purpose and at each level of abstraction, an optimum degree of generality.

The objectives of GST, then, can be set out with varying degrees of ambitions and confidence. At a low level of ambition, but with a high degree of confidence, it aims to point out similarities in the theoretical constructions of different disciplines, where these exist, and to develop theoretical models having applicability to different fields of study. At a higher level of ambition, but perhaps with a lower level of confidence, it hopes to develop something like a "spectrum" of theories-a system of, systems that may perform a "gestalt" in theoretical constructions. It is the main objective of GST, says Boulding, to develop "generalized ears" that overcome the "specialized deafness" of the specific disciplines, meaning that someone who ought to know something that someone else knows isn't able to find it out for lack of generalized ears. Developing a framework of a general theory will enable the specialist to catch relevant communications from others.

In the closing section of his paper, Boulding referred to the subtitle of his paper: GST as "the skeleton of science." It is a skeleton in the sense-he says-that:

It aims to provide a framework or structure of systems on which to hang the flesh and blood of particular disciplines and particular subject matters in an orderly and coherent corpus of knowledge. It is also, however, something of a skeleton in a cupboard-the cupboard in this case being the unwillingness of science to admit the tendency to shut the door on problems and subject matters which do not fit easily into simple mechanical schemes. Science, for all its success, still has a very long way to go. GST may at times be an embarrassment in pointing out how very far we still have to go, and in deflating excessive philosophical claims for overly simple systems. It also may be helpful, however, in pointing out to some extent where we have to go. The skeleton must come out of the cupboards before its dry bones can live.

The two papers introduced above set forth the "vision" of the systems movement. That vision still guides us today. At this point it seems to be appropriate to tell the story that marks the genesis of the systems movement. Kenneth Boulding told this story at the occasion when I was privileged to present to him the distinguished scholarship award of the Society of General Systems Research at our 1983 Annual Meeting. The year was 1954. At the Center for Behavioral Sciences, at Stanford University, four Center Fellows-Bertalanffy (biology), Boulding (economics), Gerard (psychology), and Rappoport (mathematics)-had a discussion in a meeting room. Another Center Fellow walked in and asked: "What's going on here?" Ken answered: "We are angered about the state of the human condition and ask: 'What can we-what can science-do about improving the human condition?"' "Oh!" their visitor said: "This is not my field. . . ." At that meeting the four scientists felt that in the statement of their visitor they heard the statement of the fragmented disciplines that have little concern for doing anything practical about the fate of humanity. So, they asked themselves, "What would happen if science would be redefined by crossing disciplinary boundaries and forge a general theory that would bring us together in the service of humanities? Later they went to Berkeley, to the annual meeting of the American Association for the Advancement of Science, and established the Society for the Advancement of General Systems Theory. Throughout the years, many of us in the systems movement have continued to ask the question: How can systems science serve humanity?

3.1.1.2. Systems Philosophy. The next main branch of systems inquiry is systems philosophy. Systems philosophy is concerned with a systems view of the world and the elucidation of systems thinking as an approach to theoretical and real-world problems. Systems philosophy seeks to uncover the most general assumptions lying at the roots of any and all of systems inquiry. An articulation of these assumptions gives systems inquiry coherence and internal consistency. Systems philosophy (Laszlo, 1972) seeks to probe the basic texture and ultimate implications of systems inquiry. It "guides the imagination of the systems scientist and provides a general world view, the likes of which-in the history of science-has proven to be the most significant for asking the right question and perceiving the relevant state of affairs" ( p. 10). The general scientific nature of systems inquiry implies its direct association with philosophy. This explains the philosophers' early and continuing interest in systems theory and the early and continuing interest of systems theorists and methodologists in the philosophical aspects of systems inquiry. In general, philosophical aspects are worked out in two directions. The first involves inquiry into the What: what things are, what a person or a society is, and what kind of world we live in. These questions pertain to what we call ontology. The second question is How: How do we know what we know; how do we know what kind of world we live in; how do we know what kind of persons we are? The exploration of these questions are the domain of epistemology. One might differentiate these two, but, as Bateson (1972) noted, ontology and epistemology cannot be separated. Our beliefs about what the world is will determine how we see it and act within it. And our ways of perceiving and acting will determine our beliefs about its nature. Blauberg, Sadovsky, and Yudin (1977) noted that the philosophical aspects of systems inquiry would give us an "unequivocal solution to all or most problems arising from a study of systems" (p. 94).

3.1.1.2.1. Ontology. The ontological task is the formation of a systems view of what is-in the broadest sense a systems view of the world. This can lead to a new orientation for scientific inquiry. As Baluberg (1977) noted, this orientation emerged into a holistic view of the world. Waddington (1977) presents a historical review of two great philosophical alternatives of the intellectual picture we have of the world. One view is that the world essentially consists of things. The other view is that the world consists of processes, and the things are only "stills" out of the moving picture. Systems philosophy developed as the main rival of the "thing view." It recognizes the primacy of organizing relationship processes between entities (of systems), from which emerge the novel properties of systems.

3.1.1.2.2. Epistemology. This philosophical aspect deals with general questions: How do we know whatever we know? How do we know what kind of world we live in and what kind of organisms we are? What sort of thing is the mind? Bateson (1972) notes that originating from systems theory, extraordinary advances have been made in answering these questions. The ancient question of whether the mind is immanent or transcendent can be answered in favor of immanence. Furthermore, any ongoing ensemble (system) that has the appropriate complexity of causal and energy relationships will: (a) show mutual characteristics, (b) compare and respond to differences, (c) process information, (d) be self-corrective, and (e) no part of an internally interactive system can exercise unilateral control over other parts of the system. "The mutual characteristics of a system are immanent not in some part, but in the system as a whole" (p. 316).

The epistemological aspects of systems philosophy address: (a) the principles of how systems inquiry is conducted; (b) the specific categorical apparatus of the inquiry, and that connected with it; and (c) the theoretical language of systems science. The most significant guiding principle of systems inquiry is that of giving prominence to synthesis, not only as the culminating activity of the inquiry (following analysis) but also as a point of departure. This approach to the "how do we know" contrasts with the epistemology of traditional science that is almost exclusively analytical.

3.1.1.3. Systems Methodology. Systems methodology- vital part of systems inquiry-has two domains of inquiry: (1) the study of methods in systems investigations by which we generate knowledge about systems in general and (2) the identification and description of strategies, models, methods, and tools for the application of systems theory and systems thinking for working with complex systems. In the context of this second domain, systems methodology is a set of coherent and related methods and tools applicable to: (a) the analysis of systems and systems problems, problems concerned with the systemic/ relational aspects of complex systems; (b) the design, development, implementation, and evaluation of complex systems; and (c) the management of systems and the management of change in systems.

The task of those using systems methodology in a given context is threefold: (1) to identify, characterize, and classify the nature of the problem situation, i.e., (a), (b), or (c) above; (2) to identify and characterize the problem context and content in which the methodology is applied; (3) to identify and characterize the type of system in which the problem situation is embedded; and (4) to select specific strategies, methods, and tools that are appropriate to the nature of the problem situation, to the context/content, and to the type of systems in which the problem situation is located.

The brief discussion above highlights the difference between the methodology of systems inquiry and the methodology of scientific inquiry in the various disciplines.

The methodology of a discipline is clearly defined and is to be adhered to rigorously. It is the methodology that is the hallmark of a discipline. In systems inquiry, on the other hand, one selects methods and methodological tools or approaches that best fit the nature of the identified problem situation, and the context, the content, and the type of system that is the domain of the investigation. The methodology is to be selected from a wide range of systems methods that are available to us.

3.1.1.4. The Interaction of the Domains of Systems Inquiry. Systems philosophy, systems theory, and systems methodology come to life as they are used and applied in the functional context of systems. It is in the context of use that they are confirmed, changed, modified, and reconfirmed. Systems philosophy presents us with the underlying assumptions that provide the perspectives that guide us in defining and organizing the concepts and principles that constitute systems theory. Systems theory and systems philosophy then guide us in developing, selecting, and organizing approaches, methods, and tools into the scheme of systems methodology. Systems methodology then is used in the functional context of systems. But this process is not linear or forward-moving circular. It is recursive and multi-directional One confirms or modifies the other. As theory is developed, it gets its confirmation from its underlying assumptions (philosophy), as well as from its application through methods in functional contexts. Methodology is confirmed or changed by testing its relevance to its theoretical/philosophical foundations and by its use. The functional context-the society in general and systems of all kinds in particular-is a primary source of placing demands on systems inquiry. It was, in fact, the emergence of complex systems that brought about the recognition of the need for new scientific thinking, new theory, and methodologies. It was this need that systems inquiry addressed and satisfied.

The dynamics of the recursive and multi-directional interaction of the four domains, described above, makes systems inquiry a living system. These dynamics are manifested in the interplay between confirmation and novelty. Novelty at times brings about adjustments and at other times it appears as discontinuities and major shifts. The process described here becomes transparent as the evolution of the systems movement is reviewed next.

3.1.2 Evolution of the Systems Movement

Throughout the evolution of humanity there has been a constant yearning for understanding the wholeness of the human experience that manifests itself in the wholeness of the human being and the human society. Wholeness has been sought also in the disciplined inquiry of science as a way of searching for the unity of science and a unified theory of the universe. This search reaches back through the ages into the golden age of Greek philosophy and science in Plato's kybernetics, the art of steermanship, which is the origin of modem cybernetics: a domain of contemporary systems thinking. The search intensified during the Age of Enlightenment and the Age of Reason and Certainty, and it was manifested in the clockwork mechanistic world view. The search has continued in the current age of uncertainty (Heisenberg) and complexity, the science of relativity, (Einstein), quantum theory (Bohr & Shrodinger), and the theory of wholeness and the implicate order (Bohm).

In recent years, the major player in this search has been the systems movement. The genesis of the movement can be timed as the mid-50s (as discussed at the beginning of this chapter). But prior to that time, we can account for the emergence of the systems idea through the work of several philosophers and scientist.

3.1.2.1. The Pioneers. Some of the key notions of systems theory were articulated by the 18th-century German philosopher Hagel. He suggested that the whole is more than the sum of its parts, that the whole determines the nature of the parts, and the parts are dynamically interrelated and cannot be understood in isolation from the whole.

Most likely, the first person who used the term general theory of systems was the Hungarian philosopher and scientist Bela Zalai. Zalai, during the years 1913 to 1914, developed his theory in a collection of papers called A Rendszerek Altalanos Elmelete. The German translation was entitled Allgemeine Theorie der Systeme [General Theory of Systems]. The work was republished (Zalai, 1984) in Hungarian and was recently reviewed in English (Banathy & Banathy, 1989). In a three-volume treatise, Tektologia, Bogdanov (1921-1927), a Russian scientist, characterized Tektologia as a dynamic science of complex wholes, concerned with universal structural regularities, general types of systems, the general laws of their transformation, and the basic laws of organization. Bogdanov's work was published in English by Golerik (1980).

In the decades prior to and during World War 11, the search intensified. The idea of a General Systems Theory was developed by Bertalanffy in the late 30s and was presented in various lectures. But his material remained unpublished until 1945 (Zu einer allgemeinen Systemlehre) followed by "An Outline of General Systems Theory" (1951). Without using the term GST, the same frame of thinking was used in various articles by Ashby during the years 1945 and 1947, published in his book Design for a Brain, in 1952.

3.1.2.2. Organized Developments. In contrast with the work of individual scientists, outlined above, since the 1940s we can account for several major developments that reflect the evolution of the systems movement, including "hard systems science," cybernetics, and the continuing evolution of a general theory of systems.

3.1.3 Hard-Systems Science

Under hard-systems science, we can account for two organized developments: operations research and systems engineering.

3.1.3.1. Operations Research. During the Second World War, it was again the "functional context" that challenged scientists. The complex problems of logistics and resource management in waging a war became the genesis of developing the earliest organized form of systems science: the quantitative analysis of rather closed systems. It was this orientation from which operations research and management science emerged during the 50s. This development directed systems science toward "hard" quantitative analysis. Operations research flourished during the 60s, but in the 70s, due to the changing nature of sociotechnical systems contexts, it went through a major shift toward a less quantitative orientation.

3.1.3.2. Systems Engineering. This is concerned with the design of closed man-machine systems and larger-scale sociotechnical systems. Systems engineering (SE) can be portrayed as a system of methods and tools, specific activities for problem solutions, and a set of relations between the tools and activities. The tools include language, mathematics, and graphics by which systems engineering communicates. The content of SE includes a variety of algorithms and concepts that enable various activities. The first major work in SE was published by A. D. Hall (1962). He presented a comprehensive, three-dimensional morphology for systems engineering. In a more recent work, Sage (1977) has changed the directions of SE.

We use the word system to refer to the application of systems science and methodologies associated with the science of problem solving. We use the word engineering not only to mean the mastery and manipulation of physical data but also to imply social and behavioral consideration as inherent parts of the engineering design process (p. xi).

During the 60s and early 70s, practitioners of operations research and systems engineering attempted to transfer their approaches into the context of social systems. It led to disasters. It was this period when "social engineering" emerged as an approach to address societal problems. A recognition of failed attempts have led to changes in direction, best manifested by the quotation of Sage in the paragraph above.

3.1.4 Cybernetics

Cybernetics is concerned with the understanding of self-organization of human, artificial, and natural systems; the understanding of understanding; and its relation and relevance to other transdisciplinary approaches. Cybernetics, as part of the systems movement, evolved through two phases: first-order cybernetics, the cybernetics of the observed system, and second-order cybernetics, the cybernetics of the observing system.

3.1.4.1. First-Order Cybernetics. This early formulation of cybernetics inquiry was concerned with communication and control in the animal and the machine (Wiener, 1948). The emphasis on the in allowed focus on the process of self-organization and self-regulation, on circular causal feedback mechanisms, together with the systemic principles that underlie them. These principles underlay the computer/cognitive sciences and are credited with being at the heart of neural network approaches in computing. The first-order view treated information as a quantity, as "bits" to be transmitted from one place to the other. It focused on "noise" that interfered with smooth transmission (Weatley, 1992). The content, the meaning, and the purpose of information was ignored (Gleick, 1987).

3.1.4.2. Second-Order Cybernetics. As a concept, this expression was coined by Foerster (1984), who describes this shift as follows: "We are now in the possession of the truism that a description (of the universe) implies one who describes (observes it). What we need now is a description of the 'describer' or, in other words, we need a theory of the observer" (p. 258). The general notion of second-order cybernetics is that "observing systems" awaken the notion of language, culture, and communication (Brier, 1992); and the context, the content, the meaning, and purpose of information becomes central. Second-order cybernetics, through the concept of self-reference, wants to explore the meaning of cognition and communication within the natural and social sciences, the humanities, and information science; and in such social practices as design, education, organization, art, management, and politics, etc. (p. 2).

3.1.5 The Continuing Evolution of Systems Inquiry

The first part of this chapter describes the emergence of the systems idea and its manifestation in the three branches of systems inquiry: systems theory, systems philosophy, and systems methodology. This section traces the evolution of systems inquiry. This evolutionary discussion will be continued later in a separate section by focusing on "human systems inquiry."

3.1.5.1. The Continuing Evolution of Systems Thinking. In a comprehensive report, commissioned by the Society of General Systems Research, Cavallo (1979) says that systems inquiry shattered the essential features of the traditional scientific paradigm characterized by analytic thinking, reductionism, and determinism. The systems paradigm articulates synthetic thinking, emergence, communication and control, expansionism, and teleology. 'Me emergence of these core systems ideas was the consequence of a change of focus, away from entities that cannot be taken apart without loss of their essential characteristics, and hence can not be truly understood from analysis.

First, this change of focus gave rise to synthetic or systems thinking as complementary to analysis. In synthetic thinking an entity to be understood is conceptualized not as a whole to be taken apart but as a part of one or more larger wholes. The entity is explained in terms of its function, and its role in its larger context. Second, another major consequence of the new thinking is expansionism (an alternative to reductionism), which asserts that ultimate understanding is an ideal that can never be attained but can be continuously approached. Progress towards it depends on understanding ever-larger and more inclusive wholes. Third, the idea of nondeterministic causality, developed by Singer (1959), made it possible to develop the notion of objective teleology, a conceptual system in which such teleological concepts as fire will, choice, function, and purpose could be operationally defined and incorporated into the domain of science.

3.1.5.2. A General Theory of Dynamic Systems. The theory was developed by Jantsch (1980). He argues that an emphasis on structure and dynamic equilibrium (steady-state flow), which characterized the earlier development of general systems theory, led to a profound understanding of how primarily technological structures may be stabilized and maintained by complex mechanisms that respond to negative feedback. (Negative feedback indicates deviation from established norms and calls for a reduction of such deviation.) In biological and social systems, however, negative feedback is complemented by positive feedback, which increases deviation by the development of new systems processes and forms. The new understanding that has emerged recognizes such phenomena as self-organization, self-reference, self-regulation, coherent behavior over time with structural change, individuality, symbiosis, and coevolution with the environment, and morphogenesis.

This new understanding of systems behavior, says Jantsch, emphasizes process in contrast to "solid" subsystems structures and components. The interplay of process in systems leads to evolution of structures. An emphasis is placed on "becoming," a decisive conceptual breakthrough brought about by Prigogine (1980). Prigogine's theoretical development and empirical conformation of the so-called dissipative structures and his discovery of a new ordering systems principle called order through fluctuation led to an explication of a "general theory of dynamic systems."

During the early 80s, a whole range of systems thinking based methodologies emerged, based on what is called soft systems thinking. These are all relevant to human and social systems and will be discussed under the heading of human systems inquiry. In this section, two additional developments are discussed: systems thinking based on "liberating systems theory" and "unbounded systems thinking."

3.1.5.3. Liberating Systems Theory(Flood, pp. 210-211, 1990). This theory is (1) in pursuit of freeing systems theory from certain tendencies and, in a more general sense, (2) tasking systems theory with liberation of the human condition. The first task is developed in three trends: (1) the liberation of systems theory generally from the natural tendency toward self-imposed insularity, (2) the liberation of systems concepts from objectivist and subjectivist delusions, and (3) the liberation of systems theory specifically in cases of internalized localized subjugations in discourse and by considering histories and progressions of systems thinking. The second task of the theory focuses on liberation and emancipation in response to domination and subjugation in work and social situations.

3.1.5.5. Unbounded Systems Thinking(Mitroff & Linstone, 1993). This development "is the basis for the ,new thinking' called for in the information age" (p. 91).In unbounded systems thinking (UST), "everything interacts with everything."

All branches of inquiry depend fundamentally on one another. The widest possible array of disciplines, professions, and branches of knowledge capturing distinctly different paradigms of thought-must be consciously brought to bear on our problems. In UST, the traditional hierarchical ordering of the sciences and the professions-as well as the pejorative bifurcation of the sciences into 'hard' vs. 'soft'-is replaced by a circular concept of relationship between diem. The basis for choosing a particular way of modeling or representing a problem is not governed merely by considerations of conventional logic and rationality. It may also involve considerations of justice and fairness as perceived by various social groups and by consideration of personal ethics or morality as perceived by distinct persons" (p. 9).

3.1.5.6. Living Systems Theory. This theory was developed by Miller (1978) as a continuation and elaboration of the organismic orientation of Bertalanffy. The theory is a conceptual scheme for the description and analysis of concrete identifiable living systems. It describes seven levels of living systems, ranging from the lower levels of cell, organ, and organism, to higher levels of group, organizations, societies, and supranational systems.

The central thesis of living systems theory is that at each level a system is characterized by the same 20 critical subsystems whose processes are essential to life. A set of these subsystems processes information (input transducer, internal transducer, channel and net, decoder, associator, decider, memory, encoder, output transducer, and time). Another set processes matter and energy (ingestor, distributor, converter, producer, storage, extruder, motor, and supporter). Two subsystems (reproducer and boundary) process matter/ energy and information.

Living system theory presents a common framework for analyzing structure and process and identifying the health and well-being of systems at various levels of complexity. A set of cross-level hypotheses was identified by Miller as a basis for conducting such analysis. During the 80s, Living systems theory has been applied by a method-called living systems process analysis-to the study of complex problem situations embedded in a diversity of fields and activities. [Living systems process analysis has been applied in educational contexts by Banathy and Mills (1988).]

3.1.6 Human Systems Inquiry

Human systems inquiry focuses systems theory, systems philosophy, and systems methodology and their applications on social or human systems. This section portrays human systems inquiry as follows: (1) present some of its basic characteristics, (2) describe the various types of human or social systems, (3) discuss the nature of problem situations and solutions in human systems inquiry, and (4) introduce the "soft-systems" approach and social systems design. The discussion of these issues will help us appreciate why human systems inquiry must be different from other modes of inquiry. Furthermore, in as much as education is a human systems inquiry will lead to our discussion on systems inquiry in education.

3.1.6.1. The Characteristics of Human Systems. Human Systems Are Different is the title of the last book of the systems philosopher Geoffrey Vickers (1983). Discussing the characteristics of summary of their open nature as follows. (1) Open systems are nests of relations that are sustained through time. They are sustained by these relations and by the process of regulation. The limits within which they can be sustained are the conditions of their stability. (2) Open systems depend on and contribute to their environment. They are dependent on this interaction as well as on their internal interaction. These interactions/dependencies impose constraints on all their constituents. Human systems can mitigate but cannot remove these constraints, which tend to become more demanding and at times even contradictory as the scale of the organization increases. This might place a limit on the potential of the organization. (3) Open systems are wholes, but are also parts of larger systems, and their constituents may also be constituents of other systems. Change in human systems is inevitable. Systems adapt to environmental changes, and in a changing environment this becomes a continuous process. At times, however, adaptation does not suffice, so the whole system might change. Through coevolution and cocreation, change between the systems and its environment is a mutual recursive phenomenon (Buckley, 1968; Jantch, 1976, 1980). Wheatley (1992), discussing stability, change, and renewal in self-organizing system, remarks that in the past, scientists focused on the overall structure of systems, leading them away from understanding the processes of change that makes a system viable over time. They were looking for stability. Regulatory (negative) feedback was a way to ensure the stability of systems, to preserve their current state. They overlooked the function of positive feedback that moves the system toward change and renewal. Checkland (1981) presents a comprehensive characterization of what he calls human activity systems (HASs). HASs are very different from natural and engineered systems. Natural and engineered systems cannot be other than what they are.

Human activity systems, on the other hand, are manifested through the perception of human beings who are free to attribute meanings to what they perceive. There will never be a single (testable) account of human activity systems, only a set of possible accounts, all valid according to particular Weltanshaungen (p. 14).

He further says, that HASs are structured sets of people who make up the system, coupled with a collection of such activities as processing information, making plans, performing, and monitoring performance.

According to Argyris and Schon (1979), a social group becomes an organization when members devise procedures for "Making decisions in the name of the collectivity, delegate of inquiry. Furthermore, inasmuch as education is a human to individuals the authority to act for the collectivity, and system, such understanding and a review of approaches to setting boundaries between the collectivity and the rest of the human systems world" (p. 13). Ackoff and Emery(1972) characterize human systems as purposeful systems whose members are also purposeful individuals who intentionally and collectevely formulate objectives. In human systems, "the state of the part can be determined only in reference to the state of the system. The effect of change in one part or another is mediated by changes in the state of the whole" (p. 218).

Ackoff (1981) suggests that human systems are purposeful systems that have purposeful parts and are parts of larger purposeful systems.This observation reveals three fundamental issues, namely, how to design and manage human systems so that they can effectively and efficiently serve (1) their own purposes, (2) the purposes of their purposeful parts and people in the system, and (3) the purposes of the larger system(s) of which they are part. These functions are called: (1) self-directiveness, (2) humanization, and (3) environmentalization, respectively. Viewing human systems from an evolutionary perspective, Jantsch (1980) suggests that according to the dualistic paradigm, adaptation is a response to something that evolved outside of the systems. He notes, however, that with the emergence of the self-organizing paradigm, a scientifically founded nondualistic view became possible. This view is process oriented and establishes that evolution is an integral part of self-organization. True self-organization incorporates self-transcendence, the creative reaching out of a human system beyond its boundaries. Jantsch concludes that creation is the core of evolution, it is the joy of life, it is not just adaptation, not just securing survival. In the final analysis, says Laszlo (1987), social systems are value-guided systems. Insofar as they are independent of biological need-fulfillment and reproductive needs, cultures satisfy not body needs but values. All cultures respond to such suprabiological values. But in what form they do so depends on the specific kind of values people happen to have.

3.1.6.2. Types of Human Systems. Human activity systems (HASs), such as educational systems, are purposeful creations. People in these systems select, organize, and carry opt activities in order to attain their purposes. Reviewing the research of Ackoff (1981), Jantsch (1976), Jackson and Keys (1984), and Southerland (1973), the author developed a comprehensive classification of HASs (1988) based on: (1) the degree to which they are open or closed, (2) their mechanistic vs. systemic nature, (3) their unitary vs. pluralistic position on defining their purpose,and (4) the degree and nature of their complexity (simple, detailed, dynamic). Based on these dimensions, we can differentiate five types of HASs: rigidly controlled, deterministic, purposive, heuristic, and purpose seeking.

3.1.6.2.1. Rigidly Controlled Systems. These systems are rather closed. Their structure is simple, consisting of few elements with limited interaction among them. They have a singleness of purpose and clearly defined goals, and act mechanically. Operational ways and means are prescribed.

There is little room for self-direction. They have a rigid structure and stable relationship among system components. Examples are assembly-line systems and man machine systems.

3.1.6.2.2. Deterministic Systems. These are still more closed than open. They have clearly assigned goals; thus, they are unitary. People in the system have a limited degree of freedom in selecting methods. Their complexity ranges from simple to detailed. Examples are bureaucracies, instructional systems, and national educational.

3.1.6.2.3. Purposive Systems. These are still unitary but are more open than closed, and react to their environment in order to maintain their viability. Their purpose is established at the top, but people in the system have freedom to select operational means and methods. They have detailed to dynamic complexity. Examples are corporations, social service agencies, and our public education systems.

3.1.6.2.4. Heuristic Systems. Such systems as R&D agencies and innovative business ventures formulate their own goals under broad policy guidelines; thus, they are somewhat pluralistic. They are open to changes and often initiate changes. Their complexity is dynamic, and their internal arrangements and operations are systemic. Examples of heuristic systems include innovative business ventures, educational R&D agencies, and alternative educational systems.

3.1.6.2.5. Purpose-Seeking Systems. These systems are ideal seeking and are guided by their vision of the future. They are open and coevolve with their environment. They exhibit dynamic complexity and systemic behavior. They are pluralistic, as they constantly seek new purposes and search for new niches in their environments. Examples are (a) communities seeking to establish integration of their systems of learning and human development with social, human, and health service agencies, and their community and economic development programs, and (b) cutting-edge R&D agencies.

In working with human systems, the understanding of what type of system we are working with, or the determination of the type of systems we wish to design, is crucial in that it suggests the selection of the approach and the methods and tools that are appropriate to systems inquiry.

3.1.7 The Nature of Problem Situations and Solutions

Working with human systems, we are confronted with problem situations that comprise a system of problems rather than a collection of problems. Problems are embedded in uncertainty and require subjective interpretation. Churchman (1971) suggested that in working with human systems, subjectivity cannot be avoided. What really matters, he says, is that systems are unique, and the task is to account for their uniqueness; and this uniqueness has to be considered in their description and design. Our main tool in working with human systems is subjectivity: reflection on the sources of knowledge, social practice, community, and interest in and commitment to ideas, especially the moral idea, affectivity, and faith.

Working with human systems, we must recognize that they are unbounded. Factors assumed to be part of a problem are inseparably linked to many other factors. A technical problem in transportation, such as the building of a freeway, becomes a land-use problem, linked with economic, environmental, conservation, ethical, and political issues. Can we really draw a boundary? When we seek to improve a situation, particularly if it is a public one, we find ourselves facing not a problem but a cluster of problems, often called problematique. Peccei (1977), the founder of the Club of Rome, says that:

Within the problematique, it is difficult to pinpoint individual problems and propose individual solutions. Each problem is related to every other problem; each apparent solution to a problem may aggravate or interfere with others; and none of these problems or their combination can be tackled using the linear or sequential methods of the past" (p. 6 1).

Ackoff suggests (1981) that a set of interdependent problems constitutes a system of problems, which he calls a mess. Like any system, the mess has properties that none of its parts has. These properties are lost when the system is taken apart. In addition, each part of a system has properties that are lost when it is considered separately. The solution to a mess depends on how its parts interact. In an earlier statement, Ackoff (1974) says that the era of "quest for certainty" has passed. We live an age of uncertainty in which systems are open, dynamic; in which problems live in a moving process. "Problems and solutions are in constant flux, hence problems do not stay solved. Solutions to problems become obsolete even if the problems to which they are addressed are not" (p. 31). Ulrich (1983) suggests that when working with human systems, we should reflect critically on problems. He asks: How can we produce solutions if the problems remain unquestioned? We should transcend problems as originally stated and should explore critically the problem itself with all of those who are affected by the problem. We must differentiate well-structured and well-defined problems in which the initial conditions, the goals, and the necessary operations can all be specified, from ill-defined or ill-structured problems, the kind in which initial conditions, the goals, and the allowable operations cannot be extrapolated from the problem. Discussing this issue, Rittel and Webber (1974) suggest that science and engineering are dealing with well-structured or tame problems. But this stance is not applicable to open social systems. Still, many social science professionals have mimicked the cognitive style of scientists and the operational style of engineers. But social problems are inherently wicked problems. Thus, every solution of a wicked problem is tentative and incomplete, and it changes as we move toward the solution. As the solution changes, as it is elaborated, so does our understanding of the problem. Considering this issue in the context of systems design, Rittel suggests that the "ill-behaved" nature of design problem situations frustrates all attempts to start out with an information and analysis phase, at the end of which a clear definition of the problem is rendered and objectives are defined that become the basis for synthesis, during which a "monastic" solution can be worked out. Systems design requires a continuous interaction between the initial phase that triggers design and the state when design is completed.

3.1.8 The Soft-Systems Approach and Systems Design

From the 70s on, it was generally realized that the nature of issues in human/social systems is "soft" in contrast with "hard" issues and problems in systems engineering and other quantitative focused systems inquiry.

Hard-systems thinking and approaches were not usable in the context of human activity systems. "It is impossible to start the studies by naming 'the system' and defining its objectives, and without this naming/definition, hard systems thinking collapses" (Checkland, 198 1; Checkland and Scholes, 1990).

Churchman in his various works (1968a, 1968b, 1971, 1979, 1981) has been the most articulate and most effective advocate of ethical systems theory and morality in human systems inquiry. Human systems inquiry, Churchman says, has to be value oriented, and it must be guided by the social imperative, which dictates that technological efficiency must be subordinated to social efficiency. He speaks for a science of values and the development of methods by which to verify ethical judgments. He took issue (Churchman, 1971) with the design approach where the focus is on various segments of the system. When the designer detects a problem in a part, he moves to modify it. This approach is based on the separability principle of incrementalism. He advocates "nonseperabilty" when the application of decision rules depends on the state of the whole system, and when a certain degree of instability of a part occurs, the designer can recognize this event and change the system so that the part becomes stable. "It can be seen that design, properly viewed, is an enormous liberation of the intellectual spirit, for it challenges this spirit to an unbounded speculation about possibilities" (p. 13). A liberated designer will look at present practice as a point of departure at best. Design is a thought process and a communication process. Successful design is one that enables someone to transfer thought into action or into another design.

Checkland (1981) and Checkland and Scholes (1990) developed a methodology based on soft-systems thinking for working with human activity systems. They consider the methodology as:

a learning system which uses systems ideas to formulate basic mental acts of four kinds: perceiving, predicating, comparing, and deciding for action. The output of the methodology is very different from the output of systems engineering: It is learning which leads to decision to take certain actions, knowing that this will lead not to "the problem" being now "solved," but to a changed situation and new learning" (1981, p. 17).

The methodology defined here is a direct consequence of the concept, human activity system. We attribute meaning to all human activity. Our attributions are meaningful in terms of our particular image of the world, which, in general, we take for granted.

Systems design, in the context of social systems, is a future-creative disciplined inquiry. People engage in this inquiry to design a system that realizes their vision of the future, their own expectations, and the expectations of their environment. Systems design is a relatively new intellectual technology. It emerged only recently as a manifestation of open-system thinking and corresponding ethically based soft-systems approaches. This new intellectual technology emerged, just in time, as a disciplined inquiry that enables us to align our social systems with the new realities of the information/knowledge age (Banathy, 1991).

Early pioneers of social systems design include: Simon (1969), Jones (1970), Churchman (1968, 1971, 1978), Jantsch (1976, 1980), Warfield (1976), and Sage (1977). The watershed year of comprehensive statements on systems design was 1981, marked by the works of Ackoff, Cbeckland, and Nadler. Then came the work of Argyris (1982), Uhich (1983), Cross (1984), Morgan (1986), Senge (1990), Warfield (1990), Nadler and Hibino (1990), Checkland and Scholes (1990), Banadiy (1991), Hammer and Champy (1993), and Mitroff and Linstone (1993).

Prior to the emergence of social systems design, the improvement approach to systems change manifested traditional social planning (Banathy, 1991). This approach, still practiced today, reduces the problem to manageable pieces and seeks solutions to each. Users of this approach believe that solving the problem piece by piece ultimately will correct the larger issue it aims to remedy. But systems designers know that "getting rid of what is not wanted does not give you what is desired." In sharp contrast with traditional social planning, systems design-represented by the authors above-seeks to understand the problem situation as a system of interdependent and interacting problems, and seeks to create a design as a system of interdependent and interacting solution ideas. Systems designers envision the entity to be designed as a whole, as one that is designed from the synthesis of the interaction of its parts. Systems design requires both coordination and integration. We need to design all parts of the system interactively and simultaneously. This requires coordination, and designing for interdependency across all systems levels invites integration.

3.1.9 Reflections

In the first part of this chapter, systems inquiry was defined, and the evolution of the systems movement was reviewed. Then we focused on human systems inquiry, which is the conceptual foundation of the development of a systems view and systems applications in education. As we reflect on the ideas presented in this part, we realize how little of what was discussed here has any serious manifestation or application in education. Therefore, the second part of this chapter is devoted to the exploration of a systems view of education and its practical applications in working with systems of learning and human development.