Instructional Systems Technology

Goals of this Seminar

Through active and creative involvement in this new seminar, I expect participants to:

Learn configurational and dynamic temporal properties of systems in general.

Confirm and refute hypotheses in an educational theory based on a systems model.

Revise the educational systems theory.

Design scenarios for an educational system simulation.

In this seminar I expect to work with you in a truly cooperative venture to build the foundations for an eventual multimedia simulation of educational systems. My vision is that this simulation (call it SimEd for now) would be similar to SimCity, SimHealth, SimAnt, etc., in that the eventual user would be able to construct different kinds of educational systems and observe how they evolve through time. By observing the consequences of certain decisions and actions within SimEd, users can learn from mistakes -- without suffering the consequences had such changes actually been made in a real educational system. I envision such a tool to help educators, students, parents, school boards and administrators, and communities at large to make intelligent decisions about how to improve or change their own educational systems.

If we are successful in this seminar, we will have laid the groundwork for SimEd. Such a simulation will require a set of underlying rules or principles of system change under various conditions. If these rules are not valid, then the systems simulation might be interesting but misleading. Thus, we need to validate the rules with empirical evidence wherever we can find it in extant research.

We will start with an existing theory of education developed by Maccia and Maccia which contains 201 hypotheses concerning relationships among properties of educational systems. To understand their theory, we will need to reach mutual understanding of about 60 properties of systems in general. Some of these properties characterize system configurations (e.g., complete connectedness, vulnerability, size, complexity, wholeness) and some characterize system temporal dynamics (e.g., filtration, feedout, feedback, regulation, adaptivity, compatibility, homeostasis, stress). We will be expanding upon my manuscript in progress, aimed at furthering the understanding of the Maccia and Maccia theory.

We will most likely be revising this theory as we accumulate evidence. The revised theory will be the initial set of rules for the expert system that is the kernel for SimEd. Also, as we accumulate examples from past and present research, these may serve -- with some creative modification -- as potential scenarios for SimEd.

The primary reason that this theory has received little attention during the past 30 years is that it requires a paradigm shift in people's thinking patterns (cf., Thomas Kuhn (1970), The Structure of Scientific Revolutions). Systemic thinking is rare (Hart, 1992). Systemic thinking may even require a different kind of intelligence that is not fostered by existing cultures and educational systems. See for example, Howard Gardner's (1985), Frames of Mind: The Theory of Multiple Intelligences. Systemic thinking may be a further stage of cognitive development that goes beyond Jean Piaget's original stages of intellectual operations (cf. Senge, 1990; Campbell, 1976).

Working together, I expect us to create a manuscript which can help others to understand these systems properties and, in turn, to understand the hypotheses of the educational systems theory. I expect our efforts in R695 to result in jointly authored publications such as a book, a series of articles, and/or hypermedia documents on the World-Wide Web. In summary, I expect that the major outcomes in this course will be for each participant to make a significant contribution to this cooperative research endeavor -- the ultimate goal of which is to create a major paradigm shift in how people think about education.

This is undoubtedly an ambitious undertaking. But it should be exciting, and I believe it is very worthwhile.

The Need for Understanding Systemic Change

In the decade following the publication of A Nation at Risk in 1983, considerable effort has been undertaken to improve public schooling. Reform efforts have been typically referred to as site-based management, school restructuring, and educational systems design. Researchers such as Banathy (1991), Reigeluth (1992), Frick (1993), and Perelman (1992) have argued for systemic change in education. 'Systemic change' contrasts with numerous piecemeal reform efforts which have largely failed in twentieth century schooling.

However, the rhetoric of systemic change is not likely in itself to make any real differences in schooling. Such rhetoric has been around for some time. Understanding of educational systems change is needed for intelligent action.

Changing educational systems, if unguided by adequate theory of educational systems change, will be haphazard at best. The consequences of mistakes can adversely affect the very lives of students, teachers, administrators and their communities. Without an adequate theory of educational systems change, we will continue to restructure education largely by trial-and-error. It is no wonder that educational practitioners often distrust, resist and undermine the efforts of educational reformers. The stakes are very high. The consequences of mistakes can be devastating -- particularly when changing a whole system of education.

Understanding systemic change is not a simple matter. People will need to learn new thinking patterns. Hart (1992) has noted that the vast majority of individual belief patterns do not contain dynamic cycles. Cognitive maps of belief structures tend to be linear with few, if any, feedback loops. Hart indicated that exceptions occurred with those people in professions which taught them to think in dynamic cycles (e.g., ecologists, systems engineers).

Senge (1992) has provided insight into business organizations by identification of about 15 patterns of dynamic cycles. These patterns are not easily described or understood through static print and diagrams. Senge and his colleagues have developed role-playing activities and computer simulations in order to help business people understand these patterns of dynamic relationships -- most of which run counter to individual intuitions about how systems such as business organizations grow and change.

A Theory for Understanding Educational Change

Maccia and Maccia (1966) have developed an educational theory which is based on the SIGGS Theory Model. SIGGS in turn was created from concepts and principles in set, information, di-graph and general systems theory. Maccia and Maccia's educational theory contains 201 hypotheses, some of which have been verified through extant practice. For example, one of the hypotheses is: If centralization in an educational system increases, then active dependence decreases. Centralization is concentration of channels within a system. Active dependence is components which have channels from them. One only need look at the many instances of this pattern in the past 50 years. In the school consolidation movement during the middle part of this century, many American school systems increased in size and became highly centralized with respect to administrative decision making. The voices of concerned teachers, students, and parents and community members currently seem to have had little impact on administrative decision making. Most school systems operate largely as they have in the past, despite many well-intentioned reform efforts.

Further evidence to support this hypothesis comes from recent reform efforts in the Chicago Public Schools (Closer Look, 1994). The city-wide public school system was divided into individual and relatively autonomous local school systems. Key decisions are now made by Local School Councils, teachers and principals. Centralization has decreased, and it would appear that more parents, teachers and local community members are having their voices heard by the Local School Councils (Closer Look, 1994).

Maccia and Maccia's educational theory consists of 200 hypotheses in addition to the one illustrated above. To understand many of these hypotheses it is necessary to know the concepts and principles in the SIGGS Theory Model. Because of space restrictions, these are simply listed below with brief commentary following:

Basic SIGGS Properties: component, affect relation, information, selective information, system, negasystem, toput (system environment), input, storeput, fromput (negasystem environment), and output.

SIGGS Structural Properties (system configuration): system complete connectivity, strongness, unilateralness, weakness, disconnectivity, vulnerability, passive dependence, active dependence, segregation, interdependence, wholeness, integration, hierarchical order, flexibility, homomorphism, isomorphism, automorphism, compactness, centralization, size, and complexity.

In addition to system configuration properties -- i.e., how components are connected or related to each other -- there are dynamic properties which characterize how systems change through time.

SIGGS Dynamic Properties (system temporal change): system environmental change, feedin, feedout, feedback, feedthrough, filtration, spillage, regulation, compatibility, openness, adaptivity, efficiency, size growth, complexity growth, selective information growth, size degeneration, complexity degeneration, selective information degeneration, stability, state steadiness, state determination, equifinality, homeostasis, stress, and strain.

Click here to see Figure 1.

'Filtration' is defined as restriction in educational system toput, i.e., a restriction in the choice environment. A typical example is that state textbook adoption agencies restrict the availability of textbooks from which local schools can choose. Furthermore, state adoption committees in Texas, California, and New York act as significant filters of textbooks published in general. One of the Maccia and Maccia hypotheses is that as filtration increases, then educational system input decreases. Decreased input with respect to variety and richness of curriculum resources implies selective information degeneration in educational systems.

Click here to see Figure 2.

Understanding the Present and Past: Making the Familiar Strange

The SIGGS system properties, both structural and dynamic, can provide us with concepts and principles in order to understand existing educational systems in new ways. For example, I have known for some time about the power and influence that the textbook adoption committees in Texas, New York and California have had on the textbook publishing industry. It did not occur to me that this was an example of filtration until I tried to generate examples of this negasystem property.

The hypothesis that: "If filtration increases, then uncertainty in system input categories decreases" got me to thinking further. Input is 'selective information' in a system. 'Information' in the SIGGS theory is a characterization of occurrences through use of categories in a classification (a technical meaning from information theory). 'Selective information' means that there is uncertainty in the distribution of alternative categories. For example, if there are only two kinds of textbooks taken in by a system (such as math and history), and the probability of observing a math book is .90, versus .10 for a history book, then there is little uncertainty in the classification of textbooks. On the other hand, if the probability of a math book being observed is .50 and likewise for a history book, then uncertainty is maximum (for when there are two alternatives). An H measure from information theory can be used to indicate the uncertainty in a probability distribution of discrete alternatives.

When the uncertainty of occurrences of types of input increases, this means that there are more alternatives in the distribution of inputs; and the probability of occurrence of any one category of input is relatively small (hence greater choice within the system). When the uncertainty of input categories decreases, there is less choice within the system (fewer alternatives as a small number of categories have relatively high probabilities). If we look at categories of curriculum content selected by public educational systems, they are relatively few in number and fall into traditional subject matter domains such as history, mathematics, science, language arts, etc. Moreover, that content is represented largely in abstract form (printed text), with some static pictures -- i.e., in textbooks.

As a further example, if we go to an ice cream store, and our only choice is chocolate, then there is no uncertainty in the flavor of ice cream we might eat (that which becomes input in our digestive system). If our choices are vanilla, chocolate and strawberry, then there is greater uncertainty as to which ice cream flavor that we as a customer might choose to eat. If there are 33 flavors, uncertainty in the input distribution is likely to be even greater.

Most public school classrooms have struck me as rather barren places for learning to occur. Why is that? Basically, the choices that students have with respect to curriculum content are largely limited to a few textbooks and what a teacher says and does. Is this an example of selective information degeneration, a consequence of decreased input in an educational system that is predicted by the SIGGS theory? Compare this to the content outside of school classrooms and buildings as sources of potential learning "materials." The backyard behind my house and the city courthouse are much richer content resources, for example, for learning something about biology and the criminal justice system, respectively.

These thoughts lead me to wonder what would happen if current policies regarding textbook adoption at local, state and national levels were removed. With less filtering of content, there should be a greater variety of curriculum made available for educational systems to choose from. With more choices available to an educational system, we would expect to find a greater variety of curriculum resources taken in by that system. Hence, students in that system would have greater choice in curriculum resources to facilitate learning.

I did not have these thoughts until I had begun to consider properties of systems in general, and their relationships as hypothesized in the SIGGS educational theory. I believe that my understanding of educational systems concepts and relationships gives me new lenses -- new ways of seeing educational systems -- that I did not have before.

Inventing the Future: Making the Strange Familiar

It is difficult for us to envision new educational systems. Once we understand educational systems in new ways, we can "break set" in how we think about education. In the U.S. we typically think of an educational system as a school district consisting of a number of school buildings with classrooms, people licensed as teachers, students organized into groups largely by age, principals, a superintendent and a school board. It is hard for us to think about education differently.

Let me illustrate with some of my thinking when starting from a "clean slate" in considering education and educational systems. In the SIGGS theory a 'system' is defined a group of components with at least one affect relation which has selective information. The basic types of components in any educational system are teachers, students, content and contexts (Steiner, 1988). Instead of focussing on the components per se, I have recently found it more enlightening to focus on their interrelationships (affect relations -- cf. Frick, 1991; 1993). The basic classes of affect relations in any educational system are teacher- student, teacher-content, teacher-context, student- content, student-context, and content-context relationships.

A teacher is one who guides the learning of another. This defines a kind of affect relation between two persons. Person A may guide the learning of Person B, and Person B may guide the learning of Person A. For example my wife of Irish descent has taught me to cook Chinese style dinners. I have given her guidance in using our computer at home. Furthermore, guidance of learning is not restricted to direct instruction (e.g., lecture, demonstrate, answer questions, ask questions). Learning may be guided indirectly as it is frequently in Montessori classrooms in which it occurs through interaction with the curriculum materials. Furthermore, the older students may guide younger students in Montessori classrooms in which mixed-age groups exist. These older peers act in the role of teacher (i.e., one who guides the learning of another).

If teaching is viewed as an affect relation, then it unbinds us from thinking of teacher as a component in education. Teaching is a relationship between two persons, one of whom guides the other who follows. 'Teaching relationships' can exist among lots of pairs of persons. Such relationships are not limited to those persons in schools with licenses to guide the learning of students.

A student is one who intends to learn through guidance from a teacher. In contrast, a learner is one who attempts to learn without guidance - - e.g., by trial-and-error. An undesirable kind of affect relation would be one who is being forced to learn against his or her will. When students are forced to attend school and required to learn subjects that do not interest them, this is not a good kind of teaching- studenting affect relation. The most desirable kind of teaching-studenting affect relation is one in which one person intentionally guides another who wants to learn.

Content is that which is to be learned. There are both student-content and teacher-content affect relations. The kinds of student-content affect relations that we ought to create in education are cognitive, conative and affective. We want students to come to know the objects of learning (cognitive relationship with subject matter), to value such objects (conative), and to associate positive feelings with the objects of learning (affective). Subject matter need not be constrained to extant classifications such as mathematics, science, history, language arts, etc. The types of teacher-content affect relations can be similarly classified. Teachers should know the subject matter (and how to guide learning of subject matter, which is a further kind of understanding of content), value it, and love it.

Context is the setting in which guidance of learning occurs. When my wife helps me learn to cook, the context we work in is the kitchen. When I help her to use our computer, that usually occurs in the context of our home office area. Typical contexts of present-day, formal educational systems include classrooms in school buildings, principals, janitors, local school boards, furniture, black/white boards, overhead projectors, computers, books, libraries, gymnasiums, school buses, cash, cafeterias, food, etc. Context could also include state departments of education, and national departments of education -- if these are considered to be part of the education system.

We have student-context, teacher-context, and content-context affect relations. When I am learning to cook, student-context relations include my reading a recipe from a book, chopping vegetables, measuring rice and water, etc. When my wife is learning to use a word-processor to make large-print labels, student- context relations include her using a computer system and software program. (She makes curriculum materials for her pre-school Montessori classroom, which is a teacher-content relation.) There are also content- context affect relations. The object of learning may be symbolically represented through printed words in a book (e.g., a math textbook); the object of learning might be iconically represented through images on a videotape (e.g., a documentary on Martin Luther King); the object of learning might be physically present in the current setting (e.g., artifacts from an archeological dig; the city mayor herself).

 

References

Banathy, B. (1991). Systems design of education. Engelwood Cliffs, NJ: Educational Technology Publications.

 

Campbell, S. (Ed., 1976). Piaget sampler: An introduction to Jean Piaget through his own words. New York: John Wiley & Sons.

 

Closer Look (January, 1994). Chicago school reform. Chicago, IL: Designs for Change.

 

Frick, T. (1990). Analysis of patterns in time: A method of recording and quantifying temporal relations in education. American Eductional Research Journal, 27,1, 180-204.

 

Frick, T. (1991). Restructuring education through technology. Bloomington, IN: Phi Delta Kappa Educational Foundation.

 

Frick, T. (1993). A systems view of restructuring education. In Reigeluth, C., Banathy, B. and Olson, J., Comprehensive Systems Design: A new educational technology. Berlin: Springer- Verlag, 260-271.

 

Gardner, H. (1985). Frames of mind: the theory of multiple intelligences. New York: Basic Books.

 

Hart, J. (October, 1993). Cognitive maps. Presentation at the Cognitive Science Colloquium Series, Indiana University, Bloomington.

 

Luterbach, K. and Frick, T. (1993). Toward the design of an educational systems simulator. Paper contributed to the 1993 Asilomar Conversation on Educational Systems Design, Pacific Grove, CA.

 

Kuhn, T. (1970). The structure of scientific revolutions. Chicago: University of Chicago Press.

 

Maccia, E.S. & Maccia, G.S. (1966). Development of educational theory derived from three theory models. Washington, DC: U.S. Office of Education, Project No. 5-0638.

 

National Commission on Excellence in Education (1983). A nation at risk. Washington, DC: U.S. Governmental Printing Office.

 

Perelman, L. (1992). School's out: Hyperlearning, the new technology, and the end of education. NY: Morrow.

 

Reigeluth, C. (1992). The imperative for systemic change. Educational Technology, 32(11), 9-12.

 

Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. NY: Doubleday/Currency.

 

Steiner, E. (1988). Methodology of theory building. Sydney: Educology Research Associates.