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2000 Society for Design and Process Science Printed in the United States of America

TRANSDISCIPLINARY ENGINEERING EDUCATION AND RESEARCH MODEL

A. Ertas M. M. Tanik* T. T. Maxwell Texas Tech University Mecahnical Engineering Department Lubbock, Texas *University of Alabama at Birmingham Electrical and Computer Engineering Department Birmingham, Alabama

Since the medievel times the critical leading role of science has been a) to challenge the entrenched conceptions of human reason and b) to introduce new methods of investigation for deeper understanding of nature of things. Once again, a scientists, critical thinkers, and engineers wa are indtroducing new notions in the transdisciplinary arena from which new generation of intellectual and physical analysis and synthesis tools and techniques will be produced.These tools and techniques will take the form in which science, engineering, and management notions would be fused into a unified transdisciplinary entities. These development in integrated design and process science would in turn, once again, transform the human scene beyond recognition.

1. Introduction

“lf

you want a description of scientific method in three syllables, I propose: Guess and Test.” George Polya, Guessing and Scientific Method, in Mathematical Discovery, Wiley, 1981.

“Scientists have discovered many, peculiar things, and many beautiful things. But perhaps the most beautiful and the most peculiar thing that they have discovered is the pattern of science itself.” Steven Weinberg, Dreams of a Final Theory, Pantheon Books, 1992.

Transactions of the SDPS

DECEMBER 2000, Vol. 4, No. 4, pp. 1-11

“The result of the discovery of Harvey was the introduction of a new nomenclature. Until Harvey ‘s day, arteries were distinguished from veins by containing a different kind of blood. Men had no idea of the constant and massive change of arterial into venous, and of venous into arterial blood. A new nomenclature was therefore needed and it came with the new age which Harvey ushered in.” Charles Singer, A Short History of Anatomy and Physiology from the Greek to Harvey, Dover, 1957.

Harvey’s experimental masterpiece “An Anatomical Dissertation on the Movement of the Heart and Blood in Animals,” appeared in print in 1628. If any work is to be considered as marking the beginning of a new scientific age of Cartesian-Mechanistic thinking, it is surely Harvey’s work on circulation. In fact, the glass of knowledge had reached to a spilling point that it was ready to spill, thus causing a qualitative change, with the addition of a few more drops. It did not take long. Those additional drops came in 1637, in the form of “Discourse on Method” by Descartes thus permanently changing the way we think about nature, mathematics, and scientific process. The new age, Harvey helped ushering in, is now on its way out. The glass of knowledge is again almost full and ready to spill, thanks to almost 400 years of hard, creative, and dedicated work of fine human beings. The new age of “computing” is around the corner and we all are helping it to usher it in. There is no doubt the discipline of computing and its tools are facilitating the introduction of the missing drops to the glass of knowledge which will soon spill and will, once again, permanently change our way of thinking about nature, mathematics, and science. In the words of Nobel Laureate Steven Weinberg , “the most beautiful and the most peculiar thing,” the pattern of science will continue to evolve and help us to categorize, organize, and in one word to make sense of things and hopefully ourselves. The difference is however that we will do all these things in partnership with the ubiquitous computational element. From the pragmatic point of view, our hypothesis is that the systematic study of design and processes for their own sake has the potential of providing us the necessary notions to maintain an intellectual control over the ever expanding information expansion. Furthermore, the systematic study of business, government, and engineering processes would allow us to overcome the shortcomings of the classical Cartesian-mechanistic foundations and methods of traditional engineering by facilitating integration among disciplines. Future engineers or systems integrators, in this framework of integration, develop functional artifacts and services by taking into consideration economical, environmental, and ethical aspects of human awareness. The multi-disciplinary nature of design and process utilization would prove valuable in improving our overall research quality, productivity, and the education of our students to build, maintain, and manage the next generation of enterprises as well as their products and services (M. M. Tanik and A. Ertas, 1997).

Historical Perspective We tend to believe that the Cartesian-Mechanistic era is approaching its maturity and is being replaced by the era of integration and combinatorics. Last year (1996) was the 400th anniversary of the birth of great philosopher and mathematician Rene Descartes, widely known as the comprehensive presenter of the method of science as we know it. The modern scientific method in the Cartesian sense, based on deductive reasoning, observation, and experimentation has been in development and constant progress since the time of Thales around 600 B.C. The historical progress on the scientific method can be traced through the ages of Thales, Pythagoreans, Plate, Aristotle, Descartes, and Newton followed by the great technological advances of the last 100 years. Around 1600 Descartes’ call for experimentation

Journal of Integrated Design and Process Science

DECEMBER 2000, Vol. 4, No. 4, 2

coupled with mathematical analysis as a method of science has been embraced by large numbers of scientists and scholar. Descartes’ calling for “the infinity of experiments I require, and which it is impossible for me make without the assistance of the others” in the celebrated “Discourse on method” was implemented by scholars and engineers so effectively during the last 400 years that our success has been our failure — we are buried under the large amounts of information, knowledge and technology we produce. Therefore, we envision that the next era of scientific enlightenment will be in the assessment and integration of these mountains of information in a more controlled, humane, and intelligent way. The new era should address the issues of systematic knowledge integration (meta-fusion) to introduce some level of intellectual control on the cartesian knowledge islands. Two potential technical mechanisms to achieve this level of control are systems integration (through abstract design and process notions) (Tanik and Chen, 1991; Ertas and Jones, 1996) and use of combinatorics (interconnection mechanisms through the study of combinations). In this paper we provide examples of interconnection mechanisms between disparate areas of knowledge using the particular example of classic N-Queens problem (Ertas et al., 1992a). On the other hand, in this new era of integration teaching is primarily based on providing methods and techniques to the students so that they can obtain knowledge as needed. The instructor plays the role facilitator rather than fact-introducer. Automated tools become an integral part of teaching, as well as new knowledge generation, in this new era. New methods and protocols of knowledge generation based on meta level integration of Cartesian knowledge islands (Metafusion) will be recognized and developed. Emphasis will be on operational knowledge in the sense that new knowledge will be generated through systematic integration as an application need arises. A brief examination of the history of epistemology, from the stand point of ideas on generating new knowledge, also reveals three major themes or milestones. First come the ideas of Plato, who suggested that new knowledge is generated primarily through mathematical activity. The second milestone is Aristotle’s idea that new knowledge is generated not only by mathematical activity but also by observation and logical inference. Lastly, Descartes described knowledge in mechanistic terms and established the philosophy of the scientific method. Activities of Plato and Aristotle is classified as Platonic/Aristotelian era in which teaching style was primarily based on recognition of authority and regurgitation. Automation was not an immediate necessity for the application and success of the methods of deductive reasoning and observation. Traditionally, the social machinery for systematic knowledge generation and dissemination has been academies, lyceums, and universities. In the era of combinatorics powered by techniques of metafusion, integrated universities and polytechs guided by institutes of technosciences will be the leading mechanisms for knowledge generation. An institute of technoscience is not just a classical institute functioning as one of the known social entities of modern world. In the historical context an institute of technoscience resembles the establishment of the academies of 1600s such as “Academia dei Lincei in Rome-1603,” “Academia del Cimento in Florence - 1657,” “The Royal Society of London-1662,” or “The French Academy of Science 1666.” In modern form the institute of technoscience establishes a super-structure integrating educational institutes (the science motivation) and industry (technology motivation) into a value-added entity for the information value-chain of the society at large. Cartesian-Mechanistic era starting around 1600’s brought the method of systematic experimentation as a widely used method of science. As such, the method of science today is considered primarily as an activity composed of a combination of deductive reasoning, observation, and experimentation. The notion of Metafusion, defined as systematic integration of Cartesian knowledge units, expands the scientific method as we know it just as the notion of systematic experimentation the existing scientific method during 1600. Historical perspective for knowledge-generation and dissemination methods is summarized in Table 1 (M. M. Tanik and A. Ertas, 1997).



Table 1 Knowledge-generation and dissemination methods. Method

Era

Teaching

a)Deductive reasoning (Plato) Platonic/Aristotelian Primarily based on b) Observation and logic (Aristotle) authority and regurgitation Experimentation (Descartes)

Automation Need

Plato’s Academy Aristotel’s Lyceum

Minimal

Universities

Cartesian-Mechanistic Primarily based on instruction Increased

Meta-fusion (systematic knowledge Combinatorics/ geneartion) integration

Social Machinery

Primarily based on facilitation An integral part of the method

Integrated universities and polytechs guided by institutes of technosciences in the technopolices of the next century

Transdisciplinary Research and Education A particular area of study can be called a discipline provided that it has unified tools, techniques, and methods and a well developed jargon. Disciplines inevitably develop into self–contained hard shells which tend to minimize interaction with outside entities or other disciplines. The longer a discipline evolves, the harder its shell becomes. Practitioners of these disciplines develop an effective level of intradisciplinary communication due to their well–developed disciplinary jargon. Equally, the rigid disciplinary shell and the precision of the disciplinary jargon tend to minimize interdisciplinary communication. Thus, from the social sciences point–of–view disciplines develop territories that are fiercely defended. Obviously, these territories and disciplinary shells are not in–sync with the move toward the integration of technology. Engineering problems are not often restricted to these artificial discipline oriented boundaries. In the era of the Cartesian–Mechanistic mindset this approach served well in solving the major problems mankind faced. Times have changed, however. A massive communication infrastructure coupled with a massive computational infrastructure has promoted the attack on larger and larger problems using larger and larger groups of people. Multidisciplinary teams and programs have been developed to address real problems that stretch across several traditional disciplines. However, inadequate interdisciplinary communication and territorial concerns limit the effectiveness of most current multidisciplinary efforts. The same phenomenon can also be observed in corporate mergers. Faced with interdisciplinary problems, large corporations are buying companies to form massive conglomerates. Educational systems, due to their massive administrative and Cartesian–Mechanistic structure can not respond to these demands for educating the masses in–sync with changing times. The Cartesian– Mechanistic era is approaching its maturity and is being replaced by the era of integration and combinatorics. (Tanik, et. al., 1995a; Tanik and Ertas, 1997) In this new era of integration teaching will primarily consist of providing methods and techniques to the students so that they can obtain knowledge as needed. The instructor will play the role of facilitator rather than fact–introducer. Automated tools become an integral part of teaching, as well as new knowledge generation, in this new era. New methods and protocols of knowledge generation based on meta level integration of Cartesian knowledge islands (Meta–fusion) will be recognized and developed. Emphasis will be on operational knowledge in the sense that new knowledge will be generated through systematic integration as an application need arises. Educational systems can respond to these changes by introducing the new concept of transdisciplinary education. The transdisciplinary education concept recognizes the existence of disciplines, the existence of strong intradisciplinary connections, the naturalness of weak interdisciplinary connectivity and interaction, and as a result, the need for multidisciplinary fusion. Integrated combinations of the tools, techniques, and methods from various disciplines coupled with the development of a transdisciplinary jargon constitutes



the transdiscipline. The leap from multidisciplinary or interdisciplinary education models to transdisciplinary education emphasizes that the fundamental ideas of design and process science are key to education. The common threads of all disciplines are design and process science (Tanik, et. al., 1995b). Design and process provide the patterns, the insight and the logic necessary to apply knowledge and skills to any problem. From the pragmatic point of view, the systematic study of design and processes for their own sake has the potential of providing the necessary notions to maintain an intellectual control over the ever expanding information expansion. Furthermore, the systematic study of business, government, and engineering processes would overcome the shortcomings of the classical Cartesian–Mechanistic foundations and methods of traditional engineering by facilitating integration among disciplines. Future engineers or systems integrators, in this framework of integration, develop functional artifacts and services by taking into consideration economical, environmental, and ethical aspects of human awareness. The transdisciplinary nature of design and process utilization would prove valuable in improving overall research quality, productivity, and the education of students to build, maintain, and manage the next generation of enterprises as well as their products and services. Currently, each discipline presents the fundamentals of design and process, frequently by other names and perhaps unknowingly, in its own context and jargon. Thus, the difficulty of interdisciplinary communication. The first step in achieving transdisciplinary education is to extract the common elements, design and process, from existing disciplines and synthesize them into the foundation of the new transdiscipline. This extraction process can only be accomplished by an extensive study of the disciplines with the specific goal of identifying the truly common aspects. Once the universal aspects of design and process have been identified, they must be woven into the fabric of the transdisciplinary educational model. The transdisciplinary jargon should simultaneously begin to develop during this process.

Logic is the youth of mathematics and mathematics is the manhood of logic [Bertrand Russell, 1919] The scientific way of forming concepts differs from that which we use in our daily life, not basically, but merely in the more precise definition of concepts and conclusions; more painstaking and systematic choice of experimental material, and greater logical economy. [Albert Einstein, 1950] Nature, it seems, does not simply incorporate symmetry into physical laws for aesthetic reasons. Nature demands symmetry. [Michio Kaku, 1999]

As Einstein so eloquently expressed above, the scientific way of thinking is not fundamentally different from everyday thought processes. However, nature demands symmetry, and the machinery of logic and mathematics is waiting to be exploited and applied. The notions and patterns of design and process are so fundamental that they cut across all disciplines. These concepts introduce greater logical economy into the treatment of everyday concrete processes involving engineering activities and business relationships. Because of the enormous expansion of knowledge and the speed of introduction of new and exciting technological artifacts, this greater logical economy is needed now more than any other time in the history of mankind. Transdisciplinary education and research is the logical extension of interdisciplinary and multidisciplinary programs. As discussed above, the natural tendency for disciplines to become autonomous will always



Intradisciplinary (within a discipline)

Transdisciplinary or Multidisciplinary fusion (beyond disciplines)

Interdisciplinary or Multidisciplinary (among disciplines)

Figure 1 Disciplinary Systems.

limit the effectiveness of interdisciplinary and multidisciplinary programs, thus, the need for multidisciplinary fusion or the transdisciplinary model. Figure 1 depicts intradisciplinary, multidisciplinary, and transdisciplinary systems. Note the heavy wall which limits interactivity around the green disciplines in the first two categories. In the multidisciplinary model communication paths are established between disciplines, but these communication paths may not link all the disciplines directly and they may not be entirely adequate. The transdisciplinary model has only fuzzy interfaces—no barriers. The core design and process activities encompass all of the topical areas and some of the topical areas overlap. Communication and interaction is easily accomplished. In the transdisciplinary educational model, students’ characteristics, needs, interests, and personal learning processes are central to the learning experience; these objectives are as important than the teaching of specific knowledge and skills. Students work on independent projects and with other students on teams projects. The independent projects develop initiative, imagination and creativity, research skills, analysis and synthesis skills, self confidence, and autonomy. The team projects develop teamwork and leadership skills. As projects evolve and are completed, students acquire technical knowledge and skills. However, project goals, rather than the learning of specific knowledge areas, are the focus. The formal lectures and timetable typical of classroom courses are replaced with a completion date for each project and informal discussions among the students and faculty. Some discussions may be scheduled for convenience, but most will be occur spontaneously as problems are encountered and overcome. Thus, the learning experience is much more dynamic and exciting. Subject material can be delivered through various network communication formats. As students apply the subject material and skills to their projects discussions with faculty and other students will provide insight and examples. Just as much subject material can be presented to students as in traditional courses, but, much more will be learned and understood. Clearly the transdisciplinary educational process will require different course materials and a significantly different relationship between faculty and students than traditional courses. Faculty will act as mentors or guides to assist students in discovering, applying and understanding information, technical knowledge, and skills.



Transdisciplinary Research and Education in Engineering The transdisciplinary model for research and education can certainly be applied to engineering. This does not mean that the traditional engineering disciplines must be completely disassembled and thrown out. It does mean that the areas of knowledge typically included in each of the disciplines will be presented within the transdisciplinary structure of design and process and that the boundaries between the knowledge areas will be much softer. In addition, concepts and knowledge from traditionally non– engineering areas such as business, economics, enterprise, human relations, etc. will be included in the mix much more naturally. Thus the engineers produced by the transdisciplinary educational process will be much more well rounded and capable of dealing with complex problems which involve many issues that span the educational spectrum. An inherent characteristic of the transdisciplinary engineering research and educational model is that all of the normal engineering knowledge and skills such as analysis, experimentation, synthesis, etc. are considered tools for design. Transdisciplinary engineering research and educational programs may consist of four core courses supported by supplementary courses and team projects. The core courses are

1. 2. 3. 4.

a design fundamentals course, a process fundamentals course, a systems fundamentals course, and a metrics fundamentals course.

The design course will develop the fundamental nature of design abstractions as a key engineering tool. The process course will develop the key concept and techniques in dealing with process development and management. The systems course will develop the philosophy of integrated systems with emphasis on the interplay between tools and techniques of different disciplines. The metrics course will develop the concepts of engineering measurement as well as quality assurance. These four courses are all needed for transdisciplinary engineering education. The specific knowledge courses which constitute the remainder of a curriculum will embody the specific knowledge and skills related to that topic. For example, the vehicle engineering program will include courses that detail the integration of vehicle systems such as the engine, engine control module, transmission, vehicle electrical system, braking system, etc. Sub–system and vehicle system performance parameters and modeling of vehicle performance will be emphasized. Figure 2 indicates how the supplementary courses revolve around the core courses and are supported by a transdisciplinary team based design project. The structure shown in Figure 2 is intended for a 36 semester hour Master’s degree program which includes: core courses—12 hours, specific knowledge courses—18 hours, and a transdisciplinary team project that supports and extends the course work—6 hours. The team design projects must be closely associated with ongoing research programs such that the students are a part of the research team with the faculty. The existence of man can be viewed as a continuing effort to solve or overcome problems; technical problems, social problems, political problems, etc. The transdisciplinary approach provides an umbrella of the core design, process, systems, and metrics common to all disciplines that is necessary for problem solving. Design includes problem description, organization of resources, synthesis of ideas, construction, testing and evaluation. These steps are needed to develop an automobile, a health care organization, or a program to reorganize a criminal justice system. Process involves the methodology by which a task or set of tasks is carried out. In each of the examples above the development must proceed through a series of processes. Processes can be mechanical, electrical, chemical social, political, etc. A basic understanding of these processes and how they affect outcomes is indispensable for large team projects. Good solutions



Specific Knowledge Course Specific Knowledge Course

Specific Knowledge Course

Design Course

Process Course

Systems Course

Metrics Course Specific Knowledge Course

Specific Knowledge Course Specific Knowledge Course

Transdisciplinary Team Based Research Project

Figure 2 Transdisciplinary engineering research and education model.

to problems must be integrated systems that mesh with existing structures and organizations, not merely isolated patches. A fundamental understanding of how systems are integrated from components and sub–systems is necessary to view a problem and its environment from an overall perspective. Finally, evaluation can only be effected through the application of metrics. Interdisciplinary and multidisciplinary curricula developed and in use today represent initial steps on the road to a transdisciplinary curriculum. However, these older concepts largely involve including traditional courses from two or more disciplines in a curriculum. There is usually little or no attempt to make individual courses multidisciplinary and blend the concepts from various disciplines together. Neither traditional textbooks nor university course organization make it easy to develop and deliver true transdisciplinary courses. However the proposed transdisciplinary design curriculum will consist of true transdisciplinary courses. Boundaries for transdisciplinary courses are the boundaries of the problem being addressed, not the artificial boundaries of disciplines. A transdisciplinary course must involve multiple faculty or mentors so that the concepts covered can be presented from several perspectives and so that the integration of knowledge, skills and jargon can be more fully appreciated by the students. Course material will be divided into modules which cover specific topics or concepts. Modules will be developed by faculty directly involved in the course and by faculty or industry experts not directly involved in the delivery of the course. Each course will include project or laboratory exercise modules through which the course material will be presented and put into practice.



The challenge is to discover matching techniques and methods so that a) the courses will be mapped to a collection of specific learning competencies, b) seamlessly integrated into high technology formats, c) stored in an easily accessible multimedia database, and d) delivered in numerous formats suitable for anytime anywhere’ paradigm. To meet this challenge an innovative method of decomposing courses into electronically manageable semantic units called Operational Knowledge Units (OKU) will be utilized (Yildirim, et. al., 2000). An OKU is the least knowledge unit that an educator deems as an essential building block. When one puts say 20 to 40 blocks together they will make a given course. The OKU concept for course organization is not dependent on transdisciplinary programs; however, OKUs epitomize the transdisciplinary logic. These semantic units correspond to specific learning competencies. The innovation is that an OKU is a process not just a module in the classical sense. For example, specific information about the French revolution can be encapsulated into a module but this would not be an OKU since there is no process in this module. In a module without a process a student either recalls the information or not. Whereas, in an OKU the student has to perform a process (activity) to internalize the knowledge presented. For instance, an analytical exercise, a laboratory exercise, a discussion with other students, or perhaps a short project. What is important is that the student immediately put knowledge to use. The student then goes through the same process to generate an answer to demonstrate mastery of this specific knowledge competency. During this process a student may make a number of false starts say in solving a problem but corrects his or her mistakes and teaches himself or herself thereby assuming responsibility for his or her education. Mapping courses into OKUs representing specific learning competencies will provide many academic, administrative, and technological benefits. For example, a uniformity will be introduced for better transcript evaluations, more effective facilitation of credit transfers, adoption of courses produced by others, and more consistent student advising. The examples of technological advantages will be the seamless integration into high technology formats, easily accessible multimedia databases, and systematic delivery in numerous formats suitable for the anytime anywhere paradigm. Figure 3 depicts a typical course structure for a transdisciplinary engineering program. It should be reemphasized that the modules or OKUs will be developed by various experts from industry, the university, or research labs. Many of the OKUs will have been developed by the faculty teaching the course. A data base of OKUs is needed so that courses can be built to meet the current needs of students. OKUs will be periodically reviewed and updated as needed to keep abreast of changing technology. Appropriate network communications technology will be used to store and present the OKUs as needed. Traditional textbooks will serve only as reference material. Students can acquire hard copies of OKU materials if desired. Teaching methods must continue to evolve. Many instructors have developed ways to enhance the typical lecture style delivery of information. Repetition of information is critical to understanding and retention. However, repetition must be augmented with creativity, problem solving skills, and logic. Material should be presented to students in many formats and environments. This multiple delivery procedure can ensure that students become and remain interested in the material and that every student receives instruction in a mode that matches his/her primary learning capabilities. Further, it is critical that students be motivated to learn. Maturity of the student has much to do with his desire to learn, but the younger and less mature students must be challenged so that they become motivated to learn not only to gain specific skills and knowledge but purely for the sake of learning. Course delivery will involve a series of exercises related to the OKUs and one or more projects that reinforce material presented in the OKUs. A team approach is absolutely necessary. People working as



Specific Topic OKU

Specific Topic OKU

Specific Topic OKU

Specific Topic OKU Core OKU

Specific Topic OKU

Core OKU

Core OKU

Core OKU

Specific Topic OKU

Core OKU

Specific Topic OKU

Specific Topic OKU

Projects

Figure 3 Transdisciplinary course structure.

members of well founded and managed teams can accomplish so much more than they can as individuals. However, teams are difficult to organize and manage and teams require much support if they are to reach their full potential. Students need more than exposure to teams and team work. The entire transdisciplinary curriculum is a team based process. Instructor teams are involved in the development and delivery of courses. Students teams will be assigned to projects. However, most importantly, instructors and students will work together as a learning team. The development of a new teaching/learning paradigm that address these and other concerns must make full use of the internet and the associated tools it can provide to enhance the interaction between students and instructors. Care must be taken in developing a curriculum and associated delivery process to allow for continued adaptation to technology advances as they become available. The internet should be incorporated because it provides tools that can augment the educational process by allowing students access to presentation materials at any time so that they can work ahead or review, by providing both synchronous and asynchronous communication with instructors and other students, etc. Use of internet delivery as a part of course presentation allow for on–campus and off–campus students to participate.



Concluding Remarks A new model for higher education and research has been presented. The leap from current multidisciplinary and interdisciplinary education models to transdisciplinary education emphasizes that the fundamental ideas of design and process science are key to education. The transdisciplinary education concept recognizes the existence of disciplines, the existence of strong intradisciplinary connections, the naturalness of weak interdisciplinary connectivity and interaction, and as a result, the need for multidisciplinary fusion. Integrated combinations of the tools, techniques, and methods from various disciplines coupled with the development of a transdisciplinary jargon constitutes the transdiscipline. An integrated transdisciplinary education and research environment which combines the strength of many engineering disciplines is essential to meet the challenges of 21st century technological development.

References Tanik, M. M. and A. Ertas, A. , 1997, ‘‘Interdisciplinary Design and Process Science: A Discourse on Scientific Method for the Integration Age,“ Transcation of the SDPS: Journal of Integrated Design & Process Science, Vol 1, No 1, pp. 76-94. Ertas, A., and Jones, J. C. , 1996, The Engineering Design Process, Second Addition, John Wiley & Sons, Inc., New York, 1996. Ertas, A., Maxwell, T. T., and Jones,J. C. , 1996, IDEATE Graduate Design Program at Texas Tech University, SDPS, The Second World Conference on Integrated Design and Process Technology, IDPT–Vol. 2, pp.386–388,1996. Jones, J. C., Ertas, A., and Parten, M., 1995, Multidisciplinary Engineering Design Program at Texas Tech University, SDPS, The First World Conference on Integrated Design and Process Technology, IDPT–Vol. 1, pp. 117– 120,1995. Tanik, M. M., Ertas, A., and Rainey, V., 1995a, On the Nature of Research, Education, and Training: A Partnership Model, SDPS, The First World Conference on Integrated Design and Process Technology, IDPT–Vol. 1, pp. 506– 510, 1995. Tanik, M. M., Yeh, R. T., and Ertas, A., 1995b, Integrated Design and Process Strategies, SDPS, The First World Conference on Integrated Design and Process Technology, IDPT–Vol. 1, pp. 511–514, 1995. Tanik, M. M. and Chen, Y.T., 1991, On Quantifying Software Reuse, 15th Annual Computer Science Conference, FNTAU, Hewlett Packard, Irving, Texas, April 1991. Yildirim, A., Tanju, M.N., Tanik, M.M., and Ertas, A., 2000, An Internet Based Interactive Course on Digital Signal Processing, Proceedings of the Fifth World Conference on Integrated Design and Process Technology (IDPT 2000), June 4–8 2000, Dallas, Texas (CD–ROM), Copyright 2000 by the Society of Design and Process Science (SDPS).

