“Teaching of science at universities: present status and future challenges”

The Teaching of Scienc= es in higher education

The Present and Future Challenges

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<= span style=3D'font-size:14.0pt;mso-bidi-font-size:10.0pt'>Theme 2= : Identifying society = needs and productive sectors as well as other faculties and schools in terms of science programs and curricula, with special attention to the ethical dimen= sion in teaching of sciences

Dr. Abdallah sfeir, Vice-president for academic affairs

Lebanese American Univ= ersity - Beirut

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1- Abstract

Careers= are rapidly changing and future professionals must face the double challenge of rapidly changing technologies along with an internationalized work market imposing greater geographic and sectorial competition and mobility. This is nowhere more applicable than in careers related to science and technology. = The implications are that graduates must have a self-sustainable knowledge base= and a good preparation to live and compete in a world that extends beyond their immediate surroundings.

This presentation will d= iscuss issues related to the identification of needs of the productive sectors and= how such needs may be addressed as far as science education is concerned. The subject is addressed from a structural macro view on science education, rat= her than enumerative listings of subject matter. Emphasis is on the need for industry-education partnership as well as highlighting the dangers of “just-in-time” production of graduates. Ethical and moral implications are considered through the broader question of societal needs = of education.

2- Introduction

I am tempted to start this talk by repeating an amended version of a famous saying by a French mathematician: If I try to address the question concisely, I will certainly not be accurate, and if I try to be precise, we will not have the time to cover the subject. Actually, irrespective of the = time allotted, it would be too presumptuous to say that I have the answer, at be= st, I have some parts of the answer. This theme, as indeed, the larger question= of “what education for what society” is one of the most challenging problem that decision makers have grappled with ever since education has emerged as one of the most important factor in the socio-economic developme= nt of nations.

Reducing the difficulty by focusing again on science programs will = make answers easier to come by, but again, I will not have the audacity of being= too affirmative, but will instead highlight the main trends and current beliefs shared by the education sector. Local conditions will be emphasized, but without loosing sight of the global worldwide picture.

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3- Educa= tion and societal needs.

Firstly, I will challenge the idea that education, even when limite= d to science education, is meant essentially to address specific needs of the productive sector of the economy. I equally disagree with many educators who hold the the view that education is dissociated from societal needs and concerns.

I will challenge the first proposition in a very pragmatic way: addressing specific productive sector needs is no more possible in today’s’ rapid changing technologies. Moreover, even if it were possible, this will produce a “just-in-time” graduate trained to execute specific skills that will soon fall into obsolescence. <= /span>

There are more philosophical reasons to challenge this proposition,= as well as the counterproposition. Education is continually being redefined and re-invented in the context of the present market/profit driven economies. Indeed, the very concept and raison d’être of Universities and higher education seems sometime = to be in crisis. Are Universities merely the place where young men and women g= ain the skills needed for a career? To make a living? Or to have life? A lot is continuously being written about the apparent contradictions between professional education and the values upheld by the traditions of liberal a= rts and/or classic education. Whereas this topic is not specifically the subjec= t of this evening’s meeting, we will give it some attention, as it is part= of the equation. Benjamin Rush, an educator who had defining influences on lib= eral arts education in the US “wanted institutions to produce citizen-lead= ers who possessed the comprehensive knowledge and virtue needed to build a just, compassionate, economically sustainable democracy. He promoted a liberal-ar= ts education that would be useful and applicable for all graduates, no matter = what their occupations or service, including unequivocally, business.”

The solution lies somewhere between the extreme bounds of the proposition and its contrary. Indeed, there are several and differing answe= rs depending on:

·= ;   The education specialty (general science, engineering, technology, medical…)

·= ;   Whether public or priva= te

·= ;   The specificities of the productive sector

·= ;   Etc.<= /span>

Higher education accreditating agencies address this issue by stres= sing the “outcomes approach” whereby institutions must demonstrate t= hat they are properly and optimally graduating students that have the qualifications described in the mission statement of the institution. This = in itself does not provide a link to the “productive sector”; howe= ver, constituencies of the institution that will normally include representative= s of the local or regional socio-economic sector must define mission statements = and educational objectives.

4- Defin= ing the Needs

Defining the needs of the productive sector is far from being a tri= vial matter. I still remember this statement by the human resource manager of a major European electronics company [quoting from memory]: In 10 years-time = 80% of my staff will still be working in the company in technologies, that neit= her you nor I know anything about today. How do you [educators] train scientists and engineers for such careers?” This was addressed to science and engineering educators in a meeting with industrialists held in Brussels und= er the auspices of the EU.

At the time when technology developed at a slow pace, sectorial nee= ds were easily defined and prospective developments identified with minimal ri= sks. Ray Kurzweil states: “ An analysis of the history of technology shows that technological change is exponential, contrary to the common sense intuitive-linear view. So we won’t experience 100 years of progress in the twenty-first century, it will be more like 20,000 years of progress at today’s rate”.

Our intuitive-linear view might lead us to say that this is an exaggeration, but let us look at facts. The pattern of economic development, that charts economic value-added versus time, shows that the economy of the future derives from the science of today, and development goes through four stages [reference]:

a. Gestation: Scientific breakthrough

b. Growth: science transla= tes into technology

c. Maturity: technology is industrialized and marketed on large scale

d.Decline: optimized prod= uction reduces labor, growth slows down.

Christoffer Meyer and Stan Davies go on illustrating this cycle for= the Industrial Revolution and for the Information Technology. The cycle of the industrial revolution starting with the discovery of the basic laws of classical mechanics, thermodynamics and electricity, lasted for about 200 y= ears from 1750 to 1950. The cycle for IT is almost complete in about 60 years. <= o:p>

Another difficulty in defining needs is the large socio-economic diversity of today’s global village. There are huge differences and volatility in industrial needs, and it would be foolish to address the immediate short-term needs of the national close-proximity sectors. In a way Universities are themselves important “knowledge-industry” acto= rs as this industrial sector becomes predominant in world economics. Moreover, this sector is open to competition and the ruthless rule of survival of the fittest. Concern for immediate needs of the sectors in close proximity may prove to be fatal to the institution.

5- addre= ssing the needs

Keeping in mind the areas of uncertainties and fuzziness mentioned = the previous section, as well as the need to commit educational institutions to quantifiable outcomes we have set the stage to investigate how education can address the needs of productive sectors in science education. We mean here science in its wider sense that includes the entire natural and physical disciplines as well as mathematics, and engineering.

Evidently, we are in a situation of chasing a moving target. Depend= ing on specific sectors, the target may be moving over a larger or smaller range and at various speeds. The issue involved at this stage of the discussion is the cascade of causal relationships that drive the change in educational objectives, programs, and program delivery.

Historically, and simplifying for the sake of clarity, one could see two parallel models co-existing: universities and “professional schoo= ls”. The former were not meant to provide professional training in specific area= s of the economy, while the latter were closely linked to such an objective. Bas= ic science was the concern of universities, applied science and professional training were left to professional higher education institutions that inclu= ded medical instructions and associated disciplines as well as architecture and engineering technologies and related areas. The industry itself provided for instruction and training in areas associated with its trade. This was an outgrowth of the practice of instruction-by-apprenticeship that was used in medicine, architecture, pharmacy, engineering, etc. The “trades” later consolidated through organization of the profession and or government legislation, and instruction centralized into schools or university departm= ents dealing with the specific disciplines. Professional organizations or govern= ment legislation later forced these institutions to consolidate.

Until now, and in many countries, professional education conserves = some of the features inherited from this history. This is the case with the way schools of medicine organized in Europe and the US, the way architecture mo= ved from apprenticeship to “Beaux Arts”, the way schools of enginee= ring replaced industry-related engineering training in the US and Europe, and pa= rtly the way the French “grandes Ecoles” were born.

Through this transition, instruction through apprenticeship progressively moved to more formal teaching methods that usually comprise practical component through laboratory work, or other forms of experiential education. Consequently, distance between education and the workplace widen= ed. Presently, these historical aspects tend to disappear, and strong structural bonds between professional education and the workplace have subsided and progressively replaced by a variety of more complex of models. These relationship may retain some structural links or left to natural interactio= ns and market rules. Whereas all models have some sort of common denominator a= nd a shared concern to prepare professionals to meet societal needs, the way nee= ds are perceived and addressed differ appreciably.

5.1 Traditional sectors

Traditional industries have evolved more slowly and program content= s do not vary substantially year to year. In fact, such industries are generally based on the science that pre-dated the “Industrialization era”, and include sectors such as construction, power and mechanical systems, transportation, water technologies, etc. Not to say that these sectors have= not evolved, but their progress did not call for any new major shift in programs beyond regular curricular updates that most institutions of higher education with qualified faculty are able to do provided a number of structural links= exist with the production sector.

In Lebanon, we have a good example at hand where education matched = the need of the productive sector. This is the case of the construction industr= y where the success of the Lebanese construction companies in the region was essentially built on an exemplary collaboration between the education sector and the industry[1]. The same can be said about the succes= s of the medical sector, tourism and banking. We could easily replicate these go= od lessons from the past.

A number of these companies have established themselves as some of the most competitive civil engineering and construction businesses worldwide. Many of them have bought out other western firms, and long after the construction boom dwindl= ed down, they are competing in the rest of the world and fairing quite well. Unfortunately, the real lesson of this success has often been misunderstood. Carried over by this success, a momentum has built up leading to huge numbe= r of students seeking training in specialties relating to the construction indus= try; but employment opportunities are no more in this sector. What is perceived = as an excessive number of engineers in the country is really a mismatch in specialties and quality of training between graduates and the new economy w= ork market.

The import= ance of university-industry cooperation is the real lesson to learn. Indeed, the symbiotic relationships that existed between engineering schools and design= and construction firms during that past era were exemplary. Many faculty were i= nvolved as consultants, many practicing engineers were involved in part-time teachi= ng, students were given opportunities to train on the job, programs were strong= ly affected by the needs of the markets, etc. Most importantly, the degree of professionalism and quality of services used in that industry were at par w= ith the level of education and scholarly research practiced in universities. Th= is is the real lesson that needs be replicated in the new emerging sectors.

5.2 Mode= rn technologies

Modern technologies starting with the information revolution and associated disciplines, knowledge industries, bioengineering, genetics, nanotechnologies, etc. pose problems that are far more challenging. The tar= get is moving fast, and chasing it leads to a complex dilemma: meeting sectorial needs at the expense of long-term performance of graduates. Furthermore, institutions of higher education have more difficulties evolving their prog= rams in such areas unless they are themselves players in the field through their research activities.

We now rea= lize that the model whereby people study until their early twenties, work till t= heir sixties and retire thereafter is rapidly disappearing. One has to work while studying, and studies while working. The life cycle of what we carry out wi= th our degrees is shorter than ever. A clear demonstration of students’ abilities to “graduate” in different majors several times during their professional life is a basic requirement of modern technology. Moreov= er, the challenge is to be able to give this skill to students, while giving th= em at the same time short-term marketable skills insuring successful entry into the work market.

Such a challenge should be tackled as a joint venture between industry and academi= a. The mechanism for such an approach is not easy to find in view of the diffe= rent immediate concerns and constraints of each of the parties. Industry faces s= hort term productivity concerns that translate most of the time into putting far more emphasis on short term productivity of graduates; academia think otherwise. Industrial costs have progressively lead businesses into the “just-in-time” approach, which, quite frequently has also been applied to human resources. Long-term effects of such an approach have prov= en catastrophic in many countries. A vivid example of this is the worldwide unemployment crisis in the field of IT that was due to the gross mismatch between the work force and the emerging needs of the micro computing indust= ry, and the resulting trends in downsizing, networking, etc.

Intristing= ly, some old values are re-emerging, and solutions may be provided by less rath= er than more specialization. Obviously, program contents are but a small part = of the equation and “programming” is by itself a static exercise, where change is the required mode. Clearly, the rapid evolution and sophistication of today’s science and the unpredictable complexity of= the combinatorics of a diversity of fields cannot be confined to stringent curricula of manageable size. The question that needs answering is “h= ow to educate” rather than “what programs”.

Educating perpetual self-learners is definitely the objective that we need to address. Few will disagree with such an aim, but not all share the road map. Some of= the commonly agreed ideas include:

<= span style=3D'mso-list:Ignore'>(i)&= nbsp;           &nbs= p;    a broad-base basic science programs=

<= span style=3D'mso-list:Ignore'>(ii)=             &nb= sp; improved science-education practice= s

<= span style=3D'mso-list:Ignore'>(iii)             personalized upper-division curricu= la

<= span style=3D'mso-list:Ignore'>(iv)=              training for research at undergradu= ate level

A basic broad-base scientific education is rarely questioned. Evidently, this is ea= sier said than done, due to necessary limitations to the total program volume. B= ut this difficulty is not new, and is generally alleviated through careful selection of material, and unloading part of the content to pre-university education as has been taking place regularly [2]. Careful selection should take in consideration the fundamental aspect of the science rather than its applicability at this stage. Indeed, sacrificing to latest fads in education has proven to be counterproductive. Few years ago, many programs were started on themes such as “solar energy” and “renewable energy”; we now find that programs emphasizing the b= asic sciences, on which these disciplines are based, have been more successful. Basic thermodynamics, heat-transfer, and fluid dynamics provide a base to t= hese disciplines, but to thousands of others, many not yet known.

Improved science education practices have been the concern of many educators in the = past decades. Western industrialized countries are regularly suffering from low enrollment in science-based programs forcing them to rely increasingly on foreign students. Many initiatives have taken place, or are underway, to increase the attractivity of the sciences, as well the quality of the education.

For the most part of the twentieth century, science seemed to provide the solution to all problems of humanity, now we blame it for all its ills. The public has grown progressiv= ely suspicious about science. The public image is that science is essentially exact, procedural, deterministic, and since it is so, why didn’t scie= nce predict all the negative impacts it is now having on environment, health, depletion of resources, etc.

It is a fact that computati= onal power modeling and simulation have invaded us to the point where scientists themselves have often forgotten the essentially non-exact nature of science, its non deterministic creative component, experimentation, uncertainty, and= the fact that it is an “ever-ch= anging and open to question as part of a dynamic social enterprise”.<= /p>
In his most recent book entitled “Soyez Savant, Devenez Prophète”[3]; Nobel Prize winner George Charpack is urging educators of 21^st century children to stress the essential component of experimentation to learn science through discovery rather than through theorems and abstract laws and statements. In science, nothing is engraved in marble, and everything is open to questioning. What has changed now, is that this questioning will occur several times in the life of a hum= an being while in the past, questioning and revision of science laws occurred every few centuries.

Many distinguished scientist are even challenging the procedural deductive approach to mathematics itself. In a recent controversial book by= the creator of Mathematica, “A New Kind of Science”, Stephen Wolfram claims that mathematical analysis, an 18^th and 19^th centuries invention has practically outlived its times, and that this will progressively be replaced by a more experimental approach to science using = the computer as a laboratory instrument. This is brilliantly illustrated by a 1= 200 page book essentially devoted to cellular automata and their capacity to so= lve a variety of science and engineering problems without the use of mathematic= al analysis. Many scientists agr= ee with this thesis, and say that, without the computer, fractal mathematics w= ould have never been discovered; the computer is to fractals what the electronic microscope is to physics.

Again, the problem here comes from the way science is taught, rather than program contents. Preparing future generations of higher education fac= ulty is a central concern of many professional organizations, particularly since such faculty is usually trained through research programs where emphasis is= on getting results that would guarantee more research funding.

With a broad quality scientific basic education, one can build a multiplicity of tailor-made applied science programs to fit specific conditions. Such a solution is not without difficulties, and it involves a = very dedicated faculty, very motivated student, and a very rich environment in educational resources. Indeed, such individualized program, will involve a “coaching” faculty rather than a “teaching” faculty, for most of the teaching-learning process will not take place in classical classroom environment, but through personal research in the laboratory, library, computer centers, and outside campus. This has traditionally been = the case in graduate education, but is progressively migrating downwards to undergraduate education.

Knowledge is ubiquitous; it is everywhere and no more the monopoly = of learned people. However, knowledge has gained not only in volume but also in complexity and complication. Few disciplines live and flourish independentl= y of others, every thing affects every thing else. Hence a broad science at the = basis, and individualization at the top. This model also helps retraining for other disciplines several times during a career.

6- Ethic= al Dimensions

Ethical impacts of science and technology have become a major conce= rn of modern societies. The image of the “mad” scientist is a comm= on stereotype that, although strongly overemphasized by media, is unfortunately somewhat true. I do not mean here only the “Dr No”[4] type or those scientists that use the potent power of their specialty for criminal or delinquent acts. I also mean those well-intending researchers t= hat have to withstand the worst of the negative and unethical side effects of experimentation that touches upon philosophical questions and strongly impa= ct human values and societal concerns.

This is both a major current concern, as well as a very difficult problem that is not only of the responsibility of scientists and science education. Similar advances in social sciences and humanities have not alwa= ys accompanied societies’ technological advances. The overemphasized “faith” in science of the past couple of centuries, is often se= en as a backlash caused by centuries of obscurantism.

Clearly, the problem is not in science or its use, but in our incapacity to handle the powerful potentials that science and technology is making available to human kind. Interestingly, major scientists have always been aware of this and have written extensively about the dilemmas they fac= ed in developing their work and dealing with the political leadership[5].

This is a major problem that our societies have to grapple with. Nevertheless, scientists, medical doctors, engineers, and more generally, a= ll the intelligentsia, should provide the thinking behind, and major drive for proper solutions. This where education appears.

The age of specialization has divided human knowledge into compartm= ents that are more manageable and easy to deal with. Divide to conquer was the prevailing paradigm. Dealing with the profound ethical aspects requires us = to “recompose” the parts. The whole is larger than the sum of its parts; we have lost a lot in the break down. Whence a more holistic approac= h to education; and here I would like to propose that science students should ha= ve a thorough knowledge of social science and humanities, and students in the no= n-scientific fields should know more about science.

I will further stress the point of the holistic nature of human knowledge, rather than presenting it as separate independent parts. Human intelligence works in many ways, and the material it pugs differs. There are many writing on modern issues that unify scientific and psychological views= on life, intelligence and human thinking. The marvelous book by Hoftstadter li= nks the work of the famous logician Gödel, to the art of Escher, and the m= usic of Bach. All three have worked on self-referencing aspects, in logics, pain= ting and baroque music. The author who is a computer scientist has more recently published a book on French poetry “Le Ton Beau de Marot: In Praise of the Music of Language”. "Le ton beau de Marot" literally means "The sweet tune of Marot", but this is a word game that sounds in French as "Le tom beau de Marot"--that is "The tomb of Marot". The book explores the translation of a short poem on the death of a young girl = and “the challenge of recreating both its sweet message and its tight rhy= mes in English--jumping through two tough hoops at once.” To a scientist, such readings may seem useless, that may be, but, discovering the intricacy= of human thinking, and the beauty of poetry will undoubtedly say a lot about w= hat it is to be creative and even what it is to be human.

Many other readings by Hofstadter, Marvin Minsky or Roger Penrose a= re good candidates for this sort of curricula. These authors (as many others t= hat cannot be cited in the scope of this discussion) are all scientists, and he= nce have a priori the acceptance and respectability of the science community allowing an easier introduction in curricula. All three write on or deal wi= th artificial intelligence, a field of knowledge that is at the core of modern science. In the popular imagery, IA gave birth to the modern mad scientist = who is now a robot. This touches upon grave and serious questioning on what is “human” and what is not. Roger Penrose who is a physicist and a mathematical topologist addre= sses such issues very admirably in the “The Emperor’s New Mind: concerning computers, minds and the laws of physics”.

I believe that a community thinkers and educated professionals with= a profound knowledge of the unique and holistic nature of human knowledge can more easily address ethical dimension of the sciences and their technologic= al applications. Scientists alone should not and cannot address the issue, nor= can sociologists, political scientists, and philosophers alone decide it. The i= mpact of such issues on the way our societies have evolved, and the religious val= ues we uphold are too profound and complex to be resolved in the lab, or in parliaments.

7- Conclusions.

In concluding, I am troubled by the fact that this short discussion= my have raised more questions than it has answered. Besides being a common proposit= ion in post-modernist thought, emphasis has been to provide an agenda paper rat= her than a set of recepies. The temporal and spatial domains of the question as= ked are much too wide, and education a very serious question to be left only to educators.

The exchanges that will undoubtedly take place during the meetings = will certainly fill some of the voids. Continuous and methodical brainstorming-planning-measuring outcomes are the way to go at institutional level. Diversity in outcomes within reasonably well-defined objectives is b= oth natural and desirable.

8- Refer= ences

This paper uses freely a number of references, most particularly:

·= ;   “Preparing Future= Faculty in the Science and Mathematics, A guide for change”, Anne S. Pruitt-L= oan, Jerry G. Gaff, Joyce E. Jentoft, Council of Graduate Schools and the Association of American Colleges and Universities, Washington D.C. 2002

·= ;   “The Law of Accelerating Returns”, Raymond Kurzweil, Published on KurzwilAI.net, 2001

·= ;   “It’s Alive, The Coming Convergence of Information, Biology, and Business”, Chritopher Meyer = and Stan Davis, Center for Business Innovation, Crown Industries, 2003.

·= ;   “A New Kind of Science”, Stephen Wolfram, Wolfram Media Inc, 2001<= /span>

·= ;   “The Emperor̵= 7;s New Mind”, Roger Penrose, Oxford Press, 1989

·= ;   “Godel, Escher, B= ach: An eternal golden braid”, Douglas R. Hofstadter, 20^th Anniver= sary Edition, Perseus Book Group, 1999

About the Author

Dr. Sfeir holds a PhD from the University of California, Berkeley. = He started his academic career at AUB in 1969 where he served until 1989. In t= hat year he joined the Ecole des Mines de Nancy, and was appointed as Professor= and Director of Studies until 1996 when he returned to Lebanon and became the f= ounding Dean of the School of Engineering & Architecture at LAU. Dr. Sfeir has published three books and several papers in the areas of fluids, thermal sciences, and energy. He also served as consultant on a number of engineeri= ng projects in Lebanon and abroad.