Part 17

To show the awareness of the publishers of texts and other educational material, firms like Book of Knowledge, Encyclopedia Britannica Films, and TMI Grolier are in the “teaching machine” business, and the McGraw-Hill Book Company and Thompson Ramo Wooldridge, Inc., have teamed to produce computerized teaching machines and the programs for them. Other publishers using “programming” techniques in their books include Harcourt-Brace with its 2600 series (for 2,600 programmed steps the student must negotiate), Prentice-Hall, and D. C. Heath. Entirely new firms like Learning, Incorporated, are now producing “programs” on many subjects for teaching machines.

Subjects available in teaching machine form include algebra, mathematics, trigonometry, slide rule fundamentals, electronics, calculus, analytical geometry, plane geometry, probability theory, electricity, Russian, German, Spanish, Hebrew, spelling, music fundamentals, management science, and even Goren’s bridge for beginners.

While many of these teaching machines are simply textbooks programmed for faster learning, the conversion of such material into computer-handled presentation is merely one of economics. For example, a Doubleday TutorText book costs only a few dollars; an automatic AutoTutor Mark II costs $1,250 because of its complex searching facility that requires several thousand branching responses. However, the AutoTutor is faster and more effective and will operate twenty-four hours a day if necessary. With sufficient demand the machine may be the cheaper in the long run.

The System Development Corporation feels that its general concept of automated group education will be feasible in the near future despite the high cost of advanced electronic digital computers. It cites pilot studies being conducted by the State of California on data-processing for a number of schools through a central facility. Using this same approach, a single central computer could serve several schools with auxiliary lower-priced equipment. Even a moderately large computer used in this way could teach a thousand or more students simultaneously and _individually_, the Corporation feels. After school hours, the computer can handle administrative tasks.

In the CLASS system developed by the System Development Corporation, the “branching” concept is used. In a typical lesson program, if the student immediately answers that America was discovered by Christopher Columbus, he will be told he is correct and will then be branched to the next item. If he answers Leif Ericson, the computer takes time out to enlighten the pupil on that score. Next, it reinforces the correct date in the student’s mind before asking another question. Although it would seem that a lucky student could progress through the programmed lesson on guesswork alone, the inexorable laws of probability rule this out. He cannot complete the lesson until he has soaked up all the information it is intended to impart. He can do this without an error, in a very short time, or he can learn by the trial-and-error process, whichever is better suited to his speed and mental ability.

Making up the program for the teaching machine is a difficult task and requires the services of technical expert, psychologist, and programmer. An English-like language is used in preparing a CLASS program for the computer. Put on magnetic tape, the program goes into the memory of the computer and is called out by proper responses from the student as he progresses through the lesson.

Complex as the programming is, entries from the student’s control are processed into the computer in about one-tenth of a second, and an answer is flashed back in about the same amount of time. Remember that the CLASS computer is handling twenty students at a time, and that in addition to teaching it is keeping a complete record of how the student fared at each step of the lesson.

It is obvious that the binary or yes-no logic of the computer ties in with the concept put forth by Skinner and others of presenting small bits of information at a time. We can use the game of 20 Questions as a good analogy. Even getting only simple yes-no answers, skilled players can elicit an amazing amount of information in often far less than the permitted number of questions. Thus even complex subjects can be broken down into simple questions answerable by discrete choices from the student.

The automated group education system of the System Development Corporation is made up of the following components: a digital computer to control and select the material presented and to analyze responses, a magnetic tape storage unit, a typewriter for printing out data analysis, a slide projector and screen for presenting educational materials, and individual desks with keyboards for the students’ responses.

We have pointed out that even though it is possible to break down educational material into multiple-choice or yes-no answers to which are assigned intrinsic values, the ideal system permits answers on a linear scale. In other words, instead of picking what he considers the most nearly correct, a student writes his own answer. Some experts feel that the advances being made in optical scanning, or “reading” techniques for computers, will result in linear programming of the teaching machines within the next ten years. Such a development will do much to alleviate the complaint that the machine exerts a rigid mechanizing effect on the teaching process.

While fear of displacement motivates some teachers to distrust the machine, an honest belief that the human touch is necessary in the schoolroom is also a large factor against acceptance. Yet these same wary teachers generally use flash cards, flip charts, and other mechanical aids with no qualms. The electronic computer is a logical extension of audiovisual techniques, and in time the teacher will come to accept it for what it is.

The human teacher will continue to be an indispensable element in education, but he must recognize that as our technology becomes more complex he will need more and more help. In 1960 there were about 44 million students in our classrooms, and about 135,000 too few teachers. By 1965 it is estimated there will be 48 million students and 250,000 teachers fewer than we need. Parallel with this development is the rapidly growing need for college graduates. One large industrial firm which employs 150,000 hires only 300 college graduates a year at present, but will need 7,000 when it automates its plants. The pressure of need thus is forcing our educational system to make use of the most efficient means of educating our students.

Beyond simply taking its place with other aids, however, the computer will make great changes in our basic concepts of teaching, according to Dr. Skinner. He asks the question “Are the students who learn in spite of a confusing presentation of a subject better for the experience, or were they better students at the outset?” He advances this argument to say that perhaps “easy” learning is actually the best; that we would do well to analyze the behavior called thinking and then produce it according to these specifications. The traditional teacher finds the prospect alarming and questions the soundness of minimizing failure and maximizing success.

There is not yet definite agreement by other psychologists with Skinner’s contention that recall rather than recognition is the desired method. Neither is it sure that the negative reinforcement of a number of incorrect choices may result in remembering wrong answers. And of course the division between rote learning and creativity is an important consideration. The answers may well lie in the computer, which when properly programmed is about the most logical device we have available to us. Thus the machine may determine the best teaching methods and then use them to teach us. Regardless of these as yet unanswered questions, however, the future of the teaching machine seems to be assured. One authority has predicted that it will be a $100 million market by 1965.

An intriguing use of computer techniques in teaching is being investigated by Corrigan Communications, which scores students answering questions on telecourses. This work is being done with a course in medicine, and with the rapid growth of educational television the implications of combining it and teaching machine techniques are of great importance.

Classroom teaching is not the only educational application for the teaching machine. A computer-controlled library is an interesting thought, with the patron requesting information from a central computer and having it presented instantaneously on a viewing screen in front of him. Such a system could conceivably have access to a national library hookup, constantly updated with new material. Such a service would also be available for use during school study hall, or by the teacher during class.

Visitors to the World’s Fair in Seattle previewed the computerized information center of the future. Called Library 21, it is considered a prototype of the next century’s core libraries which will be linked to smaller branches by communications networks. Many computers were displayed, tied in with teaching machines, language laboratories, and information from the Great Books, tailored to the individual questioner’s sex, personality, and mental level. Also shown was a photo process that reduces a 400-page book to the size of a postage stamp for storage.

With this kind of progress, we can in the foreseeable future request and receive up-to-date information of any kind of human knowledge anywhere—in language we can understand. Another computer application sure to come is that of handling correspondence courses. The teaching of extension courses in the home, through television and some sort of response link, has been mentioned, and it is not impossible that the school as a physical plant may one day no longer be necessary.

Since the computer itself does not “teach,” but merely acts as a go-between for the man who prepared the lesson or program and the student who learns, it would seem that some of our teachers may become programmers. The System Development Corporation has broken the teaching machine program into three phases: experimenting with the effects of many variables on teaching machine effectiveness, developing a simplified teaching machine, and finally, analyzing the educational system to find where and how the machine fits. Research is still in the first phase, that of experiment. But it is known that some programs produced so far show better results than conventional teaching methods, and also that teaching machines can teach any subject involving factual information. Thus it is evident they will be useful in schools and also in industry and military training programs.

_Language_

If man is to use the computer to teach himself, he must be able to converse with it. In the early days of computers it was said with a good deal of justification that the machine was not only stupid but decidedly insular as well. In other words, man spoke to it in its own language or not at all. A host of different languages, or “compilers” as they are often called, were constructed and their originators beat the drums for them. With tongues like ALGY, ALGOL, COBOL, FACT, FLOWMATIC, FORTRAN, INTERCOM, IT, JOVIAL, LOGLAN, MAD, PICE, and PROLAN, to name a few, the computer has become a tower of Babel, and a programmer’s talents must include linguistics.

One language called ALGOL, for Algorithmic Oriented Language, had pretty smooth sailing, since it consists of algebraic and arithmetic notation. Out of the welter of business languages a compromise Common Business Oriented Language, or COBOL, evolved. What COBOL does for programming computer problems is best shown by comparing it with instructions once given the machine. The sample below is typical of early machine language:

Recommended by a task force for the Department of Defense, industry, and other branches of the government, COBOL nevertheless has had a tough fight for acceptance, and there is still argument and confusion on the language scene. New tongues continue to proliferate, some given birth by ALGOL and COBOL themselves. Examples of this generation are GECOM, BALGOL, and TABSOL. One worthy attempt at a sort of machine Esperanto is called a pun-inviting UNCOL, for Universal Computer-Oriented Language and seems to be a try for the computer’s vote. One harried machine-language user has suggested formation of an “ALGOLICS Anonymous” group for others of his ilk, while another partisan accuses his colleagues in Arizona of creating a new language while “maddened by the scent of saguaro blossoms.”

It was recently stated that perhaps by the time a decision is ultimately reached as to which will be the general language, there will be no need of it because by then the computer will have learned to read and write, and perhaps to listen and to speak as well. Recent developments bear out the contention.

Although it has used intermediate techniques, the computer has proved it can do a lot with our language in some of the tasks it has been given. Among these is the preparation of a Bible concordance, listing principal words, frequency of appearance, and where they are found. The computer tackled the same job on the poems of Matthew Arnold. For this chore, Professor Stephen Maxfield Parrish of Cornell worked with three colleagues and two technicians to program an IBM 704 data-processing system. In addition to compiling the list of more than 10,000 words used most often by Arnold, the computer arranged them alphabetically and also compiled an appendix listing the number of times each word appeared. To complete the job, the computer itself printed the 965-page volume. The Dead Sea Scrolls and the works of St. Thomas Aquinas have also been turned over to the computer for preparation of analytical indexes and concordances.

At Columbia University, graduate student James McDonough gave an IBM 650 the job of sleuthing the author of _The Iliad_ and _The Odyssey_. Since the computer can detect metric-pattern differences otherwise practically undiscoverable, McDonough felt that the machine could prove if Homer had written both poems, or if he had help on either. Thus far he is sure the entire _Iliad_ is the work of one man, after computer analysis of its 112,000 words. The project is part of his doctoral thesis. A recent article in a technical journal used a title suggested by an RCA 501, and suspicion is strong that the machines themselves are guilty of burning midnight kilowatts to produce the acronyms that abound in the industry. The computer is even beginning to prove its worth as an abstracter.

Other literary jobs the computer has done include the production of a book of fares for the International Air Transport Association. The computer compiled and then printed out this 420-page book which gives shortest operating distances between 1,600 cities of the world. Now newspapers are beginning to use computers to do the work of typesetting. These excursions into the written language of human beings, plus its experience as a poet and in translation from language to language, have undoubtedly brought the computer a long way from its former provincialism.

As pointed out, computer work with human language generally is not accomplished without intermediate steps. For example, in one of the concordances mentioned, although the computer required only an hour to breeze through the work, a programmer had spent weeks putting it in the proper shape. What is needed is a converter which will do the work directly, and this is exactly what firms like Digitronics supply to the industry. This computer-age Berlitz school has produced converters for Merrill Lynch, Pierce, Fenner & Smith for use in billing its stock-market customers, Wear-Ever as an order-taking machine, _Reader’s Digest_ for mailing-list work, and Schering Corporation for rat-reaction studies in drug research, to mention a few.

The importance of such converters is obvious. Prior to their use it was necessary to type English manually into the correct code, a costly and time-consuming business. Converters are not cheap, of course, but they operate so rapidly that they pay for themselves in short order. Merrill Lynch’s machine cost $120,000, but paid back two-thirds of that amount in savings the first year. There is another important implication in converter operation. It can get computer language out of English—or Japanese, or even Swahili if the need arises. A more recent Digitronics’ converter handles information in English or Japanese.

If the computer has its language problems, man has them also, to the _n_th degree. There are about 3,000 tongues in use today; mercifully, scientific reports are published in only about 35 of these. Even so, at least half the treatises published in the world cannot be read by half the world’s scientists. Unfortunately, UNESCO estimates that while 50 per cent of Russian scientists read English, less than 1 per cent of United States scientists return the compliment! The ramifications of these facts we will take up a little later on; for now it will be sufficient to consider the language barrier not only to science but also to culture and the international exchange of good will that can lead to and preserve peace. Esperanto, Io, and other tongues have been tried as common languages. One recent comer to the scientific scene is called Interlingua and seems to have considerable merit. It is used in international medical congresses, with text totaling 300,000 words in the proceedings of one of these. But a truly universal language is, like prosperity, always just around the corner. Even the scientific community, recognizing the many benefits that would accrue, can no more adopt Interlingua or another than it can settle on the metric system of measurement. Our integration problems are not those of race, color, and creed only.

Before Sputnik our interest in foreign technical literature was not as keen as it has been since. One immediate result of the satellite launching by the Russians was amendment of U.S. Public Law 480 to permit money from the sale of American farm equipment abroad to be used for translation of foreign technical literature. We are vitally concerned with Russia, but have also arranged for thousands of pages of scientific literature from Poland, Yugoslavia, and Israel. Communist China is beginning to produce scientific reports too, and Japanese capability in such fields as electronics is evident in the fact that the revolutionary “tunnel diode” was invented by Esaki in Japan.

It is understandable that we should be concerned with the output of Russian literature, and much attention has been given to the Russian-English translator developed by IBM for the Air Force. It is estimated that the Russians publish a billion words a year, and that about one-third of this output is technical in nature. Conventional translating techniques, in addition to being tedious for the translators, are hopelessly slow, retrieving only about 80 million words a year. Thus we are falling behind twelve years each year! Outside of a moratorium on writing, the only solution is faster translation.

The Air Force translator was a phenomenal achievement. Based on a photoscopic memory—a glass disc 10 inches in diameter capable of storing 55,000 words of Russian-English dictionary in binary code—the system used a “one-to-one” method of translation. The result initially was a translation at the rate of about 40 words per minute of Russian into an often terribly scrambled and confusing English. The speed was limited not by the memory or the computer itself but by the input, which had to be prepared on tape by a typist. Subsequently a scanning system capable of 2,400 words a minute upped the speed considerably.

Impressive as the translator was, its impact was dulled after a short time when it was found that a second “translation” was required of the resulting pidgin English, particularly when the content was highly technical. As a result, work is being done on more sophisticated translation techniques. Making use of predictive analysis, and “lexical buffers” which store all the words in a sentence for syntactical analysis before final printout, scientists have improved the translation a great deal. In effect, the computer studies the structure of the sentence, determining whether modifiers belong with subject or object, and checking for the most probable grammatical form of each word as indicated by other words in the sentence.

The advanced nature of this method of translation requires the help of linguistics experts. Among these is Dr. Sydney Lamb of the University of California at Berkeley who is developing a computer program for analysis of the structure of any language. One early result of this study was the realization that not enough is actually known of language structure and that we must backtrack and build a foundation before proceeding with computer translation techniques. Dr. Lamb’s procedure is to feed English text into the computer and let it search for situations in which a certain word tends to be preceded or followed by other words or groups of words. The machine then tries to produce the grammatical structure, not necessarily correctly. The researcher must help the machine by giving it millions of words to analyze contextually.

What the computer is doing in hours is reproducing the evolution of language and grammar that not only took place over thousands of years, but is subject to emotion, faulty logic, and other inaccuracies as well. Also working on the translation problem are the National Bureau of Standards, the Army’s Office of Research and Development, and others. The Army expects to have a computer analysis in 1962 that will handle 95 per cent of the sentences likely to be encountered in translating Russian into English, and to examine foreign technical literature at least as far as the abstract stage.