Educational Uses of the PLATO Computer System
`Author(s): Stanley G. Smith and Bruce Arne Sherwood
`Source: Science, Apr. 23, 1976, New Series, Vol. 192, No. 4237 (Apr. 23, 1976), pp. 344-
`352
`Published by: American Association for the Advancement of Science
`
`Stable URL: https://www.jstor.org/stable/1742096
`
`REFERENCES
`Linked references are available on JSTOR for this article:
`https://www.jstor.org/stable/1742096?seq=1&cid=pdf-
`reference#references_tab_contents
`You may need to log in to JSTOR to access the linked references.
`
`JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide
`range of content in a trusted digital archive. We use information technology and tools to increase productivity and
`facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.
`
`Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at
`https://about.jstor.org/terms
`
`American Association for the Advancement of Science is collaborating with JSTOR to digitize,
`preserve and extend access to Science
`
`This content downloaded from
`132.174.253.93 on Tue, 08 Apr 2025 13:44:45 UTC
`All use subject to https://about.jstor.org/terms
`
`i
`
`Instacart, Ex. 1033
`
`(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)
`

`

` evolution, nature has been able to find
` more than one efficient molecular mecha-
` nism for maintaining a vital organismic
` function.
`
` References and Notes
`
` 1. F. Hoppe-Seyler, Virchows Arch. Pathol. Anat.
` Physiol. 19, 233 (1864).
` 2. I. M. Klotz and S. Keresztes-Nagy, Biochemis-
` try 2, 445 (1963).
` 3. G. Bates, M. Brunori, G. Amiconi, E. Antonini,
` J. Wyman, ibid. 7, 3016 (1968); R. E. Ferrell and
` G. B. Kitto, ibid. 9, 3053 (1970); W. A. Hen-
` drickson and G. L. Klippenstein, J. Mol. Biol.
` 87, 147 (1974).
` 4. G. L. Klippenstein, D. A. Van Riper, E. A.
` Oosterom, J. Biol. Chem. 247, 5959 (1972).
` 5. J. G. Joshi and B. Sullivan, Comp. Biochem.
` Physiol. B 44, 857 (1973).
` 6. F. A. Liberatore, M. F. Truby, G. L. Klippen-
` stein, Arch. Biochem. Biophys. 160, 223 (1974).
` 7. J. S. Loehr, K. N. Meyerhoff, L. C. Sieker, L.
` H. Jensen, J. Mol. Biol. 91, 521 (1975).
` 8. I. M. Klotz, D. W. Darnall, N. R. Langerman, in
` The Proteins, H. Neurath and R. Hill, Eds.
` (Academic Press, New York, ed. 3, 1975), vol.
` 1, pp. 293-411.
` 9. D. W. Darnall and I. M. Klotz, Arch. Biochem.
` Biophys. 166, 651 (1975).
` 10. W. A. Hendrickson, G. L. Klippenstein, K. B.
` Ward, Proc. Nati. Acad. Sci. U.S.A. 72, 2160
` (1975).
` 11. K. B. Ward, W. A. Hendrickson, G. L. Klippen-
` stein, Nature (London) 257, 818 (1975).
` 12. S. Keresztes-Nagy and I. M. Klotz, Biochemis-
` try 2, 923 (1963).
` 13. I. M. Klotz and S. Keresztes-Nagy, Nature
` (London) 195, 900 (1962).
` 14. B. W. Matthews and S. A. Bernhard, Annu.
` Rev. Biophys. Bioeng. 2, 257 (1973).
` 15. A. C. T. North and G. J. Stubbs, J. Mol. Biol.
` 88, 125 (1974).
` 16. R. E. Stenkamp, L. C. Sieker, L. H. Jensen, J.
` S. Loehr, ibid. 100, 23 (1976).
` 17. A. R. Subramanian, J. W. Holleman, I. M.
`
` Klotz, Biochemistry 7, 3859 (1968); G. L. Klip-
` penstein, J. W. Holleman, I. M. Klotz, ibid., p.
` 3868.
` 18. G. L. Klippenstein, J. L. Cote, S. E. Ludlam,
` ibid. 15, 1128(1976).
` 19. R. E. Ferrell and G. B. Kitto, ibid. 10, 2923
` (1971).
` 20. G. L. Klippenstein, ibid. 11, 372 (1972).
` 21. F. A. Liberatore, thesis, University of New
` Hampshire (1974).
` 22. Abbreviations of the amino acid residues are
` Ala, alanine; Asp, aspartic acid; Asn, aspara-
` gine; Arg, arginine; Cys, cysteine; Glu, glutamic
` acid; Gln, glutamine; Gly, glycine; His, histi-
` dine;'Ile, isoleucine; Leu, leucine; Met, methio-
` nine; Phe, phenylalanine; Pro, proline; Ser, ser-
` ine; Thr, threonine; Val, valine; Tyr, tyrosine;
` and Trp, tryptophan.
` 23. G. L. Klippenstein, unpublished.
` 24. D. W. Darnall, K. Garbett, I. M. Klotz, S.
` Aktipis, S. Keresztes-Nagy, Arch. Biochem.
` Biophys. 133, 103 (1969).
` 25. G. Holzwarth and P. Doty, J. Am. Chem. Soc.
` 87, 218 (1965).
` 26. P. Y. Chou and G. D. Fasman, Biochemistry 13,
` 222 (1974).
` 27. J. B. R. Dunn, thesis, Northwestern University
` (1974).
` 28. M. Florkin, Arch. Int. Physiol. 36, 247 (1933);
` W. E. Love, Biochim. Biophys. Acta 23, 465
` (1957).
` 29. I. M. Klotz, T. A. Klotz, H. A. Fiess, Arch.
` Biochem. Biophys. 68, 284 (1957).
` 30. W. A. Hendrickson and K. B. Ward, Biochem.
` Biophys. Res. Commun. 66, 1349 (1975).
` 31. I. M. Klotz and T. A. Klotz, Science 121, 477
` (1955).
` 32. E. Boeri and A. Ghiretti-Magaldi, Biochim.
` Biophys. Acta 23, 465 (1957).
` 33. S. Keresztes-Nagy and I. M. Klotz, Biochemis-
` try 4, 919 (1965).
` 34. M. H. Klapper and I. M. Klotz, ibid. 7, 223
` (1968).
` 35. K. Garbett, D. W. Darnall, I. M. Klotz, R. J. P.
` Williams, Arch. Biochem. Biophys. 135, 419
` (1969).
` 36. M. Y. Okamura, I. M. Klotz, C. E. Johnson, M.
` R. C. Winter. R. J. P. Williams, Biochemistry 8,
`
` 1951 (1969); J. L. York and A. J. Bearden, ibid.
` 9, 4549 (1970).
` 37. K. Garbett, C. E. Johnson, I. M. Klotz, M. Y.
` Okamura, R. J. P. Williams, Arch. Biochem.
` Biophys. 142, 574 (1971).
` 38. M. Y. Okamura and I. M. Klotz, in Inorganic
` Chemistry, G. L. Eichhorn, Ed. (Elsevier, Am-
` sterdam, 1973), chap. 11.
` 39. T. H. Moss, C. Moleski, J. L. York, Biochemis-
` try 10, 840 (1971).
` 40. J. W. Dawson, H. B. Gray, H. E. Hoenig, G. R.
` Rossman, J. M. Schredder, R. H. Wang, ibid.
` 11, 461 (1972).
` 41. K. S. Murray, Coord. Chem. Rev. 12, 1 (1974).
` 42. J. A. Morrissey, thesis, University of New
` Hampshire (1971).
` 43. C. C. Fan and J. L. York, Biochem. Biophys.
` Res. Commun. 47, 472 (1972).
` 44. G. L. Klippenstein, ibid. 49, 1474 (1972).
` 45. C. C. Fan and J. L. York, ibid. 36, 365 (1969).
` 46. S. F. Andres and M. Z. Atassi, Biochemistry 12,
` 942 (1973).
` 47. J. L. York and C. C. Fan, Fed. Proc. Fed. Am.
` Soc. Exp. Biol. 29, 463 (1970); R. L. Rill and I.
` M. Klotz, Arch. Biochem. Biophys. 136, 507
` (1970).
` 48. R. M. Rill and I. M. Klotz, Arch. Biochem.
` Biophys. 147, 226 (1971).
` 49. J. L. York and C. C. Fan, Biochemistry 10, 1659
` (1971).
` 50. J. B. R. Dunn, D. F. Shriver, I. M. Klotz, Proc.
` Natl. Acad. Sci. U.S.A. 70, 2582 (1973); Bio-
` chemistry 14, 2689 (1975).
` 51. K. Garbett, D. W. Darnall, I. M. Klotz, Arch.
` Biochem. Biophys. 142, 455 (1971).
` 52. A. L. Rao and S. Keresztes-Nagy, Biochim.
` Biophys. Acta 313, 249 (1973).
` 53. H. A. DePhillips, Arch. Biochem. Biophys.
` 144, 122 (1971).
` 54. K. Garbett, D. W. Darnall, I. M. Klotz, ibid.
` 142, 471 (1971).
` 55. F. Bossa, M. Brunori, G. W. Bates, E. Antonini,
` P. Fasella, Biochim. Biophys. Acta 207, 41
` (1970).
` 56. R. E. Stenkamp, L. C. Sieker, L. H. Jensen,
` Proc. Natl. Acad. Sci. U.S.A. 73, 349 (1976).
` 57. Supported in part by NIH grant HL-08299, NSF
` grant GB-35610, and Naval Research Laboratory.
`
` Educational Uses of the PLATO
` Computer System
`
` The PLATO system is used for instruction,
` scientific research, and communications.
`
` Stanley G. Smith and Bruce Arne Sherwood
`
` The PLATO (1) computer-based educa-
` tional system has been specifically de-
` signed to provide interactive, self-paced
` instruction to large numbers of students
` (2). Lesson material is displayed on a
` screen 22 centimeters square and may
` consist of text, drawings, graphs, and
` color photographs. Students interact
`
` Dr. Smith is professor of chemistry at the Univer-
` sity of Illinois, Urbana 61801. Dr. Sherwood is asso-
` ciate professor of physics and assistant director of
` the Computer-Based Eduction Research Laborato-
` ry at the University of Illinois, Urbana.
`
` with the material through a special key-
` set that closely resembles a typewriter
` keyboard, and they receive essentially
` instantaneous reinforcement of correct
` work and assistance where they are hav-
` ing difficulty. Students can work at their
` convenience in classrooms such as the
` one shown in Fig. 1.
` The users of PLATO range from gradc
` school students learning reading and
` math to graduate students in the medical
` sciences. The system now has 950 termi-
` nals located in universities, colleges,
`
` community colleges, public schools, mili-
` tary training schools, and commercial
` organizations (3). The users have access
` to more than 3500 hours of instructional
` material in more than 100 subject areas
` (4). We will mainly describe one area of
` PLATO use-that of university science
` education and research.
`
` Examples of PLATO Lessons
`
` The character of PLATO lesson materi-
` al varies greatly since the computer sys-
` tem does not impose a pedagogical struc-
` ture on the authors of the materials.
` Some appreciation of the breadth of ap-
` proaches used may be gained by review-
` ing brief segments of a few programs in
` chemistry (5) and physics (6). The exam-
` ples below are illustrated with photo-
` graphs of the student's plasma-panel
` screen (7). Unfortunately, however,
` these static photographs do not fully con-
` vey the dynamic nature of the inter-
` actively changing displays seen by the
` student.
` A physics lesson on oscillations con-
` tains features common to many ex-
` pository science lessons. The student is
` given a table of contents for the lesson so
`
` 344 SCIENCE, VOL. 192
`
`This content downloaded from
`(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)132.174.253.93 on Tue, 08 Apr 2025 13:44:45 UTC(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)
`All use subject to https://about.jstor.org/terms
`
`

`

` Fig. 1. One of the PLATO classrooms at the University of Illinois. This classroom in the Foreign
` Language Building contains 80 terminals.
`
` that he may choose to study any section
` or even go directly to a final quiz that will
` test his understanding of the material.
` The intent of the lesson is to take stu-
` dents from no knowledge of oscillating
` systems up to a point where their under-
` standing allows them to solve typical
` homework problems.
` The first part of the lesson deals with
` an oscillator consisting of a block sliding
` up and down two smooth inclines, a
` system that the student analyzes by
` simple kinematics formulas. In order to
` help the student understand the system,
` the computer shows an animation of the
` motion and allows him to experiment
` with values of the initial displacement
` (Fig. 2).
` After the student has experimented
` with the system until he thinks he under-
` stands it, the program tests his knowl-
` example, a comparison of the sensitivity
` edge by asking a number of questions
` of the rates of ethanolysis of n-butyl
` about the system. Help is provided
` bromide and t-butyl bromide as a func-
` where necessary, but where help is re-
` tion of ethoxide concentration serves to
` quired the student must answer the same
` question later with different numerical
` clarify some aspects of the concepts of
` unimolecular and bimolecular reactions.
` factors. Such checkup sections follow
` Students can quickly discover what hap-
` each expository section of the lesson.
` pens through simulated experiments in
` The final quiz is constructed from
` which the computer plots the percent
` questions asked in the earlier sections
` reaction as a function of time as would
` with randomly chosen numerical factors.
` be observed under the experimental con-
` No help is provided. The lesson distin-
` ditions they suggest. Since the student is
` guishes between incorrect numerical re-
` free to explore the relation between ex-
` sults and typing errors, such as unbal-
` perimental conditions and reaction rate,
` anced parentheses. In this lesson, if the
` it is important to have the program ask
` student misses more than two out of six
` questions and, if necessary, suggest addi-
` questions, he must take the whole quiz
` tional experiments to assure that a suit-
` again. He can, of course, review sections
` able set of experiments has been done.
` of the lesson if he wishes.
` In this case, after the experimental facts
` Students also have the opportunity to
` have been established and a suitable in-
` study systems of their own design and to
` terpretation has been developed, the sys-
` program the computer with a special lan-
` tem provides a visual picture of the trans-
` guage so that they may obtain immediate
` formations involved by means of an ani-
` graphical results. Figure 3 illustrates an
` mation that shows the sequence of bond
` example of large-amplitude pendulum
` making and breaking which occurs.
` motion in which the student has used s
` In more advanced lessons, students
` for angle, g for gravitational accelera-
` tion, 1 for length, v for angular velocity, t
` are given a problem that can be solved
` by conducting some simulated experi-
` for time, and d for a short time interval.
` ments on the computer. The student is
` The graphs that have been produced for
` the student correspond to running the
` expected to design the experiment, se-
` lect the compounds and reaction condi-
` program with a starting angle of 45 de-
` grees and with a starting angle of 179
` tions, and then collect the experimental
` data, do the mathematical analysis, and
` degrees.
` outline the conclusions that can be de-
` Since much of science is based on the
` rived from his experiments. This ap-
` results of experiments, it seems impor-
` tant to have students learn to design
` proach to teaching is possible because
` the computer can rapidly calculate the
` experiments and interpret the experimen-
` outcome of experiments of a given type
` tal data. However, many of the key ex-
` from algorithms which describe the re-
` periments in the development of impor-
` sults of actual experiments that may be
` tant concepts cannot be carried out by
` large numbers of students because of the
` beyond the experimental skills of the
` lack of adequate equipment, time, and
` students and the available laboratory fa-
` cilities.
` experimental technique. The use of com-
` puter simulation can serve to provide
` It is also necessary for students to gain
` some experience with the concepts. For
` experience in dealing with problems for
`
` which there are many possible solutions.
` The synthesis of organic compounds is
` an example of this type of situation, in
` which there are many viable routes from
` the starting materials to the designated
` product. This is illustrated in Fig. 4 where
` the student is given the task of converting
` a given starting material into a desig-
` nated product molecule. He proceeds
` by suggesting a reagent for each step
` in the transformation. Since there are
` many possible paths between the starting
` material and the product, the computer
` is programmed (8) to carry out the re-
` action suggested by the student and com-
` pare the structure of the product with
` that of the desired material. If they are
` the same, the synthesis is judged com-
` pleted. If not, the reagent for the next
` step is requested. This approach does
` not impose a specific solution to the prob-
` lem on the student but recognizes a wide
` range of acceptable routes.
` One way to provide practice problems
` for organic reactions is illustrated in Fig.
` 5 where the student has been given 16
` compounds and ten reagents and is
` asked to find at least 20 different ways of
` interconverting pairs of the compounds
` with the use of the reagents shown.
` To cause the interaction, the student
` simply points to a compound and then to
` the reactant or product side of the reac-
` tion arrow to indicate his choice. The
` computer senses which compound the
` student is pointing at by means of a
` matrix of infrared light-emitting diodes
` and sensors that lie in a 16 by 16 array
` around the edge of the display screen.
` The use of such a "touch" sensitive
` display makes it easy and quick for the
` student to specify the reactants and prod-
` ucts. Errors are corrected by having the
` computer show either the correct pro-
` duct for a given reactant and reagent or
`
` 23 APRIL 1976 345
`
`This content downloaded from
`(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)132.174.253.93 on Tue, 08 Apr 2025 13:44:45 UTC(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)
`All use subject to https://about.jstor.org/terms
`
`

`

` the required reagent for a reactant pro-
` duct pair.
` Additional flexibility in the use of the
` computer as an aid to teaching comes
` from the ability to have the computer
` control the projection of color photo-
` graphs on the plasma panel. This is illus-
` trated in Fig. 6, which has been abstract-
` ed from a lesson on the use of an analyti-
` cal balance. In this example the student
` must identify the function of the knob on
` the side of the instrument.
`
` Structure of Lessons
`
` The successful application of program
` segments such as those described above
` to a real teaching situation involves the
` integration of practice problems and as-
` sociated help sequences with the devel-
` opment of the necessary theoretical
` framework to assist the students in un-
` derstanding the material. The ability of
` the PLATO system to support a one-to-
` one dialogue with the student offers the
`
` possibility of presenting the material in
` unique new ways that make the student
` an active participant in an effective learn-
` ing situation. Well-designed lesson mate-
` rial tends to be highly interactive and
` requires frequent inputs from each stu-
` dent in the form of answers to questions,
` predictions of the outcome of some ex-
` periment, parameters to be used in simu-
` lated experiments, and interpretation of
` a set of data or facts. In addition, since
` the understanding of the subject matter
`
` Fig. 2 (left). The student can choose the amplitude of this nonlinear oscillator and study the effect of amplitude on frequency. Fig. 3 (right).
` The student has written a numerical integration program to study the motion of a pendulum with large-amplitude swings. The two graphs
` correspond to amplitudes of 45 degrees and 179 degrees.
`
` Fig. 4 (left). Typical multistep synthesis in which the student has typed in the reagent for each step as the computer draws the structure of the
` reaction product. Fig. 5 (right). The student can specify the starting material, reagent, and product by simply touching the compound on the
` screen. A 16 by 16 array of infrared light-emitting diodes and sensors determines where the student is pointing.
`
` 346 SCIENCE, VOL. 192
`
`This content downloaded from
`(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)132.174.253.93 on Tue, 08 Apr 2025 13:44:45 UTC(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)
`All use subject to https://about.jstor.org/terms
`
`

`

` that a student has before starting a given
` program varies enormously, it is desir-
` able to structure the program to ac-
` commodate students who just need a
` brief review as well as those who are
` learning the material for the first time.
` One simple way to provide students with
` flexibility in the way they study and use a
` given program is to provide an index to
` the lesson which allows easy access to
` any section.
` Since students can proceed at their
` own rate, time spent in the lesson, unlike
` a lecture, automatically adjusts to the
` needs of the student. In fact, students
` proceed at greatly different rates when
` given the opportunity. For many lessons
` the time required for students to com-
` plete the lesson often varies (9) by a
` factor of 3 to 7.
` lessons need to be assembled in a form
` Although lesson material can make
` that is easy for students to use. All of the
` some adjustments to meet the needs of
` lessons associated with a particular
` individual students, it is important to
` course can be made available from an
` develop criteria and data that indicate
` index. Then, when a student signs on to
` how the difficulty of the programs match-
` the PLATO system with his name and the
` es the abilities of the students. One crite-
` rion that has been used is the percentage
` name of the course, he may choose top-
` ics or lessons to study. He makes his
` of the questions posed within the pro-
` gram which students answer correctly on
` selection from a list of descriptive titles,
` their first try. The assumption in this
` much as chapters in a book are selected
` from the table of contents. (As men-
` approach is that if nearly all student re-
` tioned above, many lessons have, in ad-
` sponses in instructional material are cor-
` rect, then the programs are not adequate-
` dition, a table of contents for the sub-
` ly challenging them, while a very small
` sections of the lesson.)
` percentage correct suggests that the les-
` If there are a large number of lessons
` son is unduly discouraging. The plot of
` associated with a particular course, it
` riTy be desirable to provide the student
` percentage OK on the first try as a func-
` tion of the number of students, shown in
` with some guidance in the selection of
` Fig. 7, suggests that for most of the
` lessons that are appropriate to the course
` students the level of the material was
` at that time. The PLATO system makes
` adequately adjusted for the class (10).
` this possible by a course management
` In addition to allowing multiple entry
` scheme that allows an instructor to set
` points and the ability to review as fre-
` up an index of lessons by simply select-
` quently as desired, lessons should tend
` ing the lessons from a catalog of lessons
` to adjust to each student within each
` displayed on the screen. Many such in-
` section. For example, help should be
` dexes may be set up for a course. For
` provided either when requested by the
` example, all of the lessons associated
` student (there is a key on the keyset
` with a given topic or concept may be
` labeled HELP) or when it is clear that he
` placed on one index. The instructor then
` is having difficulty. The number of prob-
` specifies the criteria for allowing stu-
` lems presented can be easily adjusted to
` dents to move from one index of lessons
` the student by such simple means as
` to another. For example, the student
` requiring that he get two right in a row of
` might be required to complete three of
` a certain type or, perhaps, simply by
` four lessons before moving ahead to the
` returning a given problem to the list of
` next topic. Or, this criterion may be
` those that need to be worked if the stu-
` modified so that at a given date the next
` set of lessons is made available even
` dent needed assistance in working it.
` Data from lessons are used to check that
` if the specified number of earlier les-
` the lesson is adjusting properly to the
` sons has not been completed, so that
` a student who has gotten behind at one
` students' needs.
` point in the course can keep up with
` the new material. If on-line quizzes or
` exams are included in a given module or
` set of lessons, a satisfactory score can
` be included in the criteria specified 'for
` completion before new topics are pre-
` sented.
`
` Computer-Managed Instruction
`
` A complete lesson on PLATO has many
` of the characteristics of a chapter in a
` textbook. Like chapters in a book, such
`
` Fig. 6. The student must give the function of
` the knob on the side of the analytical balance.
` The computer controls the projection of color
` photographs from a microfiche onto the back
` of the plasma panel.
`
` The relations among the student, in-
` structor, and the lesson author are dia-
` gramed in Fig. 8. This scheme, which
` is available to all instructors, provides
` guidance to the student on current work,
` makes it easy to review earlier lessons,
` and allows students to work ahead of the
` rest of the class. The result is an efficient
` and effective integration of the tech-
` niques of computer-based teaching and
` computer-managed instruction. While
` this generally available management
` scheme is used by many instructors, it is
` also possible to create other manage-
` ment structures to meet special require-
` ments.
`
` Integration of PLATO Activities
`
` PLATO has been integrated into the
` structure of courses in several ways. For
` example, in a classical mechanics course
` (11), computer-based tutoring made it
` possible to drop one of the two weekly
` lectures. The remaining lecture is used
` chiefly for demonstrations rather than
` for basic instruction. The discussion peri-
` od is spent in the physics PLATO class-
` room (which has 30 terminals), where
` students work individually but can get
` help from the instructor. Students spend
` additional study time at a terminal on a
` nonscheduled basis. Thirty terminals
` used 60 hours per week, providing 4
` hours of contact to each student, can
` serve 450 students. Large numbers of
` terminals are required to make an impact
` on instruction.
` There are three main components of
` the PLATO aspects of the course: instruc-
` tional lessons, homework, and an on-line
` gradebook. Students are assigned in-
` structional lessons to study, and part of
` their grade is based on how many of
` these lessons they complete. Homework
` is graded by PLATO rather than by the in-
` structors. The student is given printed
` homework problems that he is encour-
` aged to work at home. When the student
` is ready, he goes to a terminal to enter
` his results. If the problem involves nu-
` merical quantities, each student has dif-
` ferent numbers. A convenient calculator
` is always available. The student obtains
` a numerical score on the homework;
` homework scores form another basis for
` the course grade.
` Both lesson completion data and
` homework scores flow automatically in-
` to an on-line gradebook. Instructors also
` enter other grades into this gradebook,
` such as exam scores and lab report
` scores. Each student can look at his own
` scores and can see his position in a graph-
` ical display of distributions throughout
` the course to compare how he is doing
`
` 23 APRIL 1976 347
`
`This content downloaded from
`(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)132.174.253.93 on Tue, 08 Apr 2025 13:44:45 UTC(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)
`All use subject to https://about.jstor.org/terms
`
`

`

` with respect to the rest of the students.
` Each instructor can look at and change
` the scores of his own students and can
` see scores for his section marked on the
` course distribution graph. The overall di-
` rector of the course can look at the status
` of any section. One important benefit of
` this machinery is that an instructor can
` plan class activities on the basis of up-to-
` date information on how far students
` have gotten in their studies. Instructors
` also get rapid and accurate indications of
` students who are falling behind.
` Just as the same textbook is used in as-
` sociation with many different kinds of
` courses, PLATO materials are integrated
` in various ways with other activities.
` The same PLATO physics materials used
` at the University of Illinois in the rather
` structured scheme described above are
` used at Carnegie-Mellon University in a
` self-paced course where PLATO instruc-
` tional lessons are simply another re-
` source for student study. In addition, the
` modularity of PLATO lessons makes them
` easy to use with diverse textbooks.
` PLATO has been integrated into instruc-
` tion in many other ways. For example, in
` language courses (including French,
` Spanish, German, Russian, Hebrew, Lat-
` in, and Esperanto), PLATO iS used heavi-
` ly to drill the student on vocabulary and
` grammar and to give practice in trans-
` lating sentences from one language to the
` other. A two-semester course designed
` to teach students how to read Russian
` consists of a standard textbook plus
` PLATO lessons for each chapter of the
` textbook (12). This reading course is an
`
` alternative track to the general language
` course for undergraduates and graduate
` students who wish only to read Russian.
` Optional laboratory drills for the stan-
` dard beginning Russian course are also
` on PLATO.
` The function of the PLATO lessons is
` not only to give practice but also to test,
` with instant feedback, whether the stu-
` dent understands the concepts presented
` in the textbook. The materials are also
` used for review, either within the course,
` or by persons who want to refresh their
` knowledge of Russian. There is normally
` a class discussion before and after each
` textbook lesson, occurring every one-
` and-a-half to two weeks. The student
` spends the bulk of his study time at the
` PLATO terminal. In all areas, PLATO les-
` sons are usually integrated with addition-
` al classroom activities. However, in
` such environments as continuing or adult
` education where, because of constraints
` of time or distance, the student may not
` be able to participate in scheduled class-
` room activities, a course consisting only
` of PLATO materials is a viable alterna-
` tive.
` Another important integration of
` PLATO into courses is illustrated by the
` use in chemistry of simulated laboratory
` experiments as a means of better pre-
` paring the student for a real laboratory
` experiment. Merely simulating an experi-
` ment would be inappropriate if the manu-
` al techniques themselves and not just the
` intellectual content are important. A
` PLATO lesson on the theory of titration is
` followed by a PLATO simulation of an ac-
`
` tual titration, in which the student must
` specify all the steps, including con-
` trolling the flow from the buret, and then
` analyze the data. Errors made in doing
` the simulated experiment lead to the
` same problems that would be observed
` in the laboratory. These preparatory ac-
` tivities are then completed by going into
` the laboratory and actually performing
` the experiment, at a time when the stu-
` dent has a thorough understanding of the
` content of the experiment and can con-
` centrate on the practical complications
` that arise. PLATO lessons may also be
` used to extend laboratory experience by
` simulated experiments which, because
` of limitations of time, facilities, and ex-
` perimental skills, students are not able to
` do in the laboratory. One such example
` is shown in Fig. 9, which is taken from a
` lesson on fractional distillation.
` There are ambitious curriculum devel-
` opment projects for reading (13) and
` mathematics (14) in the elementary
` school. Both of these projects constitute
` highly integrated packages of instruction-
` al materials, with automatic routing from
` one activity to another (based on per-
` formance) and extensive reporting to the
` teachers.
`
` Writing Lesson Material in TUTOR
`
` Lesson material for use on the PLATO
` system is written in the TUTOR program-
` ming language (15) which has been de-
` signed to facilitate the development of in-
` teractive instructional programs on a
`
` Fig. 7 (left). Histogram showing the percentage of the questions which students got correct on their first try. Fig. 8 (right). Outline of the PLATO
` computer-based education system. Students who have been put on the roster have access to lesson material selected by the instructor from the
` catalog of lessons. Students have access only to their own grades in the gradebook, which can automatically collect scores from lessons. Data
` related to the lesson performance are stored for review by the author of the programs.
`
` 348 SCIENCE, VOL. 192
`
`This content downloaded from
`(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)132.174.253.93 on Tue, 08 Apr 2025 13:44:45 UTC(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)(cid:0)
`All use subject to https://about.jstor.org/terms
`
`

`

` graphic computer system. As a further
` aid to authors, who should be primarily
` concerned with the problems of teaching
` and not with learning about computers,
` professional consultants can be reached
` easily through a PLATO terminal. The
` consultant, who can be at another termi-
` nal anywhere on the system, can see the
` program on the author's screen and type
` and receive comments at the bottom of
` the screen. In addition, a very complete
` random access, cross-indexed descrip-
` tion of TUTOR and its use is available by
` simply typing one of more than 2000 key
` words that describe the type of thing on
` which information is desired (16). The
` key words do not have to be spelled cor-
` rectly, yet information is delivered to the
` requester almost instantaneously. More
` than 1600 such requests per day are an-
` swered by the system. A single key press
` returns the lesson author to the point in
` his work where he requested informa-
` tion. Another crucial feature is that an
` author can construct a display consisting
` of text and line drawings on the screen,
` and PLATO will generate automatically
` the TUTOR program corresponding to
` that display. The extensive on-line help
` for authors of lesson material makes the
`