Applications of computers and computer software in teaching

T.C. O’Haver Department of Chemistry and Biochemistry University of Maryland College Park, MD 20742 Most instructional software has been developed for use i n secondary schools and the first year of college. This is also true for instructional software in chemistry, and a substantial amount exists for microcomputers such as the Apple I1 and IBM PC. Because most instruction in analytical chemistry occurs at more advanced levels, the market is smaller and there is less incentive to develop commercial products. Nevertheless, computers play an important role in the teaching of analytical chemistry because they are important in the Practice of modern analytical chemistry as tools for instrument and robotics control, data acquisition and signal processing, laboratory information management, and scientific communication. Computers and computer software can be used in the teaching of analytical chemistry as tools for delivery of instruction; as tools for data processing and analysis; and as objects of study itself, especially in the context of computer interfacing and control of analytical systems. In this article I will survey and evaluate some of the commercially available software tools that have potential applications in 0003-2700/91/0363-521 A/$02.50/0 0 1991 American Chemical Society

Tools for instruction Tools for instruction are programs developed specifically for teaching purposes that would not ordinarily be used by the professional. The four main types of instructional software are drill and practice, tutorial, simulation, and student tool. There may be some overlap among these categories, and often one program incorporates more than one of these aspects. Drill and practice consists of a series of questions to answer or problems to solve. I t is particularly effective in exposing the student to a

some goal. The student tool format gives the student a scaled-down version of a computer tool that is used by professionals in that field, serving as a less costly and less intimidating introduction to professional practice. An example in chemistry is the use of microcomputer - based molecular modeling packages. By nature, simulations and student tools are more open-ended and less structured than tutorials and are better suited to in-depth treatment of a specialized topic, whereas tutorials are better suited to carefully structured coverage of broader areas with less depth. Tutorials and drill

large number of examples or problems. The tutorial format is essentially a n electronic textbook that combines text and graphics with questions. I t can be enhanced with corrective feedback, navigation aids, concept maps, place keeping and tracking, and pop-up glossaries. The simulation format is based on a model of some physical system (e.g., a reaction, experiment, or instrument). Students perform simulated experiments in which they adjust parameter values to see how other parameters are affected, record data, and typically try to achieve

and practice programs tend to be self-contained; simulations and stu dent tools must be accompanied by written or oral explanations and background information. It is easier to adapt simulations and student tools to local needs; tutorials and drill and practice programs are more fixed in content coverage and are designed for individual student use, requiring one computer for each student. Simulations and student tools, however, can also be used as lecture demonstrations, requiring only one computer for the class. How effective are these various

the analytical chemistry curriculum.

ANALYTICAL CHEMISTRY, VOL. 63, NO. 9, MAY 1, 1991

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formats in improving student learning? Although the drill and practice format has fallen out of favor with software developers in recent years, Weyh and Crook (I) found that the use of well-designed drill and practice programs significantly improved test scores in an introductory chemistry course on writing and balancing equations, stoichiometric relationships, and chemical equilibrium. Alperson and O’Neil (2) performed a comparative evaluation of the effectiveness of tutorial and simulation formats in teaching lower division undergraduate students in anthropology and psychology. Based on multiple-choice test scores and student evaluations, they found that beginning students learn more from tutorials than from simulations. They concluded that simulations are more effective for upper division under graduate and graduate students, who already know the fundamentals of the discipline, are more self-motivated, and have the required conceptual framework to direct their own learning. Considering that most instruction in analytical chemistry occurs at the sophomore level and higher, it is perhaps not surprising that much of the material available for analytical chemistry is based on the simulation format. Simulations of various types are widely used in chemistry and i n chemistry teaching (3, 4). In analytical chemistry, simulations have been used as pre-lab exercises to help students understand a particular type of measurement before doing a laboratory experiment. They are also used to allow exploration of advanced topics or procedures that would take too long in the laboratory and to replace laboratory experiments when suit able equipment is not available. Simulation- based pre-lab exercises might encourage more efficient use of the limited laboratory time available and would be useful adjunct experiences for students in courses without scheduled laboratories. Instrument simulators. Although simulations of analytical methods and instruments cannot help students develop manual manipulative skills, they can be used to illustrate and reinforce many important concepts, including the physical basis of the measurement, sensitivity and selectivity, precision and accuracy, interferences (i.e., the difference between additive and multiplicative interferences), signal-to-noise ratio (S/N), resolution, instrument optimization, and calibration techniques. The ideal analytical instrument sim522 A

ulator should encompass sample preparation, reagent choice, sample presentation, choice of instrument and operating mode, optimization of instrument settings, signal processing and data management, analytical calibration, statistical calculation, and report generation. It should even be possible to simulate real-world effects such as contamination, volumetric errors, instrument noise, and drift. The basic requirement is that there be a model for each aspect of the system that is to be included in the simulation. Several examples of simulator based software for analytical chemis t r y instruction a r e commercially available. The Analytical Chemistry by Open Learning (ACOL) group at Thames Polytechnic, London, has developed a set of materials for train-

Table 1.

ing and continuing education in analytical chemistry that incorporates some elements of computer simulation. The units currently available cover atomic a b s o r p t i o n , h i g h performance liquid chromatography (HPLC), polarography, radiochemistry, GC, fluorescence, and quantitative IR and UV. Each unit includes a book and a computer program that simulates the optimization of instrument conditions of the relevant instruments. The ACOL materials are currently available from ACS Soft ware (Table I). Bob Rittenhouse of Eastern Michigan University has developed a n HPLC simulator for use by chemistry students. This program (Figure 1) simulates a binary gradient LC system with a U V absorption detector and has been published in JCE Soft-

Instructional software for analytical chemistry

Product

CamPatible hardware

Vendor

Analytical Chemistry by Open Learning

MS-DOS

ACS Software American Chemical Society 1155 Sixteenth St. N.W. Washington, DC 20036 (800) 227-5558

HPLC simulator Proton NMR spectrum simulator

MS-DOS Macintosh

JCE Software University of Wisconsin Dept. of Chemistry Madison, WI 53706 (608) 262-5153

IR and NMR simulators SpectraDeck Squalor

MS-DOS, Macintosh

Trinity Software Box 960 Campton, NH 03223 (603) 726-4641

MicroCAP II

MS-DOS

Spectrum Software 1021 S. Wolfe Rd. Dept. B Sunnyvale, CA 94087 (408) 738-4387

Extend

Macintosh

Imagine That, Inc. 7109 Via Carmela San Jose, CA 95139 (408) 365-0305

MathCAD

MS-DOS, Macintosh

Mathsoft, Inc. 1 Kendall S uare Cambridge,&A 02139 (800) 628-4223

SPECTRUM

Macintosh, Microsoft Windows

Office of Technology Liaison Lee Bldg., Room 2114 Universi of Maryland College !ark, MD 20742 (301) 454-6559

MATLAB

MS-DOS, Macintosh, VAXNMS, Sun, Apollo

Mathworks, Inc. 24 Prime Park Way Natick, MA 01760 (508) 653-1415

TK Solver Plus

MS-DOS, Macintosh

Universal Technical Systems, Inc. 1220 Rock St. Rockford, IL 61101 (815) 963-2220

ANALYTICAL CHEMISTRY, VOL. 63, NO. 9, MAY 1,1991

Macintosh MS-DOS

ware (5).The chromatograms are calculated by the program based on a model of reversed-phase column behavior. Students can choose the solvent system, prepare samples, adjust detector sensitivity, set up the gradie n t programmer, a n d even add spikes of standard to the samples. Experience with this program has shown that the underlying model is good enough to predict what the real chromatogram of a particular mixture will look like in most cases (3) and that the simulation takes only about one-tenth the time of running a real chromatogram, allowing many more experiments to be performed in a limited time. Paul Schatz of the University of Wisconsin has developed simulators for IR and NMR spectrometers (Figure 2) that allow students to practice

correct instrument operational procedures and to explore the effects of instrument settings on peak distortion, S/N, and so on. Note that these programs are instrument simulators, not spectrum simulators; they do not attempt to calculate the spectrum from the molecular structure but rather read the spectrum for each sample from a data file. Spectrum simulators. There are a number of NMR simulation programs available that can calculate the spectrum of a molecule from its molecular structure. These are aimed more at organic structure determination than at quantitative analysis. One example is Proton NMR Spectrum Simulator developed by Kersey Black of Claremont College (6). This program is designed to help students correlate proton NMR spectra with

Product

Compatible hardware

Vendor

Mystat Systat

MS-DOS, Macintosh MS-DOS, Macintosh

Systat, Inc. 1800 Sherman Ave. Evanston, IL 60201 (708) 864-5670

LabView 2.0 LabWindows

Macintosh MS-DOS

National Instruments 12109 Technology Blvd. Austin, TX 78727 (800) 433-3488

WorkBench PC WorkBench Mac

MS-DOS Macintosh

Strawberry Tree Computers 160 S. Wolfe Rd. Sunnyvale, CA 94086 (408) 736-8800

Plus

MS-DOS, Macintosh

Spinnaker Software 1 Kendall S uare Cambridge,%lA 02139 (617) 494-1200

ToolBook

Microsoft Windows

Asymetrix Corp. 110 110th Ave., N.E. Bellview, WA 98004 (206) 462-0501

Wingz

Macintosh Microsoft Windows

lnformix Software Box 15998 Lenexa, KS 66219 (913) 492-3800

CT MacQual

Macintosh, MS-DOS Macintosh

Falcon Software, Inc. Box 200 Wentworth, NH 03282 (603) 764-5788

Sigma Plot

MS-DOS

Jandel Scientific 65 Koch Rd. Corte Madera, CA 94925 (800) 874-1 888

Student versions of MathCAD 2.0, MicroCAP II, /icr;Lo#ic II, and

MS-DOS

Addison-Wesley Publishing Co. 1 Jacob Way Reading, MA 01867 (617) 944-3700

Cleopatra

MS-DOS

Elsevier Scientific Publishers P.O. Box 103 1000 AH Amsterdam The Netherlands 31-20-586 291 1

molecular structure. The program provides a set of drawing tools with which the student can draw a molecular structure. It then calculates the spectrum of the molecule by means of a rule-based algorithm t h a t estimates chemical shifts and coupling constants. A variety of spectrometer field strengths can also be chosen. The structure and the spectrum are dynamically linked so that clicking on any peak in the spectrum highlights the corresponding hydrogen atoms in the molecular structure drawing. Conversely, clicking on any hydrogen atom i n t h e molecular structure drawing highlights the peak or multiplet generated by t h a t hydrogen atom and other “equivalent” hydrogen atoms (Figure 3). As a supplement to conventional textbooks and lectures, such a simulator provides an inexhaustible source of examples, allows students to perform “what if” experiments, and is much more visually engaging and interactive than the usual printed examples. Qualitative organic analysis laboratory simulators. Trinity Software’s Squalor and Falcon Software’s MacQual are examples of simulations of a qualitative organic analysis laboratory (7). These programs allow a student to select an inst r u ct o r - g e n e r a t e d “unknown, ” choose from a long list of standard tests and physical properties (e.g., melting point, solubility), and at tempt to identify the compound. Supplementary utilities allow the instructor to create new unknowns, enter digitized spectra, and so forth. These are not full laboratory simulations-test results are simply displayed unambiguously in text form (e.g., “a dense white precipitate forms,” “melting point: 35-39 ‘C”+ but such programs can help students to practice the logic of qualitative analysis schemes. Pavia (7) found that student performance in solving actual unknowns improved dramati cally after practice with the simulation. Squalor received the 1988 EDUCOM/NCRIPTAL awards for best chemistry and best simulation. Circuit simulators. Training in basic electronics is very useful for the modern analytical chemist, a n d many chemistry departments offer a n “electronics for chemists” course. A number of programs that simulate the operation of electronic circuits are commercially available for various microcomputer and workstation platforms and can be useful in basic electronics training. This is a welldeveloped area because such simula-


523 A

AAC INTERFACE tors are widely used by electrical engineers for solving design problems. There are basically three types of electronics simulators: Component - level analog simula tors, in which the basic elements are electronic components such as resis tors, capacitors, inductors, diodes, transistors, and operational amplifi ers. An example is MicroCAP by M. S. Roden of California State University. A low-cost student edition of this program for the IBM PC, published by Addison- Wesley, is shown in Figure 4. I have used this program effectively as a lecture demonstration aid in my electronics for chemists course. Digital simulators, in which the basic elements are gates, flip-flops, and other logic modules. Examples are MicroLogic I1 and DigiSim, a public-domain program available from several online sources. System simulators, in which the basic elements are subsystems such as amplifiers, integrators, filters, phase-locked loops, comparators, and signal and noise sources. An example is Bob Diamond’s Extend simulation package, which I have used to demonstrate to students the internal operation of commonly used S/N enhancement instruments such as lockin amplifiers. All of these programs allow a circuit to be constructed on the computer screen by drawing a schematic or block diagram; circuit elements are selected from a menu or palette, placed on the screen, and connected together as if being wired to a real circuit. The program then simulates

the operation of the resulting circuit and displays a graph of voltage versus time or of amplitude versus frequency at specified points in the circuit. The construction and testing of simulated circuits is much faster than those of real circuits and much more satisfying than studying static circuit diagrams and graphs. Simulations can be a useful adjunct to, but not a replacement for, practical laboratory experience; many important aspects of real-world electronics are missing in simulations, such as lead dress, grounding, shielding, noise and drift, cold solder joints, and defective components. Math systems. MathCAD is a n environment t h a t integrates text, mathematical equations, and graphics in an interactive “live document” screen format that automatically re calculates and replots graphs when parameters are changed. MathCAD has been used widely for instruction in engineering fields. Sets of MathCAD documents in the areas of electrical, chemical, civil, and mechanical engineering; statistics; and numerical methods are sold separately, but nothing in the area of analytical chemistry is available. A low-cost student PC edition of this program is published by AddisonWesley (8).A simple example of application to spectroscopy is shown in Figure 5. This screen shows a portion of a MathCAD document that describes the basic theory of a diffraction pattern for multiple slits (e.g., a diffraction grating). Here N represents the number of slits or grooves in the grating. By increasing N to

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524 A


larger numbers, the evolution of the resolution can be clearly seen. Tools for analysis and research The programs described in this section are not designed specifically for instruction but are commonly used as productivity tools by professionals. Programs of this type often serve a dual role: They can be used as tools for instruction when combined with the appropriate ancillary material (data sets, documents), and they can become part of the subject matteras tools that students should learn to use both in school and in their professional lives. Like MathCAD, these programs tend to be generic rather than focused on one discipline, so the expense of volume purchases or site licenses can perhaps be shared with other departments. Spreadsheets and data plot ting. Spreadsheets are probably the most widely used tools for simple laboratory data calculations (9),although they were initially designed for business applications. A spreadsheet is essentially a large electronic grid consisting of rows and columns of cells into which the user may enter numbers, text labels, or algebraic formulas that define some cells in terms of other cells. Clearly, any student of analytical chemistry should know how to use spreadsheets, and indeed many instructors make computers available to laboratory students for data reduction and plotting. Designing a spreadsheet is much simpler than writing a custom computer program and requires no programming experience. Modern spreadsheet programs are very easy to learn; a few minutes of instruction is generally all that is necessary to introduce students to the basics of data entry and editing, creating and copying formulas, and plotting data. Macros (a built-in programming language to automate complex and repetitive tasks) are somewhat more difficult to learn to use, but the instructor can write macros to simplify such tasks as scientific data plotting and curve fitting and can make them available to the student. The macro r e c o r d e r s a v a i l a b l e on modern spreadsheets make macro creation much easier. Data-plotting programs, such as SigmaPlot, are a related category of application software that is a useful laboratory tool and whose use should be a routine part of students’ laboratory work. These programs have evolved to the point where they are easily used to produce attractive, clear, scientific data graphs and to

-

perform least - squares curve fitting. Generally, plotting and curve fitting are easier in a data-plotting program than in a spreadsheet, but complicated calculations are more difficult. Experience has shown that students actually enjoy running calculations and plotting data using these programs; it is so much easier and faster than manual calculation and plotting that it is possible to assign more work and larger data sets than would otherwise be practical. Signal processing. Computer based signal processing and data analysis operations are used routinely by an increasing number of analyt ical chemists. Professionals often use complex and expensive data analysis software packages, such as Macmillan’s Asyst or Galactic’s Spectra Calc, or dedicated software t h a t comes bundled with commercial instrumentation systems. It is important for students of analytical chemistry to appreciate the capabilities and limitations of these modern signalprocessing packages. For teaching purposes, the ideal software is less complex and less expensive than these professional packages yet sufficiently powerful to be used as a genuine research tool. An example is SPECTRUM (Signal Processing for Experimental Chemistry Teaching and ResearcWniversity of Maryland), an interactive, graphics oriented signal - processing program that implements the most widely used postrun signal - processing oper ations in a menu-driven user interface (Figure 6). This program allows students to explore the application and optimization of these techniques on previously recorded digitized instrument signals, without getting bogged down in computer program ming or command syntax. The program comes with a library of prerecorded signals and a self-guided tutorial on the applications of signalprocessing techniques in spectroscopy and chromatography. The tutorial is designed to occupy a standard 3 - h laboratory period. The data files are simple ASCII text files, easily imported from various sources. I have used this program effectively for individual student assignments in an advanced undergraduate course on applications of computers in data acquisition and analysis. SPECTRUM r e c e i v e d t h e 1990 E D U C O M / NCRIPTAL awards for best chemistry and best design. Chemometrics. Instruction in chemometrics is increasingly a part of graduate-level instruction in analytical chemistry, and naturally such

instruction is based on computer software. Elsevier Scientific Publishers offers a program called Cleopatra that is specifically aimed at instruction in chemometrics. It covers sampling, correlation, curve fitting, Fourier filtering, simplex optimization, and Kalman filtering. A more openended approach is MATLAB, a highlevel programming environment de signed for t h e manipulation of vectors and matrices, which is used by several of the leading research groups involved in chemometrics as an alternative or supplement to conventional general-purpose languages. MATLAB is well suited for the

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large class of multivariate chemometric procedures that are based on matrix algebra (10). For example, the q u a n t i t a t i v e spectrophotometric analysis of complex mixtures of components whose spectral features are poorly resolved is often accomplished by multivariate calibration procedures based on multilinear regression. In MATLAB, these calculations can be performed by a single line of code. Many chemometric procedures involve an iterative maximization or minimization of some response. MATLAB provides a simple function t h a t implements a Nelder-Mead (modified) simplex minimization of a function of several variables. Factor

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Figure 2. Paul Schatz’s NMR simulator (top) and IR simulator (bottom) allow students to practice correct instrument operational procedures and to explore the effects of instrument settings on peak distortion, S/N, etc. Courtesy Trinity Software.


525 A

A/C INTERFACE analysis methods, such as the evolving factor analysis for the resolution of overlapping chromatographic peaks, or rank annihilation for the resolution of overlapping fluorescence peaks, are easily performed using MATLAB. An example of a MATLAB application is shown in Figure 7, which illustrates an evolving factor analysis method being applied to a simulated c h r o m a t o g r a m . T h e MATLAB “script’’ that performs the calculations and generates the graphics is

displayed in the window labeled Edit 1. Note how much is done by so few lines of code. Although designed as a professional tool, availability of substantial classroom discounts makes MATLAB a practical instructional tool as well. Statistics packages. There are, of course, a large number of commercially available statistics packages for small computers-including microcomputer versions of the big systems such as SAS, SPSS, and Systat-that can be useful in teaching

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Figure 3. Kersey Black’s Proton NMR Spectrum Simulator calculates the spectrum of a student-drawn molecule by means of a rule-based algorithm that estimates chemical shifts and coupling constants. Reprinted with permission from Reference 6.

Figure 4. MicroCap II, a component-levelanalog simulator that allows a circuit to be constructed on the computer screen and then simulates its detailed dc, ac, and transient performance. Courtesy Spectrum Software.

526 A


analytical chemistry data processing. Such programs do not actually teach statistical analysis, of course, but several textbooks on basic statistics come with software and data sets t h a t allow students to engage in hands-on exercises (11,12).Students should also be aware that Mystat, a student - sized but capable statistics package, is distributed by Systat, Inc., at no or low cost to students and faculty. Equation solvers. Declarative (nonprocedural) equation solvers are a class of programs designed to compute numeric solutions to sets of algebraic equations. The user simply enters all of the equations that apply to a particular type of problem and gives numeric values t o all t h e known quantities. This set of equations is referred to as a model. The program will then attempt to perform all the substitutions required to solve the model and evaluate the unknowns, optionally performing iterative solutions of sets of equations that cannot be solved by substitution. The difference between this and a spreadsheet or custom program solution is that the user does not need to provide a n explicit solution for the unknowns or know beforehand what the unknowns are going to be. Therefore one model can be used to solve a large number of variations for each type of problem, depending on which variables are known and which are unknown. Moreover, one can typically define a set of units and the relationships between them so that the user can specify the knowns and obtain the unknowns in any of those units. There are basically two ways to use this kind of software in instruction: model using, in which students investigate the quantitative behavior of a previously created model, and model construction, in which students use the program as a tool to construct their own models to solve certain problem types. We use the former approach only when the models a r e very complex and when the quantitative behavior of the model rather that the computational procedure is the main point. For example, students in our environmental chemistry class use TK Solver Plus, one of the most popular commercial equation solvers, to investigate the influence of atmospheric chemistry on the pH of rain using the Charson-Vong equilibrium model, which consists of 27 equations (13). The program can also be used by students as an alternative to spreadsheets or custom programming to

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A / i INrERFACE solve homework problems that are computationally too difficult to be performed by hand. This allows the instructor to assign more realistic problems, avoiding the oversimplifi cations that are sometimes used to keep problems computationally convenient. Allan Smith (13) has had considerable success with this approach i n analytical and physical chemistry courses. I have also used this program as an instructor’s tool in teaching instrumental analysis courses to prepare and check problem sets and exam questions for standard types of numeric word problems. Using a n equation solver cuts down on a lot of the nuisance work involved in generating large problem sets with answers. However, in preparing problems for manual solution on exams, one has to be careful not to compose problems that the students cannot work by direct substitution or by some other pencil-and-paper method. Note that the students do not work directly with these models, because they are all of a type that students would be expected to work manually. Interfacing. Instruction in laboratory instrument interfacing and data acquisition has become widespread in physical science since the introduction of personal computers (14).There are now plenty of sources of high-quality, low-cost commercial data acquisition hardware for the popular microcomputers. The development of new hardware and software proceeds at such a rapid pace that it is difficult for authors of textbooks and laboratory manuals to keep up to date. Departments that offer a course in laboratory instrument interfacing, or incorporate such instruction into existing courses, often create their own materials. One recent example of a commercially available textbook in this area (15) covers analog-to-digital and digitalto - analog conversion, digital input and output, RS-232 and IEEE-488 conventions, a n d t i m e r s a n d counters. It also includes less commonly encountered but useful infor mation on noise reduction and data analysis (e.g., peak detection). This book even comes with a diskette of software routines written in BASIC. Although most laboratory programming is still done in conventional procedural languages such as Fortran, BASIC, Pascal, or C, there is an increased interest in advanced, high level, graphics-based programming environments. Good examples are National Instruments’ LabView and 528 A

modules (procedures and functions) represented as movable icons, the user selects and arranges the modules into a graphical representation of the desired operation, much like drawing a flow chart or wiring a circuit diagram in a circuit simulator.

Labwindows and Strawberry Tree’s WorkBench PC and WorkBench Mac. These software products allow sophisticated d a t a acquisition and analysis programs to be created without conventional programming. From a set of independent program

Figure 5. MathCAD, an environment that integrates text, mathematical equations, and graphics in an interactive “live document” screen format, is widely used for instruction in engineering fields. This is a portion of a MathCAD document that describes the basic theory of a diffraction pattern for multiple slits (e.g., a diffraction grating). Courtesy Mathsoft, Inc.

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A/C INrERFACE These systems are not generalpurpose programming languages; they typically work very well (in terms of ease and speed of construction, execution speed, and ease of

maintenance) when performing data acquisition, control, and numerical analysis operations for which there a r e appropriate existing modules. They work less well when one is try-

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Figure 7. MATLAB, a high-level vector-matrix language well suited to chemometrics applications, is shown performing an evolving factor analysis on a chromatogram. The calculations and graphics shown here were generated by the simple "script" in the window labeled Edit 1. Courtesy Mathworks, Inc.

Figure 8. Pulse-width modulator constructed in WorkBench, a high-level, graphics-based programming environment in which icons representing independent program modules (procedures and functions) are selected and arranged by the user into a flow chart or circuit diagram of the desired operation. Courtesy Strawberry Tree Computers.

530 A

ANALYTICALCHEMISTRY, VOL. 63, NO. 9, MAY 1, 1991

ing to do nonstandard things. The greatest benefit of this approach is probably that the designs are more easily read, understood, and maintained by nonprogrammers. Figure 8 shows a pulse-width modulator constructed i n WorkBench. The analog input modules read the hardware analog- to- digital converters, and the output-here displayed with the aid of a graphic display module-could be routed to an analog output module that controls the hardware digital - to - analog converter.

Tools for courseware development Instructional computing has not be come as common as the pioneers of 20 years ago had predicted, and the reason usually given is the shortage of good instructional software. But there is no shortage of textbooks or of published laboratory experiments and lecture demonstrations, because these can be created by individual instructors with skills they already have. The new development tools discussed in this section make it much easier for individual instructors to create publishable educational soft ware without the detailed knowledge of programming and large time investment usually required. General-purpose languages. Conventional programming languages, such as Fortran, BASIC, Pascal, and C, are widely used in scientific programming. They are well suited to quantitative calculations based on the evaluation of algebraic expressions. However, they may not always be the best choices because it takes a great deal of time and specialized skill to develop software that meets the expectations of students and other instructors who are accustomed to modern, professionally developed products. For example, in most languages it is difficult to create a modern directmanipulation user interface (windows, pull-down menus, etc.); to import and display graphics generated in other programs; to prepare a n attractive Cartesian coordinate graph of a data set or function; to generate a simple animation sequence; and to display scientific text with sub scripts, superscripts, italics, Greek characters, and properly formatted math equations. There is also the difficulty of porting programs from one hardware platform to another; generally a substantial amount of rewriting must be done. Programming for nonprogram mers. The first microcomputers to be widely used in education, the Apple

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ANALYTICAL CHEMISTRY, VOL. 63, NO. 9, MAY I,1991

I1 and IBM PC, were designed with built-in BASIC interpreters in readonly memory (ROM). BASIC interpreters were easy to learn and required little memory but were slow in execution and not well suited to large projects. Nevertheless, because it could be assumed that all owners of these computers would have t h a t language available, BASIC became a kind of lingua franca for amateur programmers in the early days of microcomputers. Most of the programs developed by instructors were written in that language. Newer microcomputer designs, such as the Macintosh and the NexT, no longer have b u i l t - i n BASIC interpreters but rather are supplied with their own alternative development systems (Hypercard and Nextstep, respectively) that permit screen layouts and other user interface aspects to be constructed easily from templates by pointing and clicking. These development systems are beginning to replace BASIC a s t h e language of choice for instructor-written drill and practice and tutorial material, because they allow custom software creation without conventional programming. In addition to Hypercard there are also Plus a n d ToolBook, both of which are available in versions for IBM PC compatible computers. Hypercard was the first of these systems to be widely used and has by far the largest number of developed applications and add-on utilities. For cross -platform development, Plus has the advantage of being nearly identical on the IBM PC and the Macintosh; moreover, it can import most existing Hypercard stacks. Like BASIC, these systems are easy to learn but relatively slow in execution speed compared with conventional compiled languages (although there are third-party add-ons available that increase the speed of numeric calculations and animations, control external peripherals, etc.). Unlike BASIC, these systems make it very easy to assemble programs with the kind of graphic direct -manipulation interface that is rapidly becoming a standard user expectation (Le., pulldown menus, scrolling windows, clicking buttons). It is also easy to include graphics imported from a variety of sources (clip a r t collections, draw-and-paint programs, scanners, and special-purpose programs such as chemical structure drawing and molecular modeling). Macro languages. The macro facilities in modern spreadsheets are another alternative to conventional

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533 A

A/C INTERFACE exact but mathematically cumber some model. It was designed as a lecture demonstration and took about 2 h to put together. The slider bars at the top left are used to adjust the volume of acid titrated, the acid and base concentrations, and the K, of the acid, and the titration instantly changes accordingly. Compared with the usual textbook presentation of a set of overlapping titration curves a t various K, values, the computer presentation is more dynamic a n d allows r e l a t i v e l y straightforward investigation of such questions as: “What is the weakest acid that gives a discernible inflection at the endpoint?” or “Can titration be used a t trace concentration levels by using a very dilute titrant?” Developing for multiple hardware platforms. One of the frustrations in trying to make one’s educational software development efforts accessible to other institutions is the wide range of computer hardware owned by different schools, much of which is obsolete by today’s standards. For the most part, a program written specifically for one machine will not run on another without extensive rewriting. The traditional approach to producing “portable” soft ware is to restrict the functionality to the lowest common denominator of the target machines, relying on simple text-only displays that make little demand on the hardware. In the long run, however, it will be necessary to upgrade existing hardware so that the lowest common denominator will not be quite so low. In fact, many experts now recommend a 32-bit processor and a t least 1 or 2 Mbyte of memory for use with the graphical environments that are becoming increasingly common in business, professional, and educational applica tions. At colleges and universities, the main platforms for individual student workstations are the IBM PC and the Macintosh. For these machines, developing in spreadsheet macro languages (e.g., Excel or Wingz) or in math-based packages (e.g., TK Solver, MATLAB, MathCAD) is advantageous, because there are compatible versions of all these tools on both platforms. However, a difficulty with these approaches for general - purpose development is that they cannot create stand-alone exe cutable files (binaries). The same is true of spreadsheet macro programs. Therefore each user must have a copy of the e n t i r e program and enough memory to run it. Moreover, all these approaches are suited main-

ly for projects that emphasize numerical computation; they are not really general -purpose programming languages. Courseware languages. Several special - purpose programming lan guages have been developed for courseware. One of the most exciting is called cT, which is the microcomputer version of Carnegie Tutor, an integrated programming environment developed at the Center for Design of Educational Computing a t Carnegie Mellon University. I t is a rare example of a programming language whose source code is directly transportable between versions for UNIX, IBM PC, and Macintosh without change, which compiles executable (and license-free) binaries, a n d which supports all the modern userinterface conventions. But beyond this, cT has many special features that are particularly valuable for science and chemistry software development. For example, its source text editor works like a word processor, allowing literal strings (analogous to the text in a BASIC program’s PRINT statement) to be typed in character-by-character styled text (i.e., subscripts, superscripts, different fonts and sizes, Greek and math characters, and italics). When the program runs, that text is displayed just as it appears in the source text. (This is a big improvement over the contortions one usually has to go through to display proper chemical formulas and math equations from within a program.) You can also create and modify program graphics codes by clicking the mouse in the execution display window. An example of an application written in cT is shown in Figure 10. This is a simple optical bench, written by Bruce Sherwood of Carnegie Mellon’s Physics Department, that does simple ray- tracing calculations, allowing students to perform experiments in basic geometrical optics by using the mouse to select and arrange lenses, mirrors, a p e r t u r e s , a n d a light source. Without an advanced development language like cT, a program such as this would be very difficult to write. Conclusion The real payoff of computer courseware is its ability to do the things that paper textbooks-or even multimedia video-cannot do a t all: namely, to allow the student and the instructor to work interactively and dynamically with quantitative models, simulations, and analysis tools.

534 A * ANALYTICAL CHEMISTRY, VOL. 63, NO. 9, MAY 1, 1991

The microcomputer software tools described here make it easier than ever before for the analytical chemistry instructor to construct and use effective computer-based demonstrations and exercises that truly take advantage of the power of the computer as a machine for learning. References (1) Weyh, J.A.; Crook, J. R. Academic Computing 1988, 3 7 ) June, 32-36 and 52-54. (2) Alperson, J. R.; O’Neil, D. H. Academic Computing 1990, 4(5) Feb., 18-19 and 47-49. (3) Moore, J. W. Academic Computing 1987, 3 3 ) Nov., 18-21 and 45-49. (4) Bourque, D. R.; Carlson, G. R. J. Chem. Ed. 1987, 64, 232. (5) Rittenhouse, R. C. “HPLC Simulator” JCE Software 1988, Ib(1). (6) Black, K. “ProtonNMR Spectrum Simulator”;JCE Software 1990, IIc (1). (7) Pavia, D. L. Academic Comfiuting 1990, 4(5) Feb., 8-10 and 32-34. (8) Anderson, R. B. The Student Edition of MathCAD; Addison- Wesley: Reading, MA, 1988. (9) Ouchi, G. I. Personal Computers for Scientists; American Chemical Society: Washington, DC, 1987. (10) O’Haver, T. C. Chemom. Intell. Lab. SySt. 1989, 6, 95-103. (11) Frankenberger,W.; Blakemore, T. Introductory Statistics Software Package; Addison-Wesley: Reading, MA, 1987. Disk included. (12) Velleman, P. F. Learning Data Analysis with Data Desk; W. H. Freeman: New York, 1989. Disk included. (13) Smith, A. L. Applications of TK Solver Plus in Chemical Equilibrium and Chemical Analysis; McGraw-Hill:New York, 1990. Includes disk of models. (14) Mendenhall, M. M. Academic Computing 1989,3(7)March, 20-23 and 44-45. (15) Gates, S. C.; Becker, J. Laboratory Automation Using the IBM PC; Prentice Hall: Englewood Cliffs, NJ, 1989. Disk included. (16) Ghosh, A.; Morison, D. S.; Anderegg, R. J. J. Chem. Educ. 1988,65, A154.

T.C. O’Haver earned a B.S. degree jkom Spring Hill College (1963) and a Ph.D. in analytical chemistry (1968) from the University of Florida. He then joined the faculty of the University of Maryland where he has pursued research interests in analytical spectroscopy and instrumentation, derivative and wavelength modulation spectroscopy, continuum-source and multielement atomic absorption spectrometry, computer applications, and laser photoionization spectroscopy.

Applications of computers and computer software in teaching

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