COMPUTER and MULTIMEDIA TOOLS
for ENGINEERS and SCIENTISTS
using or teaching APPLIED MATHEMATICS

Láng-Lázi, M.,(*) Kollár-Hunek, K., Viczián, Zs., Donáth, K.(**) Technical University Budapest,
(*) Inst. of Mathematics, (**) Dept. of Chemical Information Technology
e-mail:
lazi@ch.bme.hu

Abstract

Computer aided mathematical calculations, design, qualified data banks and quality assurance have become a very important part in the education of engineers. At the end of the 20-th century this importance implies the using of the best SOFTWARE and the best tools of information technology that are available for teaching and research. The paper presented summarizes the experiences of using computers in the basic mathematical and some advanced (Ph.D. or voluntary student research) courses at the Chemical Engineering Faculty of the Technical University Budapest (TUB) and at the Brevard Community College (BCC, FL, USA). A new way of teaching is given by the MULTIMEDIA. One of the authors has been a popular instructor of a special TV course in Statistics of the Quality Assurance direction for three terms in the USA. We show the specialities of this telecourse, too, and the possibilities of its transfer to the Hungarian education .

Introduction

Mathematics is one of the most important - or perhaps the most important - base of the engineering sciences. If the students have terrible difficulties in understanding and using the algebraic steps or the methods of the calculus they will be burdened in every level in their studies and this fact doesn't depend on their later specialization - whether they will be studying Analytical Chemistry, Mechanics, Reactionkinetics, Quality Assurance , Chemical, Mechanical, Electrical or Civil Engineering, perhaps Transportation. In every subject of their special field they have to use either differentiation and integration or statistical methods to analyse errors or confidence - and all of this is full of algebraic and also computational steps. Now, at the end of the 20th century we have to change our way of teaching and applying Mathematics in Engineering - it means we not only have to make its theoretical parts understandable - but we also ought to teach the students how to find the available formal and applied mathematical software on the netware, to develop the ability in the students to use these tools.

Computer Algebra: PLATO? DERIVE? MAPLE? or...?

PLATO Courseware has been designed by the Computer-Based Training and Education Company: TRO Learning, Inc.(4660 West 77th Street, Edina, Minnesota 55436, USA) for skill development with real life applications in several fields. (Table 1.)

Table 1. Moduls of PLATO

Modul No. of SM Lab. Hours / Objectives in a SubModul
Communication 5 139/466 ; 40/134 ; 122/455 ; 60/112 ; open/100
Mathematics 10 95/671 ; 23/177 ; 36/298 ; 20/136 ; 27/75 ; 10/78 ; 45/156 ; 16/36 ; 38/182 ; 36/164
Science 5 42/869 ; 48/135 ; 40/38 ; 35/92 ; 21/99
Social Studies 1 40/318
Technology 2 9/26 ; open ended
Life Skills 3 30/119 ; 15/65 ; 6/30
Technical Skills 7 6/25 ; 20/83 ; 290/391 ; 54/63 ; 37/49 ; 40/37 ; 20/44
PLATO Workskills 4 29/72 ; 39/132 ; 42/79 ; 24/61

One of the authors was using at BCC (FL/USA) the modul Mathematics in the courses Preparative Algebra (College credit-prerequisit course) and Calculus 2. with Analytical Geometry (University and College credit course). In Table 2. we are showing the submoduls of Mathematics used in the Calculus university-credit course.

Table 2. PLATO submoduls in Mathematics used in Calculus

Submodul Number of Chapters Used Chapters Used Objectives
Advanced Algebra 5 Coordinates and curves Parabolas, Ellipses and Hyperbolas
Calculus 2 17 L'Hospital's Rule L. H. rule ; Further Indeterminate Forms
Numerical Integration Trapezoidal and Simpson's Rule
Improper Integrals Improper Integrals
Lengths of Curves Lengths of Curves
Sequences Sequences, Taylor's Theorem
Series Introduction, Results on Infinite Series

Corresponding to our experiences the most effective way of using PLATO in Mathematics is to use the TUTORIAL part by every student and after having it completed to offer a choice to the students: to continue by the TEST part of PLATO, to write a usual paper-pencil test or to start with the more advanced DERIVE software. As an example we are showing a small part (about 10% of a one-hour lab.) of a PLATO -TUTORIAL and the corresponding DERIVE exercise:

1. PLATO: Given is the equation: (y+3)2/64 - (x-1)2/9 = 1

Determine whether the hyperbola opens up and down or left and right
Find the coordinates of the vertices and foci V1( , ) V2( , ) F1( , ) F2( , )

When the correct answer is given the PLATO TUTORIAL responds by the graph of the equation labelling the asked points.

2. DERIVE: Sketch the graph of the conic section given by the equation: 9x2 + 12xy + 4 y2 + 2x - 3y = 0.

Author soLve Plot Plot


The conic section is a  


The angle of rotation is: 1/2arctan[b/(a-c)]= The asymptotes are:
(Plot them!)
 

As we see DERIVE needs more independent imagination. After a certain level of knowledges it is more effective than PLATO.

The software DERIVE is a very flexible tool at every level of teaching and using Mathematics. As we have shown DERIVE can be used just after learning the first basic sections in Analytical Geometry or in Algebra. It is a real "Easy to Use" software and in its further possibilities DERIVE can be applied in some Ph.D. courses or even in research work, as well. (Berry and Mason 1993) Another advantage we have to mention is the velocity of DERIVE. In the Calculus textbook of Zill (1992) for a certain integral the given computation time of the MATHEMATICA software is about three times as much as the same integral needs by DERIVE. We had similar experiences comparing MAPLE and DERIVE in a numerical problem of our research - a surface fitting where we had to solve a parametric linear system with 15 unknowns.

The complex system in teaching and applying Mathematics and Informatics

At TU Budapest we use Computer Algebra and other software for Numerical Analysis in the undergraduate (B.Sc.), graduate (M.Sc.) and postgraduate (Ph.D.) courses as well. Our system is the following: We have a team with co-workers from several departments of the Chemical Engineering Faculty and of the Institute of Mathematics. The Dept. of Chemical Information Technology and the Dept. of Analysis in the Inst. of Mathematics are responsible for the courses on Computing and Mathematics at the Chemical Engineering Faculty. They offer some Ph.D. courses in Computing and Numerical Analysis so that one part of these courses consists of traditional lectures, the second part is the solution of a numerical analysis problem given by the research work of the Ph.D. student and the third part of these courses is teaching - the Ph.D. students teach in the undergraduate Computing or Computational Mathematics courses and usually they develop one or two new exercises for the M.Sc. courses, as well.

In this complex system our Ph.D. students have the chance to choose any software from the available DERIVE, MAPLE, MATHEMATICA, perhaps the older NUMBOX or for some special problems in mechanical engineering the MATHCAD, for the solution of their own research-problem. They have the same freedom in developing new exercises or new software for the M.Sc. courses.

We have utilized the experiences of our Ph.D. students in small-group-classes (12-24 students/group) of the regular B.Sc. courses in Mathematics and Computing. We have developed a very effective contact between these classes, that is for all first-year-students (about 250) a COMPUTER-SHOW was held in Mathematics after the chapters Differentiation, Sketching graphs of functions, Taylor expansion, Determinants, Matrices using the possibilities of MULTIMEDIA. Thereafter in the small-groups as a part of their Computing classes the students prepared a WINWORD document for the mathematical formulas and inserted their own developed DERIVE graphs or EXCEL tables and graphs in these documents. The advantages of this computer-supported-Mathematics were obvious at every level, first of all in the English courses of the TUB and in the Calculus 1-2 courses of the BCC Florida. The reason of the evident effectivness in the latter two courses is the fact that the students enrolling in these courses come with very different levels of knowledge, so they really need to face what they learn in theory .

In Table 3. we are showing the area of Ph.D. exam-works (Numerical Analysis) or voluntary student research (TDK) workers in Chemical Engineering, Mechanical Engineering Physical Chemistry, Physics and directly in Information Technology.

Table 3. TDK and Ph.D. exam works
(Num. Analysis and Information Techn.)

Title Num. Methods used Software
Characteristics of complex
hydrocarbon mixtures
Roots of Equations
Numerical Integration
Spline
FittingDifferentiation
DERIVE
MATHEMATICA
Velocity distribution and
flow zones in a conical hopper
Num. Solution of O.D.E.-s
Extrema of Functions
Curve Fitting (Polynomial)
DERIVE
MATHCAD
NUMBOX
Ternary Vapour-Liquid Equilibrium
calculations
Num. Solution of P.D.E.
Surface Fitting
Lin Algebra
DERIVE
MAPLE
own PASCAL pr.
Computer implementation of
polarographic analytical method
Line Fitting
Extrema of Functions
own programs
and Macros
Stability of dynamical systems
(a bifurcation-problem)
Num. Solution of O.D.E-s
Critical Points of Functions
Depending on 2 Variables
Num. Methods of Lin. Algebra
DERIVE
own PASCAL
program

One may ask what is the reason of developing a program of our own when a wide scale of excellent and even not very expensive software is available nowadays.

As a very interesting example we show first the quite simple problem of ternary equilibrium pressure-surfaces. The so called triangle-diagrams are as well-known in Chemistry as in Mathematics the C' surfaces over the basic R2 simplex. But there is not any graphic software available that can plot a surface over a non-rectangular region. In this figure we are showing the graphic result of our own PASCAL program where one can obviously see the binary pressure curves: the boundaries of the ternary pressure surface.

Our second example in which our own program is inevitable is an interface program for polarograph used for data collection and evaluation. This figure is showing in the first window the polarogram before filtering and in the second window the measured data.




Statistics and Television Courses

Brevard Community College, along with Daytona Beach Community College and Valencia Community College, has recently been selected by the PBS Adult Learning Service of the United States as one of 20 model college partnerships in a unique pilot project for Going the Distance: The Distance Learning College Degree Project. The goal of this project is to provide distance learning courses that lead to an A.A. degree in General Studies. A telecourse is an integrated learning system that contains televised lessons, related assignments, optional on-campus review oppurtunities and minimal required on-campus sessions for orientation, discussions and examinations. BCC has offered telecourses since 1974 and they experienced a dramatic increase in telecourse student enrollment to 3,500 students for the academic year 1993-94.

It is difficult to measure, that the most profound impact is felt by the students selecting the distance learning experience to meet their unique needs. Citing the words of several students enrolled in BCC's telecourses during Fall 1992:

The TV STATISTICS (STA 2014) is a 3-credit-hour-class required in the Quality Assurance direction. It consists of four on-campus meetings (orientation, 1. and 2. Test, Exam) , 26 half-hour-TV lessons , ten homework exercises in two groups and advising hours (4-6 hours/week) when the students may call the instructor or have a walk-in consultation.

In Table 4. we are showing the time-schedule of STA 2014 with the covered chapters and assignments of the textbook by Moore and Mc. Cabe (1993), the units of the Telecourse Study Guide by Moore (1993) and the tests scheduled in the BCC's summer term '95 .

Table 4. TV Statistics - time schedule

Chapter # Unit # Topics Homework Test
1. 1,2,3,4,5. Describing distributions 1.23. ; 1.51. ; 1.92.  
2. 6,7,8,9,10,11. Relationships, Correlation 2.23. ; 2.65.
3. 12,13,14. Blocking and Sampling   1. Test
4. 15,16. Random Variables 4.12. ; 4.89. ; 4.96.  
5. 17,18. Binomial distribution, Control charts 5.50.  
6. 19,20. Confidence intervals, Significance (u,t) tests    
7. 21,22. t-test for one meanu and t test for two means 7.44.  
8. 23.24. Inference for proportions and two-way tables   2. Test
9. 25.26. Inference for relationships   Exam

In our experiences this type of time and assigment's schedule have developed a good learning habit in the students. Due to the large amount of homework in the first 3-4 weeks, for the later chapters that are not accompained by the same amount of assignments or for the last ones that aren't discussed in every detail, the students acquired an ability to see and extract the most important parts.

At the Chemical Faculty of TUB we teach Statistics in five different courses, directions or levels: Mathematical Statistics - this covers the principles of Probability and Statistics for the B.Sc students ; Biometry - which is the same principal course for the students in the Biological Engineering direction, Design of Experiments and Chemometry - these are facultative classes at the M.Sc. or Ph.D. level.

Three years ago the Chemical Engineering Faculty developed a MULTIMEDIA classroom for 300 students. This new classroom offers the possibility to develop a videotape oriented course similar to the BCC's TV course. At the same time we are able to make the whole videotape series available in our library or even in the HUNGARIAN DISTANCE LEARNING PROGRAM of the TUB and the UHFI. This last program is extremely important with respect to our neighbour-countries where the possibility of studying in Hungarian, broadened with a new aspect for the Hungarian minority living there.

Acknowledgement

The authors wish to express their gratitude to the CCID/USA, to S. M. Campbell, to N. Harbour and to Prof. Dr. D. Argo (BCC/UCF), to the Hungarian National Research Foundation OTKA (grant # T-023258) and to the Ph.D. and voluntary research students of the TUB, N. S. Ha, K. Hermann, N.B. Thuy, J. Heszberger and I. Berente.

References