Spring Constant Rhetoric:

The Information Design of a

Computerized Physics Tutorial

Anne Marie Guldberg

Rhetoric 5196

Plan B Design Project

Dr. Longo

05/12/2005

2

Introduction

In this paper, I will explore the intersection of theory and practice for the technical

communication and information design questions I encountered in the process of building a

computerized physics tutorial for myPlan B design project.

Project Explanation

Information design is indivisible from educational endeavors, especially the sciences:

―Visual representations…have been inseparable from science because they make it possible for

scientists to interact with complex phenomena in an essential way‖ (Richards 184).

My main task during my Plan B design project was building a computerized introductory

physics tutorial for use in the University of Minnesota’s Department of Physics. My supervisor

for thetask was Dr. Leon Hsu, who is an assistant professor in the GeneralCollege, and my

advisor for the project was Dr. Bernadette Longo, who is an assistant professor in the Rhetoric

Department. My objectives for this project were to apply information design theory to

computerized physics tutorials, utilizephysics educational theory, use a context-rich problem in

accordance with information design, program a tutorial, and present a deliverable.

Information Design Theoryof Computerized Tutorials

Most of society as a whole takes for granted that we now live in an information age.

Practically, the

computer as both tool and environment is quickly becoming as ubiquitous as the

telephone in the work and recreational lives of not only North Americans, but also

for a significant portion of the world’s population (O’Sullivan 61).

Yet, as opposed to other well-known and popular technologies such as automobiles,―in the case

of computers, the technology itself is treated as and responded to as an interactant capable of

direct communication‖ (Sundar and Nass 700). People understand computers as an entity unto

themselves:

The fact that computers are programmed and can be used as media seems to be

psychologically irrelevant when users are in the midst of an interaction. It is the

proximate source, the computer, that receives attention as well as social

attributions. That is, psychologically, computers themselves, like human beings,

are sources (Sundar and Nass 700).

Thus, since people view computers as sources and not merely objects, they impart power to

them. This unique communication relationship that computers have with human beings allows

for a tremendous opportunity in computerized learning. As Spiro and his colleagues state in

"Cognitive Flexibility, Constructivism, and Hypertext: Random Access Instruction for Advanced

Knowledge Acquisition in Ill-Structured Domains,‖

3

The computer is ideally suited, by virtue of the flexibility it can provide, for

fostering cognitive flexibility.In particular, multidimensional and nonlinear

hypertext systems, if appropriately designed to take into account all of the

considerations discussed above, have the power to convey ill-structured aspects of

knowledge domains and to promote features of cognitive flexibility in ways that

traditional er-based [sic] drill) could not (although such traditional media can be

very successful in other contexts or for other purposes) (Spiro et al.)

Flexibility can be seen as desirable not only from an instructor’s perspective but from the

student’s point of view since ―students understand technologies and have the aptitude to learn

them quickly‖ (Kastman Breuch 268). Moreover, the best of these computerized programs will

be guided by information design as the computer’s role as information source should not be

undermined by poor understanding of the target student audience.

Physics Educational Theory

Computerized learning has been successfully integrated into many different science and

engineering classes. Kurtis G. Paterson explains how an electronic bulletin board, multimedia

homework assignments, and Internet-based term project reports were used in an atmospheric

chemistry and physics course in ―Student Perceptions of Internet-Based Learning Tools in

Environmental Engineering Education.‖Overall, Paterson notes that ―successful integration of

Internet-based tools within engineering courses opens up unprecedented possibilities for

learning, communication, information exchange, and interactivity‖ (303).The success of

computerized learning has also been noted qualitatively. In ―Java Applets Enhance Learning in a

Freshman ECE Course,‖ Charles R. Graham, and Timothy N. Trick explain how Mallard, an

Internet-based homework program was used in a first-year electrical and computer engineering

course;―the results from the survey of the students indicate that students enjoy using Mallard and

feel that it was effective in helping them to learn the course material‖ (Graham and Trick 396).

Concrete student improvement has also been documented using computerized tutorials. John

Milton-Benoit, Ian R. Grosse, Corrado Poli, and Beverly Park Woolf explain the success of one

such tutor in ―The Multimedia Finite Element Modeling and Analysis Tutor.‖ This FEA (Finite

Element Modeling and Analysis) tutor was used to teach both undergraduate and graduate

students in mechanical engineering, and ―preliminary results showed that the students that used

the FEA Tutor performed 30 percent better than those that attended the traditional lecture‖ (515).

Physicists and physics teachers have also begun to consider computerized tutorials for

improving physics education, whose traditional lecture based instruction has fallen under

scrutiny. Alan Van Heuvelen maintains in ―Learning to think like a physicist: A review of

research-based instructional strategies‖ that

students should become active participants during lectures (and in other parts of the

course) in constructing concepts, in confronting preconceptions that are misconceptions,

in reasoning qualitatively about physical processes, and in learning to use concepts to

solve problems (896).

Yet, in current introductory physics classes, students are not being engaged in this manner; he

notes ―many studies indicate that students leave our courses in about the same status as they

4

entered‖ (891).Lillian Christie McDermott agrees in her ―Millikan Lecture 1990: What we teach

and what is learned-Closing the gap‖ where she writes ―there is considerable evidence that the

curriculum is not well matched to many students in the introductory course‖ (McDermott 302).

She continues by stating the central issue in physics education explicitly:

The problem with the traditional approach is that it ignores the possibility that the

perception of students may be very different from that of the instructor (304).

Computerized tutorials can and do help address this problem. Specifically―Teaching scientific

thinking skills: Students and computers coaching each other‖ by Frederick Reif and Lisa A. Scott

details success with computerized physics tutorials. These computerized physics tutorials are

better known as PALs, which stands for Personal Assistants for Learning. Reif and Scott

conducted an experiment where students used PALs in a physics class, and their summary notes:

We used these PALs to carry out a comparative experimental study to assess their

efficacy in the context of a physics course. This study showed the following: (a)

The PAL tutorials were nearly as effective as individual tutoring by experienced

human tutors, but required much less instructor time. (b) The PAL tutorials

prevented nearly all the students from failing the subsequent test (i.e., of getting

scores less than 65%). By contrast, about half of the equivalently able and

motivated students failed this test when they had received only the instruction

provided in the course. (c) Students liked using the PALs, found them very

helpful to their learning, and perceived that they were learning useful methods of

thinking about physics (828).

Therefore, the methodology of PALs in improving both student performance and understanding

in physics has been born out by experimental evidence. The computerized physics tutorial I

completed for my Plan B design project is also a PAL.

These PALs use a framework of five steps for answering physics problems because when

physics professors and students that have completed two semesters of introductory physics

courses are given the same test, the physics professors all follow a similar framework in order to

do the problems while the students’ approaches are more haphazard, dissimilar, and prone to

error. ―A physicist depends on qualitative analysis and representations to understand and help

construct a mathematical representation of a physical process‖ (Van Heuvelen 891),whereas

students’ approaches vary among themselves and from problem to problem.Students also fail to

take advantage of physics problem solving techniques such as drawing vector diagrams. The

five steps used in these PALs are:

1. Focus the Problem

2. Describe the Physics

3. Plan the Solution

4. Execute the Plan

5. Evaluate the Answer (Hsu).

This structured five step framework for learning how to do physics problems used by the PALs

matches the problem solving techniques used by physicists. Thus, the PALs have students

5

follow the same process as physicists in order to encourage them to think like physicists. This

makes learning the material easier since physics has its own rules and discourse.

The other advantage these PALs provide is student practice. Physics courses are

designed around solving problems, and students watch the professor demonstrate how to do this

in lecture. But they may spend only 40 minutes or so a week solving problems in an

environment where they can receive feedback on their work, such as from a Teaching Assistant

in weekly discussion time. PALs fill the gap by allowing the student to gain extra practice in a

structured problem solving environment whenever and wherever there is a computer with the

appropriate software and fonts available.

Information Design of Context-Rich Problems

In information design ―the power comes from the modes and strategies by which the

designer organizes it and offers visual, conceptual, and technological affordances to the material‖

(Lunenfeld 68).One of the strategies involved in my PAL was the use of a context-rich problem.

Context-rich problems are problems that connect the physics in a question to the real world. An

example of the difference between the two is:

Non-Context Rich Problem: Two submarines arrive at the same place at the same time.

They start out at the same time from positions equally distant from the rendezvous point, both

going in a straight line. The first submarine travels at an average velocity of 20 km/hr for the

first 500 km, 40 km/hr for the second 500 km, 30 km/hr for the next 500 km, and 50 km/hr for

the final 500 km. If the second travels at a constant velocity, what is its magnitude?

Context-Rich Problem: You are writing a short adventure story for English class. In

your story, two submarines on a secret mission need to arrive at a place in the middle of the

Atlantic Ocean at the same time. They start out at the same time from positions equally distant

from the rendezvous point. They travel at different velocities, but both go in a straight line. The

first submarine travels at an average velocity of 20 km/hr for the first 500 km, 40 km/hr for the

second 500 km, 30 km/hr for the next 500 km, and 50 km/hr for the final 500 km. In the plot, the

second submarine is required to travel at a constant velocity, so the captain needs to determine

the magnitude of that velocity.

This example was taken and adapted from page 3-14 of the University of Minnesota’s The

Competent Problem Solver for Introductory Physics, Calculus Version. The information design

theory behind these kinds of problems is that students will not only be more engaged in a

problem that comes out of an actual plausible situation instead of nothing, but also will be better

able to mentally connect the abstract physics concepts together when given a concrete real-world

framework to use as a guide.

Therefore, in order to use one of these context-rich problems in my PAL, Dr. Hsuand I

chose a problem with a Navy plane taking off from an aircraft carrier. The problem reads as:

The Navy wants a new airplane launcher for their aircraft carriers, and you are on the

design team. The launcher is effectively a large spring that pushes the plane for the first

5 meters of the 20 meter long runway. During that same time, the plane’s engines supply

a constant thrust of 5.4·104 N for the entire length of the runway. The 2000 kg planes

6

need to have a velocity of 45 m/s by the end of the runway. What should be the spring

constant for the launcher?

Here the context-rich environment of the problem forces the student to critically think through

what is being asked without jumping right in and assigning values to variables. It also asks the

student to determine what variable matches which quantity. The fact that m (mass) = 2000 kg, v

(velocity) = 45 m/s, d (distance that the spring pushes the plane) = 5 m, L (length of the runway)

= 20 m, and F (force) = 54000 N is not immediately apparent. Moreover, the student must know

that the spring constant is known as k where k is measured in N/m (Newtons per meter) or kg/s2

(kilograms per second squared), and where to look for the appropriate equations for this

situation.

Tutorial Programming

Another of the information design strategies involved in my PAL was using logical

positivism for the solution to the tutorial.Logical positivism applies reason to the external

physical world and says that real objective truth exists. Humans only need to observe and talk

about it in a correct manner in order to grasp it. As Peter Sedgwick in Descartes to Derrida: An

Introduction to European Philosophyputs it:

This approach argues that if a proposition cannot be validated by way of observation in a

manner whose standard is set by the example of the empirical sciences, then such a

proposition has no meaning (85).

Logical positivism’s emphasis on objective truth, empirical observation, and clear mathematical

based language matches the solution for my PAL since physics is the study of matter and energy.

Therefore, while many decisions about the tutorials were left to Dr. Hsu and me, the idea of a

correct solution to the problem asked was already objectively determined.

Question: What is the value of k, the spring constant, in this problem?

Answer: (using the system of the plane and the spring)

Solve using Conservation of Energy

Final Energy – Initial Energy = Energy Input – Energy Output

Ef –Ei = Ein - Eout

½mv2 - ½kd

2 = F ·L

(because Kinetic Energy = ½mv2, Spring Potential Energy = ½kd

2,

and Energy = Force · Distance)

- ½kd2 = F ·L - ½mv

2

½kd2 = ½mv

2– F ·L

kd2 = mv

2– 2FL

k = (mv2– 2FL)/d

2

When I began programming the PAL tutorial, I had to build the tutorial from scratch,

except for content libraries, shared fonts, and some aspects of the code borrowed from other

7

PALs. I used Macromedia Authorware 6.5 and then 7.0, which offers ―extensive content

creation tools with slick graphics and animations‖ (O’Sullivan 66) in order to build the tutorial. I

later made use of both Inspiration 6 (a brainstorming/outlining software program) and Adobe

Illustrator 8.0 (a vector graphics software program) in order to read the outlines Dr. Hsu sent me

and draw graphics for my PAL problem. But the vast majority of my work was done in

Authorware since it can ―create useful instructional material which might be used in conjunction

with a site that makes use of the communication possibilities of the World Wide Web‖

(O’Sullivan 66).

The Deliverable

The final deliverable for this project was a PAL tutorial that can be run on personal

computers equipped with the necessary software and fonts.

The nature of the PAL that I worked on followed this structure:

1. The PAL gives student the Navy problem and asks them to solve it on paper.

2. The PAL then asks student what their answer is and how confident they are

correct.

3. Depending on the student’s response and confidence, PAL either checks their

answer or helps the student find their mistake.

This structure is ―convenient from a navigational perspective since the content can be accessed in

a nonlinear fashion‖ (Babu et al. 584). Students may go back and forth through the program

depending on their individual needs and answer.

The following screenshots from the PAL tutorial also help to explain both the deliverable

and its structure:

8

The PAL title screen:

The problem description screen:

9

The enter answer screen; the PAL branches at this point based on the student’s answer.

If the student entered an answer, he or she is then asked how confident he or she is in it.

10

Based on their answer and response, he or she may be asked how to evaluate the answer.

The student’s answer is then checked for the correct units.

11

The student’s answer is then checked for functional dependencies of the variables.

If the student’s answer is correct on the first try, he or she receives this message:

12

If the student chooses ―I got stuck‖ on the enter answer screen or is incorrect at any point during

the evaluation, he or she is sent to the first help section:

If the student wants help, he or she is then asked about receiving help for each part:

13

If the student declines help, his or her answer is checked step-by-step:

Additional check screen:

14

The help screens are also accessed by incorrectly answering a check question:

Additionalhelp screen:

15

Once the check, help, or some combination of the two sections has been completed, the PAL

asks if the student would like to enter another answer or receive more help.

If he or she chooses help, he or she completes the second help and/or check section:

16

This also applies to the third helpsection:

The process repeats until the student enters the correct answer or after several attempts, is given

the correct answer by the PAL. This is the solution using the plane as the system:

17

Conclusion

As mentioned in the beginning of this paper, the world has entered an information age,

and ―the ability to solve problems in a variety of contexts is becoming increasingly important in

our rapidly changing technological society‖ (Hsu and Heller). Towards this end, my Plan B

design projectobjectives were to apply information design theory to computerized physics

tutorials, utilize physics educational theory, use a context-rich problem in accordance with

information design, program a tutorial, and present a deliverable.The PAL as detailed here is a

flexible tutorial that students can use to practice problem solving.In addition, the PAL’s role as

coach matches the expectations of students since people treat computers as sources. These PALs

could also be modified to work in other fields such as biology, chemistry, or even reading

education.

Overall, I have enjoyed the process of working on this project. I have learned many

different things, from how to use information design to guide the construction of a PAL to how

to use Authorware, Illustrator, and Inspiration. I also learned that traditional lecture physics

education can be improved through supplementation with PAL tutorials and context-rich

problems. I believe that the PAL has tremendous potential to help students in introductory

physics courses based on my own experiences as an undergraduate physics major. Had tutorials

like these been available during that time, I certainly would have taken advantage of them. I also

enjoyed the opportunity to put technology to use in an innovative way; as computers become

more and more indispensable to daily human life, quality information design becomes even more

important in order for people to get the most out of computers and other complicated technology.

Further Research

This PAL is one of six that Dr. Hsu will be utilizing in introductory physics courses and

will be usability tested by students this summer. Usability testing will not only allow the PALs

to be adjusted based on student input and experience but will also take advantage of features

already built into the PALs themselves. For instance, the PALs already keep track of how long it

takes students to click on objects, so this information can be utilized to see where students are

getting stuck, either due to the physics of the problem or something in the tutorial itself.

Were I to continue with this project, the next two steps would be to add additional

features to the PAL. The first would be student error tracking. The PAL would keep track of the

student’s progress through each part of the checking and helping sections and display this

information to the student at the end of the tutorial. This error tracking system would allow

students to see exactly which steps in the five step problem solving process they have the most

difficulty completing correctly. The second step would be to make the review menu more

interactive. Right now, this menu can only be accessed after completing each section, and it

would be more helpful for the student if it could be accessed immediately after completing a step

successfully. Finally, I would further refine the existing tutorial.

Works Cited:

Babu, S. V., I.I. Suni, and D. H. Rasmussen. ―Development of a CD-ROM in Thin Film

Technologies: Design, Usability Assessment, and Challenges.‖ Journal of

18

Engineering Education 87 (1998): 583-589.

Graham, Charles R., and Timothy N. Trick. ―Java Applets Enhance Learning in a

Freshman ECE Course.‖Journal of Engineering Education 87 (1998): 391-397.

Hsu, Leon. PALs: Simple cognitively-based computer tutorials for teaching scientific

thinking skills. University of Minnesota. 3 May 2005<http://www.pals.gen.umn.edu/>.

Hsu, Leon, and Kenneth Heller.―Computer Problem-Solving Coaches.‖ Personal

correspondence. 10 May 2005.

Heller, Kenneth and Patricia Heller.The Competent Problem Solver for Introductory

Physics, Calculus Version. University of MinnesotaSchool of Physics and

Astronomy.Ed. Julie Kehrwald.Boston: McGraw-Hill, 2000.

Kastman Breuch, Lee-Ann. ―Thinking Critically about Technological Literacy:

Developing a Framework to Guide Computer Pedagogy in Technical

Communication.‖Technical Communication Quarterly 11 (2002): 267-288.

Lunenfeld, Peter. ―Media design: new and improved without the new.‖New Media and

Society. 6 (2004): 65-70.

McDermott, Lillian Christie.―Millikan Lecture 1990: What we teach and what is

learned—Closing the gap.‖ American Journal of Physics 59 (1991): 301-315.

Milton-Benoit, John, Ian R. Grosse, Corrado Poli, and Beverly Park Woolf. ―The

Multimedia Finite Element Modeling and Analysis Tutor.‖Journal of

Engineering Education 87 (1998): 511-517.

O’Sullivan, Mary F. ―Worlds within Which We Teach: Issues for Designing World Wide

Web Course Material.‖Technical Communication Quarterly 8 (1999): 61-72.

Paterson, Kurtis G. ―Student Perceptions of Internet-Based Learning Tools in

Environmental Engineering Education.‖Journal of Engineering Education 88

(1999): 205-304.

Reif, Frederick, and Lisa A. Scott.―Teaching scientific thinking skills: Students and

computers coaching each other.‖ American Journal of Physics 67 (1999): 819-

831.2 May 2005

<http://www.gen.umn.edu/faculty_staff/hsu/pal/pdffiles/ajp.pdf>.

Richards, Anne R. ―Argument and Authority in the Visual Representations of Science.‖

Technical Communication Quarterly 12 (2003): 183-206.

Sedgwick, Peter. Descartes to Derrida: An Introduction to European Philosophy. Malden:

Blackwell, 2001.

19

Spiro, Rand J., Paul J. Feltovich, Michael J. Jacobson, and Richard L. Coulson.

"Cognitive Flexibility, Constructivism, and Hypertext: Random Access

Instruction for Advanced Knowledge Acquisition in Ill-Structured Domains.‖

Educational Technology 31 (1991): 24-33. 2 May 2005

<http://www.ilt.columbia.edu/publications/papers/Spiro.html>.

Sundar, S. Shyam, and Clifford Nass. ―Source Orientation in Human-Computer

Interaction: Programmer, Networker, or Independent Social Actor?‖

Communication Research 27 (2000): 683-703.

Van Heuvelen, Alan. ―Learning to think like a physicist: A review of research-based

instructional strategies.‖ American Journal of Physics 59 (1991): 891-897.