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October 1, 1995
Vol. 53
No. 2

Image Processing: A State-of-the-Art Way to Learn Science

An innovative technology that scientists use has come to the classroom, where it is significantly changing the face of teaching and learning.

Image processing done on a Macintosh computer doesn't beep if a student enters a wrong answer; nor does it chime if the answer is correct. This is because image processing isn't a standard computer-assisted instructional package, preprogrammed for some step-by-step learning pattern. Rather, it is the real thing—what scientists do at the cutting edge of research.
Scientists—or students—create images by scanning or photographing objects with a digital or video camera, a process that translates a picture into a matrix of dots, or digits. Virtually any set of measurements (light, temperature, x-rays, and so on) can be compiled into a rectangular array of numbers and then displayed on a computer screen as a photographic-quality image. With image processing, scientists—or students—can edit, analyze, and enhance these digital images to gain more information from the data. The methods they use can distinguish shades, colors, and relationships not visible to the human eye. For example, scientists use the technology to create digital images of the earth from interplanetary space probes; doctors, to manipulate images generated during CAT scans; and meteorologists, to create weather maps from satellite information.
Now students are using the same technology in classrooms around the country to learn science and mathematics.

Where the Idea Began

The Image Processing for Teaching project (IPT) began in 1989 in the Lunar and Planetary Laboratory at the University of Arizona. Richard Greenberg and Robert Strom, scientists familiar with digital image processing from spacecraft research, wanted to develop a usable, hands-on program that K–12 teachers could learn and bring back to their schools. They felt that the manipulation of images would be a more accessible way of teaching science and math concepts with technology than the many language-based tutorial programs—especially for students from diverse cultural backgrounds. Because NIH Image, the powerful research software used in the project, is in the public domain, the expense to school districts would be minimal, apart from computer purchase and teacher education. Subsequently, the project received a three-year development grant and a subsequent four-year dissemination grant from the National Science Foundation to pursue the project.
Nearly 2,000 teachers have taken part in Image Processing for Teaching project workshops. All receive a CD-ROM and a manual of image processing activities for use in the any science or mathematics classroom equipped with color Macintosh computers. Additional CD-ROMs in subject areas like physics and biology are available, with others under development.
To date, classroom teachers have developed more than 100 project activity units for K–12 students in physics, chemistry, biology, earth science, and mathematics. Each activity consists of a set of images that can be loaded on the computer, along with a guided pathway through analyses and manipulations of these data. In addition to NIH Image software, teachers and their students can access extensive data sets of imagery from biomedicine, planetary exploration, environmental science, and all areas of science.
Teachers give their students a series of digital images provided by the Image Processing for Teaching project (or students can generate their own images) on a particular subject, which they can observe, enhance, and magnify. Once students are familiar with the image set, they take measurements, do graphing, analyze data, and solve problems. Instructions that accompany the image sets guide students without limiting their exploration. In time and with practice, students learn to use their own judgment and to follow intuitions and hunches. Project materials encourage multiple solutions to messy real-world problems, much the way scientists working in astronomy, biomedicine, and other fields use data.
The project has almost unlimited expansion potential. Hundreds of thousands of images from federal research programs are available on CD-ROMs through the Internet, or from the student's own labwork—all of which can be used with NIH Image software. In addition to what's available in the public domain, students can create or capture their own images with video cameras and digitizers.

Image Processing in a High School

What are high school students doing with this technology? Gayle Wilson teaches computers and mathematics at Rio Grande High School in Albuquerque, New Mexico. Rio Grande has the largest number of Chapter 1 students of any high school in the city. Approximately 60 percent read below grade level, and about two-thirds of the freshmen do not graduate. Since she joined the project in 1992, Wilson has used image processing materials to improve her students' skills in math, science, technology, and communication. Her students range from sophomores to seniors, from learning disabled to gifted.
After going over the math and science concepts needed in the activities, Wilson says all she has to do is supervise her class. The students become the experts: When students have questions, I expect them to ask one another first, then the tutors [former students of Wilson's], and finally, if all else fails, come to me.
Wilson uses the flexibility of image processing to full advantage. Advanced students tackle original problems. For example, a skateboarder videotaped himself doing jumps, then, with his physics teacher's help, analyzed the forces involved in the jumps. Meanwhile, less advanced students modify project activities from the CD-ROM. Students work in pairs on these projects, developing their science, math, writing, and oral communication skills, as well as their critical thinking and teamwork competencies. Scanners, video cameras, the Internet, and digital still cameras are among the technological tools that students can use in conjunction with project activities.
When students get turned on to a problem-solving situation, they approach math and science with a more positive attitude—and sometimes, overcome major hurdles in the process. For example, Melanie, a student with a reading disorder and low motivation, perked up when she saw an image processing presentation by Wilson's students in her chemistry class. She asked Wilson to be admitted into the computer class because she liked being able to see what she was doing while problem solving. Melanie did well in the class, despite her reading difficulties, and her attendance has begun to improve as well.

From Learner to Teacher

In the first semester of a yearlong course with image processing at the center, Wilson takes her students through the training activities that come on the Image Processing for Teaching CD-ROM. Her students find these activities fun; hidden clues, mysteries, and other simple challenges help students learn the basics of image processing.
Second semester, they are ready to be leaders in an image processing environment. Wilson arranges with other math and science teachers in the same school for each of her students to teach an image processing activity to another class. Most of her students choose to teach in pairs. In introducing image processing to a class, they have to demonstrate the features of the software and explain how an image is data. They also get firsthand experience identifying the science and mathematics underlying the problem in the activity and then teaching these concepts.
Wilson's young teachers also learn a lot more than image processing when instructing a class of their peers. For example, in addition to patience and understanding, Benjamin Turrietta, a junior, learned that “not all people are as smart as they appear.” Although his students included the highest-achieving math students in the school, first-time use of image processing software was no easier for them than it was for basic math students.
Junior Malinda Gomez, who taught image processing to a basic math class, described how the activity itself got her students' attention: At first, they were playing around with the computers, drawing on the screens, and wouldn't really let my partner and I start the presentation. But after a while, they decided to listen. They were really interested and wanted to know how to do the activity. Malinda's teaching experience also taught her that “I can do anything I put my mind to.”

Image Processing in Junior High School

Junior high students also enjoy and excel at image processing. Loretta Milligan teaches physical science at Heizer Junior High in Hobbs, New Mexico. Some of her less academically successful students are the best image processing peer teachers. Teaching in rural New Mexico, Milligan finds that only a handful of her pupils come to school with basic computer skills. About 15 percent of her students are Spanish-only speaking.
Since 1991, she has been using image processing both to teach math and science and to show her students how the computer functions as a problem-solving tool. Typically, Milligan previews an activity provided by the Image Processing for Teaching materials development group. Next she works intensively with a couple of student pairs at the computers. Then she relies on the students to help one another.
Working cooperatively, Milligan's class completes on average five project activities a year with minimal teacher supervision. She engages the rest of the class in other activities while four or five students at a time work on the one computer in her room.
Another advantage of image processing is its visual basis, which Milligan says enables her students to bridge language barriers. Whenever possible, she pairs a Spanish-only speaking student with one who speaks both languages. Even when Spanish-only speaking and English-only speaking students are paired, they can communicate during an image processing activity by pointing and demonstrating, because project materials rely far less on language than other computerized tutorials do.

A Boost for Lower-Achieving Students

When she first joined the project, Milligan was concerned that lower-achieving students would not be able to learn how to use image processing from other students. It didn't take long to convince her otherwise.
David Stroud agrees. Stroud works with special education students in grades 3–5 at Naaba Ani Elementary School in Bloomfield, New Mexico. Though he is a language arts specialist, he uses the technology because its visual environment holds his students' interest and assists kids who have trouble expressing themselves in writing. In fact, his students became so proficient at image processing that they taught it to a gifted 5th grade class through the activity “Don't Bug Me.”
Stroud's students taught the 5th graders how to measure the size of a rove beetle using a scanned electron microscope image of a rove beetle and a scaling function that they had to learn to calibrate. They then measured and charted their data. Although some students panicked at the idea of teaching a class, once at the computer with the visiting students, Stroud's 3rd and 4th graders did a great job. He thinks that it's because they're not afraid of computers. They're willing to take chances, and as a result of all this experimentation, they begin to do things intuitively at the computer.

From Learner to Researcher

Ideally, in an Image Processing for Teaching environment, some students can rise to the highest level and do real science in the classroom. Jeff Lockwood, a physics teacher at Sahuaro High School in Tucson, Arizona, has such aspirations for his students. He designed and teaches an astronomy research class for students who are having difficulty in traditional classes. Believing that time constraints are what bedevil these students, he gives his students only one deadline: to complete their astronomy research projects by the end of the semester. As they work together to examine the surfaces of planets, they quickly learn, as anyone who's done research knows, that without cooperation, they will fail.
Lockwood's students formulate a hypothesis, organize and collect data, and then write up their results, as well as an abstract. Lockwood serves as facilitator and coach. Students may draw on the expertise of research scientists from the University of Arizona, who serve as advisors and mentors. In their most recent project, students classified and measured the diameters of small volcanic domes on the surface of Venus.
One of the most thrilling phases of the research took place when Lockwood's students traveled to Houston to give presentations at NASA's annual Lunar and Planetary Science Conference. There they explained and defended their research on Venus and Mars to dozens of practicing planetary astronomers. Their results were published in the proceedings of the conference.
Mike, a sophomore with what Lockwood called “an abysmal grade point average,” including failure in college algebra, entered the astronomy research class a few years ago. Although Mike liked computers, he hadn't found a way to apply them to his academic work. In Lockwood's class, Mike did nearly 10 times the work required by each student, classifying 2,000 volcanic edifices on Venus. Last year, he and a student in Vancouver, Washington, explored whether there are associations of small volcanic edifices with major geologic features on Venus. The two did all the work themselves, through e-mail, and presented their research at the conference in Houston.
According to Lockwood, Mike worked harder on his math than ever before, and retook and passed college algebra in high school. Last year Mike entered the University of Arizona, majoring in physics.

Success Stories

These are not isolated examples. Elementary, middle, and high school teachers participating in the Image Processing for Teaching project tell us that the technology is an ideal tool to encourage student discovery, promote a constructivist science or math experience, and adapt easily into their classrooms. Teachers applaud the fact that image processing is not a routine tutorial, a computerized textbook, or abstract lab with no connection to students' interest. A wide range of students, some not motivated in traditional classrooms, participate actively in the projects.
With image processing the computer becomes a tool to pose and answer questions about real-world phenomena. Just as no two researchers sequence their questions in the same manner, no two students using image processing in their K–12 science or math class will have the same experience. But all of them will learn what they could not possibly have learned from standard computer-assisted instruction—namely, how visualization techniques can help each learner make his or her own way through science and math.
End Notes

1 The grants support development of activities, teacher education, technical support, and an ongoing formative evaluation to ascertain the long-term value of image processing in science instruction

Jacqueline Raphael has been a contributor to Educational Leadership.

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