Flick, L., & Bell, R. (2000). Preparing tomorrow’s science teachers to use technology: Guidelines for Science educators. Contemporary Issues in Technology and Teacher Education [Online serial], 1 (1). Retrieved from https://www.citejournal.org/volume-1/issue-1-00/science/preparing-tomorrows-science-teachers-to-use-technology-guidelines-for-science-educators

Preparing Tomorrow’s Science Teachers to Use Technology: Guidelines for Science Educators

by Larry Flick, Oregon State University; & Randy Bell, University of Virginia

Science and technology education have enjoyed a meaningful
partnership across most of this century. The work of scientists
embraces an array of technologies, and major accomplishments in
science are often accompanied by sophisticated applications of
technology. As a result, a complete science education has, in
principle, involved a commitment to the inclusion of technology,
both as a tool for learning science content and processes and as a
topic of instruction in itself (American Association for the
Advancement of Science [AAAS], 1993; National Research Council
[NRC], 1996). These elements have traditionally been a part of
teacher education in secondary science.

Science education has generally involved teaching not only a
body of knowledge but also the processes and activities of
scientific work. This view has linked the scientific uses of
technology with hands-on experiences. The term “hands-on science”
was descriptive of the major curriculum reform projects of the
1960s and became a label for a revolution in teaching science
through the next two decades (Flick, 1993). So-called “hands-on
science” instruction impacted teacher education as new curricula
made its way into preservice courses. Teacher education was also
influenced by teaching methods, such as the learning cycle (Lawson,
Abraham, & Renner, 1989), based on theories of student learning
that implied the necessity of interacting with physical
materials.

The explosion of digital technology has created a revolution
similar to the “hands-on” movement of the 1960s. The flexibility,
speed, and storage capacity of contemporary desktop computers is
causing science educators to redefine the meaning of hands-on
experience and rethink the traditional process of teaching. The
challenge facing both science educators and science teacher
educators is to evaluate relevant applications for information
technologies in the science curriculum. At the same time,
instruction utilizing information technologies must reflect what is
known about the effectiveness of student-centered teaching and
learning.

The impact of digital technologies on science teacher education
is more pervasive than any curricular or instructional innovation
in the past. The impact can be felt on three fronts. First, as with
the hands-on science movement, digital technologies are changing
the ways teachers interact with students in the classroom.
Psychological theories (Borich & Tombari, 1997) based on the
importance of language to learning, the ways organizing and
relating information facilitates understanding, and the influence
of social factors in the classroom are all impacted by digital
technologies. Second, teacher education courses are not only
influenced by new K-12 curricula, they are also influenced by
instructional approaches, fueled by the National Science Education
Standards (NRC, 1996), that incorporate a variety of digital
technologies. Technological applications go beyond K-12 curriculum
to the delivery of college level content. For instance, faculty and
students explore web resources for educational statistics or
education-related reports and course resources.

Both of the major national reform documents are on the web
(AAAS, 1993, at http://www.project2061.org//

and NRC, 1996, at http://www.nap.edu/catalog/4962.html
). Third, faculty and students alike are interacting in new ways
afforded by digital technologies. Faculty and students have virtual
discussions related to course content, advice, and counseling in a
wide variety of times and places through via email, cell phones,
pagers, and features of the web. Faculty and students now produce
documents with more information and in far more diverse formats as
a result of desktop publishing, online libraries and databases, and
file transfer capabilities. The pervasiveness of digital
technologies motivates a thorough review of technological impacts
on curriculum and instruction in science teacher education.

The following technology guidelines for science education are
intended to provide assistance in designing instruction and to
guide applications of technology to support science teacher
education reform, as framed by Benchmarks for Scientific
Literacy
(AAAS, 1993) and the National Science Education
Standards
(NRC, 1996). The Association for the Education of
Teachers in Science (AETS) joins other national associations of
teacher educators in mathematics, English, and social studies
through the National Technology Leadership Initiative to guide
thoughtful consideration for how best to use contemporary
technologies to enhance subject-matter focused educational goals in
the preparation of teachers.

Proposed Guidelines for Using Technology in the Preparation
of Science Teachers

  1. Technology should be introduced in the context of
    science content.

  2. Technology should address worthwhile science with
    appropriate pedagogy.

  3. Technology instruction in science should take
    advantage of the unique features of technology.

  4. Technology should make scientific views more
    accessible.

  5. Technology instruction should develop students’
    understanding of the relationship between technology and
    science.

1.
Technology should be introduced in the context of science
content.

The first principle is centered on the notion that technology
should not be taught merely for its own sake in the preparation of
science teachers. Features of technology should be introduced and
illustrated in the context of meaningful science. In other words,
technology should be presented as a means, not an end. This
principle has implications for teaching science content, as well as
for science teacher preparation. For example, preservice teachers
in science education programs are often required to take a generic
educational technology course taught by an instructional technology
expert. In this class, the preservice teachers are supposed to
develop a variety of technology-related skills, including the
ability to use word processors, presentation software,
spreadsheets, and the Internet. Preservice teachers typically are
then left to apply their newly developed technology skills to
teaching content in their subject area.

This approach is backwards. Teaching a set of technology or
software-based skills and then trying to find scientific topics for
which they might be useful obscures the purpose of learning and
using technology in the science classroom—to enhance the
learning of science. Furthermore, this approach can make science
appear to be an afterthought. Preservice teachers are, in essence,
left to develop contrived activities that integrate a set of
decontextualized instructional technology skills into the context
of their classroom.

If the purpose of technology in science teaching is to enhance
science teaching and learning (rather than for the technology’s
sake alone), a different approach is necessary. For example,
teacher educators at Oregon State University and the University of
Virginia are collaborating on a project designed to teach Internet
and spreadsheet skills to preservice science and mathematics
teachers in the context of an exploration of the El Niño
weather phenomenon. Considering its impact on local weather and
climate, El Niño holds both interest and relevance to the
average student. Certainly, it has provided meteorologists and
climatologists with a powerful framework for interpreting and
predicting weather patterns.

Recent media coverage of the impacts of El Niño has made
it a familiar scientific topic for students of all ages. However,
fact and fiction became confused in the public’s eye as the media
began blaming El Niño for all sorts of natural and social
events. This hype resulted in a variety of misunderstandings about
the phenomenon. Thus, while most students are familiar with the
concept, few can confidently discuss its causes and impacts.
Preservice teachers may be challenged, for example, to use Internet
resources to locate accurate information concerning the causes and
effects of El Niño (see Appendix A ,
“What Is El Niño?” Background Resources).

Such an activity supports the development of skills typically
addressed in educational technology courses, including using the
Internet to locate relevant information and discriminating between
useful and non-useful information. It also sets the stage for
discussion of the advantages and concerns of student use of the
Internet. Where it differs from the traditional approach is that
these lessons are situated in the context of learning science.

2.
Technology should address worthwhile science with appropriate
pedagogy.

Much has been learned about effective science instruction since
the emergence of science education as a field in the 1950s.
Teaching science for understanding, instead of for rote
memorization, requires students to be active participants who are
engaged in asking questions, observing and inferring, collecting
and interpreting data, and drawing conclusions (AAAS, 1993; Bybee,
1997; Goodrum, 1987; Matthews, 1994; NRC, 1996; Tobin, Treagust,
& Frasier, 1988). In essence, teacher education courses should
emphasize methods for providing students with opportunities to
do science, in addition to learning the facts and concepts
of science.

Content-based activities using technology should be used in the
process of modeling effective science teaching for new teachers.
Thus, appropriate uses of technology should enhance the learning of
worthwhile science concepts and process skills, as well as reflect
the nature of science. This guideline and Guideline 1 are based on
the same principle that science should be learned in a meaningful
context. Additional work has been done related to this important
guideline, and Appendix B contains a
more extended review.

Furthermore, activities involving technology should make
appropriate connections to student experiences and promote
student-centered, inquiry-based learning. Activities should support
sound scientific curricular goals and should not be developed
merely because technology makes them possible. Indeed, the use of
technology in science teaching should support and facilitate
conceptual development, process skills, and habits of mind that
make up scientific literacy, as described by the National
Science Education Standards
(NRC, 1996) and Project 2061
(AAAS, 1993).

It is clear from the Standards (NRC, 1996) that “student
inquiry in the science classroom encompasses a range of activities”
(p. 33) that are scaffolded by the teacher. Teachers scaffold
student engagement in inquiry by providing opportunities for,
observing, collecting data, reflecting on their work, analyzing
events or objects, collaborating with teacher and peers,
formulating questions, devising procedures, deciding how to
organize and represent data, and testing the reliability of
knowledge they have generated.

Technological support for inquiry is not the implementation of
one application but a bundle of applications (Germann & Sasse,
1997). Consequently, teacher education courses must make
appropriate pedagogy visible through the complex interactions among
students and classroom technologies. Technology can support student
investigations and direct collection and presentation of data
through real-time data collection via microcomputer based
probeware. PowerPoint or spreadsheet functions support
presentations that demonstrate the relationship between hypothesis
and data. Further manipulations of the display can help students
formulate conclusions based on data. For example, by examining
various graphical formats, students can be guided to think about
implications by looking for trends, identifying categories, or
making comparisons. Through microteaching environments and
supervised experience, new teachers should become aware of how
applications of technology help students share and collaborate in
building their knowledge of science and scientific inquiry.

The previously described El Niño project is an example of
a project in a methods course for modeling the blending of
worthwhile science with appropriate pedagogy. Searching the Web to
locate information about the El Niño phenomenon is a typical
way the Internet is used in K-12 and higher education classrooms.
New teachers learn what science has to say about the concept of El
Niño, as well as how to use the Internet to locate current
information. However, if teaching stops here, teachers do not
develop the appropriate pedagogy of scaffolding student
participation in scientific inquiry. Without the follow-through to
include inquiry, such an approach may be criticized for conveying
the products of scientific investigation without due attention to
the processes of how scientific knowledge is produced, and the
tentative nature of the knowledge itself. As Schwab commented in
1962, science is too commonly taught as

…a
nearly unmitigated rhetoric of conclusions in which the current and
temporary constructions of scientific knowledge are conveyed as
empirical, literal, and irrevocable truths (in which students are
asked) to accept the tentative as certain, the doubtful as
undoubted, by making no mention of reasons or evidence for what it
asserts. (p. 24)

Such criticism, while commonly applied to traditional curricular
materials, is just as appropriate to common usage of the Internet
in schools today.

An extension of the El Niño activity that also
incorporates inquiry would start with students asking questions
(see Appendix C , El Niño Project). Most
students are curious to know whether El Niño actually
impacted local weather—one aspect of this project in which
students also find relevancy. It turns out that historical and
current weather data are available on the web, and students can use
these data to support an answer to their question. They will not
find the answer handed to them on a silver platter, however. Once
they locate the data, they will find they need to organize and
manipulate it so they can reach and support a conclusion.

Throughout this student-centered process, new teachers see
science taught in a manner consistent with the way scientists do
their work. They ask a scientific question and devise a method for
answering the question. They collect and organize data. They reach
conclusions based on that data, and they share their conclusions
with their peers. Furthermore, by discussing the details of the
data and the various approaches to analyzing the data, students
have opportunities to consider the tentative nature of scientific
knowledge.

While seeing science presented in an authentic context, new
teachers also learn to use web-based databases, import and export
data sets, use spreadsheets to calculate summary statistics and
construct tables and graphs, and use word processing and/or
presentation software. Thus a bundle of applications (Germann &
Sasse, 1997) is learned in the context of appropriate inquiry-based
science instruction.

Modeling the use of technologies in the context of learning
science is critical in teacher education for another reason. A
common maxim in teacher preparation is that “teachers teach the way
they were taught.” Experience has shown that few preservice
teachers are able to make the intellectual leap between learning to
use technology out of context in their teacher preparation programs
and using it in the context of teaching science in the classroom.
Teachers need to see specific examples of how technology can
enhance science instruction in their content areas before they can
hope to appropriately integrate technology in their own
instruction.

3. Technology instruction in science should take advantage of
the unique features of technology.

Technology modeled in science education courses should take
advantage of the capabilities of technology and extend instruction
beyond or significantly enhance what can be done without
technology. New teachers should experience technology as a means of
helping students explore topics in more depth and in more
interactive ways. An evaluation study of the Technology-Enhanced
Secondary Science Instruction (TESSI) project (Pedretti,
Mayer-Smith, & Woodrow, 1998) documented the impact of
technologies integrated at many levels. A preservice methods course
could critically examine the content and outcomes of this study as
a way of applying unique features of technology for learning
science. For example, students in TESSI classrooms ran virtual labs
and demonstrations using the technology to slow down the action and
repeat complex activity. Students were able to rerun virtual force
and motion demonstrations and follow how each step was represented
on the screen in graphical form. Students in the methods course
could discuss how well these examples utilize unique technological
features.

Studies have clearly documented the value of technological
capabilities for enhancing the presentation of complex or abstract
content, such as computer visualization techniques (Baxter, 1995;
Lewis, Stern, & Linn 1993). However, a concurrent concern is
that novelty and sophistication of modern technologies might
distract or even mislead students in understanding science concepts
that are the target of instruction. Discussion in the methods class
could continue with a critical look at technological applications
to assess whether their capabilities supported or detracted from
learning opportunities. An objective of the TESSI project was to
document the roles and perspectives of learners, teachers, and
researchers participating in the project (Pedretti et al., 1998).
One hundred forty-four students were either interviewed or surveyed
after completing one school year of physics or general science in
the project. Classroom instruction involved student use of (a)
simulations to extend understanding of physics concepts; (b) laser
discs, video tape, and CDs; (c) real-time data collection and
graphical analysis tools associated with computer-interfaced probes
and sensors; (d) computer analysis of digitized video; (e)
presentation software; and (f) interactive student assessment
software. A goal of instructional design was to employ technology
to enhance the teacher’s role in the classroom, not to replace it.
Discussion of this study and others like it helps establish this
central goal that should be used in the assessment of instructional
design and implementation in teacher education courses.

None of the students interviewed felt that computer experiences
should entirely replace the “doing” and “seeing” of actual
laboratory or in-class demonstrations. They were clear in stating
that computer technologies and hands-on lab experiences play a
complementary role, so that the actual event under study, such as a
wave propagating down a spring, can be perceived as a concrete
event then analyzed by appropriate simulations. Cognizant of
balancing technological enhancements with checks of student
understanding, the teachers designed study guides that kept
students mindful of instructional goals, integrated technology with
teacher-direct instruction, and prompted student self-evaluation
through small-group reviews and conferences with a teacher.

Another criteria for assessing instructional design tasks in
methods courses is that taking advantage of technology does not
mean using technology to teach the same scientific topics in
fundamentally the same ways as they are taught without technology.
Such applications belie the usefulness of technology. Students in
the Pedretti et al. (1998) study took tests on computers. The
software was able to score and give general feedback more quickly
than a teacher-scored test. More sophisticated, experimental
software is being designed to provide structured guidance as
students analyze and interpret data (Cavalli-Sforze, Weiner, &
Lesgold, 1994, http://advlearn.lrdc.pitt.edu/
). Through an Argument Representation Environment, the prototype
software helps students construct and propose theories and guides
individuals or groups in designing is experimental software
highlights another issue for science methods instructors: Different
types of software will require different kinds of support for new
teachers. For instance, course activities and discussion should
guide new teacher understanding of the processes of coding and
layering of data in ArcView in order to appreciate the scientific
meaning in ArcView graphics (see http://www.esri.com/industries/k-12/k-12.html

). In taking advantage of the real-time graphing capabilities
using probeware and computers, researchers have found that college
students preparing to be elementary teachers must be more carefully
taught how to interpret graphs (Svec, Boone, & Olmer,
1995).

Using technology to perform tasks that are just as easily or
even more effectively carried out without technology may actually
be a hindrance to learning. Such uses of technology may convince
teachers and administrators that preparing teachers to use
technology is not worth the extra effort and expense when, in fact,
the opposite may be true.

4. Technology should make scientific views more
accessible.

Many scientifically accepted ideas are difficult for students to
understand due to their complexity, abstract nature, and/or
contrariness to common sense and experience. As Wolpert (1992)
aptly commented,

I would
almost contend that if something fits in with common sense it
almost certainly isn’t science. The reason again, is that the way
in which the universe works is not the way in which common sense
works: the two are not congruent. (p.11)

A large body of literature concerning misconceptions supports
the notion that learning science is often neither straightforward
nor consistent with the conceptions students typically construct
from everyday experiences (Minstrell, 1982; Novick & Nussbaum,
1981; Songer & Mintzes, 1994; Wandersee, Mintzes, & Novak,
1994; among many others). Whether described as misconceptions or
simply non-intuitive ideas in science (Wolpert, 1992), teachers are
faced with concepts that pose pedagogical conundrums. New teachers
may not even recognize that these instructional puzzles exist
unless they are made explicit through their teacher education
course work. Developing the skills for making scientific views more
accessible is an example of what Shulman (1987) called developing
“pedagogical content knowledge.” The profession of teaching,
Shulman argued, may be distinguished from other disciplines by the
knowledge that teachers develop linking knowledge of content with
knowledge of instruction, knowledge of learners, and knowledge of
curriculum. Developing new teacher awareness of the pedagogical
content knowledge domain and how to add to that knowledge is a
central goal of science teacher education.

Appropriate educational technologies have the potential to make
scientific concepts more accessible through visualization,
modeling, and multiple representations. Secondary teachers may have
experienced examples of these technologies in college science
courses. Elementary teachers may have had limited experiences in
college science. Teacher education course work has the task of
providing experiences and linking previous experience with
technologies whose purpose it is to provide representations of
concepts that are difficult to represent in everyday experience.
For example, kinetic molecular theory, an abstract set of concepts
central to the disciplines of physics and chemistry, may be easier
for students to understand if they can see and manipulate
representations of molecules operating under a variety of
conditions. Williamson and Abraham (1995) found support for this in
their investigation into the effectiveness of atomic and molecular
behavior simulators in a college chemistry course. In this study,
atomic/molecular simulations were integrated into the instruction
of two groups of students, while a third group received no computer
animation treatment. The two simulation treatment groups achieved
about one half standard deviation higher scores on assessments of
their understandings of the particulate nature of chemical
reactions. The authors concluded that the simulations increased
conceptual understanding by helping students form their own dynamic
mental models.

 Science education courses
should challenge teachers to analyze their teaching experience for
pedagogical conundrums, the concepts that are inherently difficult
to present to students and/or difficult for students to understand.
Once identified, the pedagogical task is to select appropriate
teaching strategies and representations of content to address these
topics. Digital technologies are an important category of options
for approaching these conundrums. For example, a familiar but
abstract science concept taught in secondary physical science
classes is the Doppler effect. The Doppler effect is commonly
defined as the change in frequency and pitch of a sound due to the
motion of either the sound source or the observer (see Video 1 ).

While the phenomenon is part of students’ everyday experiences,
its explanation is neither easily visualized nor commonly
understood. This difficulty stems from the invisible nature of
sound waves and the fact that traditional representations are
limited to static figures of the phenomenon, which by definition
involves movement.

 Computer simulations are
able to get past these limitations by simulating the sound waves
emitted by moving objects (see Video 2 ). Being able to see
representations of the sound waves emitted by moving objects
presents new opportunities for understanding by offering learners
multiple epresentations. Simulations also allow students to
manipulate various components, such as the speed of the object, the
speed of sound, and the frequency of the sound emitted by the
object. Such interaction encourages students to pose questions, try
out ideas, and draw conclusions (see Appendix D, Doppler Effect
Simulator and Activities).

Within the context of this type of example, new teachers should
be challenged to identify appropriate science pedagogy, as
described in Guideline 2.

An important consideration for all teachers when using
simulations as models for real phenomena is that, while simulations
can be powerful tools for learning science, students must not
mistake a simulation —meant to make a concept more
accessible—for the actual phenomenon. Students must
understand that a sophisticated computer graphic for molecular
motion, the Doppler effect, or any other phenomenon is still only a
model. Therefore, it is critical that preservice teachers be given
explicit opportunities to reflect on the nature of scientific
models and the role they play in the construction of scientific
knowledge, as well as encouragement and examples for how to address
these concepts in their own instruction (Bell, Lederman, &
Abd-El-Khalick, in press).

5. Technology instruction should develop understanding of the
relationship between technology and science.

Despite Western society’s heavy dependence on technology, few
teachers actually understand how technology is used in science. Nor
can they adequately describe the relationship between science and
technology. For example, one of the most common definitions of
technology used in schools today is “applied science” (Spector
& Lederman, 1990). While this familiar definition seems
reasonable at first glance, it ignores the fact that the history of
technology actually precedes that of Western science (Kranzberg,
1984) and that the relationship between science and technology is
reciprocal (AAAS, 1989). A more appropriate understanding of
technology for inclusion in teacher education courses is the
concept of technology as knowledge (not necessarily scientific
knowledge) applied to manipulate the natural world and emphasizes
the interactions between science and technology.

Using technologies in learning science provides opportunities
for demonstrating to new teachers the reciprocal relationship
between science and technology. Extrapolating from technology
applications for classrooms, new teachers can develop an
appreciation for how advances in science drive technology, and in
turn, how scientific knowledge drives new technologies.

Computer modeling of chemical structures leads to the
development of new materials with numerous uses. In reciprocal
fashion, high quality computer displays and faster computers make
possible types of scientific work impossible before such advances.
This leads to new ideas in science.

It is important to realize, however, that such understandings
are unlikely to be learned implicitly through using technology
alone. Rather, new teachers must be encouraged to reflect on
science and technology as they use technology to learn and teach
science., When using microscopes, whether the traditional optical
microscopes or the newer digital versions (see http://IntelPlay.com/home.htm
), teachers can be encouraged to think about how science influenced
the development of the microscope and the microscope, in turn,
influenced the progress of science. For example, the modern
compound microscope began as a technological development in the
field of optics in the 17th century. The instrument created a
sensation as early researchers, including Antoni van Leeuwenhock
and Robert Hooke, used it to uncover previously unknown
microstructure and microorganisms. This new scientific knowledge
led to new questions. For example, where do these microorganisms
come from? How do they reproduce? How do they gain sustenance? Such
questions, in conjunction with advances in optics, led to the
development of ever more powerful microscopes, which in turn,
became the vehicles for even more impressive discoveries. The cycle
continues to modern times with the invention of the electron
microscope and its impact on knowledge in the fields of medicine
and microbiology.

 Microteaching and supervised
practicum experiences should help preservice teachers recognize
that when students are making new discoveries of their own with
microscopes, they are well positioned to understand the reciprocal
relationship between technology and science. For instance,
fifth-grade students who are recording video footage of
microorganisms with the digital microscope can easily appreciate
the concept that new discoveries lead to new questions, as their
curiosity is piqued by their observations of the miniature world
that exists in a drop of pond water (see Video 3 ).

Furthermore, students can see how their questions fuel the
desire for new technologies, as they experience the limitations of
the microscopes available to them. A skilled teacher can exploit
the resulting “teachable moment” to encourage students to consider
how their experiences with the technology relate to those of real
scientists.

Technologies are simultaneously tools for learning about science
and examples of the application of knowledge to solve human
problems . When new teachers understand technologies
as a means of solving human problems, they can be made aware that
technologies come with risks as well as benefits. This feature of
technology should be represented in instructional objectives and be
visible in lesson plans and other relevant assignments. For
example, efficiencies of storage and retrieval of information have
the associated risks of losing large quantities of data in damaged
disks, system malfunctions, or incorrect actions on the part of
users. Uses of technology in teacher education courses can
emphasize how technologies produce trade-offs, for instance,
between gaining more sources of knowledge through the Internet and
CDs while at the same time creating a greater expenditure of time
and effort sorting appropriate, high quality information.

Summary

The draft guidelines in this paper have been synthesized from
knowledge of research, K-12 teaching experience, and teaching
experience in science teacher education with technology. They have
been drafted to be consistent with national reform goals in science
education by examining how these goals might be furthered through
the use of modern technologies. Thoughtful reflection on and
discussion about these guidelines by a broad range of educators,
based on knowledge of diverse areas of educational research and a
broad base of teaching experiences, will deepen understanding of
how technologies can improve science teaching and the preparation
of new teachers of science. Future revisions of the guidelines will
reflect the ongoing discussion in Contemporary Issues in
Technology and Teacher Education
that this article is intended
to generate.

References

American Association for the Advancement of Science. (1989).
Project 2061: Science for all Americans. Washington, DC:
Author.

American Association for the Advancement of Science. (1993).
Benchmarks for science literacy . New York: Oxford
University Press: Author.

Baxter, G. P. (1995). Using computer simulations to assess
hands-on science learning. Journal of Science Education and
Technology, 4
, 21-27.

Bell, R. L., Lederman, N. G., & Abd-El-Khalick, F. (in
press). Developing and acting upon one’s conception of the nature
of science: A follow-up study. Journal of Research in Science
Teaching.

Borich, B. D., & Tombari, M. L. (1997). Educational
psychology: A contemporary approach. New York: Longman.

Bybee, R.W. (1997). Achieving scientific literacy: From
purposes to practices
. Portsmouth, NH: Heineman.

Cavalli-Sforza, V., Weiner, A. W., & Lesgold, A. M. (1994).
Software support for students engaging in scientific activity and
scientific controversy. Science Education, 78 , 577-599.

de La Beaujardiere, J., Cavallo, J., Hasler, F., Mitchell, H.,
O’Handley, C., Shiri, R., & White, R. (1997). The GLOBE
visualization project: Using WWW in the Classroom. Journal of
Science Education and Technology, 6
, 15-22.

Fisher, B. W. (1997). Computer modeling for thinking about and
controlling variables. School Science Review, 79 ,
87-90.

Flick, L. B. (1989). “Probing” temperature and heat. The
Computing Teacher, 17
(2), 15-19. Reprinted in the Fourth
Annual Conference Issue 1990-1991.

Flick, L. B. (1993). The meanings of hands-on science.
Journal of Science Teacher Education, 4 (1), 1-8. Also
reprinted in Rezba, R. (1994). Readings for teaching science in
elementary and middle schools
. Dubuque, IA: Kendall/Hunt
Publishing Company.

Germann, P., & Sasse, C. M. (1997). Variations in concerns
and attitudes of science teachers in an educational technology
development program. Journal of Computers in Mathematics and
Science Teaching, 16
, 405-423.

Goodrum, D. (1987). Exemplary teaching in upper primary science
classes. In K. Tobin & B.J. Fraser (Eds.), Exemplary
practice in science and mathematics teaching
. Perth: Curtin
University of Technology.

Kranzberg, M. (1984). The wedding of science and technology: A
very modern marriage. Technology & Science . Davidson
College, NC, 27-37.

Lawson, A. E., Abraham, M. R., & Renner, J. N. (1989). A
theory of instruction. National Association for Research in
Science Teaching Monograph
(No. 1).

Lewis, E. L., Stern, J. L., & Linn, M. C. (1993). The effect
of computer simulations on introductory thermodynamics
understanding. Educational Technology, 33, 45-58.

Marx, R. W., Blumenfeld, P. C., Krajcik, J. S., & Soloway,
E., 1997). Enacting project-based science. The Elementary School
Journal, 97
, 431-458.

Matthews, M. R. (1994 ). Science teaching: The role of
history and philosophy of science.
New York: Routledge.

Minstrell, J. (1982). Explaining the “at rest” condition of an
object. Physics Teacher, 20 , 10-14.

National Research Council. (1996). National science education
standards
. Washington, D.C.: Author.

Novick, S., & Nussbaum, J. (1981). Pupils’ understanding of
the particulate nature of matter: A cross-age study. Science
Education, 65
, 187-196.

Palincsar, A. S. (1986). The role of dialogue in providing
scaffolding instruction. Educational Psychologist, 21 ,
73-98.

Pedretti, E., Woodrow, J., & Mayer-Smith, J. (1998).
Technology, text, and talk: Students’ perspectives on teaching and
learning in a technology-enhanced secondary science classroom.
Science Education, 82 , 569-589

Rogers, L. (1997). New data-logging tools—New
investigations. School Science Review, 79 , 61-68.

Svec, M. T., Boone, W. J., & Olmer, C. (1995). Changes in
preservice elementary teachers physics course. Journal of
Science Teacher Education, 6
, 79-88.

Sabelli, N. (1992, April). Sharing multiple complementary
representations in teaching
. Paper presented at the meeting of
the American Educational Research Association, San Francisco.

Schwab, J. (1962). The teaching of science as enquiry. In The
teaching of science
(pp. 1-103). Cambridge, MA: Harvard
University Press.

Shulman, L. S. (1987). Knowledge and teaching: Foundations of
the new reform. Harvard Educational Review, 57 , 1-22.

Spector, B., & Lederman, N.G. (1990). Science and
technology as human values
. Dubuque, IA: Kendall/Hunt.

Songer, C. & Mintzes, J. (1994). Understanding cellular
respiration: An analysis of conceptual change in college biology.
Journal of Research in Science Teaching, 31 , 621-637.

Thornton, R. K. (1987). Tools for scientific
thinking—Microcomputer-based laboratories for physics
teaching. Physics Education, 22 , 230-238.

Thornton, R. K., & Sokoloff, D. R. (1990). Learning motion
concepts using real-time microcomputer-based laboratory tools.
American Journal of Physics, 58 , 858-867.

Tobin, K., Treagust, D.F., & Frasier, B.J. (1988). An
investigation of exemplary biology teaching. American Biology
Teacher, 50
, 142-147.

Wandersee, J.H., Mintzes, J.J, Novak, J.D. (1994). Research on
alternative conceptions in science. In D.L. Gabel (Ed.),
Handbook of Research on Science Teaching and Learning . New
York: Macmillan.

Williamson, V., & Abraham, M. (1995). The effects of
computer animation on the particulate mental models of college
chemistry students. Journal of Research in Science Teaching,
32
, 521-534.

Wolpert, L. (1992). The unnatural nature of science. Why
science does not make (common) sense
. Cambridge, MA: Harvard
University Press.

APPENDIX A
WHAT IS EL NIÑO? BACKGROUND
RESOURCES

What is El Niño?

Try to answer this question using the Internet. Here are some
web sites that might help.

http://www.elnino.com/
This site briefly describes El Niño in laymen’s
terms.

http://www.pmel.noaa.gov/toga-tao/el-nino-story.html
This site provides more detailed and technical discussion of the
El Niño phenomenon. It includes some very good graphics.

http://www.macontelegraph.com/special/nino/html/nino1mov.htm
This site combines some basic information with a neat
downloadable movie clip with sound.

http://members.aol.com/windgusts/ElNino.html
This is another site that includes basic discussion of the El
Niño phenomenon.

APPENDIX B

ADDITIONAL EXAMPLES OF USING TECHNOLOGY TO
ADDRESS WORTHWHILE SCIENCE WITH APPROPRIATE PEDAGOGY

Using Technology to Promote Relevancy

Technology-augmented activities should help students perceive
the relevance of science to their personal experiences. Students
are exposed to sophisticated computer representations of weather
data every day through television weather reports. These reports
use integrated displays of cloud patterns, moisture levels, wind,
barometric pressure, and temperature. Often these representations
go unappreciated or misunderstood. The Internet and desktop
computers can help students see the meaning of these data by
connecting students with sources of real data representing weather
in their region of the country. Further programs offer
opportunities for students to contribute data as part of a larger
picture of national and global climate. The Global Learning and
Observations to Benefit the Environment (GLOBE) project is a
multinational program of science education (de La Beaujardiere et
al., 1997). Students enter weather data, and graphical tools allow
them to manipulate how the data from the region, country, or world
is represented (see http://www.globe.gov/ ). The
instructional sequence and outcomes might be outlined as follows:
(a) student experience is translated into weather measurements; (b)
students enter measurements into a worldwide Internet data base;
(c) students manipulate data and forge meaning under the guidance
of a classroom teacher; and (d) student understanding and
appreciation of personal experiences are enhanced.

The use of motion detectors to graph the position of a student
walking toward or away from the detector helps students experience
an analytical expression of a common experience. Even at the
college level, this type of interactive learning tool enhances
student understanding of velocity and acceleration (Svec, Boone,
& Olmer, 1995; Thornton, 1987; Thornton & Sokoloff, 1990).
Other devices record temperature in real time and represent it on
the screen as a thermometer or temperature versus time graph.
Classroom work demonstrates that students are better able to
separate personal sensations of “hot” and “cold” from physical
measurements of temperature (Flick, 1989).

Numerous school science topics can be used to model and resolve
situations arising in the physical, biological, environmental,
social, and managerial sciences. The use of extended student
projects formed the basis for Project-Based Science (PBS) that
focused on student-designed problems and investigations (Marx,
Blumenfeld, Krajcik, & Soloway, 1997). PBS made extensive use
of software for accessing information and data manipulation to
support student work on complex problems. Teachers guided students
in identifying problems and carrying out procedures for addressing
those problems. By focusing on the personal significance of
classroom tasks, teachers, supported by computer tools for
accessing relevant information, helped students connect science
concepts to their own lives.

Using Technology to Promote Understanding of Scientific
Inquiry

A national consensus has established the central role of inquiry
in science education. “Scientific inquiry is at the heart of
science and science learning” (NRC, 1996, p.15). Use of technology
should support student understanding of scientific inquiry and how
scientific investigations are conceived and conducted. Helping
students understand the meaning behind a scientific approach to
problem solving requires developing student skills with forms of
scientific thinking. To accomplish this task, teachers must provide
instructional scaffolding to support student thinking (while
remaining aware of developmental constraints (Palincsar,

1986). Teachers must also be mindful of the limited experience
students have in systematically thinking through problems. Computer
tools are beginning to offer support for this type of complex
instruction. A case study of a teacher proficient with a computer
modeling program documented development of student thinking skills
necessary for controlling variables (Fisher, 1997). The computer
model allowed students to isolate and control variables in ways
that may be obscured in direct, lab experience, due to
uncontrollable variables or the untrained observational skills of
students. Another case study showed how software for logging and
manipulating data encouraged students to reflect on the meaning of
data and choose appropriate representations (Rogers, 1997). In the
hands of skilled teachers, modern information technologies can be
tools for focusing instruction and providing students with an
interactive, educational environment for thinking about and doing
scientific investigations.

One of the more difficult aspects of getting students engaged in
scientific inquiry is posing questions that are meaningful to
students yet open to scientific inquiry. Texts often lead students
to think of inquiry as an algorithm, the mythic “scientific
method.” This is especially true if teachers do not mediate text
presentations with supplementary instruction about scientific
inquiry. If students cannot see the creative, problem-solving side
of scientific work, they often do not believe scientific
investigations are meaningful. Addressing this important
epistemological question was the goal of a project to develop a
software environment for scaffolding scientific activity.
Researchers at the Learning Research and Development Center at the
University of Pittsburgh have taken as their initial focus the
development of tools for displaying and evaluating scientific
controversies (Cavalli-Sforza, Weiner, & Lesgold, 1994). The
software design effort is developing tools for the graphical
display of arguments, evidence, and supporting knowledge. For
example, interacting through a system of menus and graphical
representations, students can seek evidence in support of a
particular theory for the extinction of dinosaurs. The software
will advise students of particular data, such as the fossil record,
and state why it supports or does not support a particular theory.
The computer scaffolding acts as resource for students and an
instructional tool for the teacher in developing student
understanding of the value of theories in posing scientific
questions and the role of theories in establishing the meaning of
data.

The Internet offers more free-form opportunities for teachers to
develop student thinking skills that support inquiry. The display
of earthquake data on a world map can be used to guide students to
question why geographic locations form the patterns they do.
Through discussion that develops understanding of how the data are
gathered and represented in the visual database, students can be
prompted to design investigations that lead them to seek related
data, such as occurrences of volcanic activity (see, for example,
http://volcano.und.nodak.edu/
and http://gldss7.cr.usgs.gov/neis/bulletin/bulletin.html

.

Using Technology to Promote Student-Centered Learning

A major goal of learning in science is to develop reflective,
independent learning in students. The focus on science as inquiry
implies taking contemporary science education beyond teaching just
the science processes of the 1960s and 70s. “Inquiry is a step
beyond science as process. The Standards combine the use of
processes of science and scientific knowledge as they use
scientific reasoning and critical thinking” (NRC, 1996, p. 105). In
a complete science education, students learn relevant bodies of
knowledge, ways to conduct scientific inquiry, and the nature of
scientific work. To accomplish this complex task, teachers must
promote learning cognitive and social skills that make instruction
more student centered.

The TESSI project (Pedretti et al., 1998) integrated the use of
multiple technologies. Teachers in the project found that relevant
and meaningful use of these technologies required a “departure from
the teacher-centered format which characterizes much of traditional
science instruction” (p. 573). Observations of classroom
instruction revealed high levels of teacher interactions with
students, including (a) teachers consulting in small group work,
(b) teachers directing the use of resources, and (c) purposeful
instruction within the context of larger student projects. More
important were specific efforts by the teachers to design

instruction that would put the technologies in the hands of
students. As a result of access to relevant technologies, revised
curricula that took advantage of these technologies, and
instructional designs in which technology played important but
supporting role, student interviews and surveys suggested that
students gained a stronger sense of purpose and self-direction in
their classroom work. Students also found traditional materials,
such as texts, laboratory work, demonstrations, problem sets, and
field work, valuable supplements to classroom learning. Technology
was a catalyst for change, but the energy and direction of change
came from the teachers working with students in new ways that put
students at the center of the instructional process.

A majority of students interviewed in the TESSI study (Pedretti
et al., 1998) commented about learning and learning how to learn.
For example, students noted the importance of talking with other
students.

“The teacher always says we have to `learn to learn,’ it’s a
little weird but I guess it’s true because we’re learning how to
learn on our own with the different materials that are available,
like through other people. (Shelley, Physics 11, Fall 1995)” (p.
585)

In addition to reflecting on the importance of talk in learning
science, 52% of students surveyed or interviewed mentioned the
structure of instruction and teachers’ expressed intentions, and
how these factors affected their approach to learning. These
students became aware of and acted on teacher goals for learning
responsibility, independence, self-reliance, and problem-solving.
These results may in part be attributed to capable students in high
school science classes and to a large investment in new
technologies that has temporarily focused attention on these
classrooms. The validity of educational innovations is always
learned over time. TESSI is obtaining these results after 6 years
duration of the project and the participation of over 3,000
students. These effects are long after initial novelty has worn off
and after a broad cross-section of students have experienced the
program.

APPENDIX C
EL NIÑO PROJECT

How can I tell if the 1997-98 El Niño has
impacted a particular region?

1. First, go to the Regional Climate Center to locate data for
the region you are interested in.

http://www.wrcc.dri.edu/rcc.html

2. Next, find the average monthly temperature and precipitation
data. The SERC lists monthly averages for entire states.
http://water.dnr.state.sc.us/climate/sercc/region_avg_info.html

Here’s a site where you can find monthly precipitation data for
select cities in several states:
http://www.ncdc.noaa.gov/ol/climate/online/coop-precip.htm
l

The Western Regional Climate Center is much better for our
purposes, but only includes data for the western states.
· Go to http://www.wrcc.dri.edu/
rcc.html.
This can be linked to from the Regional Climate
Center site shown in step one.
· Select Western U.S. Climate Historical Summaries http://www.wrcc.dri.edu/climsum.html

· Select the state for which you want data
· Select the individual station for which you want data

· Scroll down to Temperature in the left frame and select
“Average” under “Monthly

Temperature Listing”

· Scroll down to Precipitation in the left frame and
select “Monthly Totals” under “Monthly Precipitation Listings”

3. Import the two data lists into Microsoft Excel (or a
comparable spreadsheet). Since data sets on the Web are typically
not saved in Excel format, you will usually find it necessary to
first save the data as a *.txt file before you try to open it in
Excel. Upon opening the data set in Excel, the program will provide
a “Data Import Wizard,” which will help you properly format the
data in a few easy steps.

4. Calculate a separate average for the temperature data for
each month. Students will often want to compare the average
temperature data for each month of the entire data set to that of
the El Nino year. This is a good time to discuss the differences
between an average temperature and a normal temperature range. When
comparing data that vary, it is important that the comparison
reflect the variability of the data. Therefore, comparing means
alone is not very useful. A better approach is to use some measure
of variability about the mean, such as standard deviation, if the
data reflect a normal distribution. If the data distribution is
significantly skewed, it may be more appropriate to use upper and
lower quartile ranges about the median. The important point is that
the comparison reflects the variability of the data, so that we are
comparing a typical temperature range to the El Nino year.
So, for example, if the data are normally distributed, you could
calculate the standard deviation for each month. Next, create a row
that calculates the Average + One Standard Deviation, and a
separate row that calculates the Average -One Standard
Deviation.

Hint: You might want to click on the
 button a couple times to decrease the number of decimal
places.

5. Graph three lines on a single graph:

· Average + 1 standard deviation

· Average -1 standard deviation
· El Niño year in question (make two graphs, one for
1997 and one for 1998)
For example, your 1997 graph might look like this:

6. Where the El Niño year line falls outside your 1
standard deviation boundaries, you can say that the El Niño
temperatures for that month were warmer (or colder) than about 70%
of your data. This may be enough to conclude that El Niño
had an effect on that particular region, or you may decide that
stronger evidence is necessary. For instance, you may decide that
the El Niño temperature must lie at least 2 standard
deviations from the mean before you are willing to consider the
difference significant). This is a good time to have a discussion
about what it might take for scientists to conclude that El
Niño had an effect.


APPENDIX
D

DOPPLER EFFECT SIMULATOR AND
ACTIVITIES


Suggested Activities for Exploring the Doppler
Effect Simulator at ExploreScience.com

Use the following activity suggestions with the
ExploreScience Web site
(http://explorescience.com/activities/Activity_page.cfm?ActivityID=45)

1. Set the “Speed of Object” slider to “0.”

  • Compare the wavelengths (distance between
    individual waves) as you adjust the “frequency” slider to a high
    number (say, 4) and a low number (say, 2). Which would produce a
    higher pitch?

  • Adjust the “frequency” slider back to 0.3
    and press the “Start” button. Notice the pattern of waves that is
    produced. Would you describe it as regular on all sides or skewed?
    Would the pitch of the sound produced by the object be equivalent
    on all sides? Repeat with different frequencies (but keep the speed
    of object at 0).

2. Set the “Speed of Object” slider to “0.6” and
press the “Start” button.

  • Notice the pattern of waves produced as
    the object moves across the screen. Would you describe it as
    regular on all sides or skewed?

  • Would the pitch of the sound produced by
    the object be equivalent on all sides? How does this compare to
    when the object was stationary?

  • How would the pitch of the sound emitted
    by the object change if it were approaching you? How would it
    change if it were moving away?

  • Relate the motion of the object to the
    change in pitch an observer experiences as the object approaches
    and passes by. Why does the pitch change occur (think of the motion
    of the object in relation to the motion of the sound waves it
    emits)? Would an observer inside the car hear the change in pitch?
    Why or why not?

3. Other things to try:

  • Notice what happens to the sound waves
    preceding the object as you adjust its speed closer and closer to
    the speed of sound (1.0). Is the Doppler Effect most pronounced
    when the speed of the object is near to that of sound, or when it
    is much less than the speed of sound? Why?

  • What do you think will happen to the sound
    waves preceding the object when you set the speed of the object
    equal to the speed of sound? Try it and see! The object is
    traveling at the same rate as the waves emitted in front of the
    object, causing the waves to “pile up.” This piling effect produces
    what is commonly referred to as the sound barrier.

  • What pattern of waves do you predict when
    you increase the speed of the object to higher than the speed of
    sound? Again, try it and see. Now, the object is actually
    outrunning its own waves. The v-shaped “wake” of sound waves
    traveling behind the object produces a sonic boom when they reach
    an observer. What do you think an observer traveling inside the
    object would hear?

Contact information

Larry Flick
Department of Science and Math Education
239 Weniger Hall
Oregon StateUniversity
Corvallis, OR 97331
flickl@ucs.orst.edu