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Park, J. C., & Slykhuis, D. A. (2006). Guest Editorial: Technology proficiencies in science
teacher education. Contemporary Issues in Technology and Teacher Education [Online serial], 6(2). Available: http://www.citejournal.org/vol6/iss2/science/article1.cfm
Guest Editorial: Technology Proficiencies in Science
Teacher Education
John C. Park
North Carolina State University
Technology Committee, Association for Science Teacher Education
ASTE Representative to the National Technology Leadership Coalition
David A. Slykhuis
James Madison University
Technology Committee, Association for Science Teacher Education
ASTE Asst. Representative to the National Technology Leadership Coalition
The mission of the Association for Science Teacher
Education (ASTE) is to promote leadership in and support for those involved
in the professional development of teachers of science. The organization originated
in the late 1920s through visits and meetings to discuss science teacher education
standards among faculty members of teacher education institutions in the northeast
region of the United States. Eventually, the “Conference on the Education
of Science Teachers” became a national organization. In 1953, the members
of the conference voted to change the name to the Association for the Education
of Teachers in Science (AETS). The name was revised in 2004 to the present ASTE.
The leadership of the organization met in 1993 to establish the present mission
statement and to create goal statements to guide the organization into the future.
One of these goal statements was “to produce and promote guidelines for
improving science teacher education.” In 2002, an ad hoc technology committee
was created to provide leadership through technology-based workshops and sessions
and to assist with the selection of the new National Technology Leadership Initiative
award for science education. This committee consisted of professionals who integrated
instructional technology in their teaching, developed new technologies or methodologies
implementing technology, and researched the effects of technology in the learning
and teaching of science and science education.
Although there had been previous examples of creating guidelines for instructional
technology for teacher education (Flick & Bell, 2000; ISTE, 2002), the ASTE
had no guidelines or position papers specifically for technology in science
teacher education. In 2004, the ASTE Technology Committee co-chairs, Alec M.
Bodzin and John C. Park, began working with the committee to establish a position
statement on technology in science teacher education on behalf of the organization.
In 2005, the ASTE board of directors revised and approved the document (see
appendix). They also changed the status of the Technology
Committee from ad hoc to standing committee.
Using technology as a tool for science inquiry by pupils in the school science
classroom and laboratory is the central theme of the ASTE position statement.
This is congruent with the National Science Education Standards (National
Research Council [NRC], 1996), which emphasized that science should be learned
using inquiry methods. The methodologies related to using technology tools in
school science discussed in the ASTE document can be categorized into four broad
groups: (a) Gathering scientific information; (b) data collection and analysis
by pupils; (c) creating and using models of scientific phenomena; and (d) communication.
Gathering Scientific Information
Thirty years ago, when a pupil needed to find information about a topic in
science, they might have been able to find it in reference books in the classroom,
or they could go to the library and search through encyclopedias or journals.
Today, in the Internet Age when computers are easily accessed, when more information
is needed about a specific topic, most people use a search engine on the Web.
This is no less true for pupils in school science. If pupils need to find out
about the specifics of a certain element, they can search the Web to find WebElements™,
and with a click of a button they can find interesting facts about any element
from the periodic table. If they want to locate information about the North
America robin, a search would probably turn up the Cornell Lab of Ornithology,
where abundant information about many species of birds could be easily reviewed.
Locating resources is much easier than it has been in the past due to the use
of information technology. However, learners must evaluate the resources they
discover. Most anyone can publish a Web page, whether the information found
in the site is factual or not. Preservice science teachers need the skills to
evaluate the validity of Web sites.
Bodzin (2005) created an instrument (Web-based Inquiry for Learning Science
– WBI) that guides teachers to identify Web-based inquiry activities for
learning science. The WBI directs the teachers to classify those activities
along a continuum from learner-directed to materials-directed for each of the
five essential features of inquiry (NRC, 2000). Instruments of this type help
preservice science teachers develop the evaluation skills necessary to select
appropriate Web sites for inquiry activities in the classroom.
Scientific information can also be collected and distributed via the Web to
enhance science learning. Although there are numerous projects on the Web that
allow pupils and scientists to collaborate in the data collection and analyzation
process, one such project is the GLOBE project (http://www.globe.gov).
The GLOBE project can be used by elementary through secondary pupils to learn
about ecology and biology. Bombaugh, Sparrow, and Mal (2003) illustrated how
this process can help foster inquiry learning in a high school biology class.
The use of secondary data is highly desirable when the pupils are unable to
measure and collect the data themselves. However, whenever possible the national
standards promote student collection of data for subsequent analysis.
Data Collection and Analysis by Pupils
The science curriculum projects of the late 1950s and 1960s focused upon posing
problems for pupil investigations. The curriculum provided additional media
and materials to aid pupil understanding of the concepts being studied. Science
process skills were emphasized, and the school science laboratory was the center
of learning. The National Science Education Standards (National Research
Council, 1996) embraced the same philosophy. The science teaching standards
include the following:
- Teaching Standard A: Teachers of science plan an inquiry-based science program
for their students.
- Teaching Standard B: Teachers of science guide and facilitate learning.
- Teaching Standard D: Teachers of science design and manage learning environments
that provide students with the time, space, and resources needed for learning
science.
- Teaching Standard E: Teachers of science develop communities of science
learners that reflect the intellectual rigor of scientific inquiry and the
attitudes and social values conducive to science learning.
Data can be collected from a variety of sources, measurements can be made from
events that happen within the classroom, quantitative and qualitative data can
be measured or observed from still or moving images, and data can be “mined”
from the Web that pupils can analyze. The next few sections discuss methodology
for collecting this data through images, graphics, and probeware.
Scientific Visualization
The teaching of school science has a history of invention and use of instructional
technology. A review of early school science textbooks reveals an extensive
use of representative and analytical drawings and photographs. Early projection
devices, called “magic lanterns,” projected photographic images
developed on glass plates. Soon after motion picture cameras and projectors
were invented, science teachers were using moving picture technology in their
classrooms. Before the advent of talking-pictures, societies promoting visual
education encouraged the use of both still and moving images in all course subjects.
Early science teachers wanted to “fix” the images that pupils were
viewing or drawing onto the pupils’ minds, much as chemicals fix the photographic
image onto film.
From that early history, the importance of the use of images in science education
was never disputed. Whether the image is on a glass plate and is projected on
the wall in a science classroom in 1905, or the sequence of images is viewed
in a QuickTime™ movie on the Internet in 2005, the science teacher needs
to emphasize the power of keen observation skills.
Media that display scientific visualizations consist of two main types: Images
of actual objects (photographs); or graphics of objects, graphs, or other representations
of ideas or data. For example, a photograph of common table salt can be used
to show the color and general cubic shape of the salt grains. An electron microscope
may produce an image of the surface of the salt crystal; however, the orientation
of the particles that make up the salt crystal would most likely be shown in
a graphic, with spheres representing the sodium and chloride ions in a specific
pattern. A pupil could watch a movie of a salt crystal slowly dissolving in
water, or the pupil could watch an animation of the molecular bombardment by
the water molecules on the crystal, and subsequent dynamic distribution of the
ions amongst water molecules. The different visualizations of the same phenomena
yield different understandings about what is happening.
Linn (2003) reported that visualizations of abstract phenomena are most useful.
For example, complex data sets can be made into visualizations that describe
weather patterns, molecular structures, heat flow, and geologic structures.
She warned, however, that some representations can either mislead pupils or
reinforce intuitive ideas. For example, pupils attributed features to individual
molecules that are actually attributed to the aggregate of molecules such as
color, viscosity, or structure after interacting with molecular visualizations.
Sandvoss et al. (2003) described the development of the Common Molecules graphics
collection. This is a Web-based resource of interactive 3-D representations
of molecules. These molecular representations can be viewed as wire models,
ball and stick models, or space filling models. Pupils can click and drag on
the images to view the molecules from various perspectives. There are options
to view them using special glasses that produce the anaglyph 3D effect.
Image Analysis
Geographic Information Systems technology is a tool that empowers pupils to
engage in real-life scenarios while they identify problems, hypothesize, collect
data, develop procedures, and produce workable results that they communicate
to others (Ramirez & Althouse, 1995). Research by Baker (2002) included
eighth-grade Earth science pupils who studied local air quality indicators using
GIS. The GIS pupils showed a modest improvement in their integration of science
process skills, particularly data analysis (geographic and mathematical) activities.
Hagevik (2003) found that using GIS may aid pupils in constructing concepts
and in promoting understanding of environmental content, problem solving, experimental
design, and data analysis and in communicating findings to others.
The video technology of 2005 enables pupils to analyze motion electronically.
Using a digital video camera on a tripod, video editing software, and video
analysis software, pupils can shoot, edit, and analyze one- or two-dimensional
motion.
Suppose a pupil desires to analyze the motion of a toy “pull-back”
car. The pupil sets up the event on a table where the motion will be perpendicular
to the line between the video camera and the event. Included in the scene is
an object of known length that is the same distance from the camera as the motion
event. The pupil starts the video camera and begins the motion event; once recorded,
the digital information can be transferred to a video-editing program where
only the most salient motion is kept. The pupil creates a title page that gives
pertinent information regarding the event, such as the title of the event, the
creators of the video, and the mass of the pull-back car. The edited video is
saved as a QuickTime movie. The analysis software is opened and the movie is
imported into the software. With a click of a few buttons, the movie is scaled
to the desired size, the reference length in the movie is calibrated, and then
the pupil places a point on the front bumper of the car. The movie advances
to the next frame for another point. This process continues until the pupil
completes each frame in the video. Since the computer has stored the frame rate
of the video, and the calibrated distance from one point to the next in each
succeeding frame, the computer can compute distance, velocity, and acceleration
during the motion of the object. Having the mass of the car stored in the computer
memory, the net force acting on the car can be calculated at regular intervals
of the video.
Another motion analysis technique would be to create a “stop-motion”
animation movie. Instead of creating motion and videotaping the event, the pupil
would create individual frames of an object with slight variation of position
between subsequent frames. Knowing the distance the object is moved, and the
frame rate used in assembling the movie, the object would be seen traveling
at a specific rate. See Park and Bell (2005) for specific details on the creation
and use of stop-motion animation in physical science activities.
Probeware and Analysis Software
Probeware is the term describing the use of transducers that change measured
physical quantities into electrical quantities that can be interpreted by microprocessors.
These transducers react to changes in physical environments such as temperature,
pressure, force, or pH. Most transducers, or probes, connect to interfaces that
are, in turn, connected to microcomputers, calculators, or palm devices. A calibrated
device can be interpreted by the microprocessor, and the data can be displayed
in tabular or graphic form. The transducer, interface, microprocessor, and software
can be collectively referred to as probeware. For examples of the wide variety
of probeware available, check Vernier Software and Technology (http://www.vernier.com/)
and PASCO (http://www.pasco.com/), both of
which market many of the common probeware systems to schools.
The first study of probeware with children occurred in 1982 by Tinker and Barclay.
Tinker reported that this was the “first indication of the power of kinesthetic
real-time interactions to lead to understandings of abstract representations”
(Tinker, 2000, p. 7). In the same study, the short exposure of pupils to the
apparatus helped them to have an intuitive understanding of decimal numbers.
Mokros and Tinker (1987) later found that if pupils walked back and forth in
front of a motion detector while they were watching the graph of their motion
they could quickly learn to interpret position graphs.
In that same year, Brassell (1987) reported that the simultaneous display of
the real-time data resulted in significant learning, whereas a delayed display
of the data did not. The use of the displayed data to encourage pupil learning
was confirmed in a study by Russell, Lucas, and McRobbie (2003). They ascertained
that “students used the display, almost exclusively, as representing the
experimental phenomena or task problem” (p. 225), “the nature of
the display was supportive of a deep approach to learning” (p. 229), “students
critically evaluated the appearance of the graphic display” (p. 230),
and “the kinematics graphic display supported students’ working
memory” (p. 234).
The use of probeware in itself is not the “magic pill” for learning
in science education. Tailored designs of data collection and representation
technology are required for best results. Linn and Hsi (2000) reported that
after a series of eight iterations of changes in a 12-week thermodynamics curriculum,
using real-time data collection resulted in a 400% increase in pupil understanding
of the differences between heat and temperature. This research led to a new
framework called scaffolded knowledge integration, which offers principles of
experimental design for learning science and practices that promote knowledge
integration (Linn, 2003).
Laboratory activities using probeware are also not inherently inquiry activities,
as the probeware could be used in “cookbook” fashion. Royuk and
Brooks (2003), however, found that when probeware was designed to be used in
an inquiry-based manner learning was increased compared to traditional cookbook
labs in a college physics class. Slykhuis (2004) demonstrated that inquiry-based
curriculum that incorporates the use of probeware could be effectively delivered
over the Web to high school physics pupils.
The power of probeware is real-time data collection. However there is only
one time-based activity where the pupils are looking at the collected data as
the exploration continues: using the motion detector while walking, trying to
match pre-existing graphs. For most other explorations, the user begins the
data collection, turns his/her attention to the event to watch it to completion,
and then turns back to the computer to see the results. The next generation
of probeware merges visualization with analysis. Vernier Software and Technology’s
Logger Pro has the capability to synchronize the collected data and resulting
graph with a movie of the event. If a digital video captured the event as the
data is being collected with the probe, the resulting digital video can by synched
to the data. Pupils can scroll across the graph and view the movie simultaneously,
stopping and starting, or replaying critical regions of the graph to see exactly
what is happening in the event during interesting points on the graph.
Atar (2003) questioned high school AP chemistry pupils as to the strengths
and weaknesses of using probeware. The pupils reported they enjoyed and valued
the probeware activities, and over 90% expressed a desire to complete more in
the future. Among the few frustrations expressed by some pupils was a sense
of detachment from the event as the data were collected by the computer and
a struggle to be aware of the scale of the computer-generated graphs.
Creating and Using Models of Scientific Phenomena
Data collection and pattern recognition are essential components for the predictive
power of the scientific method. Pupils can take data collected from an investigation
and use tool software to investigate the relationships among variables. For
example, a pupil can use probeware to collect data on an object in free fall.
Using data analysis software, the pupil can explore the relationship between
position and time using a curve-fitting option. After discovering that the quadratic
equation is the best fit for the data, the pupil applies meaning to the variables
in the equations, and one of the fundamental kinematic equations is discovered.
This mathematical model can then be used to predict distances objects travel
in free fall for a given amount of time. This is one aspect of modeling: pupil
generated models.
Clement (2000) stated that part of scientific investigation is creating, testing,
and revising models. Further, Hestenes (1987) suggested that mathematical modeling
of the physical world should be the central theme of physics instruction. Hestenes
defined a model as a representation of structure in a physical system and/or
its properties. Using this idea, models can be mathematical or physical representations.
Once a model is created, it can be simulated. Simulations can be computational,
graphical, or a combination of both. Those who operate the simulation are able
to change variables in the model and view the results. An example of a graphical
simulation with a hidden mathematics framework is a solar eclipse simulation
found on the NC State Science Junction Web site (http://www.ncsu.edu/sciencejunction/depot/simulate/eclipse98/visualize.html).
Pupils can explore this simulation by selecting two locations from which to
view the 1998 total solar eclipse. After observing the simulation, pupils find
patterns in what is observed. An example of a graphic model that does not use
factual mathematical modeling of the event nor uses proper scaling is also found
on the Science Junction Web site (http://www.ncsu.edu/sciencejunction/station/gameroom/react/index.html).
The intent of this simulation is to emulate conditions necessary for a reaction
to occur: molecules must collide, collide with appropriate energy, and collide
with correct molecular orientation. A factual, mathematically correct simulation
is not necessary to demonstrate the conditions for a reaction.
Stieff and Wilensky (2003) used chemistry simulation software that allowed
pupils to explore how atomic/molecular microlevel changes result in macrolevel
changes. The results suggested that pupils who interacted with the software
tended to move away from memorized answers and toward conceptual questions and
attempted to answer with more reasoning and justification. Williams, Chen, and
Seaton (2003) examined the effectiveness of haptics-augmented computer simulations
with sixth-grade pupils. Inexpensive commercially available joysticks with haptic
feedback were paired with online simulations of simple machines. The preliminary
results suggested that the pupils thought the devices were effective. The pupils
reported enjoying the activities with minimal or no technical difficulties in
their use nor the navigation of the sites.
Simulation software can be used to teach traditionally hard to reach pupil
groups. Huppert, Lomask, and Lazarowitz (2002) studied the effect of computer
simulation software dealing with the growth of microorganisms on high school
biology pupils. The research included 181 pupils in two groups, one with the
simulation software, lecture and lab activities, and one with traditional lecture
and lab activities. Results suggested significant gains for the treatment groups
over the control group for the concrete and transitional operational learners,
regardless of gender. There was no difference between the groups with formal
operational pupils.
Since simulations are often highly visually dependant, Yang, Andre, and Greenbowe
(2003) studied the effect on the use of animations in a college chemistry course.
Over 400 students were given a visualization pre-test, in an effort to determine
if animations were more or less effective for those with higher visual-spatial
abilities. Animations resulted in increased achievement on the post-test on
the chemistry concepts. There was some ambiguity as to whether students with
higher visual-spatial ability were able to benefit more from the animations.
Communication
The National Science Education Standards, Teaching Standard E, begins,
“Teachers of science develop communities of science learners…”
(NRC, 1996, p. 45). It is understood that the “glue” that keeps
the communities together is communication. Internet-based communication tools
include email, lists, forums, blogs, wikis, and Web sites. Recent research has
clarified the contributions of collaborations and discussions as relates to
science learning.
Most studies stated that having the tools themselves are not enough to establish
a well-developed network of peers. There must be a structure to the development
of the community, a common goal, or a common problem to solve. Scardamalia and
Bereiter (1992) developed a series of prompts to guide contributions to promote
evidence-based discussions. Bodzin and Park (2000) required preservice science
teacher participants to place a forum posting to the Critical Incidents in the
Science Classroom topic on their Web forum. Critical incidents are defined as
an event that confronts teachers and makes them decide on a course of action
that involves some kind of explanation of the scientific enterprise.
Other forms of communications that classroom teachers have implemented with
their pupils is to require the pupils to communicate the result of their explorations
using slideware presentations, or by creating a Web site of their work. Boxie
and Maring (2002) reported the results of a successful project with preservice
science teachers and eighth-grade pupils. Working through the Web, the pupils
collaborated on completing a science investigation and writing project. Both
sets of pupils reported the benefits of this method of communication.
Future Directions
The ASTE position statement on Technology in Science Teacher Education encompasses
a broad spectrum of technology use. However, research on the pupil use of the
technologies has not kept pace with development of the technology. Perhaps researchers
are more interested in researching the latest new invention instead of implementing
extended research on the technologies that are evolving and maturing. For example,
one technology that shows a great deal of promise is the synchronized movie
analysis of data using probeware. If the real-time data collection using probeware
makes a difference in pupil understanding of science concepts, being able to
study the data with synchronized movies extends this idea to a higher level.
Yet, since probeware has been available for over 20 years, it may not have the
appeal for research as the latest “gizmo” might have.
Scientific visualization has been accepted as a means of instruction in school
science with little research on how students use images. With newer research
capabilities using eye-tracking, more studies could occur related to what and
how students view when interacting with either a still or moving image. Are
the students focused on the critical features of an image, or are they distracted
by what is unimportant? Can student experiences using visual technology be tailored
to enhance their spatial abilities?
As the technology becomes smaller and less expensive with more capabilities,
how will this enhance our quest for student inquiry? When video cameras are
reduced to the size of a dime and can transmit the image wirelessly over greater
distances, how will science teachers use this technology? And does this technology
assist those students who are physically challenged, or does the technology
broaden the opportunity gap? It is our hope that we not only research the capabilities
of new technologies, but also to continue to research the effect of the older
technologies that have matured in the past few decades.
References
Atar, H. Y. (2002, March). Chemistry pupils’ challenges in using
MBL’s in science laboratories. Paper presented at the Association
of Educators for Teachers in Science, Charlotte, NC.
Baker, T. R. (2002). The effects of geographic information system (GIS)
technologies on students' attitudes, self-efficacy,and achievement in middle
school science classrooms. Unpublished doctoral dissertation. University
of Kansas, Lawrence.
Bombaugh, R., Sparrow, E., & Mal, T. (2003). Using GLOBE plant phenology
protocols to meet the “National Science Education Standards.” American
Biology Teacher, 65(4), 279-285.
Bodzin, A. (2005). Implementing web-based scientific inquiry in preservice
science methods courses. ContemporaryIssues in Technology and Teacher Education.
Retrieved May 12, 2006, from
http://www.citejournal.org/vol5/iss1/general/article1.cfm
Bodzin, A. M., & Park, J. C. (2000). Dialogue patterns of preservice science
teachers using asychronous computermediated communications on the World Wide
Web. Journal of Computers in Mathematics and Science Teaching, 19(2),
161-194.
Boxie, P., &Maring, G. H. (2002). Using Web-based activities to enhance
writing in science: The dynamic earth project. Teacher Educator, 38(2),
99-111.
Brassel, H. (1987). The effect of real-time laboratory graphing on learning
graphic representations of distance and velocity. Journal of Research in
Science Teaching, 24(4), 385-395.
Clement, J. (2000). Model-based learning as a key research area for science
education. International Journal of Science Education, 22(9), 1041-1053.
Flick, L., & Bell, R. (2000). Preparing tomorrow's science teachers to
use technology: Guidelines for science educators. Contemporary Issues in
Technology and Teacher Education, 1(1), 39-60.
Hagevik, R. A. (2003). The effects of online science instruction using
geographic information systems to foster inquiry learning of teachers and middle
school science students. Unpublished doctoral dissertation, North Carolina
State University, Raleigh.
Hestenes, D. (1987). Toward a modeling theory of physics instruction. American
Journal of Physics, 55(5), 440-454.
Huppert, J., Lomask, S. M., & Lazarowitz, R. (2002). Computer simulations
in the high school: Students’ cognitive stages, science process skills
and academic achievement in microbiology. International Journal of Science
Education, 24(8), 803-821.
International Society for Technology in Education. (2002). National educational
technology standards for teachers. Eugene OR: Author
Linn, M. C. (2003). Technology and science education: Starting points, research
programs, and trends.
International Journal of Science Education, 25(6), 727-758.
Linn, M. C. & Hsi, S. (2000). Computers, teachers, peers: Science learning
partners. Mahwah NJ: Lawrence Erlbaum Associates.
Mokros, J., & Tinker, R. (1987). The impact of microcomputer-based labs
on children’s ability to interpret graphs. Journal of Research in
Science Teaching, 24(4) 369-383.
National Research Council. (2000). Inquiry and the national science education
standards: A guide for teaching and learning. Washington, DC: National
Academy Press.
National Research Council. (1996). National science education standards.
Washington DC: National Academy Press
Park, J. C., & Bell, R. L. (2005). Digital images in the science classroom.
In G. L. Bull& L. Bell (Eds.), Teaching with digital images: Acquire,
analyze, create, communicate (pp. 65-100). Eugene OR: International Society
for Technology in Education.
Ramirez, M., & Althouse, P. (1995). Fresh thinking: GIS in environmental
education. T.H.E. Journal, 23, 87-91.
Royuk, B., & Brooks, D. W. (2003) Cookbook procedures in MBL physics exercises.
Journal of Science Education and Technology, 12(3), 317-324.
Russell, D. W., Lucas, K. B., & McRobbie, C. J. (2003). The role of the
microcomputer-based laboratory display in supporting the construction of new
understandings in kinematics. Research in Science Education, 33(2),
217-243.
Sandvoss, L. M., Harwood, W. S., Korkmaz, Alk Bollinger, J. C., Huffman, J.
C., & Huffman, J. N. (2003).
Common molecules: Bringing research and teaching together through an online
collection. Journal of Science Education and Technology, 12(3), 277-284.
Scardmalia, M., & Bereiter, C. (1992). A knowledge building architecture
for computer supported learning. In E. De Corte, M. C. Linn, H. Mandl, &
L. Verschaffel (Eds.), Computer-based learning environments and problem
solving. Berlin: Springer-Verlag.
Slykhuis, D. A. (2004). The efficacy of World Wide Web-mediated microcomputer-based
laboratory activities in the high school physics classroom. Unpublished
doctoral dissertation, North Carolina State University, Raleigh.
Stieff, M., & Wilensky, U. (2003). Connected chemistry—Incorporating
interactive simulations into the chemistry classroom. Journal of Science
Education and Technology, 12(3), 285-302.
Tinker, R. (2000). A history of probeware. Retrieved May 12, 2006,
from the Stanford University MakingSENS Web site: http://makingsens.stanford.edu/pubs/AHistoryOfProbeware.pdf
Williams, R. L., II, Chen, M.-Y., & Seaton, J. M. (2003). Haptics-augmented
simple-machine educational tools. Journal of Science Education and Technology,
12(1), 1-12.
Yang, E., Andre, T., & Greenbowe, T. J. (2003). Spatial ability and the
impact of visualization/animation on learning electrochemistry. International
Journal of Science Education, 25(3), 329-349.
Author Note:
This editorial was originally posted on the Web site for the Society for Information
Technology and Teacher Education, 2006 (http://site.aace.org/pubs/foresite/ScienceEducation.pdf).
The original version has been edited for publication in CITE Journal.
John C. Park
Department of Mathematics, Science, and Technology Education
North Carolina State University, USA
email: john_park@ncsu.edu
David A. Slykhuis
Department of Middle, Secondary, and Mathematics Education
James Madison University, USA
email: slykhuda@jmu.edu
Appendix
ASTE Position Statement on the Technology in Science Teacher
Education
Approved July 2005
Technology-integrated materials when used appropriately can enhance science
teaching and learning. It is therefore the position of the Association for Science
Teacher Education that the qualified science teacher educator should possess
a strong knowledge base in understanding how implementing technology in science
curricular contexts may be used to promote the teaching and learning of science.
Technologies such as Web-based resources, real-time data collection with probeware,
simulations, Geographic Information Systems, and real-time video-conferencing
offer science teachers new opportunities for creating learning environments
that meet the needs of diverse learners.
Science teachers can promote student-centered, inquiry-based learning with
activities involving technology-based materials. In addition, Internet-based
telecommunications offer science teachers opportunities to expand their professional
networks beyond the walls of the school building.
To effectively integrate technology in the preparation and development of science
teachers, science teacher
educators should:
- Identify and locate technology-based materials and resources and evaluate
them for suitability and
accessibility for science instructional purposes.
- Understand how integrating technologies into science instruction can enhance
science teaching and
learning for all.
- Model technology-based science curricular activities with appropriate pedagogy.
- Design activities involving technology-integrated materials to promote student-centered,
inquiry-based
learning for all.
The following are examples of how technology-based materials may be used to
promote science teaching and learning.
- Support student investigations with real-time data collection via hand-held
or microcomputer-based
probeware.
- Use scientific visualizations to show phenomena that cannot be seen with
typical classroom resources.
- Use a simulation to explore a complex scientific phenomena.
- Use multimedia resources, such as animations, video clips, or still images
to illustrate science content,
concepts, or processes.
- Use distributed information sources such as real-time data, online databases,
peer groups, and
mentors/experts in many locations to investigate scientific questions.
- Use Web-based photojournals and virtual field trips to explore remote geographic
locations.
- Use Geographic Information Systems (GIS) to visualize, manipulate, analyze,
and display spatial data.
- Engage in a Web-based inquiry activity to investigate a scientifically
oriented question.
- Use a spreadsheet or database to analyze a data set.
- Incorporate Web-based primary sources for guided explorations and information-gathering
research tasks.
- Use telecommunication networks, such as a listserv or Web-based forum,
to collaborate on a project or
communicate conclusions from an investigation.
- Use modeling tools to build, test, and revise scientific explanations and
represent scientific understandings.
Note: This position statement is congruent with the best technology
integration practices from the International Society for Technology in Education’s
(ISTE) National Educational Technology Standards, the National Science
Teachers Association’s (NSTA) Position Statement on the Use of Computers
in Science Education, and the National Geography Standards.
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