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Bryan, J. (2004). Video analysis software and the investigation of the conservation of mechanical energy. Contemporary Issues in Technology and Teacher Education [Online serial], 4(3). Available: http://www.citejournal.org/vol4/iss3/science/article1.cfm
Video Analysis Software and the Investigation of the Conservation of Mechanical Energy
Joel Bryan
Texas A&M University
Abstract
National science and mathematics standards stress the importance of integrating
technology use into those fields of study at all levels of education.
In order to fulfill these directives, it is necessary to introduce both
in-service and preservice teachers to various forms of technology while
modeling its appropriate use in investigating “real world”
problems and situations. Using the conservation of mechanical energy of
a falling and bouncing ball as its context, this paper describes how inexpensive
video analysis technology makes possible the investigation of numerous
types of motion with detail and precision that would be incredibly difficult,
if not impossible, without the use of this technology.
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National standards for mathematics and science teaching and learning currently
emphasize the use of technology in mathematics and science courses in order
to facilitate the development of a “technologically literate” society
that is prepared to be productive in today’s technology-dependent society.
The National Science Teachers Association (NSTA) position statement on the use
of computers in science education states plainly that “computers should
have a major role in the teaching and learning of science” (NSTA,
1999, ¶1) and emphasize technology’s use for data collection,
manipulation, and presentation. According to the Technology Principle stated
in the National Council of Teachers of Mathematics (NCTM, 2000) Principles
and Standards for School Mathematics, “electronic technologies…are
essential tools for teaching, learning, and doing mathematics” because
“they furnish visual images of mathematical ideas, they facilitate organizing
and analyzing data, and they compute efficiently and accurately” (p. 24).
These same standards further call for making mathematics and science relevant
to learners. Making the connections between what is studied in class and what
is experienced in life outside of the classroom leads to a more developed and
deeper understanding of the concepts (Boaler, 1998; Borenstein, 1997). Because
technology has rapidly become a part of people’s everyday experiences
in life outside of the classroom, its use in the classroom serves as an excellent
means for helping educators meet the relevancy objectives.
If technology use and real world applications of concepts are desired in our
nation’s mathematics and science classrooms, then courses that prepare
future teachers of these subjects should incorporate and model effective uses
of each of these. According to Flick
and Bell’s (2000) guidelines for technology use in science teacher
preparation, “technology should be introduced in the context of science
content,” “technology instruction in science should take advantage
of the unique features of technology,” and “technology should make
science views more accessible” (p. 40). Similar to this are Garofalo,
Drier, Harper, Timmerman, and Shockey’s (2000) guidelines for technology
use in mathematics teacher preparation. Among other things, they too contend
that instructors should “introduce technology in context” (p. 67)
and that technology should be used to “extend beyond or significantly
enhance what could be done without technology” (p. 71). As a general rule,
technology should be used when it allows one to either do something that could
not be done at all without it or to do something better than could be done without
it.
Although much of the focus on the use of technology in mathematics and science
has centered on the use of graphing calculators (Adie, 1998; Embse & Engebretsen,
1996; Korithoski, 1996), computer-based laboratory sensors (Lapp & Cyrus,
2000; Thornton & Sokoloff, 1990), and computer simulations (Wilkinson, 1995),
another more recently developed and relatively inexpensive technology meets
each of these criteria and provides an excellent opportunity for preservice
science and mathematics teacher content and/or pedagogy courses to model investigations
that are greatly enhanced through technology use. By using inexpensive video
analysis software and movie clips, students can now quickly and efficiently
gather data from real-world situations, which can then be manipulated, analyzed,
and graphed in ways and with ease not always so accessible with those other
forms of technology.
Examples of Currently Available Video Analysis Programs
A number of relatively inexpensive video analysis programs are currently available,
including VideoPoint (which is
promoted by the American Association of Physics Teachers), Physics
ToolKit (formerly known as World-in-Motion), and Measurement-in-Motion.
Increasing interest in this type of technology and the awareness of its potential
for enhancing student learning has led makers of calculator-based software and
probes, such as Vernier’s
LoggerPro, to incorporate similar video analysis capabilities into the latest
upgrades of their existing programs.
Not only do these video analysis programs come prepackaged with video clips
that are ready to be analyzed, they also allow users to import and analyze video
clips from other sources, including movies produced by students in the laboratory
setting immediately before analysis. Of these programs, VideoPoint has the most
sophisticated features and is perhaps the most versatile, although Physics ToolKit
may be the most cost effective. Users of this software may find, as I did, that
the video clips contained in the Physics ToolKit program are more suitable for
introductory level physics investigations than those contained in VideoPoint.
However, VideoPoint also functions as a video capture program, allowing users
to easily make movies in the lab setting for immediate use with the analysis
program. Macintosh users may prefer Measurement-in-Motion. It was originally
designed for exclusive use with Macintosh computers, but it has recently become
available for use with Windows-based personal computers.
The feature common to these and other video analysis programs is that the
computer mouse cursor is used to "mark" the position of an object
in each frame of a video clip. Users most likely will then instruct the software
to convert pixel locations to more applicable position units and, generally,
also have the option to translate and rotate the coordinate axes to meet the
parameters of the specific phenomena being investigated. With just a click of
the mouse button, the software program will then take the position data and
make relevant calculations necessary to produce informative graphs. Position,
velocity, acceleration, force, momentum, and energy graphs, among others, can
all be quickly produced and graphed. Most of the video analysis programs also
have the capability for computing and reporting “best fit” equations
for these curves.
A free software program called Tracker
contains many of the same features contained in the previously described commercial
programs. Users “mark” video frames, set the origin to the desired
location, and calibrate the video for real-world measurement values. Tracker
then calculates motion values, constructs graphs, and draws and manipulates
force, velocity, and acceleration vectors. The Tracker Web page contains links
to tutorials and several video clips ready for analysis. Tracker also has the
capability of creating a line profile tool that measures the brightness of the
image pixels it lies on in order to generate spectral line profiles and analyze
diffraction and interference patterns, a feature not currently available with
other video analysis programs.
Another free software program, called DataPoint,
is available, but it requires students to import the marked data into a spreadsheet
and then manipulate it to produce the relevant information. Although this program
is copyrighted, its developer allows it to be downloaded from his Web site free
of charge. He does ask that users notify him that they are using the software
and let him know how it serves their needs and how it can be improved. In order
to obtain more meaningful results, students using this program will need to
convert their data sets, which contain x and y pixel positions
of the location of the object with time, to appropriate position units using
proportions and a known measurement standard. Users may also need to make linear
translation manipulations to move the origins to desired locations. The use
of a more “bare bones” program such as this may be preferred if
the instructor desires that students have more responsibility for manipulating
data and generating velocities and accelerations from position changes.
A video analysis informational page linked to the Texas
A&M University Center for Mathematics and Science Education Web site
contains 19 short video clips that may be downloaded and analyzed in any of
these programs. Also linked to this Web site are instructional videos demonstrating
the use of VideoPoint, DataPoint, and the Microsoft Excel spreadsheet program
for data analysis, along with suggestions for the use of each video clip.
A VideoPoint Investigation of a Bouncing Ball’s Conservation
of Mechanical Energy
Introductory level physics courses typically present rising and/or falling
objects as one example of the conservation of mechanical energy. Instructors
and textbooks typically inform students that after a ball is tossed upward,
it loses kinetic energy (KE = 0.5mv2, where m = the mass of the object
and v = the speed of the object) and gains gravitational potential energy (PEg
= mgh, where m = the mass of the object, g = the gravitational acceleration
value of 9.8 m/s/s, and h = the height above the arbitrarily chosen zero position)
as it rises; and then loses gravitational potential energy and gains kinetic
energy as it falls, such that the total mechanical energy (TE = KE + PEg) remains
constant at every location during the trip. Seldom do the students or instructor
perform any actual measurement-based calculations of the energies involved,
except for using the maximum height above the arbitrarily chosen zero position
of the ball before release to determine its maximum gravitational potential
energy.
Since the stationary ball’s kinetic energy at this maximum height is
known by direct observation to be 0, the total mechanical energy of the ball
at any location is, therefore, equal to its maximum gravitational potential
energy. Although students will predictably use the mechanical energy conservation
relationship (TE = KE + PEg) to specify the amounts of kinetic and gravitational
potential energies at any location of the ball’s path, they rarely collect
any actual data to support these calculations.
Inexpensive video analysis technologies now make possible a more detailed
investigation of the conservation of energy involved in this and many other
situations. By using this technology, students not only generate actual data
supporting claims of energy conservation for a rising and falling ball, they
may also investigate the loss of mechanical energy during bouncing and the changes
in the velocity, acceleration, and net force on the ball at any location of
its movement.
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Figure 1. PHYS 205 instructor demonstrates the
use of VideoPoint at the SMART Board. |
Preservice teachers taking a conceptual physics course (PHYS 205) designed
for middle grades science and mathematics specialists at Texas A&M University
used VideoPoint video analysis software to gather data in order to analyze this
and three other motion situations. For these four video analysis activities,
students met in the College of Education and Human Development’s Verizon
Interactive Classroon (VIC), a state of the art “classroom of the future”
that was constructed through funding obtained from the Verizon
Foundation. Contained in the VIC were moveable tables/work stations with
wireless laptop computers having compact disk burning capabilities, an LCD projector,
and a SMART Board
interactive white board to aid in instructional delivery. The instructor’s
use of the SMART Board to demonstrate the capabilities of VideoPoint is shown
in Figure 1.
To begin the activity, the actual ball present in the soon-to-be analyzed video
clip was dropped as a demonstration, and students were asked to describe the
changes in the falling ball’s energies. Although most all students will
correctly state that while the ball falls, its total energy remains constant
as it loses potential energy and gains kinetic energy, it is generally unknown
whether or not these students have a deeper understanding of this situation,
and if they can correctly predict the graphical representation of the energies
involved. Therefore, as a prelab investigation, students first made predictive
sketches of what they expected graphs of potential, kinetic, and total energies
to look like as a ball falls and also as a ball falls and bounces four times.
An examination of the predictions handed in by the 27 pairs of spring 2004
Physics 205 students prior to this laboratory activity confirmed that, although
most students generally said the correct words, they often failed to develop
an acceptable conceptual understanding or were unable to predict how those ideas
would be displayed graphically. Only one group failed to hand in a prediction
that displayed a decrease in potential energy and a simultaneous increase in
kinetic energy. However, despite having previously performed several laboratory
activities in which they generated quadratic curves for accelerated motion,
15 of these 26 pairs (57.7%) displayed linear, instead of quadratic, changes
(Figure 2) in their energy graphs. More surprisingly, 15 of the 27 pairs (55.6%)
of students represented their constant total energy by a line passing through
the intersection of the kinetic and potential energy curves, an occurrence which
is also indicated in Figure 2. This inability to relate actual motion to its
graphical representations, despite being able to correctly articulate the description
of the motion, has been studied and described in numerous reports (Beichner,
1994, 1996, 1999; McDermott, Rosenquist, & van Zee, 1987).
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| Figure 2. Sample energy graph I. |
Only 2 of the 27 pairs (7.4%) of students handed in predictions corresponding
to the acceptable representations of the energy graphs, one of which is shown
in Figure 3.
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| Figure 3. Sample energy graph II. |
After completing their predictions, the pairs of students (Figure 4) used the
VideoPoint program to open a video showing the 302-gram minibasketball falling
and bouncing four times after being held and released by the instructor.
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| Figure 4. Preservice teachers using VideoPoint in
Texas A&M’s VIC. |
Since most digital video cameras film at a rate of approximately 29.97 frames/second,
students were able to collect data describing precise locations of the ball
every 1/30 sec. VideoPoint allowed students to “mark” the location
of the ball in each of the 95 frames of this movie clip, resulting in the movie
window shown in Figure 5. “Marking” the frames of the video clip
was done by simply moving the mouse cursor over the ball’s location in
the frame and “clicking.” The program advanced the video clip automatically
to the next frame, and even allowed the students to predetermine whether or
not each frame of the movie was to be “marked,” that is, the students
could set the program to advance to every second, third, fourth, fifth, etc....frame,
a feature which is particularly useful when analyzing lengthy video clips. As
each frame was “marked,” the vertical and horizontal positions of
the ball at that precise time were entered into a data table and were available
for viewing by the students when desired.
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Figure 5. VideoPoint screenshot of “marked”
video. |
After marking each of the desired video frames, students quickly and easily
moved the origin to the lowest marked position of the ball, used the meter stick
in the video’s background for the scaling purpose of converting coordinates
values from pixels to meters, and entered the mass of the ball, which was necessary
for energy and force calculations. Although the video did indicate some horizontal
movement by the ball, it was irrelevant to this analysis and, therefore, ignored.
Students then used VideoPoint to produce informative graphs of the ball’s
motion. Position, velocity, and acceleration graphs of the ball’s vertical
motion with time are shown in Figure 6.
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Figure 6. VideoPoint position, velocity, and acceleration
graphs of a bouncing ball.
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These three graphs contain a wealth of information that cannot be as easily
obtained when using other data collection methods. Among other things, the position
graph indicates the vertical position of the ball as it changes with time. The
decreasing “width” of each parabolic section indicates the decreasing
amount of time the ball was in the air between bounces. The decreasing height
of each parabolic section indicates that the ball did not rise as high after
a bounce.
One of the more interesting aspects of the velocity graph is that the “gaps”
between each segment indicate the abrupt change in sign and direction of the
ball as it bounces. Each of these segments cross the horizontal axis at the
highest position of the ball and have slopes (not shown, but could be easily
calculated) approximately equal to the accepted gravitational acceleration value
(g = –9.8 m/s/s). The third graph, acceleration, not only displays the
constant negative acceleration of the ball as it rises and falls, but also the
brief but much greater positive acceleration during each bounce. The graph of
the net force on the ball with time (Figure 7) indicates that the net force
on the ball is a constant negative value corresponding to its weight (w = mg)
as it both rises and falls, but is a much greater positive value during the
brief time that the ball is in contact with the floor during a bounce.
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Figure 7. VideoPoint graph of the net force on
the bouncing ball.
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Students can further directly correlate the information contained in these
and other graphs to the motion of the ball by viewing the graphs while playing
the movie. As the movie plays, points on each graph are “highlighted”
by the program in real time. Such a feature should provide similar benefits
of “real time” graphing that make calculator-based laboratory (CBL)
probes and software effective. Also, “clicking” on any point displayed
in any graph will take the user to that precise frame in the movie.
If “a picture is worth a thousand words,” the energy graphs shown
in Figure 8 embody a novel. By examining these graphs, my students readily saw
verification that the sum total kinetic and gravitational potential energies
remained constant as the ball rose and fell. Students also saw how the kinetic
and gravitational potential energies increased and decreased inversely with
each period of time in the air. This total mechanical energy decreased after
each bounce, and its loss was indicated by the abrupt vertical “gaps”
in the horizontal total energy segments. An inspection of the relative amount
of mechanical energy lost in each bounce revealed that this ball conserved approximately
55-60% of its energy after each bounce. To conclude this exercise, students
compared the actual graphs with their prelab predictions and developed lists
of questions about each of the graphs that would be appropriate for classroom
instruction.
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Figure 8. VideoPoint graphs of kinetic, potential,
and total energies of a falling ball.
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On the exam covering concepts of work, power, and energy that was administered
to these same students 2 full weeks after this video analysis laboratory investigation,
one question asked students to sketch position, velocity, acceleration, and
energy graphs depicting the motion of a “super ball” that would
rise to 50% above its release point after each of four bounces. Although one
cannot justifiably attribute success on this question as being solely dependent
upon the use of the video analysis software, it is encouraging to note that
not one single student in this class (n = 57) drew graphs having straight
line segments for kinetic and gravitational potential energies and a total energy
curve passing through their intersections as many had done in their prelab predictions.
However, 6 students still drew a horizontal segment for total energy midway
between the maximum and minimum kinetic/potential energy levels as before, and
7 others drew kinetic and potential energies with straight line segments.
Technology savvy physics teachers may readily call attention to the fact that
similar results can be obtained in “real-time” using a microcomputer-based
laboratory (MBL) motion sensor probe. The benefits of “real-time”
graphing versus “delay-time” graphing are debatable. Although Brasell
(1987) did find that “real-time” graphing with MBLs improved students’
graphing skills more so than “delay-time” graphing of the same events,
a later study in which students analyzed motion contained on videotape showed
no significant differences (Brungardt & Zollman, 1995). Graphing using today’s
more sophisticated video analysis software, however, cannot be classified as
the typical “delay-time” graphing, because once these programs have
initially produced the graphs in delay-time, users then have the capability
of viewing the action multiple times while following the graph in real-time.
Although it is true that some investigations may be made just as easily, accurately,
and precisely using probeware and/or sensors, there are three important advantages
of video analysis over probes and sensors.
- Video analysis allows for study of two-dimensional motion, such as revolving
objects or projectiles.
- More than one object can be analyzed in any video, which can lead to detailed
comparisons of multiple objects that are in the same system.
- Video analysis can be performed without all of the cumbersome wires and
sensors associated with MBLs.
The versatility of video analysis is also an important feature. Any object(s)
in any location that can be, or has been, videotaped can be analyzed. Computer
technology today even makes possible the video analysis of any clip of motion
“captured” from any available recording in videocassette (VHS),
compact disk (CD), and digital video disk (DVD) formats.
Although computer simulations and other technologies, such as MBL probes and
sensors, often take away the possibility for “experimental error”
and raise concerns by Chinn and Malhotra (2002) that the “messiness of
the natural world is artificially cleaned up” (p. 208) so that “students
may not learn to control variables in situations where they are not presented
with a priori lists of variables” (p. 209), students may introduce and
encounter error using video analysis via the “marking” process.
Collected data can only be as accurate as students are in marking the exact
same location on the moving object(s) in each frame. Although each frame is
precisely timed by the digital recording, the exact positions of the object(s)
at those times are dependent upon the marking skill of the student.
The accuracy with which the distance scale for the motion is marked is also
a possible source of error. If the known distance is marked too short, then
all velocities and accelerations calculated by the program will be too large,
with the opposite true if the scale is marked too large. The quality of the
video is also a factor that influences marking errors. The faster the object
is moving, the more “fuzzy” it may appear in each frame. While these
error sources do not usually lead to as much error as is normally found in other
timing and position measuring techniques, the introduction of error does make
this form of analysis more realistic as a scientific process than do many simulations
and MBL probes.
Because it is a relatively recent technological development, few studies have
been conducted to examine the effectiveness of implementing video analysis as
an instruction tool in either mathematics or science. Like Escalada and Zollman
(1997), I have found that most of my students discovered the video analysis
software relatively simple to learn and recognized its benefits in helping them
learn physics.
A more recent study by Pappas, Koleza, Rizos, and Skordoulis (2002) did find
that the VideoPoint video analysis program was successful in helping preservice
teachers better understand the links between multiple representations of motion
presented in graphical, tabular, and formula formats. In addition, video analysis
software may be used for many of the same purposes currently served by MBL motion
sensors and photogates. One can cautiously make assumptions that some of the
same features that make MBLs effective, such as quickly generating graphs so
that students may spend more of their time studying physics concepts instead
of burdensome point plotting (Barton, 1998), should also lead to success using
video analysis.
Video analysis technology has improved immensely since the seemingly ancient
20th century method of placing an overhead transparency on a television screen
and marking the locations of some object during pause and advance with a videocassette
player/recorder (VCR). Today’s higher quality digital video, which increases
the number of coordinate points and allows for more precise study, causes many
past studies on the effectiveness of video analysis instructional methodologies
to be outdated or obsolete.
Therefore, many of the studies on the effectiveness of real-time and delayed-time
graphing from the past 20 years will need to be replicated in order to see if
and how recent technological advances have influenced the value of this instructional
method. Furthermore, neither the use of video analysis software, other forms
of technology, nor any innovative practices can guarantee that learning will
be enhanced for the user (Coleman, Holcomb, & Rigden, 1998). The effectiveness
of computer technology depends not only on the way in which the computer and
software are used, but also on the interactions of the students as they use
the technology (Otero, Johnson, & Goldberg, 1999).
Regardless of the type of computer technology or any other educational innovation
used in physics instruction, student learning will be maximized only when the
instructional practices “are designed according to different educational
and psychological theories and principles” (Schacter & Fagano, 1999,
p. 339) in relation to individual students’ needs and abilities. Research
on the effectiveness of video analysis should occur in a variety of instructional
methodologies, including but not limited to constructivism, guided and unguided
inquiry, and direct instruction.
Conclusion
In addition to its obvious benefits for physics investigations, video analysis
software can be an effective addition to mathematics instruction. According
to NCTM standards,
The use of real-world problems to motivate and apply theory, the use of computer
utilities to develop conceptual understanding, the connections among a problem
situation, its model as a function in symbolic form, and the graph of that
function, and functions that are constructed as models of real-world problems
[are all] topics that should receive increased attention [in mathematics classes].
(Roth, 1992, p. 307)
The use of video analysis technology not only serves these functions, but also
provides a cost and time effective means of bringing authentic investigations
into mathematics classes and serves to meet the directives of the NCTM for incorporating
technology into our teaching practices (NCTM, 2000; Rojano, 1996).
This emerging video analysis technology is rapidly changing how teaching and
learning can occur in both science and mathematics classes. Software engineers
are now developing programs similar to these that are compatible with portable
handheld technologies, which should greatly increase the versatility of video
analysis as an instruction method. Such products meet the most important guidelines
for the appropriate use of technology in science and mathematics study, and
the use of these products should be an element in courses for preservice science
and mathematics teachers and in professional development sessions for in-service
teachers.
Additionally, the development and use of computer laboratory facilities similar
to the Verizon Interactive Classroom at Texas A&M serve not only as an instructional
tool for science and mathematics content courses, but also provide a means for
demonstrating appropriate pedagogical methods and building technological literacy
in preservice teachers.
References
Adie, G. (1998). The impact of the graphics calculator on physics teaching.
Physics Education, 33(1), 50-54.
Barton, R. (1998). Why do we ask pupils to plot graphs? Physics Education,
33(6), 366-367.
Beichner, R. (1994). Testing student interpretation of kinematics graphs. American
Journal of Physics, 62(8), 750-762.
Beichner, R. (1996). Impact of video motion analysis on kinematics graph interpretation
skills. American Journal of Physics, 64(10), 1272-1277.
Beichner, R. (1999). Video-based labs for introductory physics courses. Journal
of College Science Teaching, 29(2), 101-104.
Boaler, J. (1998). Alternative approaches to teaching, learning and assessing
mathematics. Evaluation and Program Planning, 21(2), 129-141.
Borenstein, M. (1997). Mathematics in the real world. Learning and Leading
with Technology, 24(7), 34-39.
Brasell, 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.
Brungardt, J., & Zollman, D. (1995). Influence of interactive videodisc
instruction using simultaneous-time analysis on kinematics graphing skills of
high school physics students. Journal of Research in Science Teaching, 32(8),
855-869.
Chinn, C., & Malhotra, B. (2002). Epistemologically authentic inquiry in
schools: A theoretical framework for evaluating inquiry tasks. Science Education,
86, 175-218.
Coleman, A., Holcomb, D., & Rigden, J. (1998). The Introductory Physics
Project 1987-1995: What has it accomplished? American Journal of Physics,
66(2), 212-224.
Embse, C., & Engebretsen, A. (1996). A mathematical look at a free throw
using technology. Mathematics Teacher, 89(9), 774-779.
Escalada, L., & Zollman, D. (1997). An investigation on the effects of
using interactive digital video in a physics classroom on student learning and
attitudes. Journal of Research in Science Teaching, 34(5), 467-489.
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.
Garofalo, J., Drier, H., Harper, S., Timmerman, M., & Shockey, T. (2000).
Promoting appropriate uses of technology in mathematics teacher preparation.
Contemporary Issues in Technology and Teacher Education, 1(1), 66-88.
Korithoski, T. (1996). Finding quadratic equations for real-life situations.
Mathematics Teacher, 89(2), 154-157.
Lapp, D., & Cyrus, V. (2000). Using data-collection devices to enhance
students’ understanding. Mathematics Teacher, 93(6), 504-510.
McDermott, L. C., Rosenquist, M. L., & van Zee, E. H. (1987). Student difficulties
in connecting graphs and physics: Examples from kinematics. American Journal
of Physics, 55(6), 503- 513.
National Council of Teachers of Mathematics. (2000). Principles and standards
for school mathematics. Reston, VA: Author.
National Science Teachers Association. (1999). Position statement: The use
of computers in science education. Retrieved February 5, 2004, from http://www.nsta.org/positionstatement&psid=4
Otero, V., Johnson, A., & Goldberg, F. (1999). How does the computer facilitate
the development of physics knowledge by prospective elementary teachers? Journal
of Education, 181(2), 57-89.
Pappas J., Koleza E., Rizos J., & Skordoulis, C. (2002, July). Using
interactive digital video and motion analysis to bridge abstract mathematical
notions with concrete everyday experiences. Paper presented at the 2nd
International Conference on the Teaching of Mathematics, Hersonissos, Greece.
Retrieved April 13, 2004, from http://www.math.uoc.gr/%7Eictm2/Proceedings/pap299.pdf
Rojano, T. (1996). Developing algebraic aspects of problem solving within a
spreadsheet environment. In N. Bednarz, C. Kieran, & L. Lee (Eds.), Approaches
to algebra: Perspectives for research and teaching. Boston: Kluwer Academic
Publishers.
Roth, W. (1992). Bridging the gap between school and real life: Toward an integration
of science, mathematics, and technology in the context of authentic practice.
School Science and Mathematics, 92(6), 307-317.
Schacter, J., & Fagano, C. (1999). Does computer technology improve student
learning and achievement? How, when, and under what conditions? Journal
of Educational Computing Research, 20(4), 329-343.
Thornton, R., & Sokoloff, D. (1990). Learning motion concepts using real-time
microcomputer-based laboratory tools. American Journal of Physics, 58(9),
858-857.
Wilkinson, L. (1995). Physics academic software: Graphs and tracks. The
Physics Teacher, 33(4), 254-255.
Technology Resources
DataPoint - http://www.stchas.edu/faculty/gcarlson/physics/datapoint.htm
Measurement in Motion - http://www.learninginmotion.com/products/measurement/index.html
Physics Toolkit (formerly World-in-Motion) - http://members.aol.com/raacc/wim.html
SMART Board - http://www.smarttech.com/ads/smartcd/index.asp
Texas A&M’s Center for Mathematics and Science Education Video Analysis
Web site - http://www.science.tamu.edu/CMSE/videoanalysis/index.asp
Tracker - http://www.cabrillo.edu/~dbrown/tracker/index.html
Verizon Foundation - http://foundation.verizon.com/
Vernier’s Logger Pro 3 - http://www.vernier.com/soft/lp.html
VideoPoint - http://www.lsw.com/videopoint/
Author Note:
Joel Bryan
Texas A&M University
jabryan@tamu.edu
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