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Science in the palm of their hands

  • Education Technology Advisers
  • Digital Promise Global
COMMUNICATIONS OF THE ACM August 1999/Vol. 42, No. 8 21
Log On Education
Elliot Soloway, Wayne Grant, Robert Tinker, Jeremy Roschelle,
Mike Mills, Mitchell Resnick, Robbie Berg, and Michael Eisenberg
In the beginning, there are chil-
dren and the learning experi-
ences we want them to have.
Now, let’s bring in technology as
the means for enabling those learn-
ing experiences.
If we’re serious about having
children use technology in K–12
classrooms, then we need to con-
vince the gatekeepers of those
classrooms as to the worth of the
technology. Doing so requires that
we speak in the language of the
teachers’ profession: first identify
the learning experiences and their
outcomes, along with
why those are desired,
and then speak about
how to enable those
activities via technology. It’s a
feature, not a bug, that teachers
require this sort of argumentation.
Teachers are protecting our chil-
dren from gratuitous, trendy and
ultimately empty, experiences.
Here’s what the National
Research Council says: “Inquiry
into authentic questions generated
from student experiences is the
central strategy for teaching
By “authentic questions” the
NRC does not mean questions at
the end of a textbook chapter, but
rather questions generated by stu-
dents. The concern, the interest,
and the motivation must come
from the children; it is their ques-
tions. Now, teachers can surely
help a child generate a question;
an untutored 11-year-old’s ques-
tion is something like “How
many planets are there?” or “How
big is the earth.” With help from
a teacher, these students move
beyond closed questions to more
open-ended, content-rich ques-
tions such as “How do earth-
quakes stop?” and “How did
scientists discover sprites?”
By “inquiry” the NRC does not
mean the idealized scientific
method that no one actually fol-
lows so linearly—make a hypothe-
sis, for instance, and collect data.
Moreover, an inquiry is not a
hands-on, canned lab activity. For
example, measuring the speed and
acceleration of a cart on an
inclined plane. Rather, an inquiry
extends over weeks of time, where
measuring the cart’s speed, say, is
only one of a set of activities,
where collaboration with adults
(teachers and domain experts) is
integral, and where the inquiry
revolves around an authentic, stu-
dent-generated question.
Now for the technology. Inas-
much as computational tools are
used by scientists in their investi-
gations, computational tools,
appropriately redesigned with
learners in mind, must be used by
students in their investigations.
What follows is a set of short
reports from colleagues on com-
putational tools, based on hand-
held devices, that enable children
to collect data outside the class-
room, enabling children to con-
duct investigations they were not
able to before. No better argu-
ment in support of technology
could possibly be mounted.
First, Wayne Grant reports on
his company’s efforts at attaching
standard science probes to 3Coms
PalmPilot. Next, Bob Tinker, one
Science in the Palms of
Their Hands
00 Log on 7/10/99 1:11 PM Page 21
22 August 1999/Vol. 42, No. 8 COMMUNICATIONS OF THE ACM
of the inventors of microcom-
puter-based laboratories—probe-
ware—describes a new generation
of smart probes. Jeremy Roschelle
and Michael Mills envision how
handhelds can be used education-
ally. Finally, Mitchell Resnick and
colleagues describe an effort where
children build their own computa-
tionally based sensors and effec-
tors. The evidence is clear:
children find stationary probeware
exciting and productive. Now that
children can take this technology
onto the playground, and into
their houses, they can connect the
things they see, hear, and feel out-
side the classroom to ideas they
can scientifically examine.
Elliot Soloway is the director of the
Highly Interactive Computing project at the
University of Michigan.
Dave, a 16-year-old high school stu-
dent, was mildly intrigued when he
plugged the pH sensor into an inter-
face connected to his desktop computer in
the science lab. He watched the pH graph change as
he added vinegar to distilled water. This is neat, he
thought. But there must be more interesting things to
measure than vinegar.
Ms. Coltrane, the science teacher, pierced his
reverie. She was showing the class a small and
very portable handheld with sensors con-
nected to it. Dave was impressed with just
how small it was. Not much bigger than a
pager, he thought. Ms. Coltrane explained
that all kinds of sensors could be connected to
the little computer, and with the ImagiProbe
application things like light, temperature,
voltage, and even acceleration could be
An idea popped into Dave’s head. What if
I could connect an accelerometer to this
thing, hide it in my pocket, and show Mom
just how slow that old car of hers really is.
He also wondered if he could measure the
forces he felt in his stomach when riding the
roller coaster.
At the end of class he talked Ms. Coltrane into bor-
rowing the ImagiProbe system for a week to develop
some of his own science investigations. She was will-
ing to sign them out to all the kids if it motivated
their interest in science.
She handed Dave a small black bag that contained
everything he needed: the handheld with a sensor
interface clipped onto the bottom and a whole set of
sensors including the accelerometer (Figure 1). The
first thing I’m going to do is check out the accelera-
tion of the school bus, he thought.
At the end of the day. Dave rushed onto the bus
and quickly set up his experiment. Rhonda watched
over his shoulder as he plugged the accelerometer
into the interface and set up a trial to collect accelera-
tion data at 100 samples/sec. “Whatcha doing?”
Rhonda asked leaning over the back of Dave’s seat.
As Dave shared his ideas for investigations, she got
excited. “I wonder what the graph would look like if
we collected data while sitting on a swing? Do you
think it would look anything like those funny up-
and-down curves we’ve been talking about in math
Rhonda wondered if the ImagiProbe
system would work on Moms handheld
computer. We could measure things like
light, soil temperature, and soil acidity to
assess the growing conditions in our back-
yard, Rhonda thought. Maybe Mom and
I could work together on a garden science
The school bus roared to life and jolted
out of the parking lot. “Look at this,
Rhonda,” Dave said. “You can see that
the level of roar we’re hearing has no real
connection to the amount of acceleration
we’re experiencing.”
The rest of the way home Dave and
Rhonda talked excitedly about all the
things they would be able to discover in their own
The idea of hooking sensors up to a computer and
taking scientific measurements is not new. And the
educational value of conducting sensor-based science
with desktop computers has been well established by
many researchers. Even if they’re only studying the
effect on pH when adding vinegar to distilled water,
the ability to collect data and plot it in real time
motivates kids to learn more science. However, what’s
different in the Dave/Rhonda vignette is its descrip-
tion of the educational potential of placing inexpen-
Wayne Grant, ImagiWorks, Inc.
Figure 1. ImagiProbe
setup: PalmPilot, D/A
converter, probe.
00 Log on 7/10/99 1:11 PM Page 22
COMMUNICATIONS OF THE ACM August 1999/Vol. 42, No. 8 23
Log On Education
sive handhelds outfitted with sensors in the hands of
more kids so they can discover their own worlds.
Though laptops do enable such mobile inquiry,
they remain fragile, relatively expensive, and are
overkill for the task.
ImagiProbe brings sensor-based science to hand-
helds. The ImagiProbe system consists of a software
application, a Sensor interface that clips to the hand-
held, and software that enables students to copy data
onto their desktop computer. With the
system, students can set up investiga-
tions and data collection trials, collect
data and watch as it is plotted in real
time, calibrate sensors, and even anno-
tate investigations, trials, and calibrations
with notes and sketches. With the click
of a single button, students can move
data onto a desktop computer for shar-
ing, for further analysis, or for embed-
ding in science reports.
Our goal is to create products that
enable more students to experience the
thrill of discovery and become excited
about science by carrying out meaning-
ful investigations. Today, because of
ImagiProbe’s extreme portability, teach-
ers can move sensor-based science
beyond the desktop to exploit a richer range of activi-
ties that naturally transforms each student’s daily
world into a laboratory filled with interesting and rel-
evant scientific opportunity.
Tomorrow, through wireless connections, students
will be able to share their data in real time and collab-
orate with other students to undertake distributed
investigations. By creating data-modeled views of
their immediate context and comparing these with
similar views created by others, students will really
begin to understand and enjoy the collaborative
nature of science.
Wayne Grant is a cofounder of ImagiWorks, Inc.
As part of the Science Learning in
Context (SLiC) project, we have sci-
entists eagerly using probes with
handhelds. Students use Newtons, eMates,
and handhelds equipped with probes and measure-
ment software. Even seven-year-olds immediately
pick up the computers and probes and start using
them and asking questions.
Figures 2 and 3 show young scientists eagerly
using a handheld computer. One of these young
investigators wanted to know whether Popsicles got
colder faster than water and, with little prompting,
devised the controlled experiment in Figure 4.
There is no question the combination of probes
and small computers could unleash
children’s natural curiosity and help
them learn far
more from the
natural world
than we have
ever thought
possible. To
permit this to
happen, we
need to make
hardware and software better and easier to use.
One of the unanticipated needs we identified
while watching students conduct field work with
portable computers involves the design of the probe
system. In the lab, it is possible to lay out a tradi-
tional microcomputer-based lab system with cables,
interface box, and probes, but that same system can-
not just run on batteries and be expected to work
well in field applications. The problem: too many
wires and boxes requiring too much power.
Not only is this setup unwieldy, it is error-prone,
battery consuming, distracting, and potentially dan-
gerous. There are too many parts that can be incor-
Robert Tinker, the Concord Consortium
Figure 2. Measuring soil
temperature using ImagiProbe.
Figure 3. Children exploring
the PalmPilot.
Figure 4. Measuring changes
in temperature.
00 Log on 7/10/99 1:11 PM Page 23
rectly connected, dropped in water, or tripped over.
There are too many components to troubleshoot if
something such as a dead battery, bent pin, or loose
connection causes one of the components to fail. We
found students and teachers needed to spend too
much time getting the system working and, there-
fore, lost opportunities to think about science. In the
field, the system has to recede into the background.
Of course, this is also important in the teaching labo-
ratory as well; it just became more obvious when we
tried to use probes with portable computers outside.
Recent advances in low-cost and low-power chips
now make it possible to combine the interface, amplifier,
and sensor into a single low-power SmartProbe. We can
now migrate all the intelligence from the interface into a
microcomputer at the probe while incorporating a num-
ber of additional features that will simplify data collec-
tion and allow students to focus more on science
concepts and investigations. Because some low-cost
microcomputers also consume very little power, we can
create some SmartProbes without batteries.
Because the SmartProbe contains a complete
microcomputer, we can add functions to the sensor
never before possible. The SmartProbe can store
information about itself. It can tell the computer
what it measures, its accuracy, and its range. With
appropriate software, this could result in a plug-and-
play system ready to measure as soon as the Smart-
Probe is plugged in.
Current sensors send raw data to the computer,
typically a binary number between 0 and 1,023 (or
one less than some other power of 2). The software
must convert these raw data values into physical val-
ues such as degrees Celsius, force in Newtons, or
light level in lux. Because this conversion is not the
same for every probe or even the same probe at dif-
ferent times, the software needs some calibration
constants for the particular probe in use. If these con-
stants are stored in the computer, then the computer
and probe must stay together—not an easy require-
ment in a lab with many computers. A SmartProbe
can store its calibration constants internally and use
them to send to the computer values in physical
units. This means that a SmartProbe can be used on
any computer without recalibration or copying the
calibration constants.
SmartProbes are not yet available, but they are
coming. Educators can anticipate a quiet revolution
in probeware within a few years. Faster, smarter
SmartProbes will be far easier to use, more reliable,
and less error-prone. Students will be able to plug
any probe into any computer, whether portable,
pocket-sized, or a desktop model. As soon as the
probe is connected, the software will start working
and the student can start thinking immediately about
science without having to think about batteries,
interfaces, or calibrations.
Robert Tinker is a cofounder of the Concord Consortium.
As 13-year-old Mike enters his math
class, his Datagotchi, a $150 hand-
held device, beeps once. “Configur-
ing for class” reads the message. Even while
Mike is chatting to his classmate, Jenny, and finding
his way to his seat, his Datagotchi beams last night’s
homework over a short-range radio network to the
teacher workstation, and receives some special applets
that will be used during today’s class.
Jenny whispers to Mike, “I’ll beam you the data I
got last night from my bird feeder; we’ve only got 47
minutes before science class to get it together!”
“Today, we’re going to continue our explorations
of fitting lines to data in graphs and tables,” Mr.
Keck, the teacher announces. “Now, here is the
assignment.” Mr. Keck touches the stylus to his
overhead projection panel, and explains to the class
what they will be doing, sending a different data set
to each of the students’ Datagotchis. “Now get into
groups, and start working!”
Mike, Jenny, and their partners Tamara and Kirk,
gather around a small table. Each has a Datagotchi
on which they can interact with graphs using a sty-
lus, enter mathematical formulas via math-specific
handwriting recognition, manipulate data in tables,
run simulations, and more. Because of the handheld’s
size, there isnt much room to work so screens must
be dynamically configurable.
“I’ll enlarge our graph across all four, so we can see
all the data at once,” Tamara says.
“But wait,” interjects Kirk, “we’re supposed to be
fitting the data in the table to a linear equation. We
need to keep a table view, and an equation editor.”
“I’ll put the graph across Mike’s ’gotchi and mine,
24 August 1999/Vol. 42, No. 8 COMMUNICATIONS OF THE ACM
Jeremy Roschelle, SRI International and Mike Mills, IDEO
00 Log on 7/10/99 1:11 PM Page 24
the table in yours, and the equation on Jenny’s,”
Tamara says. “Then Jenny can adjust the equation,
you can check the table, and we’ll all see what kind of
fit we get on the graph.”
As the student groups work, Mr. Keck circulates
around the classroom, noting how students engage in
mathematical conversations that are supported by the
different tools on their Datagotchis. When he reaches
our foursome’s table, he realizes they’re stuck on a
problem; their data set contains an outlying point,
and they are having trouble fitting a linear function
to include it. “Let’s beam your group’s work to the
classroom overhead,” Mr. Keck suggests. “This is
something I want the whole class to see.”
Jenny explains to the class: “We’re trying to find a
slope that gets us all of these points.”
“Which points, Jenny? Use your highlighting
tool,” instructs Mr. Keck.
Jenny switches her Datagotchi to virtual mousepad
mode, which lets her remotely control the projected
display, and finishes her explanation.
After discussing how to treat outlying points, Mr.
Keck asks, “Now do any of the other groups have this
issue? If so, let’s beam them up and have a look.”
This scenario comes from a brainstorming work-
shop held by the Center for Innovative Learning
Technologies (CILT;, which drew 16
corporate- and university-based designers from per-
spectives ranging from hardware design to curriculum
development. Far from being hypothetical, most ele-
ments of this scenario are realizable now, or will be
soon. NetSchools makes a laptop with many of the
beaming capabilities we envision; the Bluetooth Con-
sortium and Suns Jini may make such networks
cheap and ubiquitous. Texas Instruments now makes
calculators with flash ROM that supports download-
able applets. The SimCalc Project has been building
experimental mathematical tools for middle schools
on the PalmPilot and on calculators (search for
“MathCars” at
The nature of the innovation we propose, there-
fore, is not making new technology, but imagining a
completely different kind of technology in class-
rooms. Why should students store work on a PC
when they change classes every 42 minutes? Why
should students work on their calculators, but go up
to the chalkboard to write their answer? Why should
students work in groups, but not exchange data and
visualizations? The math class vignette is one of five
scenarios developed to understand the ecological
niche for handheld computing in classrooms, and
against which we posed the question of designing a
future product line that was ideally suited to class-
room needs.
Workshop attendees were quick to agree on some
high-level requirements: the product should be inex-
pensive, have a long battery life, sturdy enough to be
thrown in a backpack, and focus on math-specific
capabilities, not generic multimedia. It should be part
of a product line that includes sensors, LEGO bricks,
teacher display panels, and other components.
A Datagotchi, as we called the to-be-designed
product, needs a range of ways to use modular
screens, including tiling, connecting to larger flat
panel display, and controlling a full classroom projec-
tion screen. To serve classrooms well, the Datagotchi
also should make the transition from being a personal
device—in the style of handhelds and calculators—to
a collaboration tool that supports classroom informa-
tion flows. Indeed, many scenarios required configura-
tion templates that would specify which students had
access to what information, would create a variety of
differentiated and aggregated spaces for student work,
and enforce collaboration policies. Finally, participants
stressed that the device should ideally meld character-
istics of a network terminal with aspects of a personal
calculator. When students are in class, they might well
take advantage of powerful, server-based visualizations.
When they are out of network range, their device
should still offer enough functionality to allow them
to do their homework. These bolder suggestions are
implementable, if only we can redirect the public’s
enthusiasm for learning technology on PCs to hand-
held devices that would really meet students’ needs.
Jeremy Roschelle is a senior cognitive scientist at SRI
International. Mike Mills is a designer with IDEO, Inc.
Eleven-year-old Nancy loved all types of
animals. In her backyard she had a bird
feeder she kept stocked with food. But
there was a problem. Often, the birds would
come while Nancy was away at school, so she didnt
get to see the birds. Nancy decided to try to build a
COMMUNICATIONS OF THE ACM August 1999/Vol. 42, No. 8 25
Log On Education
Mitchell Resnick, MIT Media Laboratory
Robbie Berg, Wellesley College
Michael Eisenberg, University of Colorado
00 Log on 7/10/99 1:11 PM Page 25
new type of bird feeder that would take pictures of all
the birds that landed on it (Figure 5).
Nancy started by making a wooden lever that
served as a perch for the birds. The long end of the
lever was next to a birdfood container. At the other
end of the lever, Nancy attached a simple home-
made touch sensor consisting of two paper clips.
Then she began exploring ways of connecting a cam-
era to her bird feeder. She built a motorized LEGO
mechanism that moved a small rod. She mounted
the mechanism so that the rod was directly above the
shutter button of the camera.
Nancy connected wires from the paper-clip sensor
and the LEGO mechanism to a “cricket”—a tiny
computer developed at the MIT Media
Lab. Then she wrote a program for the
cricket; the program waited until the
paper clips were no longer touching one
another (indicating that a bird had
arrived), and then turned on the motor-
ized LEGO mechanism which moved
the rod up and down, depressing the
camera’s shutter button.
After working on the project for sev-
eral hours a week over the course of
three months, Nancy had the sensor,
the LEGO mechanism, and the cricket
program all working perfectly. But when she placed
the bird feeder outside of her window at home, she
got photographs of squirrels (and of her younger sis-
ter), not of birds.
Nancy never succeeded in her original plan to
monitor what types of birds would be attracted to
which types of bird food. But the project was still a
very rich learning experience for Nancy. In our view,
kids can learn just as much (if not more) in designing
and building scientific instruments than in collecting
and analyzing data from scientific instruments.
We are testing this idea in our NSF-funded
Beyond Black Boxes project, in which we are devel-
oping new computational tools and project materials
that allow students to create, customize, and person-
alize their own scientific instruments. This approach
follows a long tradition in the scientific community,
in which scientists do not merely measure and theo-
rize but also construct the instruments needed to do
so. Indeed, many of the most important advances in
scientific history were based on a combination of sci-
ence, engineering, and design.
This instrument-building tradition of science has
been attenuated in recent years: today’s laboratories
are filled with black-box instruments. While these
instruments are highly effective in measuring and
collecting data—enabling even novices to perform
advanced scientific experiments—they are also
opaque (in that their inner workings are often hidden
and thus poorly understood by their users) and bland
in appearance (making it difficult for users to have a
personal connection with scientific activity).
Our Beyond Black Boxes project aims to reinvigo-
rate the instrument-building tradition. Kids have used
crickets and other new technologies to build a wide
variety of creative instruments: an odometer for
rollerblades (using a magnetic sensor to
count wheel rotations); a diary-security
system (using a touch sensor to monitor if
someone has been sneaking looks at your
diary); an automated hamster cage (using
a light sensor to keep track of what your
pet hamster is doing while you’re asleep).
The crickets are small enough (roughly
the size of a nine-volt battery) kids can
easily embed them in everyday objects.
Our hope is for day-long learning, in
which kids conduct scientific investiga-
tions not just in classrooms but through-
out their everyday lives.
Our research has shown that children, by building
their own scientific instruments, become more moti-
vated in science activities. Moreover, we have found
these activities help kids develop critical capacities in
evaluating scientific measurements and knowledge,
make stronger connections to the scientific concepts
underlying their investigations, and develop deeper
understandings of the relationship between science
and technology.
Our ultimate goal is to contribute to the develop-
ment of a new generation of students who are more
likely to “look inside” the technological artifacts in the
world around them—and be empowered to develop
their own tools for exploring everyday phenomena.
Mitchell Resnick is an associate professor at the MIT Media
Lab. Robbie Berg is associate professor of physics at Wellesley
College. Mike Eisenberg is associate professor of computer
science at the University of Colorado.
© 1999 ACM 0002-0782/99/0800 $5.00
26 August 1999/Vol. 42, No. 8 COMMUNICATIONS OF THE ACM
Log On Education
Figure 5. Child-constructed
sensing device.
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COMMUNICATIONS OF THE ACM August 1999/Vol. 42, No. 8 27
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... In a closely related example, probes and sensors developed through separate but interrelated efforts of researchers and several small companies. Probes and sensors are used to foster handson inquiry instruction (Soloway et al, 1999). Early research on microcomputer-based labs (e.g. ...
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Computing exponents is one of the most difficult mathematical topics to learn by high school students. Motivated by this concern, a mobile-based intelligent tutoring system (ITS) is being developed to assist students in learning laws of exponents. In this paper, the development and the proposed deployment of a mobile learning system for computing of exponents will be discussed. A randomized pretest-posttest control group design will be employed to determine if the mobile-based ITS is able to assist the students in learning exponents.
Ubiquitous computing has become an area of study in computer science and electrical engineering. Mobile devices, such as mobile phones, are widely used in daily life for various purposes. Mobile devices can facilitate human interaction and access to information resources anytime and anywhere. In this paper, we propose a mobile phone based rock classification system. For this system, the mobile phone played the roles of image capture and rock information display. Rock images were classified via the remote server. Three texture features, i.e. directionality, color and granularity, were exploited to classify rock textures. A TGA based approach was developed to generate the optimal color histogram. The granularity was quantified by the fractal dimension. To alleviate the degradation resulting from texture inhomogeneity, we propose the RW-k-NN classifier to integrate the color and granularity information. The experimental results prove our system can accurately classify rocks. This implies that our system lends itself to a ubiquitous rock classification system.
There are exciting new opportunities for mobile learning in structured and semi-structured out-of-classroom activities using inquiry-based or project-based pedagogies.Wepresent ongoing research on mobile access to context-relevant digital library resources using mobile interfaces. This project leverages the Engineering Pathway, a digital library of high-quality teaching and learning resources for applied science and math, engineering, computer science/information technology and engineering technology for K-12, higher education and beyond. We build on a previous user needs analysis of teachers, parents and students involved with mobile learning and present two mobile prototype applications that address these needs. Simple Machines in Your Life use a PDA to engage elementary school girls in learning about the simple machines in their surroundings. GreenHat uses a GPS-enabled Smartphone to encourage exploration of the natural environmentthrough expert's perspectives. These two cases evaluate the benefits of technological features and their limitations. Lessons learned and recommendations for future improvements are summarized.
Mobility and networking are two important emerging issues that affect educational practices nowadays. Learners and teachers are continuously involved in ubiquitous relationships with other people on the Internet, swapping information and sharing knowledge and skills. However, in the Mobile Learning area, a great deal of emphasis has been placed on mobile technologies and the transfer of content, whereas the potential to support community building processes and collaboration through their integration within social networks has tended to be underemphasized. With the advent of Mobile Learning, a certain growth in its practice and research has been activated by technological innovation and progress. Mobile technologies offer potentiality for the exploitation of contextual learning and have unbound learners and technologies out of the limitation of classrooms at the time that enhance collaborative processes in informal contexts. The emergence of mobile gadgets has democratized the access to technology, changed the concept of user-generated content, and allowed learners and technologies to experiment with technologies outside the classroom, although it has posed challenges to educational stakeholders on how to match the nature of their practice for both life and learning with those traits that educators would like to heighten.
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