
Research Projects and
Centers
Mainly these are projects and centers receiving
funding from US Federal Government Agencies.


Center for Innovative Learning Technologies (CILT))
[Online]. Accessed 2/10/02: http://www.cilt.org/index.html.
Quoting from the Website:
The Center for Innovative Learning Technologies
(CILT) is a distributed center designed to serve as a
national resource for stimulating research on innovative,
technologyenabled solutions to critical problems in K14
learning. Our approach is to foster and conduct
collaborative research and development in areas that we
believe promise significant advances in learning.
Center for Talented Youth at the Johns Hopkins University
[Online]. Accessed 2/26/02: http://www.jhu.edu/~gifted/.
This Center is especially known for its many
years of work with mathematically gifted students.
However, it works with a broader range of students.
Quoting from the first part of the Mission Statement:
Conduct national and international talent
searches which identify, assess, and publicly
recognize outstanding academic talent.
Provide challenging and innovative learning
opportunities in mathematics, science, and the
humanities, through:
 summer programs that meet the highest
instructional and residential standards;
 rigorous distance education programs which are
independent of time and location;  conferences
that explore diverse and exciting educational
topics and encourage broadbased, lifelong
learning programs.  awards ceremonies that affirm
and nurture respect for intellectual abilities.
Center for Technology in Learning [Online].
Accessed 2/10/02: http://www.sri.com/policy/ctl/.
This center is a component of SRI, International
located in California. It is headed by Barbara Means and
Roy Pea. Quoting from the Website:
By the early 1990s, it became very clear that
technology was to play an increasingly important role
in the education of children, youth, and adults. The
issues of how to effectively use technologies to
support learning were considered to be so important
that the Center for Technology in Learning (CTL) was
established at SRI. The Center was established within
SRI's Policy Division, where it is closely allied with
ongoing education and health research programs
National Science Foundation: Research on Learning and
Education (ROLE) [Online]. Accessed 2/10/02:
http://www.nsf.gov/pubs/2002/nsf02023/nsf02023.html
. Quoting from the Website:
Synopsis of Program: This program seeks to
capitalize on important developments in a variety of
fields related to human learning and to education. It
will support research along a fourquadrant continuum
that includes 1) brain research as a foundation for
research on human learning; 2) fundamental research on
behavioral, cognitive, affective and social aspects of
human learning; 3) research on science, technology,
engineering and mathematics (STEM) learning in formal and
informal educational settings; and 4) research on STEM
learning in complex educational systems. ROLE seeks gains
at the intersections of these areas, where issues arising
from research and educational practice can be reconciled,
and hypotheses generated in one area may be tested and
refined in others. The ROLE Program aims to advance the
knowledge base in and across these multidisciplinary
areas.
National Science Foundation: Research on Learning and
Education (ROLE) Initial Round of Awards and Base "Quadrant"
http://www.ehr.nsf.gov/ehr/rec/
ROLERoundIAwardListWithCPOs
AndAbstracts.htm#_Toc503156341. Quoting from the Website
that lists Round 1 funding:
Carnegie Mellon University Tracking the Course
of Mathematical Problem Solving, Anderson, John.
0087396 Whang IIIIII The goal of this
project is to improve our ability to track how
students solve mathematical problems. This research
will use eye tracking to make realtime inferences
about what the student is thinking and fMRI imaging to
make inferences about different styles of problem
solving. This research is done in the context of both
the ACTR theory of human cognition, which allows us
to produce computational models of cognition, and a
series of cognitive tutors for mathematics education,
which are based on the ACTR theory. The ACTR theory
is a theory of how the cognitive system adaptively
uses procedural and declarative knowledge to achieve
its goals. The research will focus on the algebra
tutor that is currently in use in high schools and is
being adapted for use in middle schools. The research
will be concerned with the effect of different
mathematical representations on problem solving and
with different strategies for mathematical problem
solving. There will be three lines of research. One,
involving eye movements, will document the
instructional opportunities associated with eye
movements in the context of the cognitive tutors. It
will particularly focus on the eye movements
associated with competent use of graphical, tabular,
and symbolic representations of functions. The second
line of research, involving fMRI brain imaging, will
study brain activation markers of the course of
mathematical problem solving. It will particularly
focus on distinguishing between students who use an
informal, verbal form of reasoning with students who
use a symbolic, visual form of reasoning. This line
will also look at how we can merge information from
imaging and eye scanning to make both methodologies
more effective. The third line of research will study
how one can use the information from fMRI scanning and
eye tracking to produce more effective instruction.
The three lines of research will converge on a
culminating study that attempts to improve the
effectiveness of the middle school tutor. It will
first use fMRI imaging to identify the learning
strategies of individual students and then collect
realtime eye movement to guide instruction as
students are learning. This will demonstrate how we
can use some of the new emerging sensing technology to
improve mathematics education.
Concord Consortium From Videogames to Science: A
Design Study of BioLogica. Horwitz, Paul.
0087579 Sloane III This project will attempt
to combine the excitement and interest students evince
when allowed to interact with openended, exploratory
computer models, with the structure and explicit
pedagogy many require to succeed at linguistically
oriented, paperandpencil tests. Using BioLogica, a
software environment we have developed on a prior NSF
grant, we will present students with a sequence of
"web labs," or computerbased, guided investigations,
that will introduce them to multilevel reasoning in
the domain of genetics. The web labs will provide the
students with challenges of increasing difficulty,
monitoring their work, offering feedback and
soliciting responses as appropriate. Each will present
students with information and questions regarding
situations or problems analogous to the ones they have
just worked on, offering metacognitive prompts
designed to promote transfer from the computer
activities to a broader understanding of the
underlying scientific concepts
University of Chicago Understanding and Teaching
Spatial Competence Huttenlocher, Janellen.
0087516 Whang III Spatial competence is a
fundamental aspect of intelligence, important to
successful functioning. A high level of spatial skill
is critical to the achievement of a technologically
sophisticated work force for the twentyfirst century.
Spatial intelligence plays a major role in effective
education in mathematics, science and engineering. The
interdisciplinary research we will carry out focuses
on understanding of spatial intelligence and
establishing methods for maximizing the development of
spatial skills. We will study spatial competence at
different levels of analysis. At the biological level,
we will will investigate the neurological foundations
for spatial growth. We will examine the growth and
organization of neural connections in areas of the
brain that underlie the processing of spatial
information. At the behavioral level, we will
investigate the mechanisms that are involved in the
mental representation of the spatial aspects of the
world. We also will study the ways in which children
come to understand spatial symbols such as maps and
models. We will study how acquisition of these symbol
systems affects the development of spatial
intelligence. This work will include computational
modelling of spatial intelligence. Finally, at the
level of educational application, we will investigate
the educational input responsible for the differential
gains in spatial skill levels children achieve in
school. We plan to identify specific teacher practices
that are associated with high gains in student
achievement. Our research team has expertise in a
variety of relevant fields, including neural science,
cognitive psychology, developmental
psychology,computer science, education, and
statistics. This research team has worked together for
the past three years on research that has identified
core elements of spatial functioning. Our goal now is
to further our understanding of how the development of
spatial competence can be enhanced .
Carnegie Mellon University Dynamic Scaffolding
to Improve Learning and Transfer of Hidden Skills.
Lovett, Marsha
0087632 VanderPutten II Failure to learn
hidden skills is a persistent obstacle to students in
science, math, and engineering domains. Hidden skills,
which include problem categorization, feature
detection, and planning, are critical to solving
problems in a domain but do not have any immediate,
external product for students to see. Unfortunately,
it is unclear how best to identify and teach these
difficulttolearn skills. Instructional scaffolding
is a popular and effective technique for providing
targeted support and guidance while students learn to
solve problems in a new domain. Scaffolding has great
potential for improving hiddenskill learning.
However, the reasons it works and how best to
implement it are largely unknown. The proposed
research will explain the effectiveness of
instructional scaffolding in terms of hidden skill
learning. Several hypotheses about the relationship
between scaffolding and hidden skills will be tested,
and new scaffolding designs will be evaluated. This
will lead to a systematic approach to teaching hidden
skills that improves students' learning and transfer.
The four specific aims of this project are: (1)
Develop a systematic, efficient method for identifying
hidden skills. While methods currently exist for
analyzing domainspecific knowledge, these methods are
not robust for identifying hidden skills, and they
tend to be difficult and slow. This project will
develop and test an automated method that combines
logistic regression models and heuristic search
algorithms to infer where hidden skills lie. (2)
Develop a theoretical explanation for why scaffolding
works. Although instructional scaffolds often lead to
better learning, there has been little theoretical
progress in explaining when and how scaffolding works.
A sequence of experiments will be conducted to test
three hypotheses that offer increasingly concrete
levels of explanation for how scaffolding benefits
learning and transfer. (3) Develop practical
guidelines for the design of effective instructional
scaffolding. Three critical questions for scaffolding
design will be examined: What level of scaffolding
support is sufficient to achieve its main benefit?
When and how should scaffolding support be built and
faded? And how can human instructors (i.e., TA's) best
complement a computerized scaffolded learning
environment? (4) Develop novel applications of our
results on scaffolding hidden skills. There are at
least two novel applications of this work, beyond the
scope of learning theory and instructional design.
First, the scaffolding designs from Specific Aim 3
will be used to develop new online assessments of
students' understanding. Second, the results from
Specific Aim 1 will be used to develop tools that
train instructors to "see" the hidden skills in
complex problems and thus better anticipate students'
learning difficulties.
TERC, Inc. Math in Motion: Investigating the
relationship between formal mathematics and body action.
Nemirovsky, Ricardo
0087573 Zia II The aim of this proposal is to
investigate new approaches to nurture and cultivate
the mathematical imagination of all students.
Mathematics as a science to imaginewith is not
incompatible with memorizing the multiplication
tables, number facts, or shortcuts to operate
fractions, but it changes what these memories are part
of. It is about imagiining space and time: shapes,
patterns, or trajectories; it is about envisioning
houw things could be; it is about discriminating the
finite and infinite, the discrete from the continuous,
and dthe possible from the impossible. The main
conjecture of this proposal is that cultivating
mathematical imagination is deeply related to
enriching bodily action/perception. The research we
propose intends to investigate this thesis through a
series of studies with high school students and
preservice teachers.
MIT The Role of Emotion in Propelling the SMET
Process. Picard, Rosalind
0087768 Whang IIIII Exploring the Role of
Emotion in Propelling the SMET Learning Process The
proposed research aims to build a computerized
Learning Companion that will be sensitive to the
affective aspects of learning and that will work with
the child to facilitate the child's own efforts at
learning. Learning complex ideas in science, math,
engineering, and technology and developing the
cognitive reasoning skills these areas demand often
involves failure and a host of associated affective
responses. When learning proceeds via humanhuman
interaction, it is often improved by communication of
affective cues (such as frustration, confusion, or
interest), and by adaptation of the learning
experience to such cues (adjusting pace of
presentation, interjecting motivation, offering an
additional view, etc.). When learning involves
humanmachine interaction, the human communication
about when, where, how, and how important it is to
adapt also often involves emotional information;
however, today's computers largely ignore this
information. Affective computing has the potential to
expand humancomputer interaction by extending
computing to include emotional communication together
with appropriate means of handling affective
information. The proposed research aims to bring new
tools of affective computing into the reach of
educators, to begin to change computerbased learning
from a style that ignores emotions to a style that can
begin to respond appropriately to student emotions.
The initial focus is on building a system that (1)
helps students increase their awareness and mastery of
the important role that emotions can play in learning
and (2) facilitates the child's learning, by
occasionally prompting with questions or feedback, and
by watching and responding to the affective state of
the childwatching for signs of frustration and
boredom that may precede quitting, for signs of
curiosity or interest that tend to indicate active
exploration, and for signs of enjoyment and mastery,
which might indicate a successful learning experience.
Tools developed for the Learning Companion should also
be useful for intelligent tutoring systems, and should
help give insight into new theories of motivation and
emotion in teaching; however, the Learning Companion
is not a teacher or tutor that knows the answers, but
a player on the side of the student. The companion
will be sensitive to the learning trajectory of each
student, helping him or her learn, and in so doing,
learn how to learn better. At the same time, the
Learning Companion will serve as an interactive system
for helping researchers identify and better understand
ways in which emotion is expressed, communicated, and
handled in successful science, math, engineering, and
technology learning experiences.
University of Maryland College Park Learning How to
Learn Science: Metacognition in postsecondary physics
education for bioscience majors. Redish, Edward
0087519 $946,855 IIIII In this project, a
crossdisciplinary team of the University of Maryland
Physics Education Research Group (UMDPERG) and an
advisory team of biologists and biologyoriented
education specialists is carrying out basic research
in science learning among collegelevel bioscience
students. An emphasis on metalearning frames the
approach of the team. This includes metacognition,
epistemologies, expectations, and the construction of
broad and powerful mental models; in short learning
that goes beyond content and helps students understand
what it means to learn science and how to learn it
effectively. The project is studying student learning
of fundamental issues in thinking about science;
modifying current bestpractices learning environments
to make them effective tools for teaching
metalearning in a largelecture environment; and
developing survey tools to permit the documentation
and evaluation of the state of student metalearning
attitudes and skills in large classes. The
"laboratory" for this research effort is an
algebrabased physics course, and the project builds
on earlier work of the UMDPERG in studying student
metalearning in high school and calculusbased
university physics classes
MIT Sources of mathematical thinking. Spelke,
Elizabeth
0087721 Whang III To understand mathematical
cognition both as it develops in the young child and
as it is taught in school, one must understand the
cognitive systems from which it is constructed and the
processes by which those systems are coordinated to
produce new concepts and skills. Based on previous
research, we hypothesize that elementary school
mathematics builds on three representational systems:
a system for representing exact small numerosities, a
system for representing approximate large
numerosities, and natural language with its system of
number words and other quantifiers. The proposed
research investigates each of these building block
systems and their interactions through experiments on
human infants, nonhuman primates, preschool children
learning counting, elementary school children learning
arithmetic and fractions, and adults. To study the
building block cognitive systems directly, experiments
investigate spontaneous number representations in
human infants and in untrained adult monkeys, using in
each population the same three converging behavioral
measures: looking time to arrays of different
numerosities and to addition or subtraction events
(building on the finding that both infants and monkeys
look longer at novel arrays or unexpected events),
manual search (building on the finding that the number
of times that an infant or monkey will search in a
container depends on the number of objects it
represents within the container), and locomotor
approach to containers with different numbers of
attractive objects (building on the finding that
infants and monkeys will approach the container with
the greater number of objects). Further experiments
investigate how preschool children assemble these
components in learning number words and the counting
routine, by using verbal and pointing tasks to assess
developmental changes in children's understanding of
number words and counting procedures. To uncover the
neural substrates underlying mathematical cognition,
both behavioral and neuroimaging experiments
investigate whether and how human adults use each of
the three representational systems in performing
numerical comparisons and elementary arithmetic.
Finally, experiments investigate number concepts and
arithmetic learning in elementary school children.
Training studies in which children are taught new
facts or concepts and then are tested on a range of
related problems will serve to investigate the
subsystems involved in this learning, to probe the
processes by which those subsystems are assembled to
meet new educational challenges, and to explore ways
of enhancing mathematics learning in elementary
school. This research promises to shed light on the
teaching and learning of mathematics through
coordinated, laboratorybased studies in which
monkeys, infants, children and adults are given the
same stimuli and often the same tasks. This
coordinated effort should provide a broad portrait of
the sources of mathematical thinking, from its
phylogenetic and ontogenetic origins to its
culmination in educated adults.
University of California  Berkeley Modeling,
Developing, and Assessing Scientific Inquiry Skills Using
a ComputerBased Inquiry Support Environment. White,
Barbara
0087583 Suter III This study investigates
cognitive models of scientific inquiry skills in
middle school science. It creates pedagogical
approaches that enable students to develop widely
applicable cognitive skills needed for collaborative
inquiry and reflective learning. It would investigate
a number of hypotheses concerning how to achieve these
objectives. The study expects to result in creating a
learning theory that links metacognition and
reflective practices to the development of expertise
in scientific inquiry. The central hypothesis is that
scientific inquiry can be taught, or facilitated,
through computer tools that support cognitive modeling
and reflective practice. The investigators would
create a support environment that houses several
software advisors that can give strategic advice and
guide students as they conduct research projects in
science and reflect on their processes of
investigation. Also, the investigators would create
assessments of students' expertise and evaluate the
use of these models increases their understanding and
performance of scientific inquiry.
Kansas State University Technology & ModelBased
Conceptual Assessment: Research in Students' Applications
of Models in Physics & Mathematics. Zollman, Dean
0087788 Zia III To improve the communication
between students and teachers, particularly in large
classes, many universities have begun using
technologybased response systems. These systems
enable an instructor to pose questions and see, within
a few minutes, the students' responses to those
questions. Another similar approach is to assign
homework that is submitted, graded and returned
quickly via the World Wide Web. Both of these
technologybased systems offer instructors the
opportunity to record each student's responses in a
database. Thus, the instructor can track students'
understanding much more completely than with
traditional homework and quizzes and can use the
resulting data to investigate more deeply how students
understand the scientific and mathematical concepts.
In addition to seeing the present level of each
students understanding the instructor can learn how
the students change their thinking by making
comparisons of responses throughout the learning
process. A present, the analyses of these responses
generally tell instructors when the students are
obtaining the right answers. However, for students who
are not answering correctly, the present systems do
little more than indicate that the student is not
applying the scientific theories and models correctly.
Still missing is an analysis tool that is based on
contemporary educational research and can provide
robust quantitative information on the students'
difficulties with the underlying scientific models and
theories, and can track how the students'
understandings of these models change during
instruction. These tools must go beyond correct answer
analysis and analyze students' incorrect answers by
incorporating theories of learning into the systems.
This project will begin with a model for students'
conceptual learning processes and with existing work
on assessing students' conceptual understanding in
physics and mathematics. Then, research will be
conducted on students' applications of scientific
models and mathematical concepts, on how the students'
thinking and applications change during instruction,
and methods to present the results of these
assessments to teaching faculty who are using
inclass, realtime response or online homework
systems. By constructing sets of questions in which
incorrect answers provide insights into the scientific
and mathematical models that students are applying,
the project's results will lead to a deeper
understanding of students' abilities to learn physics
and mathematics and the contexts in which that
learning occurs most effectively. The analysis will
also provide insight into students' abilities to
transfer knowledge between physics and mathematics
courses. The major objectives of the project are to
measure, with realtime feedback, students'
understanding of fundamental concepts and the
application of those concepts, trace changes in those
understandings and applications during instruction,
investigate how students' conceptual understanding
depends on the context in which a new concept is
studied, create analysis tools that can be used
effectively in many educational environments, provide
information about the transfer of knowledge between
physics and mathematics, and investigate how students
and instructors interact with this teaching
environment. The result of reaching these goals will
be a system that will have a large impact on the
teaching of science and mathematics. The impact will
be particularly great in large enrollment classes
where instructors are often very detached from their
students because, frequently, such information becomes
available only after students take an exam. Of
particular importance for the instructors is knowledge
of when students have begun to change their thinking
but still sometimes revert to preinstructional
applications of scientific or mathematical concepts
a mixture of understanding and a lack of
understanding. Such situations are recognized to be an
important intermediate step in the learning process.
By knowing the extent of this mixture the instructors
can plan the next step in the learning process based
on the students' present physical or mathematical
understanding and the contexts which aid fundamental
change in students' thinking. Thus, the project will
provide both information and tools to help science and
mathematics instructors learn about the present
knowledge of their students and how to use that
present knowledge constructively to improve the
students' scientific and mathematical thinking skills.
Stanford Center for Innovation in Education. Accessed 7/14/03: http://scil.stanford.edu/. Quoting from the Website:
Stanford faculty and students from many schools and departments collaborate on SCIL programs and projects, since complex learning issues are by their very nature multidisciplinary. The Stanford Learning Lab, established in 1997 and now merged with SCIL, has added its accomplished staff and formidable international research base to further the Center's objectives.
SCIL resides in Wallenberg Hall, a showcase facility with pathbreaking technology, learning, and research spaces located in the front of the Quad on the Stanford campus. Wallenberg Hall was built with generous support from the Knut and Alice Wallenberg Foundation, which has maintained a long and auspicious affiliation with Stanford University's educational mission.
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